Assessment of survival prognosis

Publicatiedatum: 05-06-2026

Beoordeeld op geldigheid: 05-06-2026

Uitgangsvraag

Key question
How can survival be estimated in individual patients with spinal metastases?

Klik hier om het in het Nederlands te bekijken.

Aanbeveling

Recommendations

Use prognostic models, such as those described by Bollen (2014) or Bartels (2011), to estimate survival in patients with symptomatic vertebral metastases. These models should be regarded solely as supportive tools.

Discuss both the prognostic estimate and the limitations of the model explicitly during the relevant multidisciplinary team meeting. Determine the final treatment based on a predictive model in combination with the judgment of the multidisciplinary team (MDO in Dutch), including the relevant organ specialist, while carefully considering the patient’s wishes, values, and needs through proactive care planning.

Klik hier om het in het Nederlands te bekijken.

Overwegingen

Considerations

Balance Between Desired and Undesired Effects

A systematic review was conducted to identify externally validated models in predominantly White populations that predict survival among patients with spinal metastases eligible for surgery and/or radiotherapy. Fifteen models were described.

The treatment of spinal metastases is multidisciplinary. An estimation of expected survival is desired when considering surgery or radiotherapy. For extensive surgeries, an estimated survival of more than three months is preferred. An estimated survival of at least four weeks is generally preferred when considering palliative radiotherapy. Studies have shown that clinical assessment by experts is not adequate for predicting survival: treating physicians often overestimate survival (Thio, 2021).

Models to predict the survival of individual patients have been developed. Bollen (2014) (3 input variables), OSRI 2013 (2 input variables), and Revised Katagiri (2014, 11 input variables) show possibly helpful or acceptable discriminative ability on 3 months survival (yes/no), while none of the validated models demonstrate sufficient calibration. The online available Bartels 2011 model (5 input variables) showed possibly helpful discriminative ability on time-to-event survival until >10 months follow-up with some concerns in the quality of the evidence. It is important to note that all models provide an estimation of expected survival; long-term estimates will be less reliable than estimates for a three-month period, given that the calibration performance for all models is insufficient in literature. The models offer a more objective measure than clinical judgment alone.

The working group is of the opinion that there is no model available for estimating the survival of all patients with spinal metastases, regardless of the primary tumor origin.

It should be noted that any model should therefore only be used as a tool, and the indication for surgery does not depend solely on expected survival. The final treatment should be discussed in the multidisciplinary team meeting (MDO in Dutch) with the relevant organ specialist, taking into account the patient’s wishes, values, and needs through proactive care planning. Although the working group is of the opinion that survival estimation is not strongly dependent on the presence or absence of symptoms, no recommendations can be formulated for patients with asymptomatic vertebral metastases, because the majority of patients described in the literature have a treatment indication, which usually means they are symptomatic. In case an estimation is needed for an asymptomatic patient, it is recommended to discuss this in a multidisciplinary team.

Quality of Evidence

For the Bartels 2011 model, the overall quality of evidence for discrimination ability on time-to-event survival is low. This indicates some uncertainty regarding the estimated effect on discrimination performance. The evidence was downgraded due to (very) serious:

Imprecision, because of the absence of 95% CIs and a relatively small sample size.

For the remaining models in which discrimination ability on time-to-event survival was evaluated, the overall quality of evidence is very low, reflecting substantial uncertainty about the estimated effect on discrimination performance. The evidence was downgraded due to (very) serious:

Risk of bias, owing to retrospective data collection and unclear validation methodology.
Imprecision, due to the absence of 95% CIs.

For the models in which discrimination ability on 3-month survival (yes/no) was evaluated, the overall quality of evidence is moderate, except for the Modified Bauer 2008, and Revised Tokuhashi 2005, for which it is low. This indicates some certainty regarding the estimated effect on discrimination performance. The evidence was downgraded due to (very) serious:

Risk of Bias, due to partly retrospective data-collection;
Imprecision, as one boundary of the 95% CI crossed the threshold of clinical relevance.

For all models evaluated for calibration ability, the overall quality of evidence is moderate. This indicates some certainty regarding the estimated effect on calibration performance. The evidence was downgraded due to (very) serious:

Imprecision, since one boundary of the 95% CI crossed the threshold of clinical relevance.
Risk of Bias, due to partly retrospective data-collection.

Values and Preferences of Patients (and, if applicable, Their Relatives/Caregivers)

The assessment is made for treatment purposes. Whether or not to use a model does not appear to be a preference-sensitive decision.

Cost Considerations

All models are freely accessible. Some models require additional investigations, such as MRI, which may lead to higher costs.

Equity (Health Equity/Equitable)

The test-treatment strategy does not impact health equity. Equity does not play a role in the use or non-use of models for survival prediction, as there is no discrimination between individuals.

Acceptability

Ethical Acceptability

The final decision is made within the multidisciplinary team meeting (MDO in Dutch). The working group considers it unethical to base decisions solely on the outcome of a model. Given that a model is more objective than clinical judgment alone, it may be ethically justified to use the model, provided that its outcome is included in the final MDO decision.

Sustainability

Sustainability aspects do not play a role in this module, partly due to the low frequency of occurrence.

Feasibility

The recommendation to use a model appears feasible to the working group. Among the models that demonstrate potentially helpful discriminative ability, Bartels 2016, Bollen 2014, and OSRI 2013 require only a small set of routinely available input variables (Table 6). Furthermore, the Bartels model has online calculator instances available, which facilitates practical implementation.

Table 6. Overview of input variables in models with fewer than 10 predictors

Model	Predictors
Bartels^§ ²⁰⁰⁷ ²⁰¹¹ ²⁰¹⁶	Gender (male or female) Primary lesion curatively treated (yes/no) KPS (10-20, 30-40, 50-70, 80, 90) Location of the primary tumor (Breast/Prostate, Kidney, Lung, Other) Cervical location of spinal metastasis (yes/no)
Bollen ²⁰¹⁴ ²⁰¹⁶	KPS:80-100/10-70 Presence of visceral or brain metastases Primary tumor type: Unfavorable/ Moderate/ Favorable (Tomita) Favorable = Breast, prostate, thyroid, multiple myeloma, malignant lymphoma. Moderate = Renal, endometrial and ovarian, sarcoma, and others. Unfavorable = Lung, colorectal, gastric, pancreatic, head and neck, esophageal, nonrenal urological, melanoma, hepatocellular, gallbladder, cervical, and cancers of unknown origin.
OSRI²⁰¹³	KPS: 80-100/50-70/10-40 Primary tumor type: Slow/ Moderate/ Rapid/ Very rapid (OC) Slow = Breast, thyroid, prostate, myeloma, haemangioma, endothelioma, non-Hodgkins’s lymphoma. Moderate = Kidney, uterus, tonsils, epipharynx, synovial cell sarcoma, metastatic thymoma. Rapid = Stomach, colon, liver, melanoma, teratoma, sigmoid colon, pancreas, rectum, unknown origin. Very rapid = Lung.
Tomita²⁰⁰¹	Presence of visceral or brain metastases: None/ Treatable/ Untreatable Extraspinal bone metastases: Solitary/Multiple* Primary tumor type: Slow/Moderate/Rapid (OC) Slow = Breast, prostate, thyroid, multiple myeloma, malignant lymphoma. Moderate = Renal, endometrial and ovarian, sarcoma, and others. Rapid = Lung cancer, colorectal, gastric, pancreatic, head and neck, esophageal, nonrenal urological, melanoma, hepatocellular, gallbladder, cervical, and cancers of unknown origin.
Van der Linden²⁰⁰⁵	KPS: 80-100/50-70/20-40 Presence of visceral or brain metastases (Yes/No) Primary tumor type: Breast, prostate, lung, or other.
Modified Bauer²⁰⁰⁸	Presence of visceral or brain metastases (Yes/No) Extraspinal bone metastases: Solitary/Multiple* Primary tumor type Lung: Yes/No Breast, kidney, lymphoma or multiple myeloma: Yes/No
Original Bauer¹⁹⁹⁵	Presence of visceral or brain metastases (Yes/No) Extraspinal bone metastases: Solitary/Multiple* Pathologic fracture (Yes/No) Primary tumor type Lung: Yes/No Breast, kidney, lymphoma or multiple myeloma: Yes/No
Revised Tokuhashi ²⁰⁰⁵	KPS: 80-100/50-70/10-40 Number of extraspinal bone metastases : 0/1-2/≥3 Number in spinal bone metastases: 1/2/≥3 Visceral or brain metastases: Unresectable/ Resectable/ Absent Frankel grade: A-B/C-D/E Primary tumor type Lung, osteosarcoma, stomach, bladder, esophagus, or pancreas; Liver, gallbladder, or unknown; Others; Kidney or uterus; Thyroid, breast, prostate, or carcinoid.
Mizumoto²⁰⁰⁸	Age:<71/≥71 (years) ECOG: 0-2/3-4 Presence of visceral or brain metastases (Yes/No) Extraspinal bone metastases: Solitary/Multiple* Previous chemotherapie (Yes/No) Calcium: ≤10/>10 mg/dL Primary tumor type Favorable = Breast, prostate, lymphoma, and thyroid (except anaplastic cancer). Unfavorable = Others.

_{Information about input variables is extracted from and Ronald 2016, Bindels 2025.}

_{*All bone metastases were combined as input variable.}

_{^§ After the literature search for guideline development, a validation study for the Bartels model (Bartels, 2025) among patients treated according to the latest oncological protocols (May 2021–Dec 2023) showed comparable results, which are not presented here as it was published at the end of the development phase.}

Onderbouwing

Background

When considering treatment for a patient with (a)symptomatic spinal metastases, it is important to weigh the burden of the treatment (e.g. time investment, short- and long-term side effects) against its effectiveness (e.g. estimated likelihood of symptom improvement and duration of effect). In addition, an assessment of whether the patient is likely to survive at least three months is needed, to avoid both overtreatment (e.g. extensive surgery in patients with limited survival) and undertreatment (withholding treatment from patients who unexpectedly live longer). Two systematic reviews have shown that clinicians often inaccurately estimate life expectancy (Glare, 2003; Chow, 2001; Nahm, 2023; Cheon, 2016). To assist in survival prediction, various prognostic models have been described in the literature, which estimate expected survival based on patient-specific risk factors. These tools can help refine treatment decisions. However, recent advances in treatment for certain malignancies have significantly altered survival outcomes. Existing models have not been validated for these new therapeutic strategies.

Summary of literature

Description of studies

Three studies were included in the analysis of the literature. Important study characteristics and results are summarized in table 3. The assessment of the risk of bias is summarized in the risk of bias tables (under the tab ‘Evidence tabellen’).

Bartels (2016) externally validated the NCCN model (Bartels, 2011) in a Dutch population receiving radiotherapy solely or radiotherapy after surgery.

Bollen (2016) externally validated six models (Tokuhashi, 2005; Bauer and Wedin, 1995; Tomita, 2001; Linden, 2005; Rades, 2013; Bollen, 2014) in a Dutch and Austrian population receiving treatment for spinal metastasis.

Bindels (2025) externally validated 12 models (two machine learning algorithms: PathFx, Skeletal Oncology Research Group - Machine Learning Algorithm (SORG-MLA) and ten scoring systems: Bollen 2014, Modified Bauer 2008, Mizumoto 2008, New England Spinal Metastasis Score (NESMS) 2015, Original Bauer 1995, Oswestry Spinal Risk Index (OSRI) 2013, Revised Katagiri, 2014; Revised Tokuhashi, 2005; Tomita, 2001 and van der Linden, 2005) in a Dutch population referred for a metastatic spine tumor, irrespective of the treatment modality administered after referral.

Table 3. Characteristics of included studies

Study

Participants

Instrument

Follow-up

Outcome measures

Comments

Risk of bias (per outcome measure)*

Bartels, 2016

N at baseline:

N=110

Age (mean, SD):

Not reported

Sex (n):

Not reported

Median survival time (range):

5.7 months (range: 0.3–68.3 months

Type of treatment (n):

Radiotherapy+surgery: 58

Radiotherapy: 52

Model: Bartels 2011

Predictors:

Gender (female vs male)
Lung carcinoma (vs breast/prostate carcinoma)
Kidney carcinoma (vs breast/prostate carcinoma)
Other carcinoma (vs breast/prostate carcinoma)
Curatively intended treatment of primary tumor
Cervical location of the metastasis
KPS (10-20)
KPS (30-40)
KPS (50-70)
KPS (80)

Outcome:

Survival (continuous)

The outcome was measured until >10 months

Discrimination: Harrel’s C-index

Calibration:
Calibration slope

Prospective data-collection from September 2009 until January 2013 from neurosurgical department of the Radboud University Medical Center and Canisius Wilhelmina Hospital (n=87)

Prospective data-collection in 2012 from neurosurtical department at The Haaglanden Medical Center The Hague (n=23)

Note that development of the model was performed in data that was partly collected at the neurosurgical department of the Radboud University Medical Center as well, but before the start of this study.

No missing data reported.

Low

Bollen, 2016

N at baseline:

N=1379

Age (mean, SD):

64.6 (12.4) years

Sex (%):

Male: 52%

Median survival time (95%CI):

5.1 (4.6 to 5.6) months

Type of treatment (n, %):

Radiotherapy: 1141 (83%)

Surgery + radiotherapy: 109 (8%)

Only surgery: 33 (2%)

Conservative treatment: 96 (7%)

Primary tumors (n,%):

Breast cancer: 388 (28%)

Lung cancer: 318 (23%)

Prostate cancer: 259 (19%)

Kidney cancer: 90 (7%)

Colon cancer: 75 (5%)

Other: 16 (18%)

Model:

Tokuhashi 2005
(not further specified)

Bauer and Wedin 1995
(not further specified)

Tomita 2001
(not further specified)

Linden 2005
(not further specified)

Rades 2013
(not further specified)

Bollen 2014
(not further specified)

Follow-up (median, 95%CI)

6.7 (5.6 to 7.7) years

Minimum follow-up: 2.3 years

Maximum follow-up: 12.3 years

The outcome was measured until >2 years

Discrimination:

Harrel’s c-statistic

Retrospective data-collection Leiden University Medical Center and Medical University of Graz between January 2000 and December 2010.

