Comparison of chemoradiotherapy (CRT) with carboplatin/paclitaxel (CP) versus cisplatin/5-FU (CF) for esophageal or junctional cancer: Experience from the Princess Margaret Cancer Centre.
Bibliographic record
Abstract
126 Background: The optimal CRT regimen for neoadjuvant or definitive treatment of locoregional esophageal or gastroesophageal junctional (GEJ) cancer is uncertain. There has been no direct comparison between concurrent Cisplatin/5-FU (CF) as per the CALGB 9781 trial (50.4 Gy) or Carboplatin/Paclitaxel (CP) as per the CROSS trial (41.4 Gy). Methods: A retrospective analysis comparing CF and CP was performed in all patients (pts) with locoregional esophageal or GEJ cancer treated in 2012-2014. Overall survival (OS) and disease-free survival (DFS) were assessed via uni- and multivariable Cox proportional hazards regression, adjusting for age, performance status and Charlson comorbidity index. Pathological complete response (pCR) rates were compared using Fisher’s exact test. Results: 64/86 (74%) pts were male. Median age was 64 years (range: 34-84). Primary sites were esophageal (56%, with 60% squamous histology) and GEJ (44%, with 11% squamous). 22 pts received CRT in 2012 (100% CF), 33 pts in 2013 (58% CF, 42% CP) and 31 pts in 2014 (16% CF, 84% CP). Surgery was undertaken in 19 (41%) CF and 27 (68%) CP pts. Median follow-up was 38 months. We found no significant OS difference between CF and CP overall (HR 0.82, 95% CI: 0.43-1.56, p = 0.55) or in the subgroup having surgery (n = 46; HR 2.01, 95% CI: 0.62-6.55, p = 0.25). However, in the subgroup without surgery (n = 40), CF (n = 27) was superior to CP (n = 13)(HR 0.11, 95% CI: 0.03-0.38, p < 0.001). OS was similar by histology (adenocarcinoma/squamous) in all-comers (p = 0.96), and in CF (p = 0.66) and CP subgroups (p = 0.66). DFS results were similar to OS. There was a non-significant numerical difference in pCR rates between CF (31%) and CP (18%) (p = 0.45). Conclusions: Survival is similar for CF and CP CRT regimens in patients undergoing trimodality therapy. pCR rates were comparable but lower than previously reported. In contrast, in the absence of surgical resection, CP given for CRT results in significantly inferior outcomes. Clinicians may prefer CP for surgical candidates given its toxicity profile. However, when treating with definitive CRT, CF may be preferable to CP as a standard regimen.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".