Evidence map›Paper›PMID 42210605›Full record

ArticleCancer medicine2026

Development of a Risk Prediction Model for Bone Metastasis in Lung Adenocarcinoma With a T1 Primary Tumor Based on Intratumoral and Peritumoral Radiomics.

Ting Li, Hui Zheng, Yang Guo, Kemeng Zhang, Meiyan Liao

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Article in Cancer medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Ting LiDepartment of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hui ZhengDepartment of Radiology, Wuhan Central Hospital, Wuhan, China.
Yang GuoDepartment of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Kemeng ZhangDepartment of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Meiyan LiaoDepartment of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China.

Funding

Zhongnan Hospital of Wuhan University lcyf202104Zhongnan Hospital of Wuhan University ZNJC202009
6 · The paper itself

Abstract

purposeBone metastasis significantly affects the prognosis of lung adenocarcinoma (LUAD) patients. This study aims to construct and validate a risk prediction model for bone metastasis in LUAD with a T1 primary tumor based on intratumoral and peritumoral radiomics features. MATERIALS AND

methodsA total of 392 patients pathologically diagnosed with LUAD and a T1 primary tumor from two medical centers were retrospectively included (training cohort: n = 217, internal validation cohort: n = 93, external validation cohort: n = 82). Univariate and multivariate analyses identified independent risk factors for the clinicoradiologic model. Radiomics features were extracted from the gross tumor volume (GTV) and peritumoral tumor volume (PTV) in the training cohort CT images to establish intratumoral and peritumoral radiomics models. The optimal radiomics model was combined with clinicoradiologic features to develop a nomogram. Model performance was assessed using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA).

resultsAmong 392 LUAD patients with a T1 primary tumor, 147 had bone metastasis. The clinicoradiologic model incorporated three predictors: lymph node enlargement, pleural effusion, and carcinoembryonic antigen (CEA) levels. The PTV (-3 to 3 mm) radiomics model showed high discrimination performance, with an AUC of 0.810 (95% CI: 0.712-0.908) in the external validation cohort. The nomogram model demonstrated the highest discrimination performance, with an AUC of 0.884 (95% CI: 0.715-0.946), and showed acceptable calibration.

conclusionIn this retrospective two-center cohort of patients with LUAD and a T1 primary tumor, the combined clinicoradiologic-radiomics nomogram showed potential for stratifying the risk of synchronous bone metastasis at baseline evaluation. Further validation in larger and more representative cohorts is warranted before broader clinical application.

Indexed as

Adenocarcinoma of LungBone NeoplasmsLung NeoplasmsAgedFemaleHumansMaleMiddle AgedNeoplasm StagingNomogramsPrognosisRadiomicsRetrospective StudiesRisk AssessmentRisk FactorsROC Curvebone metastasiscomputed tomographylung adenocarcinomaradiomics

Identifiers

PMID42210605
PMCPMC13240066

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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.