Evidence map›Paper›PMID 41869733›Full record

ArticleAnnals of medicine2026

Prediction of high-risk factor in early-stage lung cancer: micropapillary adenocarcinoma.

Linhui Yang, Ping Zhou, Jiarui Zhang, Yi Liu, Qi Qi, Sha Liu, Weimin Li, Dan Liu

Abstract read
In one paragraph

Article in Annals of medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Linhui YangDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Ping ZhouDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Jiarui ZhangDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Yi LiuDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Qi QiDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Sha LiuDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Weimin LiDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Dan LiuDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify independent risk factors for micropapillary adenocarcinoma (MPA) in lung adenocarcinoma, a subtype often associated with poor prognosis, in order to support preoperative risk assessment and treatment planning.

methodsPatients diagnosed with lung adenocarcinoma were classified into the micropapillary adenocarcinoma (MPA) group or the non-MPA group based on pathological findings. Clinical, pathological, and imaging data were collected for both groups. Patients were followed up through outpatient visits or telephone interviews. The primary outcome was disease-free survival (DFS). Independent risk factors for MPA were identified using univariate and multivariate logistic regression analyses. A preoperative predictive model and corresponding nomogram were developed. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff value and the Hosmer-Lemeshow test and bootstrap - corrected calibration curves were used to evaluate the model's predictive performance.

resultsThe recurrence rate was significantly higher in the MPA group compared to the non-MPA group. Independent risk factors for MPA included smoking history, CT-diameter (≥22.5 mm), partially-solid nodule (PSN), solid nodule (SN), lobulation, spiculation, presence of vacuoles, and volume doubling time (VDT) (≤310 days). Guided by the multivariable analysis, we constructed a clinically oriented nomogram to provide an intuitive and practical tool for predicting MPA. The nomogram demonstrated excellent discrimination for predicting MPA, with an area under the ROC curve (AUC) of 0.923.

conclusionMPA predicts worse prognosis. The developed nomogram provides improved stratification of patients and supports informed clinical management.

Indexed as

Adenocarcinoma of LungAdenocarcinoma, PapillaryLung NeoplasmsNeoplasm Recurrence, LocalAgedDisease-Free SurvivalFemaleHumansMaleMiddle AgedNeoplasm StagingNomogramsPrognosisRetrospective StudiesRisk AssessmentRisk FactorsLung adenocarcinomamicropapillary adenocarcinomapredictive modelingprognosis

Identifiers

PMID41869733
PMCPMC13011101

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