Risk and Predictors of Suicide in Colorectal Cancer Patients: A Surveillance, Epidemiology, and End Results Analysis
Bibliographic record
Abstract
Background: The risk of suicide is higher for patients with colorectal cancer (CRC) than for the general population. Given known differences in morbidity and sites of recurrence, we sought to compare the predictors of suicide for patients with colon cancer and with rectal cancer. Methods: Using the U.S. Surveillance, Epidemiology, and End Results database, adult patients with confirmed adenocarcinoma of the colon or rectum during 1973–2009 were identified. Parametric and nonparametric tests were used to assess selected variables, and Cox proportional hazards regression models were used to determine predictors of suicide. Results: The database identified 187,996 patients with rectal cancer and 443,368 with colon cancer. Compared with the rectal cancer group, the colon cancer group was older (median age: 70 years vs. 67 years; p < 0.001) and included more women (51% vs. 43%, p < 0.001). Suicide rates were similar in the colon and rectal cancer groups [611 (0.14%) vs. 337 (0.18%), p < 0.001]. On univariate analysis, rectal cancer was a predictor of suicide [hazard ratio (hr): 1.26; 95% confidence interval (CI): 1.10 to 1.43]. However, after adjusting for clinical and pathology factors, rectal cancer was not a predictor of suicide (HR: 1.05; 95% CI: 0.83 to 1.33). In the colon cancer cohort, independent predictors of suicide included older age, male sex, white race, and lack of primary resection. The aforementioned predictors, plus metastatic disease, similarly predicted suicide in the rectal cancer cohort. Conclusions: The suicide risk in CRC patients is low (<0.2%), and no difference was found based on location of the primary tumour. Sex, age, race, distant spread of disease, and intact primary tumour were the main predictors of suicide among CRC patients. Further studies and interventions are needed to target these high-risk groups.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".