Survival after surgery for spinal metastases: a population-based study
Bibliographic record
Abstract
BACKGROUND: There are limited published data on population estimates of survival after spinal surgery for metastatic disease. We performed a population-based study to evaluate survival and complications among patients with cancer who underwent surgery for spinal metastases in Ontario, Canada, between 2006 and 2016. METHODS: We used health administrative databases to identify all patients who underwent surgery for spinal metastases in Ontario between Jan. 1, 2006, and Dec. 31, 2016. We assessed overall survival, mortality rates according to primary cancer lesion and complications after surgery. We contrast the results to those for a comparable cohort from 1991 to 1998. RESULTS: A total of 2646 patients (1194 women [45.1%]; mean age 62.5 yr [standard deviation 12.2 yr]) were identified. The median survival time was 236 (interquartile range 84-740) days. Mortality was highest for patients with melanoma, upper gastrointestinal cancer and lung cancer, with 50% dying within 90 days of surgery. The longest median survival times were observed for primary cancers of the thyroid (906 d) and breast (644 d), and myeloma (830 d). Overall 90-day and 1-year mortality rates were 29% and 59%, respectively. CONCLUSION: We identified differential survivorship based on primary tumour type and a shift in the distribution of operations performed for specific primary cancers over the past 2 decades in Ontario. Overall reductions in mortality associated with this shift in treatment may reflect the use of adjuvant therapies and more personalized treatment approaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".