Timing of Surgery and Social Determinants of Health Related to Pathologic Complete Response after Total Neoadjuvant Therapy for Rectal Adenocarcinoma: Retrospective Study of National Cancer Database
Bibliographic record
Abstract
Total neoadjuvant therapy (TNT) for rectal adenocarcinoma (RAC) involves multi-agent chemotherapy and radiation before definitive surgery. Previous studies of the rest period (time between radiation and surgery) and pathologic complete response (pCR) have produced mixed results. The objective of this study was to evaluate the relationship between the rest period and pCR. This study utilized the National Cancer Database (NCDB) to retrospectively analyze 5997 stage-appropriate RAC cases treated with TNT from 2016 to 2020. The overall pCR rate was 18.6%, with most patients undergoing induction chemotherapy followed by long-course chemoradiation (81.5%). Multivariable logistic regression models revealed a significant non-linear relationship between the rest period and pCR (p = 0.033), with optimal odds at 14.7–15.9 weeks post radiation (odds ratio: 1.49, 95% confidence interval: 1.13–1.98) when compared to 4.0 weeks. Medicaid, distance to the treatment facility, and community education were associated with decreased odds of pCR. Findings highlight the importance of a 15–16-week post-radiation surgery window for achieving pCR in RAC treated with TNT and socioeconomic factors influencing pCR rates. Findings also emphasize the need for clinical trials to incorporate detailed analyses of the rest period and social determinant of health to better guide clinical practice.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".