Predictors of survival after metastasectomy of oligometastatic recurrence following gastroesophageal cancer treatment.
Bibliographic record
Abstract
e16060 Background: Recurrent gastroesophageal (GE) carcinomas carry a poor prognosis and are usually treated with palliative chemotherapy (CTX). However, recent studies suggest that certain patients with oligometastatic recurrence can have long term survival after metastasectomy. Appropriate patient selection for metastasectomy remains a challenge, as few predictors of overall survival (OS) after metastasectomy have been identified. Our primary aim was to identify predictors of OS following metastasectomy in GE cancers. Methods: We conducted a retrospective study of GE cancer patients treated from 2007 to 2015 using the Princess Margaret Hospital Cancer Registry. We included patients who underwent curative-intent surgery or definitive chemoradiation (CRT) for localized GE cancer who then had single organ recurrence treated with metastasectomy. The probability of OS from date of recurrence was estimated with the Kaplan Meier method. Predictors of OS after metastasectomy for isolated recurrence were determined using Cox proportional hazards analysis. Covariates included time to recurrence (interval from curative-intent surgery or completion of definitive CRT), site of recurrence (lung/non-lung), sex, age and race (Asian/Non-Asian). Within the multivariable model, predictors with a p-value less than 0.05 were deemed significant. Results: Of 44 patients, median age was 58 years (28-78), and 59% were male. Primary sites were: esophagus 25%, GE junction 41% and gastric 34%. Treatment of the primary was: surgery alone 13%, surgery and (neo)adjuvant CTX 76%, and CRT 11%. Recurrent sites were brain 22%, ovary 20%, lung 18%, bone 7%, adrenals 7%, liver 7%, distant lymph node 6%, and other 13%. The median follow up time was 38.9 months. The 1, 3 and 5-year (yr) OS following metastasectomy were 79% (95% CI 68-92%), 40% (27-58%) and 28% (16-49%). Univariable analysis revealed that time to recurrence greater than 1 yr (HR=0.45 95% CI 0.21-0.93, p=0.032) and lung site recurrence (HR=0.16 95% CI 0.04-0.67, p=0.012) were associated with longer OS. On multivariable analysis, only lung site recurrence was significant (HR=0.12 95% CI 0.03-0.54, p=0.0056). The 1, 3 and 5-yr OS for patients after resection of isolated lung recurrence were 100% (95% CI 100-100%), 86% (63-100%) and 69% (40-100%). Conclusions: In our study, patients with isolated pulmonary recurrences demonstrated prolonged overall survival following metastasectomy. These patients could be considered for resection following recurrence of GE cancer. [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 | 0.002 |
| 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) | 0.002 | 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".