Validation of the Spinal Instability Neoplastic Score: A Retrospective Analysis
Bibliographic record
Abstract
Introduction With improved survival rates of cancer patients, the incidence of spinal metastases is increasing. Spinal metastases increase the risk for pathological fractures that subsequently increase the risk of spinal instability, spinal cord compression, and neurological compromise. The Spinal Instability Neoplastic Score (SINS) was developed by the Spinal Oncology Study Group (SOSG) to assess neoplastic-related spinal instability and to provide a tool to guide referrals between the appropriate oncology specialists. Considering the multidisciplinary aspect of care of metastatic cancer patients, reliability of the SINS was tested among radiation oncologists and radiologists. Yet, validation of the SINS score has only been done using selected cases by the developers of the SINS. Therefore, the purpose of this study was to retrospectively validate the SINS in the clinical setting. Methods A retrospective database review of patients who underwent palliative surgery or radiotherapy only for the treatment of painful spinal metastases has been conducted. All patients were ambulatory (ASIA E and D) and the two cohorts were matched at the time of follow-up to eliminate neurological compromise and prognosis as indications or exclusion for surgical intervention. Demographics and oncology data were extracted from the hospital charts. The SINS score was calculated based on pretreatment imaging. Results A total of 124 patients were included for analysis. Patients in the surgical cohort were significantly younger and presented more often with a combination of back and radicular pain. The median SINS score in the surgical cohort was 11 (range 7–16) and differed significantly (< 0.001) from the median SINS score of 7 (range 2–16) in the radiation therapy cohort. Sensitivity–specificity analysis showed an optimal cut-off point of a SINS score of 9 for surgical consultation with a sensitivity of 84% and a specificity of 72.6%. The set cut-off value of 7 of the SOSG demonstrated a sensitivity of 96% and a specificity of 41.9% in this analysis. Conclusion In retrospect, a high SINS score corresponded with the indication for surgical intervention for the treatment of neoplastic-related spinal instability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".