Pathogenic germline variants in small cell lung cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
This systematic review and meta-analysis examined the prevalence and clinical impact of germline variants in small cell lung cancer (SCLC). Primary objectives included estimating the prevalence of germline variants in SCLC patients, while secondary objectives focused on their effects on patient outcomes. A comprehensive search was conducted in Ovid MEDLINE, EMBASE, and gray-literature databases (as of July 2024). Studies reporting germline variants in SCLC patients were included. Data were extracted to calculate pooled prevalence and hazard ratios (HRs). Study quality was assessed using the Translating ROBBINs tool, and heterogeneity was evaluated using the I 2 statistic. Of 6,117 screened studies, 124 met inclusion criteria, with 8% (10/124) reporting pathogenic/likely pathogenic (P/LP) findings. Meta-analysis using a random-effects model estimated the prevalence of P/LP germline variants in SCLC patients at 11% (95% CI: 5%–25%). Gene-level prevalence was estimated for ATM (pooled prevalence=1%; 95% CI: 0%–5%), BRCA1 (1%; 95% CI: 1%–3%), BRCA2 (1%; 95% CI: 1%–3%), and TP53 (1%; 95% CI: 0%–3%). Patients with P/LP variants in DNA damage repair genes showed a non-significant prognostic survival benefit (pooled HR: 0.8; 95% CI: 0.51–1.29, I 2 = 8%). We have conducted a comprehensive systematic review of germline variants and their impact on clinical outcomes of SCLC patients. Our meta-analysis identified an estimated prevalence of P/LP variants in SCLC patients, suggesting a rationale for screening in the clinic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".