Peripheral artery disease (PAD) is a leading cause of cardiovascular morbidity and mortality1; however, the extent to which genetic factors increase risk for PAD is largely unknown. Using electronic health record data, we performed a genome-wide association study in the Million Veteran Program testing ~32 million DNA sequence variants with PAD (31,307 cases and 211,753 controls) across veterans of European, African, and Hispanic ancestry. The results were replicated in an independent sample of 5,117 PAD cases and 389,291 controls from UK Biobank. We identified 19 PAD loci, 18 of which have not been previously reported. 11 of the 19 loci were associated with disease in three vascular beds (coronary, cerebral, peripheral), including LDLR, LPL, and LPA, suggesting that therapeutic modulation of LDL cholesterol, the LPL pathway or circulating lipoprotein(a) may be efficacious for multiple atherosclerotic disease phenotypes. Conversely, 4 of the variants appeared to be specific for PAD, including F5 p.R506Q, highlighting the pathogenic role of thrombosis in the peripheral vascular bed and providing genetic support for Factor Xa inhibition as a therapeutic strategy for PAD. Our results highlight mechanistic similarities and differences among coronary, cerebral, and peripheral atherosclerosis and provide therapeutic insights.
IMPORTANCE Prostate cancer (PCa) disproportionately affects African American men, but research evaluating the extent of racial and ethnic disparities across the PCa continuum in equal-access settings remains limited at the national level. The US Department of Veterans Affairs (VA) Veterans Hospital Administration health care system offers a setting of relatively equal access to care in which to assess racial and ethnic disparities in self-identified African American (or Black) veterans and White veterans. OBJECTIVETo determine the extent of racial and ethnic disparities in the incidence of PCa, clinical stage, and outcomes between African American patients and White patients who received a diagnosis or were treated at a VA hospital. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study included 7 889 984 veterans undergoing routine care in VA hospitals nationwide from 2005 through 2019 (incidence cohort). The age-adjusted incidence of localized and de novo metastatic PCa was estimated.Treatment response was evaluated, and PCa-specific outcomes were compared between African American veterans and White veterans. Residual disparity in PCa outcome, defined as the leftover racial and ethnic disparity in the outcomes despite equal response to treatment, was estimated.EXPOSURES Self-identified African American (or Black) and White race and ethnicity. MAIN OUTCOMES AND MEASURESTime to distant metastasis following PCa diagnosis was the primary outcome. Descriptive analyses were used to compare baseline demographics and clinic characteristics. Multivariable logistic regression was used to evaluate race and ethnicity association with pretreatment clinical variables. Multivariable Cox regression was used to estimate the risk of metastasis.RESULTS Data from 7 889 984 veterans from the incidence cohort were used to estimate incidence, whereas data from 92 269 veterans with localized PCa were used to assess treatment response.Among 92 269 veterans, African American men (n = 28 802 [31%]) were younger (median [IQR], 63 [58][59][60][61][62][63][64][65][66][67][68] vs 65 [62-71] years) and had higher prostate-specific antigen levels (>20 ng/mL) at the time of diagnosis compared with White men (n = 63 467; [69%]). Consistent with US population-level data, African American veterans displayed a nearly 2-fold greater incidence of localized and de novo metastatic PCa compared with White men across VA centers nationwide. Among veterans screened for PCa, African American men had a 29% increased risk of PCa detection on a diagnostic prostate biopsy compared with White (hazard ratio, 1.29; 95% CI, 1.27-1.31; P < .001). African American men who received definitive primary treatment of PCa experienced a lower risk of metastasis (hazard ratio, 0.89; 95% CI, 0.83-0.95; P < .001). However, African American men who were classified as (continued) Key Points Question Are there racial and ethnic disparities associated with the incidence, clinical stage, and outcomes of prostate cancer among men treated in the Veterans Affairs health care...
Introduction Identifying occurrences of medication side effects and adverse drug events (ADEs) is an important and challenging task because they are frequently only mentioned in clinical narrative and are not formally reported. Methods We developed a natural language processing (NLP) system that aims to identify mentions of symptoms and drugs in clinical notes and label the relationship between the mentions as indications or ADEs. The system leverages an existing word embeddings model with induced word clusters for dimensionality reduction. It employs a conditional random field (CRF) model for named entity recognition (NER) and a random forest model for relation extraction (RE). Results Final performance of each model was evaluated separately and then combined on a manually annotated evaluation set. The micro-averaged F1 score was 80.9% for NER, 88.1% for RE, and 61.2% for the integrated systems. Outputs from our systems were submitted to the NLP Challenges for Detecting Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0) competition (Yu et al. in http://bio-nlp.org/index.php/projects/39-nlp-challenges , 2018 ). System performance was evaluated in three tasks (NER, RE, and complete system) with multiple teams submitting output from their systems for each task. Our RE system placed first in Task 2 of the challenge and our integrated system achieved third place in Task 3. Conclusion Adding to the growing number of publications that utilize NLP to detect occurrences of ADEs, our study illustrates the benefits of employing innovative feature engineering.
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