RESUMEN
The ways in which the social drivers of health, also known as the social determinants of health (SDOH), affect health outcomes for people with inherited bleeding disorders (PwIBDs) is unclear. This systematic review of the published literature examines the impact of SDOH on health outcomes in PwIBDs. Articles that included the following parameters in PubMed informed this study: published in English between 2011-2021; available in free full text; study population diagnosed with an inherited bleeding disorder; and study measured at least one of the clinical/non-clinical outcome measures: bleeding frequency, chronic pain, mortality, quality of life (QOL), and/or cost. The main findings from the 13 included articles emphasized the unmet need for reducing the economic burden with sustainable population health strategies and treatment options for PwIBDs. Rural location was also a significant contributor to both delayed diagnosis and decreased access to care. Furthermore, the need for a multidisciplinary comprehensive care team to address physical, psychosocial, and emotional needs of PwIBDs was raised as a priority target in the desire for equitable and optimal health. This systematic literature review suggests that the SDOH are associated with inferior health outcomes and may influence the clinical progression of inherited bleeding disorders.
RESUMEN
INTRODUCTION: Recent clinical trials are considering inclusion of more than just apolipoprotein E (APOE) ε4 genotype as a way of reducing variability in analysis of outcomes. METHODS: Case-control data were used to compare the capacity of age, sex, and 58 Alzheimer's disease (AD)-associated single nucleotide polymorphisms (SNPs) to predict AD status using several statistical models. Model performance was assessed with Brier scores and tenfold cross-validation. Genotype and sex × age estimates from the best performing model were combined with age and intercept estimates from the general population to develop a personalized genetic risk score, termed age, and sex-adjusted GenoRisk. RESULTS: The elastic net model that included age, age x sex interaction, allelic APOE terms, and 29 additional SNPs performed the best. This model explained an additional 19% of the heritable risk compared to APOE genotype alone and achieved an area under the curve of 0.747. DISCUSSION: GenoRisk could improve the risk assessment of individuals identified for prevention studies.