Large-scale characterization of gender differences in diagnosis prevalence and time to diagnosis.

We carry out an analysis of gender differences in patterns of disease diagnosis across four large observational health datasets and find that women are routinely older when first assigned most diagnoses. Among 112 acute and chronic diseases, women experience longer lengths of time between symptom onset and disease diagnosis than men for most diseases regardless of metric used, even when only symptoms common to both genders are considered. These findings are consistent for patients with private as well as government insurance. Our analysis highlights systematic gender differences in patterns of disease diagnosis and suggests that symptoms of disease are measured or weighed differently for women and men. Data and code leverage the open-source common data model and analytic code and results are publicly available.

Development and evaluation of an algorithm to link mothers and infants in two US commercial healthcare claims databases for pharmacoepidemiology research.

BACKGROUND: Administrative healthcare claims databases are used in drug safety research but are limited for investigating the impacts of prenatal exposures on neonatal and pediatric outcomes without mother-infant pair identification. Further, existing algorithms are not transportable across data sources. We developed a transportable mother-infant linkage algorithm and evaluated it in two, large US commercially insured populations. METHODS: We used two US commercial health insurance claims databases during the years 2000 to 2021. Mother-infant links were constructed where persons of female sex 12-55 years of age with a pregnancy episode ending in live birth were associated with a person who was 0 years of age at database entry, who shared a common insurance plan ID, had overlapping insurance coverage time, and whose date of birth was within ± 60-days of the mother's pregnancy episode live birth date. We compared the characteristics of linked vs. non-linked mothers and infants to assess similarity. RESULTS: The algorithm linked 3,477,960 mothers to 4,160,284 infants in the two databases. Linked mothers and linked infants comprised 73.6% of all mothers and 49.1% of all infants, respectively. 94.9% of linked infants' dates of birth were within ± 30-days of the associated mother's pregnancy episode end dates. Characteristics were largely similar in linked vs. non-linked mothers and infants. Differences included that linked mothers were older, had longer pregnancy episodes, and had greater post-pregnancy observation time than mothers with live births who were not linked. Linked infants had less observation time and greater healthcare utilization than non-linked infants. CONCLUSIONS: We developed a mother-infant linkage algorithm and applied it to two US commercial healthcare claims databases that achieved a high linkage proportion and demonstrated that linked and non-linked mother and infant cohorts were similar. Transparent, reusable algorithms applied to large databases enable large-scale research on exposures during pregnancy and pediatric outcomes with relevance to drug safety. These features suggest studies using this algorithm can produce valid and generalizable evidence to inform clinical, policy, and regulatory decisions.

The Epidemiology of Palmoplantar Pustulosis: An Analysis of Multiple Health Insurance Claims and Electronic Health Records Databases.

BACKGROUND: Palmoplantar pustulosis (PPP) is a chronic inflammatory condition characterized by sterile pustules on the palms and soles. This study evaluated the epidemiology of PPP using claims and electronic health record (EHR) databases. METHODS: Patients coded for PPP in the United States (US) and Japan from 2016 to 2020 were identified. Several PPP definitions were evaluated; the specific definition (≥ 2 visits coded for PPP, the second 31-730 days after diagnosis) was chosen for characterizing PPP epidemiology. Baseline characteristics and pre- and post-diagnosis treatments were summarized. Prevalence and incidence rates were analyzed by calendar year, sex, age, and database. RESULTS: Prevalence and incidence of PPP were higher in Japan than the US. PPP prevalence increased over time. PPP occurred predominantly in adulthood and was more common among women. Features of metabolic syndromes, anxiety, and depression were more common among US PPP patients. Consistently high baseline use of anti-bacterial, anti-inflammatory/anti-rheumatic, and obstructive airway disease treatments was observed among PPP patients. Potential miscoding or misclassification of PPP limited this analysis. Prevalence estimates from databases may differ from field- and population-based approaches. CONCLUSIONS: The burden of PPP was greater in Japan than in the US. Additional studies are needed to further elucidate PPP epidemiology worldwide.

Characteristics and treatment pathways in pediatric and adult hidradenitis suppurativa: An examination using real world data.

