Adjuvant concurrent chemoradiation using intensity-modulated radiotherapy and simultaneous integrated boost for resected high-risk adenocarcinoma of the distal esophagus and gastro-esophageal junction
Bibliographic record
Abstract
PURPOSE: Multimodality therapy leads to improved outcomes for adenocarcinoma of the distal esophagus and gastroesophageal junction (GEJ) over surgery alone. At our institution, adjuvant chemoradiation (chemoRT) using IMRT and SIB is standard of care for resected high-risk disease. In this study, we review our experience with a recent cohort of patients treated in this manner. METHODS AND MATERIALS: We identified 18 patients with resected T3 and/or N1 adenocarcinoma of the distal esophagus and GEJ who received adjuvant chemoRT. A large elective volume (PTV1) and a smaller high-risk volume (PTV2) were irradiated simultaneously using IMRT and an SIB technique. All patients received concurrent chemotherapy. Relevant clinical outcomes are reported. RESULTS: The median dose to 95% of PTV1 was 3747cGy and to 95% of PTV2 was 4876cGy. All RT was given in a median of 28 daily fractions. Four patients did not complete chemotherapy. At a median follow up of 952 days from the start of RT, 7 of 18 patients were dead; of these, 3 had developed local recurrence only; 3 had developed both local and distant recurrence; 1 died of a late toxicity, without recurrence. OS was 88% at 1year, 76% at 2 years and 58% at 3 years. Freedom from local recurrence was 88% at 1 year, 82% at 2 years and 82% at 3 years. Freedom from distant recurrence was 72% at 1 year, 67% at 2 years and 56% at 3 years. Toxicity was acceptable. CONCLUSIONS: Adjuvant concurrent chemoRT with IMRT and SIB is feasible for resected high-risk adenocarcinoma of the distal esophagus and GEJ. Our results describe how modern treatment techniques can be employed as part of a treatment paradigm that is neither commonly used nor commonly described in the literature.
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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 | 0.000 |
| 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) | 0.000 | 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".