Diabetes, Metabolic Syndrome and Obesity · Mar 24, 2026

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

By Cheang N, Chen X, Zhang H et al.

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.

doi.org/10.2147/dmso.s581946 Open access PubMed 41907107 Biomarkers