Daniel C. Beachler

Determine whether the risk factors for pancreatic ductal adenocarcinoma (PDAC) differ from other rare subtypes of pancreatic cancer, such as pancreatic neuroendocrine tumors (PNETs). In this retrospective cohort (case-only) database study, the study population was pancreatic cancer patients with histology information in the Cancer Care Quality Program between July 2014 and May 2025. Multivariate logistic regression models were developed to identify independent differences in risk factors for PNETs (vs. PDACs) and other pancreatic cancers (vs. PDACs). This study included the following incident pancreatic cancer frequencies: 7,973 PDACs, 649 PNETs, and 363 other pancreatic cancers. PNETs and other pancreatic cancer patients were younger than PDACs (mean 57 and 60 vs. 62). PNET patients were more likely to have newly diagnosed diabetes prior to their pancreatic cancer diagnosis (aOR = 1.37, 95%CI = 0.98-1.97), and less likely to smoke (aOR = 0.80, 95%CI = 0.64-1.01). PNETs and other pancreatic cancers had slightly higher baseline co-morbidity scores (Charlson) than PDACs (1.7 vs. 2.6 vs. 2.8). Other pancreatic cancers were more likely to be current alcohol drinkers (aOR = 2.86, 95%CI = 1.25-6.59). Common risk factors such as obesity and family history of pancreatic cancer were similar among the three cohorts. This study suggests there may be different risk factors for rarer pancreatic cancer subtypes. Differences such as younger age and more alcohol use were noteworthy in the rarer pancreatic subtypes.

Purpose: Active monitoring of health outcomes after COVID‐19 vaccination provides early detection of rare outcomes post‐licensure. We evaluated health outcomes following bivalent COVID‐19 Pfizer‐BioNTech (BNT162b2) and Moderna (mRNA‐1273.222) vaccination in the United States.Methods: Multiple health outcomes were monitored monthly from August 2022 to July 2023 in four administrative claims databases (CVS Health, Carelon Research, Optum, and Medicare). The study included individuals 6 months and older who received a bivalent COVID‐19 BNT162b2 or mRNA‐1273.222 vaccination during the study period and met a minimum continuous enrollment requirement in a medical insurance plan prior to COVID‐19 vaccination. Descriptive analyses monitored counts of vaccinations, outcomes, and concomitant COVID‐19 and influenza vaccination. Maximized Sequential Probability Ratio Testing (MaxSPRT) tested for elevations in the observed incidence rate of outcomes post‐vaccination compared to annual historical rates estimated from 2019 or 2020, adjusted for claims delay in the observed rate. Where case counts permitted, historical rates were standardized by age and/or sex for all persons, and race and/or nursing home residency status for Medicare persons only.Results: Overall, 13.9 million individuals 6 months and older received a bivalent COVID‐19 vaccine. A statistical signal occurred for two outcomes in one database (significance level of 1%): anaphylaxis following both bivalent COVID‐19 vaccines in persons 18–64 years and myocarditis/pericarditis following bivalent BNT162b2 vaccines in individuals 18–35 years. Among 642 142 vaccinated children 6 months–17 years, no signals were identified.Conclusions: Results were consistent with published COVID‐19 vaccine safety studies and support the safety profile of bivalent COVID‐19 mRNA vaccines.

Background and Methods: The Healthcare Integrated Research Database (HIRD) is a large, comprehensive real‐world data (RWD) source for health‐related research. Demographic and healthcare‐related characteristics of individuals are sourced from routinely updated RWD. The HIRD includes health insurance claims and other health‐related information for individuals enrolled in health insurance plans offered or managed by Elevance Health and has been utilized for research for almost two decades. Individuals in the HIRD reside throughout the United States. Data in the HIRD have been available since January 2006, and are updated monthly.Results: As of July 2024, the researchable population of the HIRD included over 91 million individuals with medical benefits, and over 24 million individuals were actively enrolled. The median age of individuals in the HIRD is 36 years (interquartile range [IQR]: 22, 54), and 50% of individuals in the HIRD are female. The median duration of continuous enrollment in the HIRD is 2.0 years (IQR: 0.8, 4.7). For those actively enrolled, the median duration of continuous enrollment is 3.8 years (IQR: 1.7, 8.3). Other important characteristics of the HIRD include the ability to trace data back to their source, support both deterministic and probabilistic linkage with external data sources, and link family members within health plans.Conclusions: The HIRD has been a trusted resource to generate real‐world evidence for a variety of health‐related research, including regulatory‐required safety studies, comparative effectiveness studies, and health economics and outcomes research.

