Comparative Efficacy and Safety of Immunotherapeutic Regimens with PD-1/PD-L1 Inhibitors for Previously Untreated Extensive-Stage Small Cell Lung Cancer: A Systematic Review and Network Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Improving therapeutic strategies for extensive-stage small cell lung cancer (ES-SCLC) remains a challenge. To date, no reports have directly compared the efficacy and safety of immune checkpoint inhibitors plus platinum-etoposide (ICIs+EP) with platinum-irinotecan (IP) or directly compared different ICIs+EP for previously untreated ES-SCLC. This study used a Bayesian approach for network meta-analysis to compare efficacy and safety between ICIs+EP and IP and between each pair of three ICIs+EP. The six treatment arms were: pembrolizumab plus platinum-etoposide (Pem+EP), durvalumab plus platinum-etoposide (Dur+EP), atezolizumab plus platinum-etoposide (Atz+EP), platinum-amrubicin (AP), IP, and platinum-etoposide (EP). No significant differences in overall survival were observed between ICIs+EP and IP and between each pair of three ICIs+EP. The incidence of ≥grade 3 adverse events (G3-AEs) was significantly higher in ICIs+EP than IP, whereas no significant difference was found in G3-AEs between each pair of three ICIs+EP. The incidence of ≥grade 3 neutropenia and thrombocytopenia was significantly higher in ICIs+EP than IP, whereas the incidence of ≥grade 3 diarrhea was significantly lower in ICIs+EP than IP. These findings will help clinicians better select treatment strategies for ES-SCLC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.021 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it