Purpose Familial Pancreatic Cancer (FPC) kindreds contain at least two affected first-degree relatives (FDR). Comprehensive data are needed to assist clinical risk assessment and genetic testing. Methods Germline DNA samples from 727 unrelated probands with positive family history (521 met criteria for FPC) were CLIA-tested for mutations in BRCA1 and BRCA2 (including analysis of deletions and rearrangements), PALB2, and CDKN2A. We compared prevalence of deleterious mutations between FPC probands and non-FPC probands (kindreds containing at least two affected biologic relatives, but not FDR). We also examined the impact of family history of breast and ovarian cancer and melanoma. Results Prevalence of deleterious mutations (excluding variants of unknown significance) among FPC probands was: BRCA1, 1.2%; BRCA2, 3.7%; PALB2, 0.6%; CDKN2A, 2.5%. Four novel deleterious mutations were detected. FPC probands carry more mutations in the four genes (8.0%) than non-FPC probands (3.5%) (odds ratio=2.40, 95% CI=(1.06, 5.44), p=0.03). The probability of testing positive for deleterious mutations in any of the four genes ranges up to 10.4%, depending upon family history of cancers. BRCA2 and CDKN2A account for the majority of mutations in FPC. Conclusion Genetic testing of multiple relevant genes in probands with a positive family history is warranted, particularly for FPC.

The inclusion of metformin in the treatment arms of cancer clinical trials is based on improved survival that has been demonstrated in retrospective epidemiologic studies; however, unintended biases may exist when analysis is performed by using a conventional Cox proportional hazards regression model with dichotomous ever/never categorization. We examined the impact of metformin exposure definitions, analytical methods, and patient selection on the estimated effect size of metformin exposure on survival in a large cohort of patients with pancreatic ductal adenocarcinoma (PDAC). Patients and MethodsOf newly diagnosed patients with PDAC with diabetes, 980 were retrospectively included, and exposure to metformin documented. Median survival was assessed by using Kaplan-Meier and logrank methods. Hazard ratios (HR) and 95% CIs were computed to compare time-varying covariate analysis with conventional Cox proportional hazards regression analysis. ResultsMedian survival of metformin users versus nonusers was 9.9 versus 8.9 months, respectively. By the time-varying covariate analysis, metformin use was not statistically significantly associated with improved survival (HR, 0.93; 95% CI, 0.81 to1.07; P = .28). There was no evidence of benefit in the subset of patients who were naïve to metformin at the time of PDAC diagnosis (most representative of patients enrolled in clinical trials; HR, 1.01; 95% CI, 0.80 to 1.30; P = .89); however, when the analysis was performed by using the conventional Cox model, an artificial survival benefit of metformin was detected (HR, 0.88; 95% CI, 0.77 to 1.01; P = .08), which suggested biased results from the conventional Cox analysis. ConclusionOur findings did not suggest the benefit of metformin use after patients are diagnosed with PDAC. We highlight the importance of patient selection and appropriate statistical analytical methods when studying medication exposure and cancer survival.