The Healthcare Integrated Research Database (HIRD) is a real-world data source for health-related research. Data elements of the HIRD, including sourcing, timeliness, and validity, demographic and healthcare-related characteristics of individuals in the HIRD, and aspects of the HIRD relevant to real-world evidence generation, are described. The HIRD includes health insurance claims and other health-related information for individuals enrolled in health insurance plans offered or managed by Elevance Health and has been utilized for research for almost two decades. Individuals in the HIRD reside throughout the United States. Data in the HIRD are available since January 1, 2006, and are updated monthly. As of July 31, 2024, the researchable population of the HIRD included over 91 million individuals with medical benefits, and over 24 million individuals were actively enrolled. The median age of individuals in the HIRD is 36 years (interquartile range, IQR: 22, 54) and 50% of individuals in the HIRD are female. The median duration of continuous enrollment in the HIRD is 2.0 years (IQR: 0.8, 4.7). For those actively enrolled, the median duration of continuous enrollment is 3.8 years (IQR: 1.7, 8.3). Other important characteristics of the HIRD include the ability to trace data back to their source, to support both deterministic and probabilistic linkage with external data sources, and to link family members within health plans. The HIRD has been a trusted resource to generate real-world evidence for a variety of health-related research, including regulatory required safety studies, comparative effectiveness studies, and health outcomes and economics research.

Purpose: We investigated time trends in validation performance characteristics for six sources of death data available within the Healthcare Integrated Research Database (HIRD) over 8 years.Methods: We conducted a secondary analysis of a cohort of advanced cancer patients with linked National Death Index (NDI) data identified in the HIRD between 2010 and 2018. We calculated sensitivity, specificity, positive predictive value, and negative predictive value for six sources of death status data and an algorithm combining data from available sources using NDI data as the reference standard. Measures were calculated for each year of the study including all members in the cohort for at least 1 day in that year.Results: We identified 27 396 deaths from any source among 40 692 cohort members. Between 2010 and 2018, the sensitivity of the Death Master File (DMF) decreased from 0.77 (95% CI = 0.76, 0.79) to 0.12 (95% CI = 0.11, 0.14). In contrast, the sensitivity of online obituary data increased from 0.43 (95% CI = 0.41, 0.45) in 2012 to 0.71 (95% CI = 0.68, 0.73) in 2018. The sensitivity of the composite algorithm remained above 0.83 throughout the study period. PPV was observed to be high from 2010 to 2016 and decrease thereafter for all sources. Specificity and NPV remained at high levels throughout the study.Conclusions: We observed that the sensitivity of mortality data sources compared with the NDI could change substantially between 2010 and 2018. Other validation characteristics were less variable. Combining multiple sources of mortality data may be necessary to achieve adequate performance particularly for multiyear studies.

Purpose Ascertainment of mortality is critical to epidemiologic studies. Secondary collected database studies face challenges given the need to record mortality data in health claims or electronic medical records. The National Death Index (NDI) is the gold standard for mortality data in the U.S. Methods This study is a secondary analysis of an advanced cancer cohort in the U.S. between January 2010 and December 2018, with an established NDI linkage. Mortality data sources, inpatient discharge, disenrollment, death master file (DMF), Center for Medicare and Medicaid Services (CMS), Utilization management data (U.M.), and online obituary data were compared to NDI. We calculated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and 95% confidence intervals (95% CI). Per each source, death identified 60 days before and 30 days after NDI death was deemed a match. Results Among 40,692 patients, 25,761 (63.3%) had a death date using NDI; the composite algorithm had a sensitivity of 88.9% (95% CI= 88.5%, 89.3%), specificity was 89.1% (95% CI= 88.6%, 89.6%). At the same time, PPV was 93.4% (95% CI= 93.1%, 93.7%), NPV was 82.3% (95% CI= 81.7%, 82.9%), and when comparing each individual source, each had a high PPV but limited sensitivity. Conclusion The composite algorithm was demonstrated to be a sensitive and precise measure of mortality in advanced cancer patients in the U.S. from 2010 to 2018, while individual database sources were accurate but had limited sensitivity compared to the NDI.

