Early Compared With Late Radiotherapy in Combined Modality Treatment for Limited Disease Small-Cell Lung Cancer: A London Lung Cancer Group Multicenter Randomized Clinical Trial and Meta-Analysis
Bibliographic record
Abstract
PURPOSE: To replicate an earlier National Cancer Institute of Canada (NCIC) trial that examined the effect on survival of the timing of thoracic radiotherapy (TRT) in patients with limited disease small-cell lung cancer (SCLC). PATIENTS AND METHODS: Patients received three cycles of cyclophosphamide, doxorubicin, and vincristine alternating with three cycles of etoposide and cisplatin. Three hundred twenty five chemotherapy- and radiotherapy-naïve patients were randomly assigned to either early TRT administered concurrently in the second cycle or late TRT administered concurrently with the sixth cycle; the dose was 40 Gy in 15 fractions over 3 weeks. RESULTS: TRT was received by 92% and 82% of patients in the early and late arms, respectively (P = .01). Sixty-nine percent of patients in the early arm received all six courses of chemotherapy compared with 80% in the late arm (P = .003). There was no evidence of a survival difference; median overall survival time was 13.7 and 15.1 months in the early and late arms, respectively (P = .23). In a meta-analysis of all eight trials that compared early and late TRT, there were three in which the proportion of patients who completed their planned chemotherapy was similar between the TRT arms (hazard ratio [HR] = 0.73; 95% CI, 0.62 to 0.86) and five in which proportionally fewer patients in the early TRT arm completed their chemotherapy (HR = 1.06; 95% CI, 0.97 to 1.17). CONCLUSION: This study failed to show a survival advantage for early TRT with chemotherapy in limited-stage SCLC, unlike the NCIC trial. However, the results of a meta-analysis suggest that it is essential to ensure that the delivery of chemotherapy is optimal when administered with early TRT.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.027 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".