Background: Hidradenitis suppurativa (HS) is a chronic, debilitating, inflammatory disease. Contemporaneous real-world data can be used to elucidate the clinical treatment of pediatric patients and how treatment strategies compare with adult hidradenitis suppurativa patients. Objective: The objective of this study is to evaluate clinical and treatment characteristics of pediatric and adult HS patients. Methods: HS adult and pediatric patients were identified in 3 the United States administrative claims databases during the study period between 2016 to 2021. Patients were required to have 2 diagnostic codes for HS and have at least 365 days of prior observation time to the first HS diagnosis. Results: Pediatric and adult HS treatments were similar. The proportions of subjects treated with topical and oral antibiotic or oral antibiotic alone or topical medication alone or surgery alone covered 90% of the treated pediatric subjects and 91% of treated adult subjects. The remaining proportion of subjects received other treatment combinations. Limitations: The databases represent subjects with commercial or government insurance coverage and thus do not necessarily represent the broader US population. The databases do not capture information about medications obtained without insurance. Conclusions: Although subtle differences exist, this study confirms that topical and systemic therapeutic treatment of HS in adults and adolescents is very similar.

Using a data-driven approach for the development and evaluation of phenotype algorithms for systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of unknown origin. The objective of this research was to develop phenotype algorithms for SLE suitable for use in epidemiological studies using empirical evidence from observational databases. METHODS: We used a process for empirically determining and evaluating phenotype algorithms for health conditions to be analyzed in observational research. The process started with a literature search to discover prior algorithms used for SLE. We then used a set of Observational Health Data Sciences and Informatics (OHDSI) open-source tools to refine and validate the algorithms. These included tools to discover codes for SLE that may have been missed in prior studies and to determine possible low specificity and index date misclassification in algorithms for correction. RESULTS: We developed four algorithms using our process: two algorithms for prevalent SLE and two for incident SLE. The algorithms for both incident and prevalent cases are comprised of a more specific version and a more sensitive version. Each of the algorithms corrects for possible index date misclassification. After validation, we found the highest positive predictive value estimate for the prevalent, specific algorithm (89%). The highest sensitivity estimate was found for the sensitive, prevalent algorithm (77%). CONCLUSION: We developed phenotype algorithms for SLE using a data-driven approach. The four final algorithms may be used directly in observational studies. The validation of these algorithms provides researchers an added measure of confidence that the algorithms are selecting subjects correctly and allows for the application of quantitative bias analysis.

Phenotype Algorithms to Identify Hidradenitis Suppurativa Using Real-World Data: Development and Validation Study.

BACKGROUND: Hidradenitis suppurativa (HS) is a potentially debilitating, chronic, recurring inflammatory disease. Observational databases provide opportunities to study the epidemiology of HS. OBJECTIVE: This study's objective was to develop phenotype algorithms for HS suitable for epidemiological studies based on a network of observational databases. METHODS: A data-driven approach was used to develop 4 HS algorithms. A literature search identified prior HS algorithms. Standardized databases from the Observational Medical Outcomes Partnership (n=9) were used to develop 2 incident and 2 prevalent HS phenotype algorithms. Two open-source diagnostic tools, CohortDiagnostics and PheValuator, were used to evaluate and generate phenotype performance metric estimates, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value. RESULTS: We developed 2 prevalent and 2 incident HS algorithms. Validation showed that PPV estimates were highest (mean 86%) for the prevalent HS algorithm requiring at least two HS diagnosis codes. Sensitivity estimates were highest (mean 58%) for the prevalent HS algorithm requiring at least one HS code. CONCLUSIONS: This study illustrates the evaluation process and provides performance metrics for 2 incident and 2 prevalent HS algorithms across 9 observational databases. The use of a rigorous data-driven approach applied to a large number of databases provides confidence that the HS algorithms can correctly identify HS subjects.

Real-World Anticoagulant Use and Incidence of Venous Thromboembolism and Major Bleeding in Children.

