Prophylactic cranial irradiation in patients with resected small‐cell lung cancer: A systematic review and meta‐analysis
Bibliographic record
Abstract
Prophylactic cranial irradiation (PCI) was recommended for limited-stage small-cell lung cancer (SCLC) patients with complete or partial response to primary chemoradiotherapy. But it is still controversial regarding its role in SCLC patients who have had radical resection. This meta-analysis aims to evaluate the efficacy of PCI in resected SCLC patients. We searched PubMed, EMBASE, Web of Science, CENTRAl, and ClinicalTrials for controlled trials and cohort studies regarding PCI in postoperative SCLC patients. The correlation between PCI and post-operative outcomes in SCLC patients, including survival and brain metastasis rate (BMR), was examined using hazard ratios (HRs) and risk ratios with corresponding 95% confidence intervals. Quality of studies was assessed by the Newcastle-Ottawa Scale (NOS), and publication bias was assessed by Begg's test. Meta-analysis of eight studies with 2688 patients in total showed PCI was associated with improved overall survival (OS) for resected SCLC (HR: 0.65, 95% CI: 0.57-0.75, p < 0.01). In addition, subgroup analysis on three studies including 923 patients confirmed the protective role of postoperative PCI in N0 SCLC patients (HR: 0.79, 95% CI: 0.61-0.97, p < 0.05). There was also a significant reduction in BMR in the PCI group pooled from six studies (HR: 0.58, 95% CI: 0.40-0.85, p < 0.01). The use of PCI delayed brain recurrence and improved OS in patients with resected, stage I-III SCLC. Importantly, patients with N0 SCLC can also benefit from postoperative PCI. In future studies, PCI's role in patients with resected N0 SCLC at different T stage may need to be explored.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".