SynthesisMedicine2019
Osimertinib or EGFR-TKIs/chemotherapy in patients with EGFR-mutated advanced nonsmall cell lung cancer: A meta-analysis.
Synthesis in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Correlation analysis on epidermal growth factor receptor (EGFR) mutations and clinicopathological characteristics in lung adenocarcinomas.Frontiers in oncology · 2025Article
- Sex differences in patients with Non-Small Cell Lung Cancer harboring driver fusions treated with tyrosine kinase inhibitors: a systematic review.Therapeutic advances in medical oncology · 2024Review
- Sex dimorphism in response to targeted therapy and immunotherapy in non-small cell lung cancer patients: a narrative review.Translational lung cancer research · 2022Review
- A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma.International journal of molecular sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this meta-analysis is to investigate the impact of Osimertinib on treatment efficacy in advanced nonsmall cell lung cancer (NSCLC).
methodsTrials comparing Osimertinib against epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs)/chemotherapy in patients with NSCLC with an epidermal growth factor receptor (EGFR) mutation were included, and the pooled data for progression-free survival (PFS), overall survival (OS), overall response rate (ORR), disease control rate (DCR), and adverse events (AEs) were analyzed.
resultsAnalysis results based on 6 eligible trials showed that Osimertinib significantly improved the overall PFS (hazard ratio [HR] = 0.38, 95% confidence interval [CI] = 0.29-0.50), improved the OS (HR = 0.66, 95% CI = 0.48-0.89), increased the ORR (odds ratio [OR] = 1.76, 95% CI = 1.14-2.72), increased the overall DCR (OR = 1.18, 95% CI = 1.02-1.37), and reduced the grade 3 or greater AEs (relative ratio [RR] = 0.50, 95% CI = 0.33-0.75) in all subgroups except in the ORR in the Exon 19 deletion (Ex19del) and/or L858R subgroup. Compared to patients with Ex19del and/or L858R mutation, patients with the T790M mutation had the benefits of a greater PFS (41.7%), a greater ORR (80.0%), a greater DCR (71.2%), and fewer grade 3 or greater AEs (70.7%) (each P < .05). Race, sex, age, EGFR mutation, and smoking history may significantly predict additional benefits from Osimertinib, but there were no significant differences between subgroups stratified by these clinical characteristics.
conclusionsOsimertinib showed greater treatment benefit for patients with NSCLC with EGFR mutation than EGFR-TKIs/chemotherapy, especially for T790M mutation-positive patients.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.