Evidence map›Paper›PMID 37833769›Full record

ArticleWorld journal of surgical oncology2023

Therapeutic impact of epidermal growth factor receptor tyrosine kinase inhibitor with various treatment combinations for advanced lung adenocarcinoma.

Ying-Yi Chen, Kuan-Hsun Lin, Yen-Shou Kuo, Yuan-Ming Tsai, Hsu-Kai Huang, Tsai-Wang Huang

Open access · goldAbstract read
In one paragraph

Article in World journal of surgical oncology, 2023. 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
0.8field-weighted citation impact, top 24% of its field
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, 3 citations in OpenAlex.

  1. Article
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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

6 authors at 1 institution in 1 country.

Ying-Yi ChenDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Republic of China. addgujfjui@gmail.com.
Kuan-Hsun LinDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Republic of China.
Yen-Shou KuoDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Republic of China.
Yuan-Ming TsaiDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Republic of China.
Hsu-Kai HuangDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Republic of China.
Tsai-Wang HuangDivision of Thoracic Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Republic of China.
National Defense Medical Center · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTyrosine kinase inhibitors (TKIs) are the primary therapeutic option for patients with advanced-stage epidermal growth factor receptor-mutant (EGFR-m) lung adenocarcinoma. However, the role of EGFR-TKIs in advanced-stage lung cancer is uncertain regardless of therapeutic methods. This study investigated the outcome of the impact of epidermal growth factor receptor (EGFR)-TKI in patients with advanced lung adenocarcinoma treated with various therapeutic strategies.

methodsThis retrospective analysis used cancer registry data from 1159 patients with lung cancer treated between January 2015 and December 2017 at Tri-Service General Hospital. Only patients with lung adenocarcinoma stages 3B and four were selected for the study. All lung adenocarcinoma patients with ever TKI treatment had an EGFR mutation.

resultsThree-hundred sixty-two patients with advanced lung adenocarcinoma with complete medical records were enrolled. According to personalized therapeutic processes, they were divided into nine groups: only TKI treatment, only chemotherapy (CT), TKI with lung cancer salvage surgery, TKI with CT, TKI with radiotherapy (RT), CT with lung cancer salvage surgery, CT with RT, TKI with CT, and lung cancer salvage surgery. A multivariate Cox regression analysis showed TKI with lung cancer salvage surgery (HR: 4.675, p = 0.005) is the only good prognostic treatment. The poor predictors for overall survival were only CT (HR: 0.336, p = 0.048) and TKI with CT (HR: 0.359, p = 0.023). Kaplan-Meier survival analysis showed a statistical significance in an average overall survival (OS) of ever TKI treatment and never TKI treatment (33.24 vs. 17.64 months, p < 0.001). Furthermore, TKI usage duration was statistically increased in TKI with lung cancer salvage surgery (40.4 ± 20.7 vs 14.96 ± 13.13 months, p < 0.001). The survival rate (p = 0.033) and OS (p < 0.001) in lung cancer salvage surgery were statistically better than the group of TKI without surgery.

conclusionThe best therapeutic strategy for advanced lung adenocarcinoma is TKI with lung cancer salvage surgery, according to significantly longer OS and better survival. It also prolonged TKI usage. Mutated EGFR lung adenocarcinoma patients with ever TKI treatment had significantly better survival than with other treatments. Regardless of the combination of other treatments, EGFR mutation with TKI therapy is recommended as a positive prognostic factor for patients with lung adenocarcinoma.

Indexed as

AdenocarcinomaAdenocarcinoma of LungLung NeoplasmsErbB ReceptorsHumansMutationProtein Kinase InhibitorsRetrospective StudiesTyrosine Kinase InhibitorsErbB ReceptorsProtein Kinase InhibitorsTyrosine Kinase InhibitorsEpidermal growth factor receptorLung adenocarcinomaSalvage surgeryTyrosine kinase inhibitor

Identifiers

PMID37833769
PMCPMC10571456
OpenAlexW4387607635

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.