‘The model by Bollen (2014) was created on the basis of a large percentage of patients also included in this study. Therefore, an additional

analysis based on external data only was conducted for

this model.’

6 patients were lost to follow-up

High due to retrospective data collection.

Additionally it is unclear whether analysis of outcome is based on the original (external validation) or new (no validation) calculated HRs.

Bindels, 2025

N at baseline:

N=953

Age (mean, SD):

65.9 (10.9) years

Sex (%):

Male: 56.1%

Survival time:

50.3% at 12 months (479/953)

Type of treatment (n, %):

Radiotherapy only: 636 (66.7%)

Surgery + radiotherapy: 198 (20.8%)

Only surgery: 75 (7.9%)

No local treatment: 44 (4.6%)

Primary tumors (n,%):

Breast cancer: 209 (21.9%)

Lung cancer: 244 (25.6%)

Prostate cancer: 184 (19.3%)

Colon and rectal cancer: 55 (5.8%)

Malignant myeloma: 53 (5.6%)

Unknown origin: 49 (5.1%)

Other: 69 (7.2%)

Model: Overview of the variables included in each model see Appendix.

Bollen 2014
(Classification system)

Mizumoto 2008
(Scoring system)

Modified Bauer 2008
(Scoring system)

NESMS 2015
(Scoring system)

Original Bauer 1995
(Scoring system)

OSRI 2013
(Scoring system)

PathFx 2020

(Algorithm)

Revised katagiri 2014
(Scoring system)

Revised Tokuhashi 2005
(Scoring system)

SORG-MLA 2019
(Algorithm)

Tomita 2001
(Scoring system)

Van der Linden 2005
(Scoring system)

Follow-up:

The outcome was measured at 3, 6 and 12 months respectively

Discrimination:

AUC

Calibration:

slope

Patients were identified from three prospective registries.

PRESENT: referred to Radiation Oncology between 2016-2021
GSTSG: referred to Orthopedic Surgery between 2016-2018
MTRON: referred to Orthopedic Surgery between 2018-2021

patients of at least 18 years of age and referred for a metastatic spine tumor, irrespective of the treatment modality administered after referral. If patients were included in more than 1 registry, only data from the registry where they provided informed consent first was used.

Low

_{*For further details, see risk of bias table in the appendix}

Results & Summary of findings

Discrimination
Bartels (2016) and Bollen (2016) reported time-to-event discrimination, measured by Harrell’s C-index, for seven different models (Table 4.). The reported discrimination abilities of these models were possibly helpful (0.6 ≤ C-statistic ≤ 0.75), except for the Rades 2013 model, whose performance was poor. Bindels (2025) reported binary discrimination, measured by the area under the curve (AUC), for 12 different models (Table 4.). The reported discrimination abilities for 3-month survival (yes/no) of Bollen, OSRI, Modified Bauer 2008, Revised Katagiri (ten and three categories), and Revised Tokuhashi 2005 were acceptable (0.7≤AUC <0.8), while the discrimination abilities of the other models for 3-month survival were poor.

Calibration
Bartels (2016) and Bindels (2025) reported the calibration slope for 13 different models (Table 5.). The reported calibration abilities of these models were insufficient (calibration slope < 0.9).

Table 4. Discrimination outcome (c-statistic, AUC at 3 months)

Author	Model	N of Variables	N	Death (n)	Measurement	Outcome (95% CI)	Performance	Certainty of the Evidence (Quality of evidence)	Conclusions
Bartels, 2016	Bartels 2011	5	110	90	c-statistic * (time-to-event discrimination until >10 months)	0.68 (not reported)$	Possibly helpful	Low¹	The Bartels 2011 model may result in possibly helpful discrimination when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
Bollen, 2016	Tokuhashi 2005	6	1379	1122	c-statistic * (time-to-event discrimination until >2 years)	0.64 (not reported)	Possibly helpful	Very low²	The evidence is very uncertain about discriminative ability of the Tokuhashi 2005 model when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
	Bauer en Wedin 1995	4	1379	1122	c-statistic * (time-to-event discrimination until >2 years)	0.64 (not reported)	Possibly helpful	Very low²	The evidence is very uncertain about discriminative ability of the Bauer and Wedin 1995 model when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
	Tomita 2001	3	1379	1122	(time-to-event discrimination until >2 years)	0.64 (not reported)	Possibly helpful	Very low²	The evidence is very uncertain about discriminative ability of the Tomita 2001 model when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
	Linden 2005	3	1379	1122	c-statistic * (time-to-event discrimination until >2 years)	0.66 (not reported)	Possibly helpful	Very low²	The evidence is very uncertain about discriminative ability of the Linden 2005 model when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
	Rades 2013	6	1379	1122	(time-to-event discrimination until >2 years)	0.44 (not reported)	Poor	Very low²	The evidence is very uncertain about discriminative ability of the Rades 2013 model when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
	Bollen 2014	3	336§	1122	c-statistic * (time-to-event discrimination until >2 years)	0.69 (not reported)	Possibly helpful	Very low²	The evidence is very uncertain about discriminative ability of the Bollen 2014 model when predicting time-to-event survival among patients eligible for treatment of spinal metastasis.
Bindels, 2025	Bollen 2014	3	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.76 (0.73-0.80)	Acceptable	Moderate³	The Bollen model likely results in acceptable discrimination when predicting 3 month survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Mizumoto 2008	7	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.69 (0.66-0.73)	Poor	Moderate³	The Mizumoto model likely results in poor discrimination when predicting 3 month survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Modified Bauer 2008	3	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.70 (0.66-0.74)	Acceptable	Low^3,4	The modified Bauer model may result in acceptable discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	NESMS 2015	5	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.59 (0.55-0.63)	Poor	Moderate³	The NESMS model likely results in poor discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Original Bauer 1995	4	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.66 (0.63-0.70)	Poor	Moderate³	The original Bauer model likely results in poor discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	OSRI 2013	2	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.75 (0.72-0.79)	Acceptable	Moderate³	The OSRI model likely results in acceptable discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	PathFx 2020	11	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.66 (0.62-0.70)	Poor	Moderate³	The PathFx model likely results in poor discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Revised Katagiri (ten categories) 2014	11	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.79 (0.76-0.82)	Acceptable	Moderate³	The revised Katagiri (ten categories) model likely results in acceptable discrimination when predicting 3 months (yes/no) survival among patients eligible for treatment of spinal metastasis.
	Revised Katagiri (3 categories) 2014	11	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.75 (0.72-0.77)	Acceptable	Moderate³	The revised Katagiri (3 categories) model likely results in acceptable discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Revised Tokuhashi 2005	6	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.70 (0.67-0.73)	Acceptable	Low^3,4	The revised Tokuhashi model may result in acceptable discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	SORG-MLA 2019	18	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.68 (0.63-0.72)	Poor	Moderate³	The SORG-MLA model likely results in poor discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Tomita 2001	3	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.64 (0.60-0.68)	Poor	Moderate³	The Tomita model likely results in poor discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Van der Linden 2005	3	953	225/360/474^§	AUC (binary discrimination: yes/no at 3 months)	0.68 (0.65-0.71)	Poor	Moderate³	The van der Linden model likely results in poor discrimination when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
_{Abbreviations:} _{* Harrel’s C-index. $Analysis using external data. ^§ Number of deaths at 3, 6 and 12 months respectively.} _{¹Downgraded two levels for Imprecision as no 95%CI is available and a low sample size was used.} _{²Downgraded for two levels for Risk of Bias due to retrospective data-collection and unclear validation methodology and one level for Imprecision as no 95%CI is available.} _{³Downgraded for one level for Risk of Bias due to partly retrospective data-collection.} _{⁴Downgraded one level for Imprecision as one border of the 95% CI crossed clinical relevance threshold.}

Table 5. Calibration outcome (Calibration slope at 3 months)

Author	Model	N of Variables	N	Death (n)	Calibration slope (95% CI)		Performance		Certainty of the Evidence (Quality of evidence)		Conclusions
Bartels, 2016	Bartels 2011	5	110	90	Until >10 months: 0.64 (0.34-0.94)		Not sufficient		Moderate¹		The Bartels 2011 model likely results in insufficient calibration when predicting time-to-event survival among patients eligible for surgery and/or radiotherapy to treat spinal metastasis.
Bindels, 2025	Bollen 2014	3	953	225/360/474^§	At 3 months: 0.76 (0.73-0.80)	Not sufficient		Moderate²		The Bollen model likely results in insufficient calibration when predicting 3 month survival (yes/no) in patients eligible for treatment of spinal metastasis.
	Mizumoto 2008	7	953	225/360/474^§	At 3 months: 0.69 (0.66-0.73)	Not sufficient		Moderate²		The Mizumoto model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Modified Bauer 2008	3	953	225/360/474^§	At 3 months: 0.70 (0.66-0.74)	Not sufficient		Moderate²		The Modified Bauer model likely results in insufficient calibration when predicting 3 month survival (yes/no) among patients eligible for treatment of spinal metastasis.
	NESMS 2015	5	953	225/360/474^§	At 3 months: 0.59 (0.55-0.63)	Not sufficient		Moderate²		The NESMS model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Original Bauer 1995	4	953	225/360/474^§	At 3 months: 0.66 (0.63-0.70)	Not sufficient		Moderate²		The Original Bauer model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	OSRI 2013	2	953	225/360/474^§	At 3 months: 0.75 (0.72-0.79)	Not sufficient		Moderate²		The OSRI model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	PathFx 2020	11	953	225/360/474^§	At 3 months: 0.66 (0.62-0.70)	Not sufficient		Moderate²		The PathFx model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Revised Katagiri (ten categories) 2014	11	953	225/360/474^§	At 3 months: 0.79 (0.76-0.82)	Not sufficient		Moderate²		The Revised Katagiri (ten categories) model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Revised Katagiri (3 categories) 2014	11	953	225/360/474^§	At 3 months: 0.75 (0.72-0.77)	Not sufficient		Moderate²		The Revised Katagiri (3 categories) model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Revised Tokuhashi 2005	6	953	225/360/474^§	At 3 months: 0.70 (0.67-0.73)	Not sufficient		Moderate²		The Revised Tokuhashi model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	SORG-MLA 2019	18	953	225/360/474^§	At 3 months: 0.68 (0.63-0.72)	Not sufficient		Moderate²		The SORG-MLA model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Tomita 2001	3	953	225/360/474^§	At 3 months: 0.64 (0.60-0.68)	Not sufficient		Moderate²		The Tomita model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.
	Van der Linden 2005	3	953	225/360/474^§	At 3 months: 0.68 (0.65-0.71)	Not sufficient		Moderate²		The Van der Linden model likely results in insufficient calibration when predicting 3 months survival (yes/no) among patients eligible for treatment of spinal metastasis.

Search and select

When reviewing literature, there is a hierarchy in quality of individual prognostic studies. Preferably, the effectiveness of the use of a prognostic instrument (e.g. prediction model) is evaluated in a clinical trial. Unfortunately, these studies are very rare. If not available, studies in which prediction models are developed and validated in an external cohort of the target population (external validation) are preferred as there is more confidence in the results of these studies compared to studies that are not externally validated. Most external validation cohorts do not completely reflect the characteristics of the total population, resulting in deviated associations, possibly having consequences for conclusions. Studies validating prediction models internally (e.g. bootstrapping or cross validation) can be used to answer the first research question as well, but downgrading the level of evidence is obvious due to risk of bias and/or indirectness as it is not clear whether models perform sufficiently in target populations. The confidence in the results of unvalidated prediction models is very low. Therefore, such models will not be graded. Not grading is also applicable for prognostic factor research. The risk factors identified from such models can be used to inform patients about the elevated risk on complications during procedural sedation and analgesia, however they are less suitable to be used in clinical decision making as the predictive value of these factors is unclear.

As the guideline panel did not expect to find studies investigating the effectiveness of a prognostic instrument predicting 3-month survival among patients with symptomatic spinal metastases, only a PICOTS (table 1) investigating the performance of prediction models was formulated.

A systematic review of the literature was performed to answer the following question(s):

Which models predict 3-month survival among patients with symptomatic spinal metastases and what is the predictive value of these models?

Table 1. PICOTS

Patients	Patients diagnosed with symptomatic spinal metastases, eligible for radiotherapy or surgery & radiotherapy treatment
Instrument	Prediction model for survival
Comparator instrument	Not applicable
Outcomes	Predictive value of the model (discrimination and calibration)
Timing	Outcome: Three months after starting treatment (radiotherapy or surgery & radiotherapy)
Setting	Decision making for treatment spinal metastasis
Other selecation criteria	Study design: systematic reviews, prognostic studies (peer reviewed) Population: At least patients treated with radiotherapy or radiotherapy and surgery were included; subgroups of patients, e.g. surgery patients only were excluded Instrument: external validation in western population

Relevant outcome measures

The guideline panel considered definitions and thresholds for clinical relevance as defined in table 2.

Table 2. Definitions and thresholds

Outcome

Definition

Threshold

Discrimination

(critical outcome measure)

C-statistic , as defined in the used studies

AUC (Area under the curves) , as defined in the used studies

C-statistic<0.6: poor

0.6≤C-statistic≤0.75: possibly helpful,

C-statistic>0,75: useful

(Foroutan, 2024)

AUC ≤0.5: no better than chance.

0.5<AUC <0.7: Poor.

0.7≤AUC <0.8: Generally considered acceptable.

0.8≤AUC <0.9: Considered excellent.

AUC ≥ 0.9: Considered outstanding.

