Treatment approaches and survival outcomes of older patients with locally advanced esophageal cancer (LAEC) in Ireland.
Bibliographic record
Abstract
e23034 Background: Neo+/- adjuvant treatment data in older patients with cancer is sparse due to exclusion of this population from clinical trials. We evaluated the management of locally advanced esophagogastric cancer (LAEC) in older Irish patients to determine treatment modalities utilized and identify factors associated with survival. Methods: Patients diagnosed with LAEC (stage II or III) over a 5 year period (2007-2011)were identified from the National Cancer Registry of Ireland. Follow-up was till end 2014.Demographic characteristicswere assessed. Treatment was classified as “best supportive care (BSC)”, “surgery only”, “neo/adjuvant treatment” and “chemo/radiation alone” (ie chemo, radiotherapy or chemoradiotherapy alone in the absence of surgery).Survival was estimated by Kaplan-Meier estimates and Cox models. Clinicopathologic factors and treatment type found to be significant in univariate analysis were included in a multivariate analysis (MVA). Results: 46%(n = 580) of the 1,251 patients were ≥70yrs, 62% had stage III disease and 51% had gastric cancer. 11% (n = 134) received BSC, 23% (n = 288) had surgery only, 31%(n = 390) had chemo/radiation alone, 35% (n = 439) had neo/adjuvant treatment. 20% (n = 39) of patients ≥75yrs had neoadjuvant treatment compared to 46% < 75 yrs. No patient ≥80yrs received neo/adjuvant treatment. With increasing age patients were less likely to receive neo/adjuvant treatment (p < 0.001), less likely to receive surgery (p < 0.001) and less likely to receive any treatment (p < 0.001).Median survival(OS) decreased with age (< 70yrs: 23months; 70-74: 19months; 75-79:13months; ≥80 years:10 months). In MVA, older age, smoking, later stage, higher grade were significantly associated with a higher risk of death.Including an interaction between treatment and age, patients receiving adjuvant or neoadjuvant treatment had lower risk of death than any other treatment group regardless of age. Conclusions: Older patients were less likely to receive any treatment for LAEC than younger patients. Patients ≥70 years benefit from neo/adjuvant treatment, however,these patients are often excluded based on age. Prospective clinical trials focusing on elderly patients and incorporating life expectancy, comorbidities and geriatric assessment are needed to best guide treatment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".