Evidence map›Paper›PMID 41907107›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2026

Clinical Characteristics and Development of a Risk-Identification Model for Incidentally Detected Cancer in Patients with Diabetes: A Case-Control Study.

Nengi Cheang, Xueru Chen, Hongmei Zhang, Qing Su, Shichun Du

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Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 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 · Who and what money

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5 authors.

Nengi CheangDepartment of Endocrinology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People's Republic of China.ORCID 0009-0007-2005-4224
Xueru ChenDepartment of Endocrinology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People's Republic of China.
Hongmei ZhangDepartment of Endocrinology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People's Republic of China.
Qing SuDepartment of Endocrinology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People's Republic of China.
Shichun DuDepartment of Endocrinology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In hospitalised adults with diabetes, asymptomatic cancers may be overlooked during admission, delaying diagnosis and potentially contributing to poorer prognosis by missing opportunities for earlier treatment. Although cross-sectional imaging can detect lesions, it is not systematically performed in asymptomatic patients. A risk signal from routine measurements could prompt targeted imaging and enable diagnosis. Methods: We conducted a single-centre retrospective case-control study at Xinhua Hospital. Cases were adults with diabetes with first, pathology-confirmed cancer (any site) detected incidentally during index admission without cancer-related symptoms. Controls were inpatients matched by age and diabetes duration. We developed two models. Model A predictors were age, sex, body mass index, HbA1c, mean glucose, mean amplitude of glycaemic excursions (MAGE) from the first 72 h of capillary glucose, 2-hour C-peptide, apolipoprotein A-I (ApoA-I), albumin, and sodium-glucose cotransporter 2 (SGLT2) inhibitor use. Model B added carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and cytokeratin 19 fragment (CYFRA21-1); albumin was not retained. Performance was assessed by area under the receiver operating characteristic curve (AUC), calibration, Brier score, decision curve analysis (DCA), and net reclassification improvement (NRI). Results: Of 281 patients, 140 were cases and 141 were controls. Model A used 219 participants and Model B 156 participants. Higher 2-hour C-peptide and ApoA-I were associated with lower odds of cancer, whereas higher CYFRA21-1 was associated with higher odds. Model B outperformed Model A (AUC 0.740 to 0.852; Brier 0.199 to 0.147). Conclusion: Using inpatient measurements, we developed a risk-identification model for incidentally detected, asymptomatic cancer among hospitalised adults with diabetes, which may help prioritise in-hospital diagnostic work-up. Adding tumour markers, particularly CYFRA21-1, improved discrimination. Prospective multicentre validation and assessment of clinical and economic impact are warranted before implementation.

Indexed as

diabetes mellitusglycaemic variabilityincidentally detected cancerinpatients

Identifiers

PMID41907107
PMCPMC13032730

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