A comprehensive clinical evaluation of first-line drugs for ALK-positive advanced non-small cell lung cancer
Bibliographic record
Abstract
Background: Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) are mainly used in the treatment of ALK-positive advanced non-small cell lung cancer (NSCLC), but a comprehensive clinical evaluation of ALK-TKIs is lacking. Hence, a comparison of ALK-TKIs for first-line treatment of ALK-positive advanced NSCLC is essential to provide rational drug use and a basis for improving national policies and systems. Methods: According to the Guideline for the Administration of Clinical Comprehensive Evaluation of Drugs (2021) and the Technical Guideline for the Clinical Comprehensive Evaluation of Antitumor Drugs (2022), a comprehensive clinical evaluation index system of first-line treatment drugs for ALK-positive advanced NSCLC was established by literature review and expert interviews. We conducted a systematic literature review, meta-analysis, and other relevant data analyses, combined with an indicator system, to establish a quantitative and qualitative integration analysis for each indicator and each dimension of crizotinib, ceritinib, alectinib, ensartinib, brigatinib, and lorlatinib. Results: The comprehensive clinical evaluation results of all dimensions were as follows: in terms of safety, alectinib had a lower incidence of grade 3 and above adverse reactions; for effectiveness, alectinib, brigatinib, ensartinib, and lorlatinib showed better clinical efficacy, and alectinib and brigatinib have been recommended by several clinical guidelines; in terms of economy, second-generation ALK-TKIs have more cost-utility advantages, and both alectinib and ceritinib have been recommended by the UK and Canadian Health Technology Assessment (HTA) agencies; for suitability, accessibility, and innovation, alectinib has a higher degree of physician recommendations and patient compliance. Except for brigatinib and lorlatinib, all other ALK-TKIs have been admitted to the medical insurance directory; the accessibility of crizotinib, ceritinib, and alectinib is good, meeting the needs of patients. Second- and third-generation ALK-TKIs have higher blood-brain barrier permeability, stronger inhibition ability, and innovation than first-generation ALK-TKIs. Conclusions: Compared with other ALK-TKIs, alectinib performs better across six dimensions and has a higher comprehensive clinical value. The results provide better drug choice and rational use for patients with ALK-positive advanced NSCLC.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".