Evidence map›Paper›PMID 35129672›Full record

ReviewJournal of cancer research and clinical oncology2022

Incidence and prognostic factors in severe drug-induced interstitial lung disease caused by antineoplastic drug therapy in the real world.

Sawako Kaku, Hidehito Horinouchi, Hirokazu Watanabe, Kan Yonemori, Takuji Okusaka, Narikazu Boku, Naoya Yamazaki, Akira Kawai, Yuichiro Ohe, Masahiko Kusumoto

Erratum issuedOpen access · hybridAbstract readReview
In one paragraph

Review in Journal of cancer research and clinical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 4% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
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  8. [Research Progress of Anti-lung Cancer Drug-related Interstitial Lung Disease].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025
    Review
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  11. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Sawako KakuDepartment of Diagnostic Radiology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Hidehito HorinouchiDepartment of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan. hhorinou@ncc.go.jp.ORCID http://orcid.org/0000-0001-9090-801X
Hirokazu WatanabeDepartment of Diagnostic Radiology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Kan YonemoriDepartment of Medical Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Takuji OkusakaDepartment of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Narikazu BokuDepartment of Gastrointestinal Medical Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Naoya YamazakiDepartment of Dermatologic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Akira KawaiDepartment of Musculoskeletal Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Yuichiro OheCourse of Advanced Clinical Research of Cancer, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Masahiko KusumotoDepartment of Diagnostic Radiology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Juntendo University · JPNational Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeInvestigate the frequency and prognostic factors of severe drug-induced interstitial lung disease (DILD) caused by antineoplastic drugs regardless of cancer types or type of drugs.

methodsFrom 2014 to 2018, we reviewed patients with a history of antineoplastic agents administration in the real-world database of our hospital's electronic medical record and extracted patients who experienced "severe" DILD, requiring hospitalization with treatment or developed during hospitalization and required treatment. We collected patients' backgrounds, clinical and radiological features, laboratory data, treatment, and survival outcomes.

results19,132 cancer patients received antineoplastic drug therapy during the study period, and 120 (0.62%) experienced severe DILD. The incidence of severe DILD in patients with thoracic cancer was highest among the patients included in this analysis (2.52% vs. 0.34% other cancers). Diffuse alveolar damage (DAD) pattern on CT was associated with higher mortality in patients with severe DILD compared with non-DAD pattern (hazard ratio [HR], 11.24; 95% CI, 4.82-26.2). Multivariate analysis revealed that the DAD pattern at diagnosis as severe DILD (HR, 3.59; 95% CI, 1.17-11.03), concurrent/previous interstitial lung disease (HR, 3.20; 95% CI, 1.27-8.10), and ECOG performance status of 2-4 (HR, 3.81; 95% CI, 1.10-13.17) were independent risk factors for mortality in patients with severe DILD.

conclusionsThe frequency of severe DILD was highest in patients with thoracic cancer. The DAD pattern was associated with a poor outcome. From the perspective of DILD, special attention should be paid when administering antineoplastic agents to patients with thoracic cancer.

Indexed as

Antineoplastic AgentsLung Diseases, InterstitialNeoplasmsHumansIncidencePrognosisAntineoplastic AgentsAntineoplastic drug therapyCancerChemotherapyDiffuse alveolar damageDrug-induced interstitial lung diseaseImmune-checkpoint inhibitorLung cancerMalignant melanomaMolecular targeted drug therapyThoracic cancer

Identifiers

PMID35129672
PMCPMC9189085
OpenAlexW4210464365

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.