PURPOSE: Children generally have a lower risk of venous thromboembolism (VTE) than adults, but those with acute and chronic conditions requiring hospitalization and surgical procedures are at increased risk. Anticoagulant use in children has not been systematically studied, and limited data exist. This study aimed to provide data on the conditions associated with use of anticoagulants, the type of anticoagulant used in children, and the incidence of thromboembolism and major bleeding events reported in this population. METHODS: To increase understanding of the use of anticoagulant therapies in children with at-risk conditions, 3 health claims databases in the United States were analyzed to describe the characteristics of use of heparins, warfarin, and direct oral anticoagulants (DOACs). Cumulative drug exposure was determined for continuous exposure, defined as >30 days. Unadjusted event rates of VTE and major bleeding after exposure to these therapies were reported. The data were presented descriptively and are not intended for comparison or to imply any causation. FINDINGS: Anticoagulants were infrequently used in the pediatric population, including at any time point after Fontan surgery for congenital heart disease. Heparins were used most frequently in the population overall and especially for patients aged <12 years. DOACs were used least often and primarily for patients ages 12 to <18 years. Among pediatric patients exposed to anticoagulants, unadjusted incidence rates of VTE per 1000 person-years of exposure ranged from 30.8 to 34.0 for all DOACs, 21.6 to 46.2 for warfarin, and 6.0 to 7.3 for heparins. Rates per 1000 person-years for major bleeding ranged from 0 to 4.9 for all DOACs, 4.3 to 6.7 for warfarin, and 3.7 to 4.6 for heparins. IMPLICATIONS: With results from clinical trials evaluating DOACs in the pediatric population expected in the next 2 years, these descriptive real-world data may provide a baseline understanding of current prescribing patterns and outcomes associated with the use of DOACs and other anticoagulants in routine pediatric clinical practice. This information represents the use of real-world evidence and may function as the benchmark for evaluating changes in prescription practices and potential outcomes in the future.

Evaluating the impact of covariate lookback times on performance of patient-level prediction models.

BACKGROUND: The goal of our study is to examine the impact of the lookback length when engineering features to use in developing predictive models using observational healthcare data. Using a longer lookback for feature engineering gives more insight about patients but increases the issue of left-censoring. METHODS: We used five US observational databases to develop patient-level prediction models. A target cohort of subjects with hypertensive drug exposures and outcome cohorts of subjects with acute (stroke and gastrointestinal bleeding) and chronic outcomes (diabetes and chronic kidney disease) were developed. Candidate predictors that exist on or prior to the target index date were derived within the following lookback periods: 14, 30, 90, 180, 365, 730, and all days prior to index were evaluated. We predicted the risk of outcomes occurring 1 day until 365 days after index. Ten lasso logistic models for each lookback period were generated to create a distribution of area under the curve (AUC) metrics to evaluate the discriminative performance of the models. Calibration intercept and slope were also calculated. Impact on external validation performance was investigated across five databases. RESULTS: The maximum differences in AUCs for the models developed using different lookback periods within a database was < 0.04 for diabetes (in MDCR AUC of 0.593 with 14-day lookback vs. AUC of 0.631 with all-time lookback) and 0.012 for renal impairment (in MDCR AUC of 0.675 with 30-day lookback vs. AUC of 0.687 with 365-day lookback ). For the acute outcomes, the max difference in AUC across lookbacks within a database was 0.015 (in MDCD AUC of 0.767 with 14-day lookback vs. AUC 0.782 with 365-day lookback) for stroke and < 0.03 for gastrointestinal bleeding (in CCAE AUC of 0.631 with 14-day lookback vs. AUC of 0.660 with 730-day lookback). CONCLUSIONS: In general the choice of covariate lookback had only a small impact on discrimination and calibration, with a short lookback (< 180 days) occasionally decreasing discrimination. Based on the results, if training a logistic regression model for prediction then using covariates with a 365 day lookback appear to be a good tradeoff between performance and interpretation.

Medications for attention-deficit/hyperactivity disorder in Japan: A retrospective cohort study of label compliance.