(Carter, 2016)

Calibration

(critical outcome measure)

Calibration slope: Observed/expected ratio, as defined in the used studies

0.9<Calibration slope<1.1

(Riley, 2020)

Search and select (Methods)

A systematic literature search was performed by a medical information specialist using the following bibliographic databases: Embase.com and Ovid/Medline. Both databases were searched from 1 January 2014 to 28 June 2024 for systematic reviews and prognostic studies developing and validating prediction models. Systematic searches were completed using a combination of controlled vocabulary/subject headings (e.g., Emtree-terms, MeSH) wherever they were available and natural language keywords. The overall search strategy was derived from three primary search concepts: (1) spinal metastasis; (2) survival; (3) prognostic filter. Duplicates were removed using EndNote software. After deduplication a total of 1304 records were imported for title/abstract screening. Initially, 91 studies were selected based on title and abstract screening with ASReview LAB (2.1). After manual selection 25 studies were selected for full text selection. After reading the full text, 23 studies were excluded (see the exclusion table under the tab ‘Evidence tabellen’), and 2 studies (Bartels, 2016; Bollen, 2016) were included.

An update was performed starting from June 1, 2024. After deduplication of the previous results, a total of 215 abstracts were identified and screened based on title and abstract using ASReview LAB (version 2.1). After manual selection 12 studies were selected for full text selection. After reading the full tekst, 11 studies were excluded (see the exclusion table under the tab ‘Evidence tabellen’), and one study (Bindels, 2025) was included.

1 - Bartels RH, de Ruiter G, Feuth T, Arts MP. Prediction of life expectancy in patients with spinal epidural metastasis. Neuro Oncol. 2016 Jan;18(1):114-8. doi: 10.1093/neuonc/nov149. Epub 2015 Aug 8. PMID: 26254478; PMCID: PMC4677416.
2 - Bartels RH, Feuth T, Rades D, Hedlund R, Villas C, van der Linden Y, Börm W, Kappelle A, van der Maazen RW, Grotenhuis JA, Verbeek AL. External validation of a model to predict the survival of patients presenting with a spinal epidural metastasis. Cancer Metastasis Rev. 2011 Jun;30(2):153-9. doi: 10.1007/s10555-011-9271-6. PMID: 21259121.
3 - Bartels RH, de Bree K, Pazira H, van Bilsen M, Jonker M, de Ruiter GC, Arts M, Westhoff P. Prediction of survival in patients suffering from spinal metastases: A prospective, multicenter validation study. The Oncologist. 2025 Oct 25:oyaf363.
4 - Bollen L, Wibmer C, Van der Linden YM, Pondaag W, Fiocco M, Peul WC, Marijnen CA, Nelissen RG, Leithner A, Dijkstra SP. Predictive Value of Six Prognostic Scoring Systems for Spinal Bone Metastases: An Analysis Based on 1379 Patients. Spine (Phila Pa 1976). 2016 Feb;41(3):E155-62. doi: 10.1097/BRS.0000000000001192. PMID: 26866742..
5 - Carter JV, Pan J, Rai SN, Galandiuk S. ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves. Surgery. 2016 Jun 1;159(6):1638-45.
6 - Foroutan F, Mayer M, Guyatt G, Riley RD, Mustafa R, Kreuzberger N, Skoetz N, Darzi A, Alba AC, Mowbray F, Rayner DG. GRADE concept paper 8: judging the certainty of discrimination performance estimates of prognostic models in a body of validation studies. Journal of Clinical Epidemiology. 2024 Jun 1;170:111344.
7 - Foroutan F, Mayer M, Guyatt G, Riley RD, Mustafa R, Kreuzberger N, Skoetz N, Darzi A, Alba AC, Mowbray F, Rayner DG, Schunemann H, Iorio A. GRADE concept paper 8: judging the certainty of discrimination performance estimates of prognostic models in a body of validation studies. J Clin Epidemiol. 2024 Jun;170:111344. doi: 10.1016/j.jclinepi.2024.111344. Epub 2024 Apr 3. PMID: 38579978.
8 - Riley RD, Ensor J, Snell KI, Harrell FE, Martin GP, Reitsma JB, Moons KG, Collins G, Van Smeden M. Calculating the sample size required for developing a clinical prediction model. Bmj. 2020 Mar 18;368.
9 - Thio QC, Pereira NR, van Wulfften Palthe O, Sciubba DM, Bramer JA, Schwab JH. Estimating survival and choosing treatment for spinal metastases: Do spine surgeons agree with each other?. Journal of Orthopaedics. 2021 Nov 1;28:134-9.

Evidence tables

Risk of Bias tables

Table of quality assessment – prediction modelling studies

(The criteria used in this checklist are based on PROBAST^A version 15/05/2019)

Study reference

(first author, year of publication)

Classification

Participant selection

1) Appropriate data sources?

2) Appropriate in- and exclusion?

Predictors

1) Assessed similar for all participants?

2) Assessed without knowledge of outcome?

3) Available at time the model is intended to be used?

Outcome

1) Pre-specified or standard outcome definition?

2) Predictors excluded from definition?

3) Assessed similar for all participants?

4) Assessed without knowledge of predictors?

5) Time interval between predictor and outcome measurement appropriate?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Analysis

1) Reasonable number of participants with event/outcome?

2) All enrolled participants included in analysis?

3) Missing data handled appropriately?

4) No selection of predictors based on univariate analysis?

5) Relevant model performance measures evaluated appropriately?

6) Accounted for model overfitting and optimism?

7) Predictors and weights correspond to results from multivariate analysis?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Overall judgment

High risk of bias: at least one domain judged to be at high risk of bias.

Model development only: high risk of bias.

Risk of bias:

Low

High

Bartels, 2016

(external validation)

Conclusion: Definitely yes

Reason: Consecutive patients, prospective dataset

Conclusion: Probably yes

Reason:
Data was collected prospectively, but method of assessment was not described.

Conclusion:

Probably yes

Reason:

Data was collected prospectively, based on previously used definitions, but method of assessment was not described.

Conclusion:

Definitely yes

Reason:

No missing data

Low

Bollen, 2016

(external validation)

Conclusion: Definitely yes

Reason: Hospital’s database

Conclusion: Definitely no

Reason:
Data was collected retrospectively.

Conclusion:

Probably no

Reason:

Data was collected retrospectively.

Conclusion:

Probably no

Reason:

Large number of participants and low percentage of missing data reported. However, it is unclear whether outcome measures (discrimination and calibration) were based on adapted HR values calculated on the current dataset or original HR values

High

Bindels, 2025 (external validation)

Conclusion: Definitely yes

Reason: All patients referred for a metastatic spine tumor in three prospective registries

Conclusion: Probably no

Reason:
Standard clinical data were collected from prospective registry, but additional clinical data were manually collected retrospectively from electronic health records. The researchers were not blinded to the outcome as survival and predictors were considered hard variables and not subjective.

Conclusion:

Definitely yes

Reason:

Survival was assessed through the official

national Personal Records Database on June 22th, 2023, which is independent from the resources of the predictors.

Survival data was available for all patients at 3, 6, and 12 months.

Conclusion:

Probably yes

Reason:

The sample size is considered to be sufficient.

The authors used bootstrapping with 2,000 samples, where each sample has an equal sample size as the original sample, to calculate 95% confidence intervals for the performance measures.

Reasonable percentage of missing data (<10%), and handled with multiple imputation. Complete case analyses yielded comparable outcome to those obtained using imputed data.

Some concerns

_{^A Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S; PROBAST Group. PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies. Ann Intern Med. 20191;170(1):51-58. doi: 10.7326/M18-1376. PubMed PMID: 30596875.}

_{¹ Development of model only / Development and external validation of model / External validation of model}

_{² Cohort, RCT or nested case-control study}

_{³ E.g. calibration (total O:E ratio; expected outcome probabilities versus observed outcome frequencies) and discrimination (range 0.5 (no discriminative ability) to 1.0 (perfect discriminative ability)}

_{⁴ Overfitting: for low ORs the predicted probability is too low, for high ORs the predicted probability is too high. Correcting is possible with shrinkage.}

