Effects of Social Determinants and Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions.

Context: The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. Objective: Evaluate aggregate contribution of social determinants, comorbidity, and gene-x-drug interactions to moderate 90-day hospital readmission. Study Design and Analysis: Non-concurrent cohort study; Multivariable logistic regression Setting: Hospital/integrated healthcare delivery system in northern Illinois Population Studied: 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel Outcome Measure: 90-day hospital readmission (primary outcome) Results: Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.66, 95% confidence interval 5.45-10.77) (p < 0.0001), major comorbidities (5+ comorbidities, OR 3.36, 2.61-4.32) (p < 0.0001), age (65 + years, OR = 2.35, 1.77-3.12) (p < 0.0001), unemployment (OR = 2.19, 1.88-2.64) (p < 0.0001), Black/African-American race (OR 2.12, 1.47-3.07) (p < 0.0001), median household income (OR = 1.63, 1.03-2.58) (p = 0.035), male gender (OR = 1.47, 1.21-1.80) (p = 0.0001), and one or more gene-x-drug interaction (defined as a prescribed CPIC medication for a patient with a corresponding actionable pharmacogenetic variant) (OR = 1.41, 1.18-1.70). Health insurance was not associated with risk of 90-day readmission. Race, income, employment status, and gene-x-drug interactions were robust in a multivariable logistic regression model. The odds of 90-day readmission for patients with one or more identified gene-x-drug interactions after adjustment for these covariates was attenuated by 10% (OR = 1.31, 1.08-1.59) (p = 0.006). Although the interaction between race and gene-x-drug interactions was not statistically significant, White patients were more likely to have a gene-x-drug interaction (35.2%) than Black/African-American patients (25.9%) who were not readmitted (p < 0.0001). Conclusions: These results highlight the major contribution of social determinants and medical complexity to risk for hospital readmission, and that these determinants may modify the effect of gene-x-drug interactions on rehospitalization risk.

Cancer-associated thrombosis by cancer sites and inherited factors in a prospective population-based cohort.

Cancer-associated thrombosis (CAT) is common and associated with mortality. We estimated CAT rate by cancer sites and inherited factors among cancer patients from the UK Biobank (N =70,406). The 12-month CAT rate after cancer diagnosis was 2.37% overall but varied considerably among cancer sites. Among the 10 cancer sites classified as 'high-risk' of CAT by the National Comprehensive Cancer Network guidelines, 6 had CAT rate <5%. In contrast, 5 cancer sites classified as 'average-risk' by the guidelines had CAT rate >5%. For inherited risk factors, both known mutation carriers in two genes (F5/F2) and polygenic score for venous thromboembolism (VTE) (PGSVTE) were independently associated with increased CAT risk. While F5/F2 identified 6% patients with high genetic-risk for CAT, adding PGSVTE identified 13 % patients at equivalent/higher genetic-risk to CAT than that of F5/F2 mutations. Findings from this large prospective study, if confirmed, provide critical data to update guidelines for CAT risk assessment.

Observed evidence for guideline-recommended genes in predicting prostate cancer risk from a large population-based cohort.

BACKGROUND: Germline testing for prostate cancer (PCa) is now recommended by the National Comprehensive Cancer Network. While multi-gene testing has been proposed, evidence for their association with PCa risk is not well established. METHODS: We tested associations of pathogenic/likely pathogenic mutations in 10 guideline-recommended genes (ATM, BRCA1, BRCA2, CHEK2, PALB2, MLH1, MSH2, MSH6, PMS2, and HOXB13) with PCa risk in the UK Biobank, a population-based cohort. Mutations were annotated based on prostate-specific transcripts using the American College of Medical Genetics and Genomics standards. Associations were tested in 4399 PCa cases and 85,403 unaffected male controls using logistic regression adjusting for age and genetic background. p < .005 was considered significant based on Bonferroni correction. RESULTS: Among the 10 tested genes, significantly higher mutation carrier rates in PCa cases versus controls were found for four genes at p < .005; HOXB13, BRCA2, ATM, and CHEK2, with odds ratios (95% confidence interval) estimated at 4.96 (3.62-6.69), 3.23 (2.23-4.56), 2.95 (2.01-4.22), 1.94 (1.43-2.58), respectively. No significant association was found between mutation carrier status and age at PCa diagnosis or family history of PCa. Despite the large sample size of this study, statistical power remains limited, especially for genes where pathogenic mutation carrier rates are extremely rare (<0.03%). CONCLUSION: Observed evidence for PCa risk was found for four of the 10 guideline-recommended genes in this large population-based study. Mutations in these four genes can be interpreted with confidence in genetic counseling for PCa risk assessment. Evidence for the remaining six genes needs to be further evaluated in larger studies.

Implementing Primary Care Mediated Population Genetic Screening Within an Integrated Health System.

INTRODUCTION: Genetic screenings can have a large impact on enabling personalized preventive care. However, this can be limited by the primary use of medical history-based screenings in determining care. The purpose of this study was to understand the impact of DNA10K, a population-based genetic screening program mediated by primary care physicians within an integrated health system to emphasize its contribution to preventive healthcare. METHODS: Construction of the patient experience as part of DNA10K shaped the context for PCP engagement within the program. A cross-sectional analysis of patient consents, orders, tests, and results of nearly 10,000 patients within the primary care specialties of family medicine, internal medicine or obstetrics/gynecology between April 1, 2019 and January 22, 2020 was conducted. RESULTS: Across all specialties, a median number of 7.5 cancer and cardiovascular disease variants per PCP was found. The average age of the study population was 49.6 years. Over 8% of these patients had at least one actionable genetic risk variant and almost 2% of patients had at least one CDC Tier 1 variant. The median numbers of patients per PCP with either hereditary breast and ovarian cancer, Lynch Syndrome, or Familial Hypercholesterolemia was 1 (Interquartile Range 0-2). DISCUSSION: The analysis of test results and the engagement of an integrated healthcare system in the implementation of a genetic screening program suggests that it can have a large impact on population health outcomes and minimal referral burden to PCPs if identified risks can lead to preventive care.

Patient perspectives following pharmacogenomics results disclosure in an integrated health system.

AIM: To assess patient perceptions and utilization of pharmacogenomics (PGx) testing in an integrated community health system. METHODS: Fifty-seven patients completed an online survey assessing their experiences with PGx testing offered through two methods: a designated PGx clinic or direct access in-home testing. RESULTS: The majority of participants perceived PGx testing as helpful in their healthcare and reported understanding their results. Some had concerns about privacy and discrimination; most lacked familiarity with the Genetic Information Nondiscrimination Act. There were no significant differences in views between participants tested through either model. CONCLUSION: Participants reported value in both methods of PGx testing. Patient experiences, understanding and result utilization will play an important role in informing future development and implementation of PGx programs.