Comparative efficacy and safety of licensed treatments for previously treated non-small cell lung cancer: A systematic review and network meta-analysis
Bibliographic record
Abstract
PURPOSE: This systematic review with network meta-analysis compared the efficacy and safety of currently licensed second-line treatments in patients with late stage non-small cell lung cancer (NSCLC). METHODS: Randomised controlled trials (RCTs) of participants with advanced/metastatic NSCLC receiving second/third line treatments were screened. We searched electronic databases (MEDLINE; EMBASE; Web of Science) from January, 2000 to July, 2017. Two reviewers screened bibliographic records, extracted data, and assessed risk of bias of included studies. The outcomes were overall survival (OS), progression-free survival (PFS), and drug-related grade 3-5 adverse-events (AEs). We pooled study-specific hazard ratios (HR; for OS and PFS) and risk ratios (RR; for AEs) using conventional and network-meta-analyses, and ranked interventions by the surface under the cumulative ranking curve. FINDINGS: We included 11 RCTs (7,581 participants) comparing nine drugs. All drugs except for erlotinib significantly improved OS compared to docetaxel. Nivolumab was the highest ranking drug followed by atezolizumab and pembrolizumab. There was no significant difference in OS across these three drugs (HR = 0.98, 95% CI 0.79, 1.21 for nivolumab vs atezolizumab; HR = 0.98, 95% CI 0.77, 1.25 for nivolumab vs pembrolizumab). For PFS, ramucirumab + docetaxel and nivolumab were the drugs with the highest ranking. All interventions except ramucirumab + docetaxel had a reduced risk for severe drug-related AEs vs. docetaxel. Of the drugs with the highest ranking on AEs, nivolumab was significantly safer compared to atezolizumab (RR = 0.55, 95% CI 0.38, 0.79) or pembrolizumab (RR = 0.52, 95% CI 0.34, 0.81). IMPLICATIONS: Nivolumab, pembrolizumab and atezolizumab exhibited superior benefit/risk balance compared to other licensed drugs used late stage NSCLC. Our results indicate that the use of immunotherapies in people diagnosed with non-specific late stage NSCLC should be promoted. The use of docetaxel may now be judged irrelevant as a comparator intervention for approval of new drugs for second line treatment of NSCLC. STUDY REGISTRATION NUMBER: PROSPERO CRD42017065928.
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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 | 0.022 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.045 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".