Evidence map›Paper›PMID 39497173›Full record

ArticleBMC pulmonary medicine2024

Evolution of treatment strategies for solid tumors with RET rearrangement in China and real-world treatment status of Non-small Cell Lung Cancer (NSCLC).

An Wang, Tao Li, Yun-Ye Mao, Ming Gao, Sheng Shu, Chang-Hong Xia, Yi Dong, Min Liu, Jin-Liang Wang, Jun-Xun Ma and 1 more

Abstract readMulticenter Study
In one paragraph

Article in BMC pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

An Wang *Department of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China.ORCID http://orcid.org/0009-0001-6032-1573
Tao Li *Department of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China.ORCID http://orcid.org/0000-0002-9038-4794
Yun-Ye Mao *Department of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China.
Ming GaoDepartment of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China.
Sheng ShuDepartment of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China.
Chang-Hong XiaGraduate School, Chinese PLA General Hospital/Medical School of Chinese PLA, Beijing, 100853, China.
Yi DongDepartment of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China.
Min LiuGraduate School, Chinese PLA General Hospital/Medical School of Chinese PLA, Beijing, 100853, China.
Jin-Liang WangGraduate School, Chinese PLA General Hospital/Medical School of Chinese PLA, Beijing, 100853, China. wangjinliang301@163.com.
Jun-Xun MaGraduate School, Chinese PLA General Hospital/Medical School of Chinese PLA, Beijing, 100853, China. majunxun74@126.com.
Yi HuDepartment of Oncology, the First Medical Center of PLA General Hospital, (Chinese PLA Key Laboratory of Oncology, Key Laboratory for Tumor Targeting Therapy and Antibody Drugs (Ministry of Education, China)), Beijing, 100853, China. huyi301zlxb@sina.com.ORCID http://orcid.org/0000-0001-9319-5692

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe present study endeavors to furnish an exhaustive review of the research advancements on solid tumors harboring RET rearrangement within the Chinese context, particularly emphasizing the examination of real-world therapeutic strategies and clinical outcomes observed in individuals diagnosed with advanced non-small cell lung cancer (NSCLC). The review delves into a critical assessment of the therapeutic efficacy of targeted RET inhibitors, while also scrutinizing the diverse array of treatment modalities employed in the Chinese patient population.

methodsThe study conducted a comprehensive review of the advancements made by Chinese scholars in the realm of RET driver genes. It delved into the analysis of the incidence of RET rearrangements in solid tumors, alongside an examination of the varied treatment paradigms and their current status within China. Utilizing the RECIST 1.1 criteria, the study evaluated the therapeutic efficacy achieved in RET-positive NSCLC patients undergoing diverse treatment modalities. Furthermore, treatment-related adverse events (TRAEs) were meticulously graded following the Common Terminology Criteria for Adverse Events (CTCAE).

resultsA retrospective, multi-center, real-world analysis was conducted, encompassing 64 patients diagnosed with pathologically confirmed RET rearrangement advanced non-small cell lung cancer (NSCLC) between December 2015 and November 2023. Notably, KIF5B-RET emerged as the most prevalent RET fusion partner, accounting for 59.4% of cases. Therapeutic interventions among these patients included specific targeted inhibitors such as Pralsetinib (48.4%), chemotherapy (34.3%), multi-target inhibitors (15.6%), and one case (1.6%) involving immunotherapy combined with anti-angiogenic therapy. In terms of progression-free survival (PFS), Pralsetinib monotherapy demonstrated a median PFS of 16.03 months, outperforming chemotherapy (2.87 months; p < 0.0001), chemotherapy combined with anti-angiogenic therapy (6.90 months; p = 0.048), and multi-target inhibitors (2.50 months; p < 0.0001). Furthermore, the one-year and two-year overall survival (OS) rates for Pralsetinib monotherapy were 64.3% and 46.4%, respectively. Regarding safety, 71.0% of patients receiving Pralsetinib experienced at least one adverse event, with 45.2% classified as grade 3-4 in severity. Notably, no fatalities were attributed to adverse events. Common adverse events included hemoglobin reduction (35.5%) and neutropenia (32.3%), indicative of an overall favorable safety profile for Pralsetinib in this patient population.

conclusionThis study encapsulates the research endeavors and treatment advancements of RET rearrangement solid tumors within the Chinese healthcare landscape, specifically highlighting the diverse real-world therapeutic approaches and their effectiveness in managing advanced RET rearrangement NSCLC among Chinese patients. Notably, targeted RET inhibitors like Pralsetinib have emerged as potent therapeutic agents, exhibiting remarkable efficacy and a manageable safety profile in this patient cohort. These findings underscore the potential of Pralsetinib and similar targeted therapies as novel treatment options for individuals with RET fusion-positive NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungGene RearrangementLung NeoplasmsProto-Oncogene Proteins c-retAdultAgedChinaFemaleHumansMaleMiddle AgedProtein Kinase InhibitorsPyrazolesPyridinesPyrimidinesRetrospective StudiespralsetinibProtein Kinase InhibitorsProto-Oncogene Proteins c-retPyrazolesPyridinesPyrimidinesRET protein, humanNon-small Cell Lung Cancer (NSCLC)PralsetinibReal-world treatment patternsRET Fusion

Identifiers

PMID39497173
PMCPMC11533424

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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.