Management and Outcomes of Localized Esophageal and Gastroesophageal Junction Cancer in Older Patients
Bibliographic record
Abstract
BACKGROUND: Older patients are commonly excluded from clinical trials in esophageal and gastroesophageal junction (gej) cancer. High-level evidence to guide management in this group is lacking. In the present study, we compared outcomes and described tolerance for curative- and noncurative-intent treatments among patients 70 years of age and older. METHODS: We retrospectively reviewed all patients 70 years of age and older diagnosed with localized esophageal and gej cancer at our centre between 2005 and 2012. RESULTS: The 74 patients identified had a median age of 77 years. Of those patients, 62% received curative-intent treatment, consisting mostly of concomitant chemoradiation therapy (n = 43, 93%). Median overall survival for patients receiving curative-intent treatment was 18.6 months [95% confidence interval (ci): 13.0 to 28.0 months], with 23% being long-term survivors (95% ci: 11.3% to 36.7%). In contrast, patients receiving noncurative-intent treatment had a median overall survival of 8.8 months (95% ci: 6.7 to 11.9 months), with none being long-term survivors (p < 0.0001). Improvement of dysphagia was seen after curative (81%) or palliative radiotherapy (78%) in symptomatic patients, and toxicities were manageable. The odds of not receiving curative treatment was higher by a factor of 8.5 among patients 80 years of age or older compared with those 70-79 years of age (95% ci: 2.5 to 28.7). CONCLUSIONS: In managing older patients with esophageal and gej cancer, curative-intent treatment (compared with noncurative-intent treatment) leads to a significant survival benefit with a reasonable toxicity profile. Informed counselling of patients and their families about a curative treatment approach and efforts to increase awareness among oncology care providers are suggested.
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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 | 0.003 |
| 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".