Table of excluded studies

Reference	Reason for exclusion
Aoude A, Fortin M, Aldebeyan S, Ouellet J, Amiot LP, Weber MH, Jarzem P. The revised Tokuhashi score; analysis of parameters and assessment of its accuracy in determining survival among patients afflicted with spinal metastasis. Eur Spine J. 2018 Apr;27(4):835-840. doi: 10.1007/s00586-016-4921-6. Epub 2016 Dec 23. PMID: 28012079.	Not western population (partly)
Carrwik C, Tsagkozis P, Wedin R, Robinson Y. Predicting survival of patients with spinal metastatic disease using PathFx 3.0 - A validation study of 668 patients in Sweden. Brain Spine. 2022 Nov 8;2:101669. doi: 10.1016/j.bas.2022.101669. PMID: 36506283; PMCID: PMC9729818.	One of two databased included only surgery patients
Dardic M, Wibmer C, Berghold A, Stadlmueller L, Froehlich EV, Leithner A. Evaluation of prognostic scoring systems for spinal metastases in 196 patients treated during 2005-2010. Eur Spine J. 2015 Oct;24(10):2133-41. doi: 10.1007/s00586-014-3482-9. Epub 2014 Aug 1. PMID: 25082760.	Wrong outcome (no model performance)
Derincek A, Guler UO, Uysal M, Ozalay M. Spinal Metastatic Disease: Survival Analysis of 146 Patients and Evaluation of 4 Different Preoperative Scoring Systems. Clin Spine Surg. 2020 Mar;33(2):E81-E86. doi: 10.1097/BSD.0000000000000858. PMID: 31393277.	Not western population
Kumar N, Tan JJ, Zaw AS, Lim JL, Wai KL, Malhotra R, Loh TK, Liu GK, Thambiah J. Evaluation of scoring systems and prognostic factors in patients with spinal metastases from nasopharyngeal carcinoma. Spine J. 2014 Dec 1;14(12):2946-53. doi: 10.1016/j.spinee.2014.06.001. Epub 2014 Jun 7. PMID: 24912121.	Not western population
Lei, M., et al. "Validation of a model with which to predict the survival prognosis of patients with spinal cord compression resulted from metastatic cancers." European Journal of Surgical Oncology (EJSO) 42.12 (2016): 1924-1930.	Only surgically treated patients included
Liu Y, Li L, Jiang D, Yang M, Gao X, Lv K, Xu W, Wei H, Wan W, Xiao J. A Novel Nomogram for Survival Prediction of Patients with Spinal Metastasis From Prostate Cancer. Spine (Phila Pa 1976). 2021 Mar 15;46(6):E364-E373. doi: 10.1097/BRS.0000000000003888. PMID: 33620180.	Not western population
Mavritsakis D, Amiot LP. A novel prognostic scoring system combining the revised Tokuhashi score and the New England spinal metastasis score for preoperative evaluation of spinal metastases. Front Surg. 2024 Mar 5;11:1349586. doi: 10.3389/fsurg.2024.1349586. PMID: 38505407; PMCID: PMC10949943.	Unclear population characteristics
Morgen SS, Fruergaard S, Gehrchen M, Bjørck S, Engelholm SA, Dahl B. A revision of the Tokuhashi revised score improves the prognostic ability in patients with metastatic spinal cord compression. J Cancer Res Clin Oncol. 2018 Jan;144(1):33-38. doi: 10.1007/s00432-017-2519-y. Epub 2017 Oct 6. PMID: 28986702.	Wrong outcome (no 3 month survival)
Morgen SS, Nielsen DH, Larsen CF, Søgaard R, Engelholm SA, Dahl B. Moderate precision of prognostic scoring systems in a consecutive, prospective cohort of 544 patients with metastatic spinal cord compression. J Cancer Res Clin Oncol. 2014 Dec;140(12):2059-64. doi: 10.1007/s00432-014-1776-2. Epub 2014 Jul 18. PMID: 25035249.	Wrong outcome (no 3 month survival)
Schoenfeld AJ, Ferrone ML, Blucher JA, Agaronnik N, Nguyen L, Tobert DG, Balboni TA, Schwab JH, Shin JH, Sciubba DM, Harris MB. Prospective comparison of the accuracy of the New England Spinal Metastasis Score (NESMS) to legacy scoring systems in prognosticating outcomes following treatment of spinal metastases. Spine J. 2022 Jan;22(1):39-48. doi: 10.1016/j.spinee.2021.03.007. Epub 2021 Mar 16. PMID: 33741509; PMCID: PMC8443703.	Model performance was not reported for 3-month mortality outcome
Schoenfeld AJ, Ferrone ML, Schwab JH, Blucher JA, Barton LB, Tobert DG, Chi JH, Shin JH, Kang JD, Harris MB. Prospective validation of a clinical prediction score for survival among patients with spinal metastases: the New England Spinal Metastasis Score. Spine J. 2021 Jan;21(1):28-36. doi: 10.1016/j.spinee.2020.02.009. Epub 2020 Feb 19. PMID: 32087387.	Proceedings
Tan JH, Tan KA, Zaw AS, Thomas AC, Hey HW, Soo RA, Kumar N. Evaluation of Scoring Systems and Prognostic Factors in Patients With Spinal Metastases From Lung Cancer. Spine (Phila Pa 1976). 2016 Apr;41(7):638-44. doi: 10.1097/BRS.0000000000001279. PMID: 27018903.	Not western population
Truong VT, Al-Shakfa F, Roberge D, Masucci GL, Tran TPY, Dib R, Yuh SJ, Wang Z. Assessing the Performance of Prognostic Scores in Patients with Spinal Metastases from Lung Cancer Undergoing Non-surgical Treatment. Asian Spine J. 2023 Aug;17(4):739-749. doi: 10.31616/asj.2022.0377. Epub 2023 Jul 6. PMID: 37408290; PMCID: PMC10460656.	Only no surgical indication or surgical indication but poor general condition
Wang, Shengjie, et al. "Validation of a scoring system predicting survival and function outcome in patients with metastatic epidural spinal cord compression (MESCC): a prospective and multicenter study." Int J Clin Exp Med 11.3 (2018): 2465-2470.	No western population
Whitehouse S, Stephenson J, Sinclair V, Gregory J, Tambe A, Verma R, Siddique I, Saeed M. A validation of the Oswestry Spinal Risk Index. Eur Spine J. 2016 Jan;25(1):247-251. doi: 10.1007/s00586-014-3665-4. Epub 2014 Nov 13. PMID: 25391625.	Only surgically treated patients included
Wick JB, Kalistratova VS, Jr DP, Fine JR, Boozé ZL, Holland J, Vander Voort W, Hisatomi LA, Villegas A, Conry K, Ortega B, Javidan Y, Roberto RF, Klineberg EO, Le HV. A Comparison of Prognostic Models to Facilitate Surgical Decision-Making for Patients With Spinal Metastatic Disease. Spine (Phila Pa 1976). 2023 Apr 15;48(8):567-576. doi: 10.1097/BRS.0000000000004600. Epub 2023 Feb 15. PMID: 36799724.	Only surgically treated patients included
Yang JJ, Chen CW, Fourman MS, Bongers MER, Karhade AV, Groot OQ, Lin WH, Yen HK, Huang PH, Yang SH, Schwab JH, Hu MH. International external validation of the SORG machine learning algorithms for predicting 90-day and one-year survival of patients with spine metastases using a Taiwanese cohort. Spine J. 2021 Oct;21(10):1670-1678. doi: 10.1016/j.spinee.2021.01.027. Epub 2021 Feb 2. PMID: 33545371.	Only surgically treated patients included
Yang M, Ma X, Wang P, Yang J, Zhong N, Liu Y, Shen J, Wan W, Jiao J, Xu W, Xiao J. Prediction of Survival Prognosis for Spinal Metastasis From Cancer of Unknown Primary: Derivation and Validation of a Nomogram Model. Global Spine J. 2024 Jan;14(1):283-294. doi: 10.1177/21925682221103833. Epub 2022 May 26. PMID: 35615968; PMCID: PMC10676151.	Wrong outcome (no 3 month survival)
Yang M, Xu W, Liu T, Yang X, Wang P, Wu S, Wei H, Zhao J, Yang C, Xiao J. Development and Validation of a Novel Survival Prediction Model in Patients With Spinal Metastasis From Non-small Cell Lung Cancer. Spine (Phila Pa 1976). 2019 Feb 15;44(4):246-257. doi: 10.1097/BRS.0000000000002816. PMID: 30059487.	Not western population
Yeung, Yuk-Nam, et al. "A study of the predictive value of the modified Tokuhashi score in metastatic spinal tumour causing cord compression in a southern Chinese population." Journal of Orthopaedics, Trauma and Rehabilitation 18.1 (2014): 15-21.	Not western population
Yu W, Tang L, Lin F, Yao Y, Shen Z. Accuracy of Tokuhashi score system in predicting survival of lung cancer patients with vertebral metastasis. J Neurooncol. 2015 Nov;125(2):427-33. doi: 10.1007/s11060-015-1934-7. Epub 2015 Sep 16. PMID: 26376655.	Not western population
Zang S, He Q, Bao Q, Shen Y, Zhang W. Establishment and validation of a novel survival prediction scoring algorithm for patients with non-small-cell lung cancer spinal metastasis. Int J Clin Oncol. 2019 Sep;24(9):1049-1060. doi: 10.1007/s10147-019-01452-8. Epub 2019 Apr 26. PMID: 31028506.	Not western population
Park SJ, Park JS, Kang DH, Lee CS. Which Prognostic Model Best Predicts Poor Prognosis in Patients with Spinal Metastases? A Comparative Analysis of 8 Scoring Systems. World Neurosurgery. 2025 Jan 1;193:553-66.	Only surgically treated patients included
Li Z, Wei F, Hu J, Zhang Y, Niu X, Li P, Tang X, Yao W, Luo S, Zhang P. Predicting Survival Outcomes in Renal Cell Carcinoma Spinal Metastases: A Multicenter Evaluation of Existing Prognostic Systems. The Spine Journal. 2025 May 8.	No western population
Ghaith AK, Yang X, Khalilullah T, Wang X, Alfonzo Horowitz M, Khalifeh J, Ahmed AK, Azad T, Weinberg J, Al-Mistarehi AH, Foster C. Histology-Specific Treatment Strategies and Survival Prediction in Lung Cancer Patients with Spinal Metastases: A Nationwide Analysis. Cancers. 2025 Apr 21;17(8):1374.	Wrong study population
Bartels R, de Bree K, Pazira H, van Bilsen M, Jonker M, de Ruiter G, Arts MP, Westhoff P. Prediction of Survival among patients Suffering from Spinal Metastases: A Prospective, Multicenter Validation Study. Multicenter Validation Study.	Only abstract available
Li L, Wu S, Han JC, Kuang X, Su LZ, Zhang XQ, Cui QT, Zhang XY. Prognostic Value of Lumbar Muscle Morphometrics for Survival of Patients with Spinal Metastasis: A Systematic Review and Meta-analysis. World Neurosurgery. 2025 Mar 31:123953.	Wrong study design
Sharif S, Afsar A, Zileli M, Vaishya S, Gokaslan Z. Outcome prediction, quality of life, and life expectancy in metastatic spine tumors: WFNS spine committee recommendation. Neurosurgical Review. 2025 Feb 3;48(1):160.	Background article
Kang DH, Park JS, Kang M, Jung K, Lee CS, Park SJ. Which Scoring System Best Predicts Long-term Survival among patients with Spinal Metastasis in the Era of Targeted Systemic Treatment? A Comparative Study of Eight Prognostic Models. Spine. 2024:10-97.	Not western population
Trathitephun W, Arunwatthanangkul P, Pakmanee N, Kamolpak J, Wanitchakorn S, Pichyangkul M, Tweeatsani N, Suvithayasiri S. Assessment of survival prediction after surgery in spinal metastases patients using the Global Spine Study Tumor Group (GSTSG) risk calculator; an external validation from a tertiary cancer hospital. European Spine Journal. 2024 Nov;33(11):4336-45.	Not western population
Zijlstra H, Kuijten RH, Bhimavarapu AV, Lans A, Cross RE, Alnasser A, Karhade AV, Verlaan JJ, Groot OQ, Schwab JH. Temporal validation of the SORG 90-Day and 1-Year machine learning algorithms for survival of patients with spinal metastatic disease. European Spine Journal. 2024 Dec 5:1-0.	Only surgically treated patients included
Yen HK, Lin WH, Groot OQ, Chen CW, Yang JJ, Bongers ME, Karhade A, Shah A, Yang TC, Bindels BJ, Dai SH. Comparison of Classically and Machine Learning Generated Survival Prediction Models for Patients With Spinal Metastasis-A meta-Analysis of Two Recently Developed Algorithms. Global spine journal. 2024 Jul 28:21925682231162817.	Only surgically treated patients included
alidation of Novel Predictive Score for Patients With Spinal Metastases (NCT03224650)	Trial registry, no results

1a. Overview of the input variables needed for each of the twelve externally validated survival prediction models

	Bollen	Modified Bauer	Mizumoto	NESMS
Number of input variables	3	3	7	5
Demographics
Age			<71/≥71 (years)
BMI
Sex
Clinical status
Functional status	KPS: 80-100/10-70		ECOG: 0-2/3-4	Intact or impaired: Non-ambulatory:
Neurologic status
Comorbidities
Oncologic Status
Visceral or brain metastases	Yes/No	Yes/No	Yes/No
Extraspinal bone metastases		Solitary/Multiple^d	Solitary/Multiple^d
Spinal bone metastases		Solitary/Multiple^d	Solitary/Multiple^d
Lymphatic metastases
Pathologic fracture
Previous therapies			Chemo: Yes/No
Primary tumor type	Unfavorable/ Moderate/ Favorable (Tomita)^a	Lung: Yes/No Breast, kidney, lymphoma, or multiple myeloma: Yes/No	OC^c
Other				Modified Bauer ≥3/<3
Laboratory values
Abs lymphocytes
Abs neutrophils
Albumin				<3.5/≥3.5 g/dL
Alkaline phosphatase
C-reactive protein
Calcium			≤10/>10 mg/dL
Creatinine
Hemoglobin
INR
LDH
Platelet count
Total bilirubin
WBC
_{Abbreviations: Abs = absolute, BMI = Body mass index, Chemo = chemotherapy, ECOG = Eastern Cooperative Oncology Group performance status, INR = Internationalized Normalized Ratio, KPS = Karnofsky Performance Score, LDH = lactate dehydrogenase, NESMS = New England Spinal Metastasis Score, WBC = white blood cell count, OC = own classification.} _{^aSlow = Breast, prostate, thyroid, multiple myeloma, malignant lymphoma. Moderate = Renal, endometrial and ovarian, sarcoma, and others. Rapid = Lung, colorectal, gastric, pancreatic, head and neck, esophageal, nonrenal urological, melanoma, hepatocellular, gallbladder, cervical, and cancers of unknown origin.} _{^bBreast, renal, lung (any), prostate, myeloma, gastric, sarcoma, other specified, or other/unknown.} _{^cFavorable = Breast, prostate, lymphoma, and thyroid (except anaplastic cancer). Unfavorable = Others.} _{^dAll bone metastases were combined as input variable.}

1b. Overview of the input variables needed for each of the twelve externally validated survival prediction models

	Original Bauer	OSRI	PathFx	Revised Katagiri
Number of input variables	4	2	11	11
Demographics
Age			Num (years)
BMI
Sex			Male/Female
Clinical status
Functional status		KPS: 80-100/50-70/10-40	ECOG: 1/2/3/4	ECOG: 1-2/3-4
Neurologic status
Comorbidities
Oncologic Status
Visceral or brain metastases	Yes/No		Yes/No	None/ Nodular visceral or cerebral/ Disseminated^a
Extraspinal bone metastases	Solitary/Multiple^f		Solitary/Multiple^f	Solitary/Multiple^f
Spinal bone metastases	Solitary/Multiple^f		Solitary/Multiple^f	Solitary/Multiple^f
Lymphatic metastases			Yes/No
Pathologic fracture	Yes/No		Yes/No
Previous therapies				Chemo: Yes/No
Primary tumor type	Lung: Yes/No Breast, kidney, lymphoma or multiple myeloma: Yes/No	Slow/ Moderate/ Rapid/ Very rapid (OC)^c	OC^d	Slow/Moderate/ Rapid (Katagiri)^b
Other			Survival estimate: 1-36 months
Laboratory values
Abs lymphocytes			Num (K/uL)
Abs neutrophils
Albumin				Normal/Abnormal/Critical^e
Alkaline phosphatase
C-reactive protein				Normal/Abnormal/Critical^e
Calcium				Normal/Abnormal/Critical^e
Creatinine
Hemoglobin			Num (g/dL)
INR
LDH				Normal/Abnormal/Critical^e
Platelet count				Normal/Abnormal/Critical^e
Total bilirubin				Normal/Abnormal/Critical^e
WBC
_{Abbreviations: Abs = absolute, BMI = Body mass index, Chemo = chemotherapy, ECOG = Eastern Cooperative Oncology Group performance status, INR = Internationalized Normalized Ratio, KPS = Karnofsky Performance Score, LDH = lactate dehydrogenase, Num = numerical variable, OC = own classification, OSRI = Oswestry Spinal Risk Index, WBC = white blood cell count.} _{^aDisseminated = pleural, peritoneal, or leptomeningeal.} _{^bSlow = Hormone dependent breast and prostate, thyroid, multiple myeloma, malignant lymphoma. Moderate = Lung cancer treated with molecularly targeted drugs, hormone independent breast and prostate, renal, endometrial and ovarian, sarcoma, and others. Rapid = Lung cancer without molecularly targeted drugs, colorectal, gastric, pancreatic, head and neck, esophageal, nonrenal urological, melanoma, hepatocellular, gallbladder, cervical, and cancers of unknown origin.} _{^cSlow = Breast, thyroid, prostate, myeloma, haemangioma, endothelioma, non-Hodgkins lymphoma. Moderate = Kidney, uterus, tonsils, epipharynx, synovial cell sarcoma, metastatic thymoma. Rapid = Stomach, colon, liver, melanoma, teratoma, sigmoid colon, pancreas, rectum, unknown origin. Very rapid = Lung.} _{^dBladder, breast, colorectal, gastric, kidney/renal, liver/hepatocellular, lung (non-small cell), lung (small cell), lung (unknown), lymphoma, melanoma, myeloma, nasopharyngeal, thyroid, prostate, or unknown/other.} _{^eAbnormal = CRP > 4 mg/dL, LDH > 250 IU/L, or Albumin < 3.7 g/dL. Critical = Platelets < 100.000/dL, Calcium ≥ 10.3 mg/dL, or total bilirubin ≥1.4 mg/dL. *All bone metastases were combined for input.} _{^fAll bone metastases were combined as input variable.}

1c. Overview of the input variables needed for each of the twelve externally validated survival prediction models

