Model to Determine Risk of Pancreatic Cancer in Patients With New-Onset Diabetes

Abstract

Background & aims: Of patients with new-onset diabetes (NOD; based on glycemic status) older than 50 years, approximately 1% are diagnosed with pancreatic cancer (PC) within 3 years. We aimed to develop and validate a model to determine risk of PC in patients with NOD.

Methods: We retrospectively collected data from 4 independent and nonoverlapping cohorts of patients (N = 1,561) with NOD (based on glycemic status; data collected at date of diagnosis and 12 months previously) in the Rochester Epidemiology Project from January 1, 2000 through December 31, 2015 to create our model. The model weighed scores for 3 factors identified in the discovery cohort to be most strongly associated with PC (64 patients with PC and 192 with type 2 diabetes): change in weight, change in blood glucose, and age at onset of diabetes. We called our model Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC). We validated the locked-down model and cutoff score in an independent population-based cohort of 1,096 patients with diabetes; of these, 9 patients (82%) had PC within 3 years of meeting the criteria for NOD.

Results: In the discovery cohort, the END-PAC model identified patients who developed PC within 3 years of diabetes onset (area under receiver operating characteristic curve 0.87); a score of at least 3 identified patients who developed PC with 80% sensitivity and specificity. In the validation cohort, a score of at least 3 identified 7 of 9 patients with PC (78%) with 85% specificity; the prevalence of PC in patients with a score of at least 3 (3.6%) was 4.4-fold greater than in patients with NOD. A high END-PAC score in patients who did not have PC (false positives) was often due to such factors as recent steroid use or different malignancy. An ENDPAC score no higher than 0 (in 49% of patients) meant that patients had an extremely low risk for PC. An END-PAC score of at least 3 identified 75% of patients in the discovery cohort more than 6 months before a diagnosis of PC.

Conclusions: Based on change in weight, change in blood glucose, and age at onset of diabetes, we developed and validated a model to determine risk of PC in patients with NOD based on glycemic status (END-PAC model). An independent prospective study is needed to further validate this model, which could contribute to early detection of PC.

Keywords: Biomarker; Enriching New-Onset Diabetes for Pancreatic Cancer; Pancreas; Screening.

Figure 1

Predictiveness curve and sensitivity of END-PAC model In Figure 1 at 80% on the x-axis [risk percentile] the pancreatic cancer risk value is 4.0% indicating that, after the END-PAC score, 80% of subjects in the cohort have a calculated risk below 4.0% and only 20% have risk at or above 4.0. The line intersecting at the 80^th percentile on the lower half of the graph gives the sensitivity (80%) and specificity (80%) of the END-PAC score at the corresponding risk percentage. Abbreviations: NOD, new-onset diabetes; PC, pancreatic cancer;

Figure 2

A. Distribution of score in all patients; B. Sensitivity of END-PAC score in PC-NOD based on lead time Abbreviations: PC-NOD, pancreatic cancer new-onset diabetes; T2-NOD, type 2 new-onset diabetes

Figure 3

Guidelines for clinical workup on new-onset diabetes for pancreatic cancer Abbreviations: CT, computerized tomography; EUS, endoscopic ultrasound; FBG, fasting blood glucose, RBG, random blood glucose;

Figure 4

Comparison of predictiveness curves of new-onset diabetes + weight loss vs. END-PAC model Abbreviations: NOD, new-onset diabetes; PC, pancreatic cancer