Timeliness of adjuvant chemotherapy in patients with resected pancreatic cancer.
Bibliographic record
Abstract
e18038 Background: Timeliness of adjuvant chemotherapy is an important predictor of survival for patients with breast and colorectal cancer whereby long delays has been shown to detrimentally impact outcomes. The effects of adjuvant treatment timing remain largely unknown for early pancreatic cancer. This study aims to identify independent predictors of treatment timeliness and overall survival in this patient population. Methods: We conducted a retrospective, population-based analysis of 179 patients with resected pancreatic cancer who subsequently started adjuvant chemotherapy between 2008 and 2014 at any 1 of 6 cancer centers across British Columbia, Canada. Logistic regression was used to identify predictive factors for adjuvant chemotherapy timing. Prognostic factors for survival were ascertained using multivariate Cox proportional hazards models. Results: Our study cohort included 91 men (51%) and 88 women (49%). At time of diagnosis, 145 patients (81%) had nodal involvement and 107 patients (60%) had good ECOG performance status (ECOG 0-1). The median age of diagnosis was 67 (range 37-85) years. The median interval between surgery and start of adjuvant chemotherapy was 70 (range 19-46) days. Abnormal bilirubin was the only factor significantly correlated with delayed chemotherapy (OR, 3.89; 95% CI, 1.55-9.73; P = 0.004). Median overall survival was 468 days following resection (95% CI, 425-538). Multivariate survival analysis showed that high CA 19-9 levels (HR, 2.44, 95% CI: 1.36-4.40, P = 0.003) and abnormal bilirubin (HR, 0.40; 95% CI, 0.22-0.73; P = 0.003) were prognostic factors for overall survival. Median survival for patients who waited up to 35, 70 or 105 days for chemotherapy following resection were 588 days (95% CI, 270-776), 490 days (95% CI, 360-688) and 466 days (95% CI, 432-538) respectively. Overall, timeliness was not predictive of survival (HR, 1.12; 95% CI, 0.64-1.97; P= 0.70). Conclusions: Patients with hyperbilirubinema experienced delays in adjuvant chemotherapy, likely due to the need for relief of biliary obstruction and subsequent recovery. However, timeliness of adjuvant chemotherapy did not influence outcomes, suggesting that treatment should still be considered irrespective of timing.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".