	Revised Tokuhashi	SORG-MLA	Tomita	Van der Linden
Number of input variables	6	18	3	3
Demographics
Age
BMI		Num (kg/m2)
Sex
Clinical status
Functional status	KPS: 80-100/50-70/10-40	ECOG: 0-2/3-4		KPS: 80-100/50-70/20-40
Neurologic status	Frankel: A-B/C-D/E	ASIA: A-D/E
Comorbidities		Any other Charlson comorbidity: Yes/No
Oncologic Status
Visceral or brain metastases	Unresectable/ Resectable/ Absent	Yes/No	None/ Treatable/ Untreatable	Yes/No
Extraspinal bone metastases	0/1-2/≥3		Solitary or isolated/ Multiple^e
Spinal bone metastases	1/2/≥3	≥3: Yes/No	Solitary or isolated/ Multiple^e
Lymphatic metastases
Pathologic fracture
Previous therapies		Systemic therapy: Yes/No
Primary tumor type	OC^a	Slow/Moderate/ Rapid (Katagiri)^b	Slow/Moderate/Rapid (OC)^c	OC^d
Other
Laboratory values
Abs lymphocytes		Num (x10³/uL)
Abs neutrophils		Num (x10³/uL)
Albumin		Num (g/dL)
Alkaline phosphatase		Num (IU/L)
C-reactive protein
Calcium		Num (mg/dL)
Creatinine		Num (mg/dL)
Hemoglobin		Num (g/dL)
INR		Num (ratio)
LDH
Platelet count		Num (x10³/uL)
Total bilirubin
White blood cells		Num (x10³/uL)
_{Abbreviations: Abs = absolute, BMI = Body mass index, ECOG = Eastern Cooperative Oncology Group performance status, INR = Internationalized Normalized Ratio, KPS = Karnofsky Performance Score, LDH = lactate dehydrogenase, Num = numerical variable, OC = own classification, SORG-MLA = Skeletal Oncology Research Group Machine Learning Algorithm, WBC = white blood cell count.} _{^aLung, osteosarcoma, stomach, bladder, esophagus, or pancreas; Liver, gallbladder, or unknown; Others; Kidney or uterus; Thyroid, breast, prostate, or carcinoid.} _{^bSlow = Hormone dependent breast and prostate, thyroid, multiple myeloma, malignant lymphoma. Moderate = Lung cancer treated with molecularly targeted drugs, hormone independent breast and prostate, renal, endometrial and ovarian, sarcoma, and others. Rapid = Lung cancer without molecularly targeted drugs, colorectal, gastric, pancreatic, head and neck, esophageal, nonrenal urological, melanoma, hepatocellular, gallbladder, cervical, and cancers of unknown origin. ^cSlow = Breast, prostate, thyroid, multiple myeloma, malignant lymphoma. Moderate = Renal, endometrial and ovarian, sarcoma, and others. Rapid = Lung cancer, colorectal, gastric, pancreatic, head and neck, esophageal, nonrenal urological, melanoma, hepatocellular, gallbladder, cervical, and cancers of unknown origin.} _{^dBreast, prostate, lung, or other.} _{^eAll bone metastases were combined as input variable.}

Beoordelingsdatum en geldigheid

Publicatiedatum : 05-06-2026

Beoordeeld op geldigheid : 05-06-2026

Initiatief en autorisatie

Initiatief:

Nederlandse Vereniging voor Neurologie

Geautoriseerd door:

Nederlandse Federatie van Kankerpatiëntenorganisaties
Nederlandse Internisten Vereniging
Nederlandse Orthopaedische Vereniging
Nederlandse Vereniging voor Anesthesiologie
Nederlandse Vereniging van Artsen voor Longziekten en Tuberculose
Nederlandse Vereniging voor Neurologie
Nederlandse Vereniging voor Nucleaire geneeskunde
Nederlandse Vereniging voor Radiotherapie en Oncologie
Nederlandse Vereniging voor Radiologie
Stichting Darmkanker
Verpleegkundigen en Verzorgenden Nederland
Nederlandse Vereniging van Revalidatieartsen

Algemene gegevens

De ontwikkeling/herziening van deze richtlijnmodule werd ondersteund door het Kennisinstituut van de Federatie Medisch Specialisten (www.demedischspecialist.nl/kennisinstituut) en werd gefinancierd door de Stichting Kwaliteitsgelden Medisch Specialisten (SKMS). De financier heeft geen enkele invloed gehad op de inhoud van de richtlijnmodule.

Samenstelling werkgroep

Voor het ontwikkelen van de richtlijnmodule is in 2023 een multidisciplinaire werkgroep ingesteld, bestaande uit vertegenwoordigers van alle relevante specialismen (zie hiervoor de Samenstelling van de werkgroep) die betrokken zijn bij de zorg voor patiënten met wervelmetastasen.

Werkgroep

dr. W. (Walter) Taal (voorzitter), neuroloog Erasmuc MC, Nederlandse Vereniging voor Neurologie
drs. L. (Lena) van Iterson, AIOS-neuroloog Elisabeth-TweeSteden Ziekenhuis, Nederlandse Vereniging voor Neurologie
drs. R.P.B. (Robin) Boltjes, neuroloog Antoni van Leeuwenhoek Ziekenhuis, Nederlandse Vereniging voor Neurologie
Prof. dr. JJ. (Jorrit-Jan) Verlaan, Orthopedisch chirurg UMC Utrecht, Nederlandse Orthopaedische Vereniging
dr. J. (Jasper) van Tiel, Orthopedisch chirurg UMC Utrecht, Nederlandse Orthopaedische Vereniging
dr. V. (Vivian) Bongers, Nucleaire geneeskunde Diakonessenhuis Utretch, Nederlandse Vereniging voor Nucleaire Geneeskunde
Prof. dr. R. (Ronald) Bartels, Neurochirurg Radboudumc, Nederlandse Vereniging voor Neurochirurgie
dr. S.O. (Selma) Algra, Radioloog UMC Utrecht, Nederlandse Vereniging voor Radiologie
drs. M.G.A. (Maaike) Schippers, radiotherapeut Instituut Verbeeten, Nederlandse Vereniging voor Radiotherapie en Oncologie
dr. J.M. (Joanne) van der Velden, radiotherapeut UMC Utrecht, Nederlandse Vereniging voor Radiotherapie en Oncologie
dr. M.S. (Marthe) Paats, longarts Erasmus MC, Nederlandse Vereniging voor Artsen voor Longziekten en TBC
dr. P.F. (Paula) Ypma, Internist hematoloog Haga Ziekenhuis, Nederlandse Internisten Vereniging
dr. F.Y.F.L. (Filip) de Vos, internist-oncoloog en kaderarts palliatieve zorg UMC Utrecht, Nederlandse Internisten Vereniging
dr. M. (Marije) Vos- van der Hulst, revalidatiearts Sint Maartenskliniek, Nederlandse Vereniging van Revalidatieartsen (vanaf oktober 2025)
Mevr. S (Silvie) Dronkers^†, patiëntvertegenwoordiger, Stichting Darmkanker (tot oktober 2025)
dr. T.A.R. (Tebbe) Sluis^†, Revalidatiearts Rijndam, Nederlandse Vereniging van Revalidatieartsen (tot mei 2025)

Klankbordgroep

Mevr. Manon Immerzeel, Verpleegkundig specialist Reinier de Graaf ziekenhuis, Verpleegkundigen en Verzorgenden Nederland
drs. A. (Anita) Ophof, anesthesioloog Antoni van Leeuwenhoek Ziekenhuis, Nederlandse Vereniging voor Anesthesiologie

Met dank aan

dr. J.H. (Jurgen) Runge, interventieradioloog, UMC Groningen, Nederlandse Vereniging voor Radiologie

Met ondersteuning van

dr. J. (Josefien) Buddeke, senior adviseur, Kennisinstituut van de Federatie Medisch Specialisten (vanaf juli 2024)
dr. L. (Linda) Oostendorp, senior adviseur, Kennisinstituut van de Federatie Medisch Specialisten (tot juli 2024)
drs. B. (Beatrix) Vogelaar, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
dr. J. (Jing) de Haan-Du, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
drs. D. (Danique) Middelhuis, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
drs. A. (Alies) Oost, informatiespecialist, Kennisinstituut van de Federatie Medisch Specialisten

Belangenverklaringen

Een overzicht van de belangen van werkgroepleden en het oordeel over het omgaan met eventuele belangen vindt u in onderstaande tabel. De ondertekende belangenverklaringen zijn op te vragen bij het secretariaat van het Kennisinstituut van de Federatie Medisch Specialisten via secretariaat@kennisinstituut.nl.

Gemelde (neven)functies en belangen werkgroep

Naam WERKGROEP	Hoofdfunctie	Nevenwerkzaamheden	Persoonlijke Financiele_Belangen	Persoonlijke Relaties	Extern Gefinancierd Onderzoek	Intellectuele Belangen Reputatie	Overige Belangen	Datum	Acties
Jasper van Tiel	Orthopedisch chirurg UMC Utrecht en Acibadem IMC	geen	geen	geen	geen	geen	geen	22-11-2023	Geen restrictie
Joanne van der Velden	Radiotherapeut bij het UMC Utrecht, betaald	Bestuurslid bij het Landelijk Platform Palliatieve Radiotherapie (NVRO), onbetaald	Geen	Geen	Deelname aan 2 extern gefinancierde onderzoeken, zie onder KWF Kankerbestrijding PRESENT+: merging and expanding cohorts into a national realworld prospective cohort to improve symp ZonMw The BLEND trial – stereotactic body radiotherapy followed by surgical stabilization within 24 hours	Verwerven van erkenning speelt mee aan mijn deelname aan de werkgroep richtlijn Wervelmetastasen	Geen overige belangen	28-12-2023	Geen restrictie
Jorrit-Jan Verlaan	Orthopedisch chirurg, UMC Utrecht (0.4 Fte) Co-founder SentryX (www.sentryx.nl), chief medical officer (0.6 Fte). Als CMO ben ik verantwoordelijk voor het medische/klinische gedeelte van de taken binnen de start-up. We ontwikkelen 'implantable anesthetics'; oplosbare slow-release depots, met een lokaal anestheticum als actieve stof, voor de behandeling van postoperatieve pijn.	Lid steering committee AO Spine Knowledge Forum Tumor (onbetaald maar met onkosten vergoeding).	Hoe de richtlijn wordt vormgegeven staat los van mijn persoonlijke financiële belangen. Er zijn ook geen belangen voor SentryX hoe de richtlijn wordt vormgegeven.	geen	Ja. EU METASTRA: Predictieve modellen, AI, wervelmetastasen ZonMW BLEND RCT: Radiotherapie en chirurgie voor wervelmetastasen combineren op dezelfde dag Hanarth Fonds PREVECAIMM: Predictieve modellen, AI, wervelmetastasen KWF CODED: Ontwikkeling hemostatische hydrogel voor glioblastoom chirurgie Philips PhD Project: Navigatie in spinale chirurgie	Ik heb nationale/internationale expertise/reputatie en een leerstoel op het gebied van de behandeling van wervelmetastasen. Een goed uitgevoerde richtlijn kan helpen deze expertise/reputatie meer exposure te geven maar de impact en eventuele belangenverstrengeling zijn mij onduidelijk.	geen	22-11-2023	Geen restrictie. Geen penvoerder bij module 'Inschatten overleving'.
Filip de Vos	Internist-oncoloog en kaderarts palliatieve zorg UMC Utrecht	geen	geen	geen	ja Foundation STOPbraintumors.org effect tumorgroei bij zwangerschap bij vrouwen met laaggradige gliomen BMS BET remmer in combinatie met standaard chemoradiatie als eerste lijnbehandeling bij glioblastoom Novartis LAG remmer na falen immuuntherapie bij solide tumoren EORTC marizomib bij standaard chemoradiatie bij glioblastoom Pfizer en Ipsen Pharma compassionate use medicatie	geen	BMS Advisory Board; Faculty member ESMO CNS tumors; Quality of Care commission Dutch Society of Medical Oncology; Quality Assurance commission EORTC	20-12-2023	Geen restrictie. (In de richtlijn worden geen systemische therapien aanbevolen.)
Maaike Schippers	Radiotherapeut Werkgever: Helios	geen	geen	geen	geen	geen	geen	3-12-2023	Geen restrictie
Marthe Paats	Longarts Erasmus MC	geen	Geen relevant voor huidige richtlijn. Vergoedingen ten alle tijden naar werkgever Betaalde adviesraden in afgelopen 3 jaar: Eli Lilly: internationale adviesraad EGFR+ NSCLC Amgen: adviesraad KRAS G12C+ NSCLC Pfizer: adviesraad TKI's in NSCLC Merck: adviesraad MET exon 14 skipping mutatie + NSCLC J&J: adviesraad EGFR exon 20 mutaties in NSCLC	geen	industrie gesponsorde studies lopend in het Erasmus MC waarbij ik lokale PI ben. Geen relevant voor huidige richtlijn. Vergoedingen ten alle tijden naar werkgever Astra Zeneca ORCHARD studie (fase 2 studie, progressie na 1L osimertinib) Abbvie M16-573 (fase 1 studie ABBV-155 +/- taxane in NSCLC/SCLC/mammaca) Navire Pharma Inc. NAV-1003 (fase 1 studie met BBP-398 en sotorasib bij KRAS G12C+ NSCLC) GSK NY-ESO (fase 1 studie NY-ESO TCR)	geen	geen	26-02-2024	Geen restrictie. In de richtlijn worden geen systemische therapien aanbevolen.
Robin Boltjes	Neuroloog in Antoni van Leeuwenhoek/NKI	geen	geen	nee	geen	geen	nee	22-11-2023	Geen restrictie
Ronald Bartels	Neurochirurg Radboudumc te Nijmegen	Medisch Adviseur	geen	nee	geen	net ontwikkelaar van een predictiemodel dat genoemd wordt in richtlijn	geen	03-04-2024	Restrictie ten aanzien van besluitvorming betreffende 'Inschatten overleving'. Vanuit expertise wel meegediscussierd over inhoud van de module, niet betrokken bij het formuleren van de aanbevelingen.
Tebbe Sluis	revalidatiearts Rijndam	geen	geen	geen	geen	geen	geen	11-12-2023	Geen restrictie
Vivian Bongers	MSB Domstad, medisch specialist	Uitgeverij Prelum, Redacteur tijdschrift IMAGO	Geen	Geen	Geen	Geen	Geen	23-11-2023	Geen restrictie
Ypma	internist hematoloog Hagaziekenhuis den Haag	geen	geen	geen	Alphabet trial sponsor Sanquin; gerandomiserd onderzoek naar3-versus5-donoren bloedplaatjesconcentraat	geen	nvt	04-05-2024	Geen restrictie
Van Iterson	AIOS neurologie ETZ Tilburg	geen	geen	geen	geen	geen	geen	25-04-2024	Geen restrictie
Selma Algra	Radioloog,St Jansdal Ziekenhuis	geen	geen	geen	geen	geen	geen	03-09-2024	Geen resctrictie
Silvie Dronkers	Stichting Darmkanker vrijwilliger team PPO (patiëntenparticipatie bij wetenschappelijk onderzoek)	geen	geen	geen	geen	geen	geen	06-02-2025	Geen restrictie
Walter Taal (voorzitter)	Neuroloog, Erasmus MC, Rotterdam	Geen	Geen	Geen	Ja. Alleen op het gebied van neurofibromatose type 1 Let's beat NF (Stichting NF) MEK remmers bij NF1 NFVN (NF ver Ned) MEK remmers bij NF1 Novartis MEK remmers bij NF1	Geen	Geen	07-06-2023	Geen restrictie
Marije Vos-van der Hulst	Revalidatie arts, Sint Maartenskliniek Nijmegen	Voorzitter werkgroep revalidatie artsen dwarslaesie (Nederlands Vlaams dwarslaesie genootschap= werkgroep van de vereniging revalidatieartsen nederland (VRA))	geen	geen	geen	geen	geen	13-10-2025	Geen restrictie
Naam KLANKBORDGROEP	Hoofdfunctie	Nevenwerkzaamheden	Persoonlijke Financiele_Belangen	Persoonlijke Relaties	Extern Gefinancierd Onderzoek	Intellectuele Belangen Reputatie	Overige Belangen	Datum	Acties
Manon Immerzeel	Deelnemer clusterstuurgroep	Geen	Geen	Geen	Geen	Voorzitter in het bestuur van V&VN pijnverpleegkundigen	Neen	22-03-2022	Geen restrictie
Anita Ophof	Antoni van Leeuwenhoek Ziekenhuis Anesthesioloog Pijnspecialist	Geen	Geen	Geen	Geen	Geen	Geen	01-05-2025	Geen restrictie

