Impact of age on outcomes and symptoms in patients with advanced gastroesophageal cancer (GEC).
Bibliographic record
Abstract
193 Background: Although age is a non-modifiable risk factor for most cancers, alone it is not very helpful in deciding on the best treatment for patients. Insufficient data exist in the oldest old ( > 75 years) compared to young-old (65-75 years) and to younger ( < 65 years) patients with de novo metastatic GEC regarding which factors influence response and outcomes. Methods: We retrospectively assessed all patients with de novo metastatic GEC seen from 2006-2015 at the Princess Margaret Cancer Center in Toronto-Ontario, Canada. We used Kaplan-Meier plots and Cox proportional hazards analyses to examine factors associated with progression-free survival (PFS) and overall survival (OS). To examine patient-reported outcomes we used the Edmonton Symptom Assessment System (ESAS) in the first six months of therapy using cross-sectional and longitudinal analyses. Results: A total of 580 de novo metastatic GEC patients were seen between 2006 and 2015. Of these (14%) were oldest old, (31%) were young-old (age 65-75) and 54% were younger ( < 65 years). Most patients (67-80%) were male. Median OS for the entire cohort was 9.1 mo. (95% confidence interval (CI) 8.0 – 10.1); the shortest OS was in the oldest old group at 4.5 mo. compared to 8.7 mo. in young-old and 9.8 mo. in younger group, p < 0.001. PFS was also significantly different among the age groups (4.4 mo., 6.1 mo., and 6.5 mo., respectively), p = 0.0145. In a multivariate model predictors for OS were age (young-old group), number of metastasis, and Eastern Cooperative Oncology Group (ECOG) performance scale (PS). Similar predictors were found for PFS; however, age was not a significant factor. Of the 55 patients who provided ESAS data, 58% were < 65 and 42% were age≥ 65. The most common symptoms at presentation were fatigue, appetite, and well-being. There were no differences by age group (all p > 0.05). Conclusions: Patients age > 75 have poorer OS compared to younger age groups but PFS does not differ, suggesting similar benefits with treatment in appropriately selected older adults with advanced GEC. Symptom profiles were similar with age. Further comprehensive care is needed for older patients with advanced GEC to improve their 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".