ALK inhibitors for non-small cell lung cancer: A systematic review and network meta-analysis
Bibliographic record
Abstract
BACKGROUND: We sought to assess the relative effects of individual anaplastic lymphoma kinase (ALK) inhibitors for the treatment of non-small cell lung cancer (NSCLC). METHODS: We searched MEDLINE, Embase, Cochrane CENTRAL, and grey literature (July 23, 2019) for randomized controlled trials (RCTs) that included participants with ALK- or ROS1-positive NSCLC who received any ALK inhibitor compared with placebo, another ALK inhibitor, or the same ALK inhibitor at a different dose. The primary outcome was treatment-related death. Secondary outcomes were overall survival (OS), progression-free survival (PFS), and serious adverse events. Data were pooled via meta-analysis and network meta-analysis, and risk of bias was assessed. PROSPERO: CRD42017077046. RESULTS: Thirteen RCTs reporting outcomes of interest among participants with ALK-positive NSCLC were identified. Treatment-related deaths were rare, with 10 deaths attributed to crizotinib (risk difference v. chemotherapy: 0.49, 95% credible interval [CrI] -0.16 to 1.46; odds ratio 2.58 (0.76-11.37). All ALK inhibitors improved PSF relative to chemotherapy (hazard ratio [95% CrI]: crizotinib 0.46 [0.39-0.54]; ceritinib 0.52 [0.42-0.64]; alectinib 300 BID 0.16 [0.08-0.33]; alectinib 600 BID 0.23 [0.17-0.30]; brigatinib 0.23 [0.15-0.35]), while alectinib and brigatinib improved PFS over crizotinib and ceritinib (alectinib v. crizotinib 0.34 [0.17-0.70]; alectinib v. ceritinib 0.30 [0.14-0.64]; brigatinib v. crizotinib 0.49 [0.33-0.73]; brigatinib v. ceritinib 0.43 [0.27-0.70]). OS was improved with alectinib compared with chemotherapy (HR 0.57 [95% CrI 0.39-0.83]) and crizotinib (0.68 [0.48-0.96]). Use of crizotinib (odds ratio 2.08 [95% CrI 1.56-2.79]) and alectinib (1.60 [1.00-2.58]) but not ceritinib (1.25 [0.90-1.74), increased the risk of serious adverse events compared with chemotherapy. Results were generally consistent among treatment-experienced or naïve participants. CONCLUSION(S): Treatment-related deaths were infrequent among ALK-positive NSCLC. PFS may be improved by alectinib and brigatinib relative to other ALK inhibitors; however, the assessment of OS is likely confounded by treatment crossover and should be interpreted with caution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| 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 | 0.000 |
| 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".