Inbreng patiëntenperspectief

Kwalitatieve raming van mogelijke financiële gevolgen in het kader van de Wkkgz

Bij de richtlijnmodule voerde de werkgroep conform de Wet kwaliteit, klachten en geschillen zorg (Wkkgz) een kwalitatieve raming uit om te beoordelen of de aanbevelingen mogelijk leiden tot substantiële financiële gevolgen. Bij het uitvoeren van deze beoordeling is de richtlijnmodule op verschillende domeinen getoetst (zie het stroomschema bij Werkwijze).

De kwalitatieve raming is toegevoegd aan het einde van elke herziene module.

Module	Uitkomst raming	Toelichting
Assessment of survival prognosis	Geen substantiële financiële gevolgen	Hoewel uit de toetsing volgt dat de aanbevelingen breed toepasbaar zijn (5.000-40.000 patiënten), volgt ook uit de toetsing dat het geen nieuwe manier van zorgverlening of andere organisatie van zorgverlening betreft. Er worden daarom geen substantiële financiële gevolgen verwacht.

Werkwijze

Voor meer details over de gebruikte richtlijnmethodologie verwijzen wij u naar de Werkwijze. Relevante informatie voor de ontwikkeling/herziening van deze richtlijnmodule is hieronder weergegeven.

Zoekverantwoording

Algemene informatie

Cluster/richtlijn: NVN Wervelmetastasen
Uitgangsvraag/modules: UV8 Hoe is op basis van een pakket aan factoren zo nauwkeurig mogelijk de overleving in te schatten bij patiënten met wervelmetastasen die in aanmerking komen voor een operatie en/of bestraling?
Database(s): Embase.com, Ovid/Medline	Datum: 28 juni 2024, 15-7-2025
Periode: vanaf 2014	Talen: geen restrictie
Literatuurspecialist: Alies Oost	Rayyan review: https://rayyan.ai/reviews/1078463
BMI-zoekblokken: voor verschillende opdrachten wordt (deels) gebruik gemaakt van de zoekblokken van BMI-Online https://blocks.bmi-online.nl/ Deduplication: voor het ontdubbelen is gebruik gemaakt van http://dedupendnote.nl/
Toelichting: 15-7-2025 Er is een update gedraaid vanaf 1-6-2024. Het resultaat is ontdubbeld t.o.v. het vorige resultaat. De studie: ‘External validation of 12 existing survival prediction models for patients with spinal metastases’wordt gevonden in het resultaat. 28-6-2024 Voor deze vraag is gezocht op de elementen: wervelmetastasen overleving prognostisch filter (predictiemodellen) De sleutelartikelen worden gevonden met deze search.
Te gebruiken voor richtlijntekst: In de databases Embase.com en Ovid/Medline is op 15-7-2025 systematisch gezocht naar studies over het inschatten van overleving bij patiënten met wervelmetastasen. De literatuurzoekactie leverde 1519 unieke treffers op.

Zoekopbrengst

15-7-2025	EMBASE	OVID/MEDLINE	Ontdubbeld
Totaal	224	90	215
28-6-2024	EMBASE	OVID/MEDLINE	Ontdubbeld
SR	55	25	58
RCT	193	82	236
Observationele studies	934	469	956
Overig	54	61	54
Totaal	1236	637	1304*

_{*in Rayyan}

Zoekstrategie

Embase.com (Update 15 juli 2025)

No.	Query	Results
#1	'spine metastasis'/exp OR 'spinal cord metastasis'/exp OR 'cervical lymph node metastasis'/exp OR (('spinal cord tumor'/exp OR 'spine tumor'/exp OR 'spinal cord compression'/exp OR (((spinal* OR medulla) NEAR/3 (compress OR impingement OR pinch)):ti,ab,kw)) AND ('metastasis'/de OR 'bone metastasis'/de OR metasta:ti,ab,kw OR oligometasta:ti,ab,kw OR micrometasta:ti,ab,kw OR (((neoplas* OR carcinoma OR cancer* OR malignan* OR tumor* OR tumour) NEAR/4 (dissemination OR disseminated OR spread OR secondary OR migrat* OR seed)):ti,ab,kw))) OR (((spine OR spinal* OR intraspinal OR vertebr* OR 'cauda equina' OR cervicothoracic OR cord* OR coccyx OR duralsac* OR 'dural sac' OR epidural OR extradural OR 'extra dural' OR intervertebr OR lumbar OR lumbosac* OR 'lumbo sac' OR orthothoracic OR sacral OR sacrum OR 'thecal sac' OR thoracolumbar OR odontoid OR 'anterior horn' OR 'posterior horn' OR 'extrapyramidal tract' OR 'pyramidal tract' OR 'substantia gelatinosa' OR 'spinothalamic tract') NEAR/4 (metast OR oligometast* OR micrometast)):ti,ab,kw) OR ((cervical:ti,ab,kw OR medulla:ti,ab,kw OR intramedulla:ti,ab,kw OR thoracic:ti,ab,kw) AND (spine:ti,ab,kw OR spinal:ti,ab,kw OR intraspinal:ti,ab,kw OR vertebr:ti,ab,kw OR intervertebr:ti,ab,kw OR lumbar:ti,ab,kw) AND (metast:ti,ab,kw OR oligometast:ti,ab,kw OR micrometast*:ti,ab,kw)) OR mescc:ti,ab,kw OR mscc:ti,ab,kw
#2	'survival'/exp OR 'mortality'/exp OR 'cancer prognosis'/exp OR 'scoring system'/exp OR survival:ti,ab,kw OR mortalit:ti,ab,kw OR ((life NEAR/3 (expect OR estimat* OR prognos* OR exten*)):ti,ab,kw)	4236149
#3	'area under the curve'/exp OR 'brier score'/exp OR 'computer prediction'/exp OR 'c statistic'/exp OR 'c statistics'/exp OR 'integrated discrimination improvement'/exp OR 'net reclassification improvement'/exp OR 'net reclassification index'/exp OR 'prediction'/exp OR 'predictive model'/exp OR 'predictive modeling'/exp OR 'predictive validity'/exp OR 'predictive value'/exp OR 'regression analysis'/exp OR 'statistical model'/exp OR 'area under the curve':ti,ab,kw OR 'brier score':ti,ab,kw OR 'c statistic' OR 'computer prediction':ti,ab,kw OR 'decision curve anal':ti,ab,kw OR (('net reclassification' NEAR/2 (improvement OR index)):ti,ab,kw) OR (((predict OR statistical) NEAR/3 (model OR validity OR value)):ti,ab,kw) OR 'proportional hazards model':ti,ab,kw OR 'r square':ti,ab,kw OR regression:ti,ab,kw OR predict:ti OR multivariate:ti,ab,kw OR multivariab:ti,ab,kw	3513945
#4	#1 AND #2 AND #3 NOT (('conference abstract'/it OR 'editorial'/it OR 'letter'/it OR 'note'/it) NOT 'clinicaltrial':dtype) NOT (('animal'/exp OR 'animal experiment'/exp OR 'animal model'/exp OR 'nonhuman'/exp) NOT 'human'/exp) NOT (('adolescent'/exp OR 'child'/exp OR adolescent:ti,ab,kw OR child:ti,ab,kw OR schoolchild:ti,ab,kw OR infant:ti,ab,kw OR girl:ti,ab,kw OR boy:ti,ab,kw OR teen:ti,ab,kw OR teens:ti,ab,kw OR teenager:ti,ab,kw OR youth:ti,ab,kw OR pediatr:ti,ab,kw OR paediatr:ti,ab,kw OR puber:ti,ab,kw) NOT ('adult'/exp OR 'aged'/exp OR 'middle aged'/exp OR adult:ti,ab,kw OR man:ti,ab,kw OR men:ti,ab,kw OR woman:ti,ab,kw OR women:ti,ab,kw))	1688
#5	#4 AND [01-06-2024]/sd	224
#6	'meta analysis'/exp OR 'meta analysis (topic)'/exp OR metaanaly:ti,ab OR 'meta analy':ti,ab OR metanaly:ti,ab OR 'systematic review'/de OR 'cochrane database of systematic reviews'/jt OR prisma:ti,ab OR prospero:ti,ab OR (((systemati OR scoping OR umbrella OR 'structured literature') NEAR/3 (review* OR overview)):ti,ab) OR ((systemic NEAR/1 review):ti,ab) OR (((systemati OR literature OR database* OR 'data base') NEAR/10 search):ti,ab) OR (((structured OR comprehensive* OR systemic) NEAR/3 search):ti,ab) OR (((literature NEAR/3 review):ti,ab) AND (search:ti,ab OR database:ti,ab OR 'data base':ti,ab)) OR (('data extraction':ti,ab OR 'data source':ti,ab) AND 'study selection':ti,ab) OR ('search strategy':ti,ab AND 'selection criteria':ti,ab) OR ('data source':ti,ab AND 'data synthesis':ti,ab) OR medline:ab OR pubmed:ab OR embase:ab OR cochrane:ab OR (((critical OR rapid) NEAR/2 (review* OR overview* OR synthes)):ti) OR ((((critical OR rapid) NEAR/3 (review OR overview* OR synthes)):ab) AND (search:ab OR database:ab OR 'data base':ab)) OR metasynthes:ti,ab OR 'meta synthes':ti,ab	1041201
#7	'clinical trial'/exp OR 'randomization'/exp OR 'single blind procedure'/exp OR 'double blind procedure'/exp OR 'crossover procedure'/exp OR 'placebo'/exp OR 'prospective study'/exp OR rct:ab,ti OR random:ab,ti OR 'single blind':ab,ti OR 'randomised controlled trial':ab,ti OR 'randomized controlled trial'/exp OR placebo:ab,ti	4060691
#8	'major clinical study'/de OR 'clinical study'/de OR 'case control study'/de OR 'family study'/de OR 'longitudinal study'/de OR 'retrospective study'/de OR 'prospective study'/de OR 'comparative study'/de OR 'cohort analysis'/de OR ((cohort NEAR/1 (study OR studies)):ab,ti) OR (('case control' NEAR/1 (study OR studies)):ab,ti) OR (('follow up' NEAR/1 (study OR studies)):ab,ti) OR (observational NEAR/1 (study OR studies)) OR ((epidemiologic NEAR/1 (study OR studies)):ab,ti) OR (('cross sectional' NEAR/1 (study OR studies)):ab,ti)	8297412
#9	'case control study'/de OR 'comparative study'/exp OR 'control group'/de OR 'controlled study'/de OR 'controlled clinical trial'/de OR 'crossover procedure'/de OR 'double blind procedure'/de OR 'phase 2 clinical trial'/de OR 'phase 3 clinical trial'/de OR 'phase 4 clinical trial'/de OR 'pretest posttest design'/de OR 'pretest posttest control group design'/de OR 'quasi experimental study'/de OR 'single blind procedure'/de OR 'triple blind procedure'/de OR (((control OR controlled) NEAR/6 trial):ti,ab,kw) OR (((control OR controlled) NEAR/6 (study OR studies)):ti,ab,kw) OR (((control OR controlled) NEAR/1 active):ti,ab,kw) OR 'open label':ti,ab,kw OR (((double OR two OR three OR multi OR trial) NEAR/1 (arm OR arms)):ti,ab,kw) OR ((allocat NEAR/10 (arm OR arms)):ti,ab,kw) OR placebo:ti,ab,kw OR 'sham-control':ti,ab,kw OR (((single OR double OR triple OR assessor) NEAR/1 (blind* OR masked)):ti,ab,kw) OR nonrandom:ti,ab,kw OR 'non-random':ti,ab,kw OR 'quasi-experiment':ti,ab,kw OR crossover:ti,ab,kw OR 'cross over':ti,ab,kw OR 'parallel group':ti,ab,kw OR 'factorial trial':ti,ab,kw OR ((phase NEAR/5 (study OR trial)):ti,ab,kw) OR ((case* NEAR/6 (matched OR control)):ti,ab,kw) OR ((match NEAR/6 (pair OR pairs OR cohort* OR control* OR group* OR healthy OR age OR sex OR gender OR patient* OR subject* OR participant)):ti,ab,kw) OR ((propensity NEAR/6 (scor OR match)):ti,ab,kw) OR versus:ti OR vs:ti OR compar:ti OR ((compar* NEAR/1 study):ti,ab,kw) OR (('major clinical study'/de OR 'clinical study'/de OR 'cohort analysis'/de OR 'observational study'/de OR 'cross-sectional study'/de OR 'multicenter study'/de OR 'correlational study'/de OR 'follow up'/de OR cohort:ti,ab,kw OR 'follow up':ti,ab,kw OR followup:ti,ab,kw OR longitudinal:ti,ab,kw OR prospective:ti,ab,kw OR retrospective:ti,ab,kw OR observational:ti,ab,kw OR 'cross sectional':ti,ab,kw OR cross?ectional:ti,ab,kw OR multicent:ti,ab,kw OR 'multi-cent':ti,ab,kw OR consecutive:ti,ab,kw) AND (group:ti,ab,kw OR groups:ti,ab,kw OR subgroup:ti,ab,kw OR versus:ti,ab,kw OR vs:ti,ab,kw OR compar:ti,ab,kw OR 'odds ratio':ab OR 'relative odds':ab OR 'risk ratio':ab OR 'relative risk*':ab OR 'rate ratio':ab OR aor:ab OR arr:ab OR rrr:ab OR ((('or' OR 'rr') NEAR/6 ci):ab)))	15203455
#10	#5 AND #6	55
#11	#5 AND #7 NOT #10	193
#12	#5 AND (#8 OR #9) NOT (#10 OR #11)	934
#13	#5 NOT (#10 OR #11 OR #12)	54
#14	29567516:ui OR 34298515:ui OR 31781995:ui	3
#15	#5 AND #14	3
#16	#10 OR #11 OR #12 OR #13	224

