Trial reportBioMed research international2018
Clinical Characteristics and Survival Outcomes for Non-Small-Cell Lung Cancer Patients with Epidermal Growth Factor Receptor Double Mutations.
Trial report in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Novel EGFR tyrosine kinase inhibitors exhibiting intrinsic fluorescence.Investigational new drugs · 2026Article
- Microfluidics-based EGFR mutation detection and its implication in the resource-limited clinical setting.International journal of experimental pathology · 2024Article
- A Comprehensive Review of Epidermal Growth Factor Receptor Mutation Abundance in Non-Small Cell Lung Cancer Treated with Tyrosine Kinase Inhibitors.Oncology research and treatment · 2024Review
- Clinical Pathological Characteristics and Prognosis of Multigene Co-Mutations in Elderly Patients With Non-Small Cell Lung Cancer: A Retrospective Analysis.Clinical Medicine Insights. Oncology · 2023Article
- Article
- Analysis of EGFR Mutation Status in Algerian Patients with Non-Small Cell Lung Cancer.Asian Pacific journal of cancer prevention : APJCP · 2021Article
- Co-occurring genetic alterations and primary EGFR T790M mutations detected by NGS in pre-TKI-treated NSCLCs.Journal of cancer research and clinical oncology · 2020Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple randomized clinical trials have demonstrated that epidermal growth factor receptor (EGFR) exon 19 deletion (19Del) and exon 21 L858R mutation (L858R) are highly correlated with sensitivity to epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) treatment in non-small-cell lung cancer (NSCLC). A mutation in exon 20 (T790M) is reportedly associated with resistance to EGFR-TKIs. However, few studies have focused on patients harboring double mutations in these 3 mutation sites. In this retrospective study, forty-five patients (45/2546, 1.7%) harbored double mutations of 19Del, L858R, and T790M. Twenty-four patients with EGFR double mutations received EGFR-TKI therapy. Clinical characteristics of these patients, including the response to EGFR-TKIs and progression-free survival outcome for EGFR-TKI treatment (PFS-TKI), were analyzed. Patients with EGFR double mutations were more likely to be nonsmokers, have an Eastern Cooperative Oncology Group Performance Status (ECOG PS) of 0-1, have adenocarcinoma, and be at stage III-IV. The ORR, DCR, and median PFS-TKI in patients harboring EGFR double mutations were lower than in patients with a single EGFR-activating mutation. The differences in ORR and DCR were statistically insignificant between the 3 groups. Patients with double mutations of 19Del and T790M had longer PFS-TKIs than patients in the other 2 groups.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.