Management of metastatic gastric and esophageal cancer in older adults.
Bibliographic record
Abstract
163 Background: Older adults are under-represented or excluded from pivotal trials of palliative chemotherapy for metastatic gastric and esophageal (GE) cancers. Little is known about how older patients are treated in the real world. The objective of this study was to examine the impact of age on treatment and survival. Methods: Patients aged ≥65 years were identified from a retrospective database of patients with metastatic GE cancer (Princess Margaret Cancer Centre; 2011-2016). The impact of age ≥75 years (old-old) versus (vs.) 65-74 years (young-old) on treatment and survival was assessed using multivariable logistic and Cox proportional hazard regression models, respectively, adjusted for known prognostic factors including sex, comorbidity, primary site, histology, grade, stage at initial diagnosis, metastatic sites, and chemotherapy use. Results: Of 183 patients, median age was 72 (range 65-92) years; 31% were old-old. Old-old patients were less likely to be treated with any chemotherapy (12.3% vs. 45.2% young-old; adjusted odds ratio = 0.12 (95% confidence interval (CI) 0.05-0.31)). With a median follow-up of 5.7 months, 135 (74%) had died during follow-up; median overall survival (OS) was 5.2 months (mo) for the old-old vs. 8.4 mo (young-old). There was no significant difference in survival between the two groups after adjustment for known prognostic factors (old-old vs. young-old: univariable hazard ratio (HR) 1.75 (95% CI 1.2-2.5); adjusted HR 1.1 (95% CI 0.7-1.7). Treatment with any chemotherapy was associated with an improvement in survival: adjusted HR 0.34 (95%CI 0.22-0.52). Conclusions: In this single-centre study of older adults with metastatic GE cancer, there was an overall low rate of treatment with chemotherapy; those ≥75 were rarely treated. After accounting for known prognostic factors, there was no observed difference in survival between patients ≥75 and those 65 to 74. Comprehensive geriatric assessment may improve treatment selection in the older population. [Table: see text]
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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 | 0.001 |
| 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) | 0.001 | 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".