Evidence map›Paper›PMID 34398337›Full record

SynthesisEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2021

Prognostic scores for survival as decisional support for surgery in spinal metastases: a performance assessment systematic review.

S Smeijers, B Depreitere

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Trial
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  4. Article
  5. Review
  6. Review
  7. Predictive Modeling for Spinal Metastatic Disease.Diagnostics (Basel, Switzerland) · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
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  14. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

S SmeijersDepartment of Neurosurgery, University Hospitals Leuven, Herestraat 49, 3000, Leuven, Belgium.ORCID 0000-0002-3548-1022
B DepreitereDepartment of Neurosurgery, University Hospitals Leuven, Herestraat 49, 3000, Leuven, Belgium. bart.depreitere@uzleuven.be.ORCID 0000-0002-7458-0648

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo review the evidence on the relative prognostic performance of the available prognostic scores for survival in spinal metastatic surgery in order to provide a recommendation for use in clinical practice.

methodsA systematic review of comparative external validation studies assessing the performance of prognostic scores for survival in independent cohorts was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Eligible studies were identified through Medline and Embase until May 2021. Studies were included when they compared at least four survival scoring systems in surgical or mixed cohorts across all primary tumor types. Predictive performance was assessed based on discrimination and calibration for 3-month, 1-year and overall survival, and generalizability was assessed based on the characteristics of the development cohort and external validation cohorts. Risk of bias and concern regarding applicability were assessed based on the 'Prediction model study Risk Of Bias Assessment Tool' (PROBAST).

resultsTwelve studies fulfilled the inclusion criteria and covered 17 scoring systems across 5.130 patients. Several scores suffer from suboptimal development and validation. The SORG Nomogram, developed in a large surgical cohort, showed good discrimination on 3-month and 1-year survival, good calibration and was superior in direct comparison with low risk of bias and low concern regarding applicability. Machine learning algorithms are promising as they perform equally well in direct comparison. Tokuhashi, Tomita and other traditional risk scores showed suboptimal performance.

conclusionThe SORG Nomogram and machine learning algorithms outline superior performance in survival prediction for surgery in spinal metastases. Further improvement by comparative validation in large multicenter, prospective cohorts can still be obtained. Given the heterogeneity of spinal metastases, superior methodology of development and validation is key in improving future machine learning systems.

Indexed as

Spinal NeoplasmsHumansMulticenter Studies as TopicNomogramsPrognosisProspective StudiesRetrospective StudiesMachine learningPerformance assessmentSpinal metastasisSurvival prognostic scoreSystematic review

Identifiers

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.