28 juni 2024

No.	Query	Results
#1	'spine metastasis'/exp OR 'spinal cord metastasis'/exp OR 'cervical lymph node metastasis'/exp OR (('spinal cord tumor'/exp OR 'spine tumor'/exp OR 'spinal cord compression'/exp OR (((spinal* OR medulla) NEAR/3 (compress OR impingement OR pinch)):ti,ab,kw)) AND ('metastasis'/de OR 'bone metastasis'/de OR metasta:ti,ab,kw OR oligometasta:ti,ab,kw OR micrometasta:ti,ab,kw OR (((neoplas* OR carcinoma OR cancer* OR malignan* OR tumor* OR tumour) NEAR/4 (dissemination OR disseminated OR spread OR secondary OR migrat* OR seed)):ti,ab,kw))) OR (((spine OR spinal* OR intraspinal OR vertebr* OR 'cauda equina' OR cervicothoracic OR cord* OR coccyx OR duralsac* OR 'dural sac' OR epidural OR extradural OR 'extra dural' OR intervertebr OR lumbar OR lumbosac* OR 'lumbo sac' OR orthothoracic OR sacral OR sacrum OR 'thecal sac' OR thoracolumbar OR odontoid OR 'anterior horn' OR 'posterior horn' OR 'extrapyramidal tract' OR 'pyramidal tract' OR 'substantia gelatinosa' OR 'spinothalamic tract') NEAR/4 (metast OR oligometast* OR micrometast)):ti,ab,kw) OR ((cervical:ti,ab,kw OR medulla:ti,ab,kw OR intramedulla:ti,ab,kw OR thoracic:ti,ab,kw) AND (spine:ti,ab,kw OR spinal:ti,ab,kw OR intraspinal:ti,ab,kw OR vertebr:ti,ab,kw OR intervertebr:ti,ab,kw OR lumbar:ti,ab,kw) AND (metast:ti,ab,kw OR oligometast:ti,ab,kw OR micrometast*:ti,ab,kw)) OR mescc:ti,ab,kw OR mscc:ti,ab,kw	29236
#2	'survival'/exp OR 'mortality'/exp OR 'cancer prognosis'/exp OR 'scoring system'/exp OR survival:ti,ab,kw OR mortalit:ti,ab,kw OR ((life NEAR/3 (expect OR estimat* OR prognos* OR exten*)):ti,ab,kw)	4236149
#3	'area under the curve'/exp OR 'brier score'/exp OR 'computer prediction'/exp OR 'c statistic'/exp OR 'c statistics'/exp OR 'integrated discrimination improvement'/exp OR 'net reclassification improvement'/exp OR 'net reclassification index'/exp OR 'prediction'/exp OR 'predictive model'/exp OR 'predictive modeling'/exp OR 'predictive validity'/exp OR 'predictive value'/exp OR 'regression analysis'/exp OR 'statistical model'/exp OR 'area under the curve':ti,ab,kw OR 'brier score':ti,ab,kw OR 'c statistic' OR 'computer prediction':ti,ab,kw OR 'decision curve anal':ti,ab,kw OR (('net reclassification' NEAR/2 (improvement OR index)):ti,ab,kw) OR (((predict OR statistical) NEAR/3 (model OR validity OR value)):ti,ab,kw) OR 'proportional hazards model':ti,ab,kw OR 'r square':ti,ab,kw OR regression:ti,ab,kw OR predict:ti OR multivariate:ti,ab,kw OR multivariab:ti,ab,kw	3513945
#4	#1 AND #2 AND #3 NOT ('conference abstract'/it OR 'editorial'/it OR 'letter'/it OR 'note'/it) NOT (('animal'/exp OR 'animal experiment'/exp OR 'animal model'/exp OR 'nonhuman'/exp) NOT 'human'/exp) NOT (('adolescent'/exp OR 'child'/exp OR adolescent:ti,ab,kw OR child:ti,ab,kw OR schoolchild:ti,ab,kw OR infant:ti,ab,kw OR girl:ti,ab,kw OR boy:ti,ab,kw OR teen:ti,ab,kw OR teens:ti,ab,kw OR teenager:ti,ab,kw OR youth:ti,ab,kw OR pediatr:ti,ab,kw OR paediatr:ti,ab,kw OR puber:ti,ab,kw) NOT ('adult'/exp OR 'aged'/exp OR 'middle aged'/exp OR adult:ti,ab,kw OR man:ti,ab,kw OR men:ti,ab,kw OR woman:ti,ab,kw OR women:ti,ab,kw))	1493
#5	#4 AND [2014-2024]/py	1236
#6	'meta analysis'/exp OR 'meta analysis (topic)'/exp OR metaanaly:ti,ab OR 'meta analy':ti,ab OR metanaly:ti,ab OR 'systematic review'/de OR 'cochrane database of systematic reviews'/jt OR prisma:ti,ab OR prospero:ti,ab OR (((systemati OR scoping OR umbrella OR 'structured literature') NEAR/3 (review* OR overview)):ti,ab) OR ((systemic NEAR/1 review):ti,ab) OR (((systemati OR literature OR database* OR 'data base') NEAR/10 search):ti,ab) OR (((structured OR comprehensive* OR systemic) NEAR/3 search):ti,ab) OR (((literature NEAR/3 review):ti,ab) AND (search:ti,ab OR database:ti,ab OR 'data base':ti,ab)) OR (('data extraction':ti,ab OR 'data source':ti,ab) AND 'study selection':ti,ab) OR ('search strategy':ti,ab AND 'selection criteria':ti,ab) OR ('data source':ti,ab AND 'data synthesis':ti,ab) OR medline:ab OR pubmed:ab OR embase:ab OR cochrane:ab OR (((critical OR rapid) NEAR/2 (review* OR overview* OR synthes)):ti) OR ((((critical OR rapid) NEAR/3 (review OR overview* OR synthes)):ab) AND (search:ab OR database:ab OR 'data base':ab)) OR metasynthes:ti,ab OR 'meta synthes':ti,ab	1041201
#7	'clinical trial'/exp OR 'randomization'/exp OR 'single blind procedure'/exp OR 'double blind procedure'/exp OR 'crossover procedure'/exp OR 'placebo'/exp OR 'prospective study'/exp OR rct:ab,ti OR random:ab,ti OR 'single blind':ab,ti OR 'randomised controlled trial':ab,ti OR 'randomized controlled trial'/exp OR placebo:ab,ti	4060691
#8	'major clinical study'/de OR 'clinical study'/de OR 'case control study'/de OR 'family study'/de OR 'longitudinal study'/de OR 'retrospective study'/de OR 'prospective study'/de OR 'comparative study'/de OR 'cohort analysis'/de OR ((cohort NEAR/1 (study OR studies)):ab,ti) OR (('case control' NEAR/1 (study OR studies)):ab,ti) OR (('follow up' NEAR/1 (study OR studies)):ab,ti) OR (observational NEAR/1 (study OR studies)) OR ((epidemiologic NEAR/1 (study OR studies)):ab,ti) OR (('cross sectional' NEAR/1 (study OR studies)):ab,ti)	8297412
#9	'case control study'/de OR 'comparative study'/exp OR 'control group'/de OR 'controlled study'/de OR 'controlled clinical trial'/de OR 'crossover procedure'/de OR 'double blind procedure'/de OR 'phase 2 clinical trial'/de OR 'phase 3 clinical trial'/de OR 'phase 4 clinical trial'/de OR 'pretest posttest design'/de OR 'pretest posttest control group design'/de OR 'quasi experimental study'/de OR 'single blind procedure'/de OR 'triple blind procedure'/de OR (((control OR controlled) NEAR/6 trial):ti,ab,kw) OR (((control OR controlled) NEAR/6 (study OR studies)):ti,ab,kw) OR (((control OR controlled) NEAR/1 active):ti,ab,kw) OR 'open label':ti,ab,kw OR (((double OR two OR three OR multi OR trial) NEAR/1 (arm OR arms)):ti,ab,kw) OR ((allocat NEAR/10 (arm OR arms)):ti,ab,kw) OR placebo:ti,ab,kw OR 'sham-control':ti,ab,kw OR (((single OR double OR triple OR assessor) NEAR/1 (blind* OR masked)):ti,ab,kw) OR nonrandom:ti,ab,kw OR 'non-random':ti,ab,kw OR 'quasi-experiment':ti,ab,kw OR crossover:ti,ab,kw OR 'cross over':ti,ab,kw OR 'parallel group':ti,ab,kw OR 'factorial trial':ti,ab,kw OR ((phase NEAR/5 (study OR trial)):ti,ab,kw) OR ((case* NEAR/6 (matched OR control)):ti,ab,kw) OR ((match NEAR/6 (pair OR pairs OR cohort* OR control* OR group* OR healthy OR age OR sex OR gender OR patient* OR subject* OR participant)):ti,ab,kw) OR ((propensity NEAR/6 (scor OR match)):ti,ab,kw) OR versus:ti OR vs:ti OR compar:ti OR ((compar* NEAR/1 study):ti,ab,kw) OR (('major clinical study'/de OR 'clinical study'/de OR 'cohort analysis'/de OR 'observational study'/de OR 'cross-sectional study'/de OR 'multicenter study'/de OR 'correlational study'/de OR 'follow up'/de OR cohort:ti,ab,kw OR 'follow up':ti,ab,kw OR followup:ti,ab,kw OR longitudinal:ti,ab,kw OR prospective:ti,ab,kw OR retrospective:ti,ab,kw OR observational:ti,ab,kw OR 'cross sectional':ti,ab,kw OR cross?ectional:ti,ab,kw OR multicent:ti,ab,kw OR 'multi-cent':ti,ab,kw OR consecutive:ti,ab,kw) AND (group:ti,ab,kw OR groups:ti,ab,kw OR subgroup:ti,ab,kw OR versus:ti,ab,kw OR vs:ti,ab,kw OR compar:ti,ab,kw OR 'odds ratio':ab OR 'relative odds':ab OR 'risk ratio':ab OR 'relative risk*':ab OR 'rate ratio':ab OR aor:ab OR arr:ab OR rrr:ab OR ((('or' OR 'rr') NEAR/6 ci):ab)))	15203455
#10	#5 AND #6 - SR	55
#11	#5 AND #7 NOT #10 - RCT	193
#12	#5 AND (#8 OR #9) NOT (#10 OR #11) - observationeel	934
#13	#5 NOT (#10 OR #11 OR #12) - overig	54

Ovid/Medline (Update 15 juli 2025)

