Evidence map›Paper›PMID 35088212›Full record

ArticleInvestigational new drugs2022

Classification and regression tree for estimating predictive markers to detect T790M mutations after acquired resistance to first line EGFR-TKI: HOPE-002.

Motohiro Tamiya, Kei Fujikawa, Hidekazu Suzuki, Toshihide Yokoyama, Takeshi Uenami, Akihiro Tamiya, Yuki Sato, Go Saito, Junji Uchida, Mitsunori Morita and 9 more

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Article in Investigational new drugs, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. J-REGISTER: real-world study of Japanese patients withFuture oncology (London, England) · 2025
    Observational
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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

19 authors at 9 institutions in 1 country.

Motohiro TamiyaDepartment of Thoracic Oncology, Osaka International Center Institute, Osaka, Japan. moto19781205@yahoo.co.jp.ORCID http://orcid.org/0000-0001-6529-3092
Kei FujikawaDepartment of Biostatistics, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Hidekazu SuzukiDepartment of Thoracic Malignancy, Osaka Habikino Medical Center, Osaka, Japan.
Toshihide YokoyamaDepartment of Respiratory Medicine, Kurashiki Central Hospital, Okiyama, Japan.
Takeshi UenamiDepartment of Thoracic Oncology, National Hospital Organization Osaka Toneyama Medical Center, Osaka, Japan.
Akihiro TamiyaDepartment of Internal Medicine, National Hospital Organization Kinki-Chuo Chest Medical Center, Osaka, Japan.
Yuki SatoDepartment of Respiratory Medicine, Kobe City Medical Center General Hospital, Hyogo, Japan.
Go SaitoDepartment of Respirology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Junji UchidaDepartment of Respiratory Medicine, Osaka General Medical Center, Osaka, Japan.
Mitsunori MoritaDepartment of Respiratory Medicine, Osaka General Medical Center, Osaka, Japan.
Tomonori HirashimaDepartment of Thoracic Malignancy, Osaka Habikino Medical Center, Osaka, Japan.
Yasushi FukudaDepartment of Respiratory Medicine, Kurashiki Central Hospital, Okiyama, Japan.
Masaki KanazuDepartment of Thoracic Oncology, National Hospital Organization Osaka Toneyama Medical Center, Osaka, Japan.
Kazutaka HosoyaDepartment of Respiratory Medicine, Kobe City Medical Center General Hospital, Hyogo, Japan.
Takuji SuzukiDepartment of Respirology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Kiyonobu UenoDepartment of Respiratory Medicine, Osaka General Medical Center, Osaka, Japan.
Daichi FujimotoDepartment of Respiratory Medicine, Kobe City Medical Center General Hospital, Hyogo, Japan.
Toru KumagaiDepartment of Thoracic Oncology, Osaka International Center Institute, Osaka, Japan.
Satoshi TeramukaiDepartment of Biostatistics, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kobe City Medical Center General Hospital · JPOsaka Prefectural Medical Center · JPChiba University · JPKurashiki Central Hospital · JPKyoto Prefectural University of Medicine · JPToneyama National Hospital · JPNHO Kinki Chuo Chest Medical Center · JPOsaka International Cancer Institute · JPOsaka International Cancer Institute · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveOsimertinib as first-line treatment for patients with non-small cell lung cancer (NSCLC) harboring epidermal growth factor (EGFR) mutations remains controversial. Sequential EGFR-tyrosine kinase inhibitor (TKI) might be superior to the first line osimertinib in patients at risk of developing acquired T790M mutations.

methodsWe enrolled consecutive patients with EGFR-mutated (deletion 19 or L858R) advanced NSCLC treated with first-line drugs and evaluated predictive markers using classification and regression tree (CART) for the detection of T790M mutations based on patient backgrounds prior to initial treatment.

resultsPatients without acquired T790M mutations had worse outcomes than those with T790M mutations (median OS: 798 days vs. not reached; HR: 2.70; P < 0.001). CART identified three distinct groups based on variables associated with acquired T790M mutations (age, CYF, WBC, liver metastasis, and LDH; AUROC: 0.77). Based on certain variables, CART identified three distinct groups in deletion 19 (albumin, LDH, bone metastasis, pleural effusion, and WBC; AUROC: 0.81) and two distinct groups in L858R (age, CEA, and ALP; AUROC: 0.80). The T790M detection frequencies after TKI resistance of afatinib and first-generation EGFR-TKIs were similar (35.3% vs. 37.4%, P = 0.933). Afatinib demonstrated longer PFS (398 vs. 279 days; HR: 0.67; P = 0.004) and OS (1053 vs. 956 days; HR: 0.68; P = 0.051) than first-generation EGFR-TKIs.

conclusionIdentification of patients at risk of acquiring T790M mutations after EGFR-TKI failure may aid in choice of first-line EGFR-TKI. Furthermore, afatinib may be the more effective 1st-line EGFR-TKI treatment for patients at risk of developing T790M as initial EGFR-TKI resistance.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsAfatinibEpidermal Growth FactorErbB ReceptorsHumansMutationProtein Kinase InhibitorsAfatinibEGFR protein, humanEpidermal Growth FactorErbB ReceptorsProtein Kinase InhibitorsClassification and regression treeEGFRNon-small cell lung cancerPredict markerT790MTyrosine kinase inhibitors

Identifiers

PMID35088212
OpenAlexW4221120933

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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.