Introduction At the time of dapagliflozin’s approval in Europe (2012) to treat patients with type 2 diabetes mellitus, concerns regarding acute liver injury and severe complications of urinary tract infection (sUTI) led to two post-authorization safety (PAS) studies of these outcomes to monitor the safety of dapagliflozin in real-world use. Objective To investigate the incidence of hospitalization for acute liver injury (hALI) or sUTI (pyelonephritis or urosepsis) among patients initiating dapagliflozin compared with other glucose-lowering drugs (GLDs). Methods These two noninterventional cohort studies identified initiators of dapagliflozin and comparator GLDs in November 2012–February 2019 using data from three longitudinal, population-based data sources: Clinical Practice Research Datalink (UK), the HealthCore Integrated Research Database (USA), and the Medicare database (USA). Outcomes (hALI and sUTI) were identified with electronic algorithms. Incidence rates were estimated by exposure group. Incidence rate ratios (IRRs) were calculated comparing dapagliflozin to comparator GLDs, using propensity score trimming and stratification to address confounding. The sUTI analyses were conducted separately by sex. Results In all data sources, hALI and sUTI incidence rates were generally lower in dapagliflozin initiators than comparator GLD initiators. The adjusted IRR (95% confidence interval) pooled across data sources for hALI was 0.85 (0.59–1.24) and for sUTI was 0.76 (0.60–0.96) in females and 0.74 (0.56–1.00) in males. Findings from sensitivity analyses were largely consistent with the primary analyses. Conclusions These real-world studies do not suggest increased risks of hALI or sUTI, and they suggest a potential decreased risk of sUTI with dapagliflozin exposure compared with other GLDs.

Introduction Dapagliflozin is a sodium-glucose cotransporter 2 inhibitor approved to treat type 2 diabetes mellitus (T2DM), among other conditions. When dapagliflozin was approved in Europe for treating T2DM (2012), potential safety concerns regarding its effect on kidney function resulted in this post-authorization safety study to assess hospitalization for acute kidney injury (hAKI) among dapagliflozin initiators in a real-world setting. Objective The aim of this study was to evaluate the incidence of hAKI in adults with T2DM initiating dapagliflozin compared with other glucose-lowering drugs (GLDs). Methods This noninterventional cohort study identified new users of dapagliflozin and comparator GLDs from November 2012 to February 2019 from three longitudinal, population-based data sources: Clinical Practice Research Datalink (CPRD; United Kingdom), the HealthCore Integrated Research Database (HIRD; United States [US]), and Medicare (US). Electronic algorithms identified occurrences of hAKI, from which a sample underwent validation. Incidence rates for hAKI were calculated, and incidence rate ratios (IRRs) compared hAKI in dapagliflozin with comparator GLDs. Propensity score trimming and stratification were conducted for confounding adjustment. Results In all data sources, dapagliflozin initiators had a lower hAKI incidence rate than comparator GLD initiators (adjusted IRRs: CPRD, 0.44 [95% confidence interval (CI), 0.22–0.86]; HIRD, 0.76 [95% CI, 0.62–0.93]; Medicare, 0.69 [95% CI, 0.59–0.79]). The adjusted IRR pooled across the data sources was 0.70 (95% CI, 0.62–0.78). Results from sensitivity and stratified analyses were consistent with the primary analysis. Conclusions This study, with > 34,000 person-years of real-world dapagliflozin exposure, suggests a decreased risk of hAKI in patients with T2DM exposed to dapagliflozin, aligning with results from dapagliflozin clinical trials. Study registration European Union Post-Authorisation Studies Register, EUPAS 11684; ClinicalTrials.gov, NCT02695082.