Esophageal cancer management controversies: Radiation oncology point of view
Bibliographic record
Abstract
Esophageal cancer treatment has evolved from single modality to trimodality therapy. There are some controversies of the role, target volumes and dose of radiotherapy (RT) in the literature over decades. The present review focuses primarily on RT as part of the treatment modalities, and highlight on the RT volume and its dose in the management of esophageal cancer. The randomized adjuvant chemoradiation (CRT) trial, intergroup trial (INT 0116) enrolled 559 patients with resected adenocarcinoma of the stomach or gastroesophageal junction. They were randomly assigned to surgery plus postoperative CRT or surgery alone. Analyses show robust treatment benefit of adjuvant CRT in most subsets for postoperative CRT. The Chemoradiotherapy for Oesophageal Cancer Followed by Surgery Study (CROSS) used a lower RT dose of 41.4 Gray in 23 fractions with newer chemotherapeutic agents carboplatin and paclitaxel to achieve an excellent result. Target volume of external beam radiation therapy and its coverage have been in debate for years among radiation oncologists. Pre-operative and post-operative target volumes are designed to optimize for disease control. Esophageal brachytherapy is effective in the palliation of dysphagia, but should not be given concomitantly with chemotherapy or external beam RT. The role of brachytherapy in multimodality management requires further investigation. On-going studies of multidisciplinary treatment in locally advanced cancer include: ZTOG1201 trial (a phase II trial of neoadjuvant and adjuvant CRT) and QUINTETT (a phase III trial of neoadjuvant vs adjuvant therapy with quality of life analysis). These trials hopefully will shed more light on the future management of esophageal cancer.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".