MétaCan
Menu
Back to cohort
Record W3007156832 · doi:10.1371/journal.pone.0229179

ALK inhibitors for non-small cell lung cancer: A systematic review and network meta-analysis

2020· review· en· W3007156832 on OpenAlexafffund
Jesse Elliott, Zemin Bai, Shu‐Ching Hsieh, Shannon Kelly, Li Chen, Becky Skidmore, Carine Zheng, David J. Stewart, George A. Wells

Bibliographic record

VenuePLoS ONE · 2020
Typereview
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsCeritinibAlectinibCrizotinibAnaplastic lymphoma kinaseMedicineInternal medicineLung cancerALK inhibitorOncologyHazard ratioOdds ratioConfidence interval

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0120.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.128
GPT teacher head0.361
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations92
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicLung Cancer Treatments and MutationsFrench-language works237,207