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      Comparative Efficacy of Targeted Therapies in Patients with Non-Small Cell Lung Cancer: A Network Meta-Analysis of Clinical Trials

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          Abstract

          This study aims to investigate the efficacy of targeted therapies in the treatment of non-small cell lung cancer (NSCLC) by using a network meta-analysis of clinical trials. PubMed, EMBASE, Cochrane Library, and Clinicaltrials.gov were searched by using keywords related to the topic on 19 September 2018. Two investigators independently selected relevant trials by pre-determined criteria. A pooled response ratio (RR) for overall response rate (ORR) and a hazard ratio (HR) for progression-free survival (PFS) were calculated based on both the Bayesian and frequentist approaches. A total of 128 clinical trials with 39,501 participants were included in the final analysis of 14 therapeutic groups. Compared with chemotherapy, both ORR and PFS were significantly improved for afatinib, alectinib, and crizotinib, while only PFS was significantly improved for cabozantinib, ceritinib, gefitinib, and osimertinib. Consistency was observed between the direct and indirect comparisons based on the Bayesian approach statistically and the frequentist approach visually. Cabozantinib and alectinib showed the highest probability for the first-line treatment ranking in ORR (62.5%) and PFS (87.5%), respectively. The current network meta-analysis showed the comprehensive evidence-based comparative efficacy of different types of targeted therapies, which would help clinicians use targeted therapies in clinical practice.

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          Most cited references18

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          Novel targets in non-small cell lung cancer: ROS1 and RET fusions.

          The discovery of chromosomal rearrangements involving the anaplastic lymphoma kinase (ALK) gene in non-small cell lung cancer (NSCLC) has stimulated renewed interest in oncogenic fusions as potential therapeutic targets. Recently, genetic alterations in ROS1 and RET were identified in patients with NSCLC. Like ALK, genetic alterations in ROS1 and RET involve chromosomal rearrangements that result in the formation of chimeric fusion kinases capable of oncogenic transformation. Notably, ROS1 and RET rearrangements are rarely found with other genetic alterations, such as EGFR, KRAS, or ALK. This finding suggests that both ROS1 and RET are independent oncogenic drivers that may be viable therapeutic targets. In initial screening studies, ROS1 and RET rearrangements were identified at similar frequencies (approximately 1%-2%), using a variety of genotyping techniques. Importantly, patients with either ROS1 or RET rearrangements appear to have unique clinical and pathologic features that may facilitate identification and enrichment strategies. These features may in turn expedite enrollment in clinical trials evaluating genotype-directed therapies in these rare patient populations. In this review, we summarize the molecular biology, clinical features, detection, and targeting of ROS1 and RET rearrangements in NSCLC.
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            Comparison of gefitinib, erlotinib and afatinib in non‐small cell lung cancer: A meta‐analysis

            Gefitinib, erlotinib and afatinib are three widely used epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) for treating advanced non-small cell lung cancer (NSCLC) with proven efficacy. We undertook a systematic review and meta-analysis to synthesize existing studies with direct comparisons of EGFR TKIs in NSCLC in terms of both efficacy and safety. Eight randomized trials and 82 cohort studies with a total of 17,621 patients were included for analysis. Gefitinib and erlotinib demonstrated comparable effects on progression-free survival (hazard ratio [HR], 1.00; 95% confidence interval [CI], 0.95 to 1.04), overall survival (HR, 0.99; 95% CI, 0.93 to 1.06), overall response rate (risk ratio [RR], 1.05; 95% CI, 1.00 to 1.11), and disease control rate (RR, 0.98; 95% CI, 0.96 to 1.01), which did not vary considerably with EGFR mutation status, ethnicity, line of treatment, and baseline brain metastasis status. Gefitinib was associated with more grade 3/4 liver dysfunction, but tended to cause lower rates of dose reduction, treatment discontinuation, total grade 3/4 adverse events (RR, 0.78; 95% CI 0.65 to 0.94), and a number of specific adverse events such as rash and diarrhea. No solid evidence was found that afatinib had greater efficacy than gefitinib or erlotinib in first-line treatment of EGFR-mutant NSCLC. However, afatinib was more effective than erlotinib as second-line treatment of patients with advanced squamous cell carcinoma. The grade 3/4 adverse events rate of afatinib was comparable to that of erlotinib but higher than that of gefitinib.
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              Targeting HER2 in the treatment of non-small cell lung cancer.

              Oncogenic driver mutations have emerged as major treatment targets for molecular therapies in a variety of cancers. HER2 positivity has been well-studied in breast cancer, but its importance is still being explored in non-small cell lung cancer (NSCLC). Laboratory methods for assessment of HER2 positivity in NSCLC include immunohistochemistry (IHC) for protein overexpression, fluorescent in situ hybridization (FISH) for gene amplification, and next generation sequencing (NGS) for gene mutations. The prognostic and predictive significance of these tests remain to be validated, with an emerging association between HER2 gene mutations and response to HER2 targeted therapies. Despite the assay used to determine the HER2 status of lung tumors, all patients with advanced HER2 positive lung adenocarcinoma should be evaluated for treatment with targeted agents. Several clinical approaches for inclusion of these drugs into patient treatment plans exist, but there is no defined algorithm specific to NSCLC.
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                Author and article information

                Journal
                J Clin Med
                J Clin Med
                jcm
                Journal of Clinical Medicine
                MDPI
                2077-0383
                09 April 2020
                April 2020
                : 9
                : 4
                : 1063
                Affiliations
                [1 ]Department of Cancer Biomedical Science, National Cancer Center Graduate School of Cancer Science and Policy, Goyang 10408, Korea; 75256@ 123456ncc.re.kr (T.H.); jskim@ 123456ncc.re.kr (J.K.)
                [2 ]Division of Cancer Epidemiology and Management, National Cancer Center Research Institute, Goyang 10408, Korea
                [3 ]Department of Family Medicine and Center for Cancer Prevention and Detection, National Cancer Center Hospital, Goyang 10408, Korea
                [4 ]Health Data Science Program, Institute of Public Health, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany; thuphamhup@ 123456gmail.com
                [5 ]Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), 13125 Berlin, Germany
                [6 ]Department of Obstetrics and Gynecology, Ewha Womans University College of Medicine, Seoul 07804, Korea; goodmorning@ 123456ewha.ac.kr
                [7 ]Medical Research Institute, Ewha Womans University College of Medicine, Seoul 07804, Korea
                Author notes
                [* ]Correspondence: msk@ 123456ncc.re.kr ; Tel.: +82-31-920-0479
                Author information
                https://orcid.org/0000-0001-6653-3406
                https://orcid.org/0000-0002-2129-0911
                https://orcid.org/0000-0002-0889-2686
                Article
                jcm-09-01063
                10.3390/jcm9041063
                7230601
                32283699
                60f9e986-3cf2-4e83-9a9e-1f4a18a50540
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 14 March 2020
                : 07 April 2020
                Categories
                Article

                non-small cell lung cancer,targeted therapy,network meta-analysis

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