#	Searches	Results
1	((exp Spinal Neoplasms/ or exp Spinal Cord Neoplasms/ or exp Spinal Cord Compression/ or ((spinal* or medulla) adj3 (compress or impingement or pinch)).ti,ab,kf.) and (exp Neoplasm Metastasis/ or metasta.ti,ab,kf. or oligometasta.ti,ab,kf. or micrometasta.ti,ab,kf. or ((neoplas* or carcinoma or cancer* or malignan* or tumor* or tumour) adj4 (dissemination or disseminated or spread or secondary or migrat* or seed)).ti,ab,kf.)) or ((spine or spinal* or intraspinal or vertebr* or 'cauda equina' or cervicothoracic or cord* or coccyx or duralsac* or 'dural sac' or epidural or extradural or 'extra dural' or intervertebr or lumbar or lumbosac* or 'lumbo sac' or orthothoracic or sacral or sacrum or 'thecal sac' or thoracolumbar or odontoid or "Anterior Horn" or "Posterior Horn" or "Extrapyramidal Tract" or "Pyramidal Tract" or "Substantia Gelatinosa" or "Spinothalamic Tract") adj4 (metast or oligometast* or micrometast)).ti,ab,kf. or ((cervical or medulla* or intramedulla* or thoracic) and (spine* or spinal* or intraspinal or vertebr* or intervertebr* or lumbar) and (metast* or oligometast* or micrometast*)).ti,ab,kf. or mescc.ti,ab,kf. or mscc.ti,ab,kf.	15923
2	exp Survival/ or exp Survival Analysis/ or exp Survival Rate/ or exp Mortality/ or exp Life Expectancy/ or survival.ti,ab,kf. or mortalit.ti,ab,kf. or (life adj3 (expect or estimat* or prognos* or exten*)).ti,ab,kf.	2601910
3	Area Under Curve/ or exp Forecasting/ or "Predictive Value of Tests"/ or exp Multivariate Analysis/ or exp Regression Analysis/ or exp Models, Statistical/ or area under the curve.ti,ab,kf. or brier score.ti,ab,kf. or c statistic.ti,ab,kf. or computer prediction.ti,ab,kf. or decision curve anal.ti,ab,kf. or (net reclassification adj2 (improvement or index)).ti,ab,kf. or ((predict or statistical) adj3 (model or validity or value)).ti,ab,kf. or proportional hazards model.ti,ab,kf. or r square.ti,ab,kf. or regression.ti,ab,kf. or predict.ti. or multivaria.ti,ab,kf.	2807414
4	(1 and 2 and 3) not (comment/ or editorial/ or letter/) not ((exp animals/ or exp models, animal/) not humans/) not ((Adolescent/ or Child/ or Infant/ or adolescen.ti,ab,kf. or child.ti,ab,kf. or schoolchild.ti,ab,kf. or infant.ti,ab,kf. or girl.ti,ab,kf. or boy.ti,ab,kf. or teen.ti,ab,kf. or teens.ti,ab,kf. or teenager.ti,ab,kf. or youth.ti,ab,kf. or pediatr.ti,ab,kf. or paediatr.ti,ab,kf. or puber.ti,ab,kf.) not (Adult/ or adult.ti,ab,kf. or man.ti,ab,kf. or men.ti,ab,kf. or woman.ti,ab,kf. or women.ti,ab,kf.))	928
5	limit 4 to yr="2014 -Current"	722
6	meta-analysis/ or meta-analysis as topic/ or (metaanaly* or meta-analy* or metanaly).ti,ab,kf. or systematic review/ or cochrane.jw. or (prisma or prospero).ti,ab,kf. or ((systemati or scoping or umbrella or "structured literature") adj3 (review* or overview)).ti,ab,kf. or (systemic adj1 review).ti,ab,kf. or ((systemati or literature or database* or data-base) adj10 search).ti,ab,kf. or ((structured or comprehensive* or systemic) adj3 search).ti,ab,kf. or ((literature adj3 review) and (search or database* or data-base)).ti,ab,kf. or (("data extraction" or "data source") and "study selection").ti,ab,kf. or ("search strategy" and "selection criteria").ti,ab,kf. or ("data source" and "data synthesis").ti,ab,kf. or (medline or pubmed or embase or cochrane).ab. or ((critical or rapid) adj2 (review or overview* or synthes)).ti. or (((critical or rapid) adj3 (review or overview* or synthes)) and (search or database* or data-base)).ab. or (metasynthes or meta-synthes*).ti,ab,kf.	849860
7	exp clinical trial/ or randomized controlled trial/ or exp clinical trials as topic/ or randomized controlled trials as topic/ or Random Allocation/ or Double-Blind Method/ or Single-Blind Method/ or (clinical trial, phase i or clinical trial, phase ii or clinical trial, phase iii or clinical trial, phase iv or controlled clinical trial or randomized controlled trial or multicenter study or clinical trial).pt. or random.ti,ab. or (clinic adj trial).tw. or ((singl or doubl* or treb* or tripl) adj (blind$3 or mask$3)).tw. or Placebos/ or placebo.tw.	2917584
8	Epidemiologic studies/ or case control studies/ or exp cohort studies/ or Controlled Before-After Studies/ or Case control.tw. or cohort.tw. or Cohort analy$.tw. or (Follow up adj (study or studies)).tw. or (observational adj (study or studies)).tw. or Longitudinal.tw. or Retrospective.tw. or prospective.tw. or consecutive*.tw. or Cross sectional.tw. or Cross-sectional studies/ or historically controlled study/ or interrupted time series analysis/ [Onder exp cohort studies vallen ook longitudinale, prospectieve en retrospectieve studies]	5102492
9	Case-control Studies/ or clinical trial, phase ii/ or clinical trial, phase iii/ or clinical trial, phase iv/ or comparative study/ or control groups/ or controlled before-after studies/ or controlled clinical trial/ or double-blind method/ or historically controlled study/ or matched-pair analysis/ or single-blind method/ or (((control or controlled) adj6 (study or studies or trial)) or (compar* adj (study or studies)) or ((control or controlled) adj1 active) or "open label" or ((double or two or three or multi or trial) adj (arm or arms)) or (allocat adj10 (arm or arms)) or placebo* or "sham-control" or ((single or double or triple or assessor) adj1 (blind or masked)) or nonrandom* or "non-random" or "quasi-experiment" or "parallel group" or "factorial trial" or "pretest posttest" or (phase adj5 (study or trial)) or (case adj6 (matched or control)) or (match adj6 (pair or pairs or cohort* or control* or group* or healthy or age or sex or gender or patient* or subject* or participant)) or (propensity adj6 (scor or match))).ti,ab,kf. or (confounding adj6 adjust).ti,ab. or (versus or vs or compar).ti. or ((exp cohort studies/ or epidemiologic studies/ or multicenter study/ or observational study/ or seroepidemiologic studies/ or (cohort or 'follow up' or followup or longitudinal* or prospective* or retrospective* or observational* or multicent* or 'multi-cent' or consecutive).ti,ab,kf.) and ((group or groups or subgroup* or versus or vs or compar).ti,ab,kf. or ('odds ratio' or 'relative odds' or 'risk ratio' or 'relative risk' or aor or arr or rrr).ab. or (("OR" or "RR") adj6 CI).ab.))	6038851
10	5 and 6	32
11	(5 and 7) not 10	95
12	(5 and (8 or 9)) not (10 or 11)	530
13	5 not (10 or 11 or 12)	65
14	("29567516" or "34298515" or "31781995").ui.	3
15	5 and 14	3
16	10 or 11 or 12 or 13	722
17	limit 16 to dt=20240601-20260101	90

28 juni 2024

#	Searches	Results
1	((exp Spinal Neoplasms/ or exp Spinal Cord Neoplasms/ or exp Spinal Cord Compression/ or ((spinal* or medulla) adj3 (compress or impingement or pinch)).ti,ab,kf.) and (exp Neoplasm Metastasis/ or metasta.ti,ab,kf. or oligometasta.ti,ab,kf. or micrometasta.ti,ab,kf. or ((neoplas* or carcinoma or cancer* or malignan* or tumor* or tumour) adj4 (dissemination or disseminated or spread or secondary or migrat* or seed)).ti,ab,kf.)) or ((spine or spinal* or intraspinal or vertebr* or 'cauda equina' or cervicothoracic or cord* or coccyx or duralsac* or 'dural sac' or epidural or extradural or 'extra dural' or intervertebr or lumbar or lumbosac* or 'lumbo sac' or orthothoracic or sacral or sacrum or 'thecal sac' or thoracolumbar or odontoid or "Anterior Horn" or "Posterior Horn" or "Extrapyramidal Tract" or "Pyramidal Tract" or "Substantia Gelatinosa" or "Spinothalamic Tract") adj4 (metast or oligometast* or micrometast)).ti,ab,kf. or ((cervical or medulla* or intramedulla* or thoracic) and (spine* or spinal* or intraspinal or vertebr* or intervertebr* or lumbar) and (metast* or oligometast* or micrometast*)).ti,ab,kf. or mescc.ti,ab,kf. or mscc.ti,ab,kf.	15138
2	exp Survival/ or exp Survival Analysis/ or exp Survival Rate/ or exp Mortality/ or exp Life Expectancy/ or survival.ti,ab,kf. or mortalit.ti,ab,kf. or (life adj3 (expect or estimat* or prognos* or exten*)).ti,ab,kf.	2436228
3	Area Under Curve/ or exp Forecasting/ or "Predictive Value of Tests"/ or exp Multivariate Analysis/ or exp Regression Analysis/ or exp Models, Statistical/ or area under the curve.ti,ab,kf. or brier score.ti,ab,kf. or c statistic.ti,ab,kf. or computer prediction.ti,ab,kf. or decision curve anal.ti,ab,kf. or (net reclassification adj2 (improvement or index)).ti,ab,kf. or ((predict or statistical) adj3 (model or validity or value)).ti,ab,kf. or proportional hazards model.ti,ab,kf. or r square.ti,ab,kf. or regression.ti,ab,kf. or predict.ti. or multivaria.ti,ab,kf.	2596682
4	(1 and 2 and 3) not (comment/ or editorial/ or letter/) not ((exp animals/ or exp models, animal/) not humans/) not ((Adolescent/ or Child/ or Infant/ or adolescen.ti,ab,kf. or child.ti,ab,kf. or schoolchild.ti,ab,kf. or infant.ti,ab,kf. or girl.ti,ab,kf. or boy.ti,ab,kf. or teen.ti,ab,kf. or teens.ti,ab,kf. or teenager.ti,ab,kf. or youth.ti,ab,kf. or pediatr.ti,ab,kf. or paediatr.ti,ab,kf. or puber.ti,ab,kf.) not (Adult/ or adult.ti,ab,kf. or man.ti,ab,kf. or men.ti,ab,kf. or woman.ti,ab,kf. or women.ti,ab,kf.))	843
5	limit 4 to yr="2014 -Current"	637
6	meta-analysis/ or meta-analysis as topic/ or (metaanaly* or meta-analy* or metanaly).ti,ab,kf. or systematic review/ or cochrane.jw. or (prisma or prospero).ti,ab,kf. or ((systemati or scoping or umbrella or "structured literature") adj3 (review* or overview)).ti,ab,kf. or (systemic adj1 review).ti,ab,kf. or ((systemati or literature or database* or data-base) adj10 search).ti,ab,kf. or ((structured or comprehensive* or systemic) adj3 search).ti,ab,kf. or ((literature adj3 review) and (search or database* or data-base)).ti,ab,kf. or (("data extraction" or "data source") and "study selection").ti,ab,kf. or ("search strategy" and "selection criteria").ti,ab,kf. or ("data source" and "data synthesis").ti,ab,kf. or (medline or pubmed or embase or cochrane).ab. or ((critical or rapid) adj2 (review or overview* or synthes)).ti. or (((critical or rapid) adj3 (review or overview* or synthes)) and (search or database* or data-base)).ab. or (metasynthes or meta-synthes*).ti,ab,kf.	756282
7	exp clinical trial/ or randomized controlled trial/ or exp clinical trials as topic/ or randomized controlled trials as topic/ or Random Allocation/ or Double-Blind Method/ or Single-Blind Method/ or (clinical trial, phase i or clinical trial, phase ii or clinical trial, phase iii or clinical trial, phase iv or controlled clinical trial or randomized controlled trial or multicenter study or clinical trial).pt. or random.ti,ab. or (clinic adj trial).tw. or ((singl or doubl* or treb* or tripl) adj (blind$3 or mask$3)).tw. or Placebos/ or placebo.tw.	2743847
8	Epidemiologic studies/ or case control studies/ or exp cohort studies/ or Controlled Before-After Studies/ or Case control.tw. or cohort.tw. or Cohort analy$.tw. or (Follow up adj (study or studies)).tw. or (observational adj (study or studies)).tw. or Longitudinal.tw. or Retrospective.tw. or prospective.tw. or consecutive*.tw. or Cross sectional.tw. or Cross-sectional studies/ or historically controlled study/ or interrupted time series analysis/ [Onder exp cohort studies vallen ook longitudinale, prospectieve en retrospectieve studies]	4762329
9	Case-control Studies/ or clinical trial, phase ii/ or clinical trial, phase iii/ or clinical trial, phase iv/ or comparative study/ or control groups/ or controlled before-after studies/ or controlled clinical trial/ or double-blind method/ or historically controlled study/ or matched-pair analysis/ or single-blind method/ or (((control or controlled) adj6 (study or studies or trial)) or (compar* adj (study or studies)) or ((control or controlled) adj1 active) or "open label" or ((double or two or three or multi or trial) adj (arm or arms)) or (allocat adj10 (arm or arms)) or placebo* or "sham-control" or ((single or double or triple or assessor) adj1 (blind or masked)) or nonrandom* or "non-random" or "quasi-experiment" or "parallel group" or "factorial trial" or "pretest posttest" or (phase adj5 (study or trial)) or (case adj6 (matched or control)) or (match adj6 (pair or pairs or cohort* or control* or group* or healthy or age or sex or gender or patient* or subject* or participant)) or (propensity adj6 (scor or match))).ti,ab,kf. or (confounding adj6 adjust).ti,ab. or (versus or vs or compar).ti. or ((exp cohort studies/ or epidemiologic studies/ or multicenter study/ or observational study/ or seroepidemiologic studies/ or (cohort or 'follow up' or followup or longitudinal* or prospective* or retrospective* or observational* or multicent* or 'multi-cent' or consecutive).ti,ab,kf.) and ((group or groups or subgroup* or versus or vs or compar).ti,ab,kf. or ('odds ratio' or 'relative odds' or 'risk ratio' or 'relative risk' or aor or arr or rrr).ab. or (("OR" or "RR") adj6 CI).ab.))	5723983
10	5 and 6 - SR	25
11	(5 and 7) not 10 - RCT	82
12	(5 and (8 or 9)) not (10 or 11) - observationeel	469
13	5 not (10 or 11 or 12) - overig	61

Wervelmetastasen

Wervelmetastasen

Uitgangsvraag

Aanbeveling

Overwegingen

Onderbouwing

Achtergrond

Samenvatting literatuur

Zoeken en selecteren

Referenties

Evidence tabellen

Verantwoording

Beoordelingsdatum en geldigheid

Initiatief en autorisatie

Algemene gegevens

Samenstelling werkgroep

Belangenverklaringen

Inbreng patiëntenperspectief

Werkwijze

Zoekverantwoording

Bijlagen

De Federatie Medisch Specialisten maakt gebruik van cookies