Current approaches in intensification of long-course chemoradiotherapy in locally advanced rectal cancer: a review
Bibliographic record
Abstract
Rectal cancer is one of the most prevalent cancers in the world. In many countries, the current standard of care is long-course chemoradiation (CRT), followed by total mesorectal excision. Some efforts have been made by intensifying radiation or chemotherapy components of the neoadjuvant therapy to further decrease the local recurrence and augment surgery's feasibility and improve the oncological outcomes. This paper reviews recent intensified neoadjuvant interventions in locally advanced rectal cancer (LARC) in terms of efficacy and treatment-related toxicity. Many maneuvers have been made so far to improve the oncological outcomes of rectal cancer with intensified neoadjuvant long-course CRT. Some of these approaches seem compelling and deserve further study, while some have just increased the treatment-related toxicities without evident benefits. Those endeavors with greater pathological complete response than the standard of care may make us await the long-term results on survival rates and chronic treatment-related toxicity. After introduction of neoadjuvant CRT for LARC there have been many efforts to improve its outcomes. Here, this study gathered most of these efforts that intensified the neoadjuvant therapy with some being promising and some being futile.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".