Individual patient data meta-analysis of prophylactic cranial irradiation in locally advanced non-small cell lung cancer
Bibliographic record
Abstract
Background Prophylactic cranial irradiation (PCI) was compared to observation in several randomized trials (RCTs), and a reduction greater than 50% was shown regarding the incidence of brain metastases (BM). However, none of these studies showed an improvement of overall survival (OS), possibly related to relatively small sample sizes and short follow-up. The aim of this meta-analysis was therefore to assess the impact of PCI on long term OS for stage III non-small cell lung cancer (NSCLC) compared to observation based on the pooled updated individual patient RCT data. Methods Seven RCTs were eligible, and data from the four most recent trials (924 patients) could be retrieved. The log-rank observed minus expected number of events and its variance were used to calculate individual and overall pooled hazard ratios (HRs) and 95% confidence intervals (95% CIs) with a fixed effects model. Inter-trial heterogeneity was studied using the I 2 test. In addition, the 5-year absolute survival difference between arms was calculated for all endpoints. The pre-specified toxicities were reported descriptively. Results The median follow-up was 97 months (74–108). Compared to observation, no statistically significant impact of PCI on OS was observed (HR 0.90 [0.76–1.07] p = 0.23, 5-year absolute difference 1.8% [−5.2–8.8]). PCI significantly prolonged progression-free survival (HR 0.77 [0.66–0.91] p = 0.002) and BM-free survival (HR 0.82 [0.69–0.97] p = 0.02). The number of patients with high-grade (≥3) toxicity was 6.4% (21/330) for PCI. Conclusion No OS benefit by PCI was observed, but PCI prolonged the progression-free survival and BM-free survival at an increased risk of late memory impairment and fatigue.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.053 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".