Chronotherapy in head and neck cancer: A systematic review and meta‐analysis
Bibliographic record
Abstract
Optimizing the timing of radiotherapy and chemotherapy tailored to the body's biological clock (i.e., chronotherapy) might improve treatment efficacy and reduce side effects. This systematic review evaluated the effect of chrono-radiotherapy and chrono-chemotherapy on treatment efficacy, toxicity and adverse events in head and neck cancer (HNC) patients from prospective and retrospective studies published between the date of database inception until March 2024. The primary outcome measures for chrono-radiotherapy were treatment efficacy and incidence of grade ≥3 oral mucositis, and the main outcome measures for chrono-chemotherapy were objective response rate (ORR) and overall toxicity and adverse events. Of 7349 records identified, 22 studies with 3366 patients were included (chrono-radiotherapy = 9 and chrono-chemotherapy = 13). HNC patients who underwent chrono-radiotherapy had 31% less risk of developing severe oral mucositis (grade ≥3) compared to evening radiotherapy (risk ratio: 0.69, 95% CI: 0.53-0.90, p < 0.05). Further, HNC patients who underwent chrono-chemotherapy using platinum-based and antimetabolite agents had 73% less risk of lower ORR compared to nontime-stipulated chemotherapy (risk ratio: 0.27, 95% CI: 0.09-0.84, p < 0.05). In addition, HNC patients who underwent chrono-chemotherapy had 41% less risk of lower overall toxicity and adverse events in comparison to nontime-stipulated chemotherapy (risk ratio: 0.59, 95% CI: 0.47-0.72, p < 0.05). In conclusion, chrono-chemotherapy studies showed evidence of improved treatment efficacy, while in chrono-radiotherapy it was maintained. Chrono-radiotherapy and chrono-chemotherapy studies provide evidence of reduced toxicity and adverse events. However, optimized circadian-based multicentric clinical studies are needed to support chrono-radiotherapy and chrono-chemotherapy in managing HNC.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.022 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".