Predictors of survival in patients with non‐curative stage IV cancer and malignant bowel obstruction
Bibliographic record
Abstract
PURPOSE: Malignant bowel obstruction (MBO) occurs in up to 15% of patients admitted to palliative care wards and management can be clinically challenging. Survival is generally poor with a reported median survival of 1-3 months; however, there are no studies describing predictors of survival for patients with MBO. PATIENTS AND METHODS: All patients admitted to a tertiary care hospital with a MBO were approached between March 1, 2006 and March 31, 2008 to enter the study. Demographic, clinical, laboratory, and radiographic information were prospectively collected from patient charts and the patient's functional status (Eastern Cooperative Oncology Group score, ECOG) at admission was recorded. Follow-up was until death or the end of the study (August 2008). Survival was estimated using Kaplan-Meier plots and Cox regression models were used to evaluate prognostic factors for survival. RESULTS: Thirty-five patients were recruited. Median patient age was 61% and 46% were female. Median survival of the cohort was 80 days (range 7-873). Median survival for patients with an ECOG performance status of 0-1 (n = 15) was 222 days, for ECOG 2 patients (n = 9), 63 days and for patients with an ECOG 3/4 score (n = 11) it was 27 days. ECOG status was the strongest predictor of survival on the multivariate analysis. In addition, a low blood urea nitrogen level or a high albumin on admission was also associated with prolonged survival. CONCLUSION: An ECOG score of 0/1 for patients with MBO in the setting of Stage IV non-curative cancer is the strongest predictor of overall survival.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".