A Clinical Prediction Model to Assess Risk for Pancreatic Cancer Among Patients With New-Onset Diabetes

Abstract

Background and aims Approximately 50% of all patients with pancreatic ductal adenocarcinoma (PDA) develop diabetes mellitus before their cancer diagnosis. Screening individuals with new-onset diabetes might therefore allow earlier diagnosis of PDA. We sought to develop and validate a PDA risk prediction model to identify high-risk individuals among those with new-onset diabetes. Methods We conducted a retrospective cohort study in a population representative database from the UK. Individuals with incident diabetes after the age of 35 and 3 or more years of follow up after diagnosis of diabetes were eligible for inclusion. Candidate predictors consisted of epidemiologic and clinical characteristics available at the time of diabetes diagnosis. Variables with P values below .25 in the univariable analyses were further evaluated using backward stepwise approach. Model discrimination was assessed using receiver operating characteristic curve analysis. Calibration was evaluated using the Hosmer–Lemeshow test. Results were internally validated using a bootstrapping procedure. Results We analyzed data from 109,385 patients with new-onset diabetes. Among them, 390 (0.4%) were diagnosed with PDA within 3 years. The final model (area under the curve, 0.82; 95% CI, 0.75–0.89) included age, body mass index, change in body mass index, smoking, use of proton pump inhibitors and anti-diabetic medications, as well as levels of HbA1C, cholesterol, hemoglobin, creatinine, and alkaline phosphatase. Bootstrapping validation showed negligible optimism. If the predicted risk threshold for definitive PDA screening was set at 1% over 3 years, only 6.19% of the new-onset diabetes population would undergo definitive screening, which would identify patients with PDA with 44.7% sensitivity, 94.0% specificity, and a positive predictive value of 2.6%. Conclusion We developed a risk model based on widely available clinical parameters to help identify patients with new-onset diabetes who might benefit from PDA screening.

Pancreatic Cancer Prediction Through an Artificial Neural Network

“…Recently, a clinical prediction model has been used to assess PC risk with pre-diabetic and new onset diabetic patients (Boursi et al, 2017(Boursi et al, , 2018. For pre-diabetic study, a total number of 138,232 patients with new onset impaired fasting glucose (IFG) were selected where 245 individuals were diagnosed with pancreatic ductal adenocarcinoma within 3 years of IFG diagnosis.…”

“…Chari et al (2005) showed that the 3-years cumulative incidence of PC among patients with new onset diabetes is 8 times higher than expected (Boursi et al, 2017). Hence, it can be stated that diabetes associated with PC may be a paraneoplastic phenomenon caused by the cancer (Pelaez-Luna et al, 2007;Sah et al, 2013;Boursi et al, 2017). Smoking also increases the risk of PC by a factor of two (American Cancer Society, 2017).…”

A review of lifestyle, metabolic risk factors, and blood‐based biomarkers for early diagnosis of pancreatic ductal adenocarcinoma

“…A recent study developed and internally validated a risk prediction model for PDAC among patients with newly onset diabetes, showing the promise of risk stratification among high-risk populations. 68 The study involved 109, 385 individuals with newly diagnosed diabetes, and the outcome was PDAC diagnosed within 3 years of diabetes onset. The prediction model included demographic, behavioral, and clinical variables that were routinely collected at the time of diabetes diagnosis.…”

Is Screening for Pancreatic Cancer in High-Risk Individuals One Step Closer or a Fool’s Errand?

“…Although prevalent diabetes is common in subjects >50 years of age, truly new onset diabetes is uncommon (estimates in Olmsted County range from 0.45% to 1% per year). Recently clinical risk-prediction models for PDAC in NOD have been reported but require external validation 3, 11 . There are also biomarker panels that appear promising, 12 .…”