Does Delay in Starting Treatment Affect the Outcomes of Radiotherapy? A Systematic Review
Bibliographic record
Abstract
PURPOSE: The objective of this study was to synthesize what is known about the relationship between delay in radiotherapy (RT) and the outcomes of RT. METHODS: A systematic review of the world literature was conducted to identify studies that described the association between delay in RT and the probability of local control, metastasis, and/or survival. Studies were classified by clinical and methodologic criteria and their results were combined using a random-effects model. RESULTS: A total of 46 relevant studies involving 15,782 patients met our minimum methodologic criteria of validity; most (42) were retrospective observational studies. Thirty-nine studies described rates of local recurrence, 21 studies described rates of distant metastasis, and 19 studies described survival. The relationship between delay and the outcomes of RT had been studied in diverse situations, but most frequently in breast cancer (21 studies) and head and neck cancer (12 studies). Combined analysis showed that the 5-year local recurrence rate (LRR) was significantly higher in patients treated with adjuvant RT for breast cancer more than 8 weeks after surgery than in those treated within 8 weeks of surgery (odds ratio [OR] = 1.62, 95% confidence interval [CI], 1.21 to 2.16). Combined analysis also showed that the LRR was significantly higher among patients who received postoperative RT for head and neck cancer more than 6 weeks after surgery than among those treated within 6 weeks of surgery (OR = 2.89; 95% CI, 1.60 to 5.21). There was little evidence about the impact of delay in RT on the risk of metastases or the probability of long-term survival in any situation. CONCLUSION: Delay in the initiation of RT is associated with an increase [corrected] in LRR in breast cancer and head and neck cancer. Delays in starting RT should be as short as reasonably achievable.
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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 | 0.019 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".