AIM: To assess label compliance in prescription of medications approved for treatment of attention-deficit/hyperactivity disorder (ADHD) in Japan at the time of this study: methylphenidate (MPH), atomoxetine, and guanfacine. METHODS: Retrospective descriptive study was conducted in prevalent-user cohorts from the Japan Medical Data Center database. Patients who were prescribed a study drug between January 1, 2013 and September 30, 2018 and were in the database for ≥30 days were included. A prescription was considered compliant if all 4 criteria were satisfied: appropriate age, daily dose not exceeding the approved maximum, no contraindicated concurrent medications, and no contraindicated conditions. RESULTS: Among 17 418 patients who were prescribed a study drug during 2013-2018, 73% were male and 53% were children (aged <18 years). Fewer than 2% of prescriptions were for patients outside the approved age, 10%-13% of patients in the atomoxetine and MPH cohorts received ≥1 prescription exceeding maximum approved dose, no patients were co-prescribed a contraindicated medication, and 16%-18% of patients in the MPH cohorts had ≥1 contraindicated condition. During their first 500 days of use, for approximately 73%-86% of patients, all prescriptions were compliant with all label requirements. CONCLUSIONS: Among patients exposed to ADHD medications in Japan during 2013-2018, nearly all prescriptions for these medications were label-compliant for age. For >85% of patients, all prescriptions were label-compliant for dose, and for approximately 80%, all prescriptions were label-compliant for contraindicated conditions. We did not find evidence of widespread abuse or noncompliant use of prescribed ADHD medications.

Understanding patient journey in ulcerative colitis prior to biologic initiation: a 5-year exploration.

BACKGROUND: There has been a more pronounced shift toward earlier, more aggressive therapies in Crohn's disease than in ulcerative colitis (UC). The aim of this study was to describe the pre-biologic treatment and health care experience, including co-morbidities and overall health care utilization, for UC patients who initiated biologic therapies, in the 5 years prior to the initiation of the first biologic agent. METHODS: UC patients who initiated a biologic agent approved for UC between 9/15/2005 and 1/30/2018 were identified from the IBM® MarketScan® Commercial Database, a large US database. The date of the first recorded UC biologic exposure was defined as the index date, and ≥ 5 years of pre-index records were required to evaluate patients' treatment, disease progression and overall health care utilization prior to initiating biologic agents. RESULTS: Among the 1891 eligible patients, treatment with oral corticosteroids, 5-aminosalicylates, and other non-biologic immunomodulators, all increased progressively across the 5 years prior to the index. From within year-five to within year-one prior to the index, the median duration of oral corticosteroid treatment increased from 34 to 88 days per year and the proportion of patients who experienced more extensive/pancolitis disease increased from 16 to 59%. Overall, the frequency of all-cause health care visits also increased. CONCLUSIONS: Patients with UC experienced increasing morbidity and treatment burden in the 5 years prior to initiating biologic therapy. To achieve reduced corticosteroids in UC management, better risk stratification is needed to help identify patients for more timely biologic treatment.

Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multinational network cohort study.

OBJECTIVES: Concern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA. METHODS: We performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2 <40%. RESULTS: A total of 918 144 and 290 383 users of HCQ and SSZ, respectively, were included. No consistent risk of psychiatric events was observed with short-term HCQ (compared with SSZ) use, with meta-analytic HRs of 0.96 (95% CI 0.79, 1.16) for depression, 0.94 (95% CI 0.49, 1.77) for suicide/suicidal ideation and 1.03 (95% CI 0.66, 1.60) for psychosis. No consistent long-term risk was seen, with meta-analytic HRs of 0.94 (95% CI 0.71, 1.26) for depression, 0.77 (95% CI 0.56, 1.07) for suicide/suicidal ideation and 0.99 (95% CI 0.72, 1.35) for psychosis. CONCLUSION: HCQ as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation or psychosis compared with SSZ. No effects were seen in the short or long term. Use at a higher dose or for different indications needs further investigation. TRIAL REGISTRATION: Registered with EU PAS (reference no. EUPAS34497; http://www.encepp.eu/encepp/viewResource.htm? id=34498). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine2.

Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study.

Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.

Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study.

BACKGROUND: Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis. METHODS: In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I 2 value was less than 0·4. FINDINGS: The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1·65 [95% CI 1·12-2·44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2·19 [95% CI 1·22-3·95]), chest pain or angina (1·15 [1·05-1·26]), and heart failure (1·22 [1·02-1·45]). INTERPRETATION: Hydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment. FUNDING: National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Senior Research Fellowship programme, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research and Development, IQVIA, Korea Health Industry Development Institute through the Ministry of Health and Welfare Republic of Korea, Versus Arthritis, UK Medical Research Council Doctoral Training Partnership, Foundation Alfonso Martin Escudero, Innovation Fund Denmark, Novo Nordisk Foundation, Singapore Ministry of Health's National Medical Research Council Open Fund Large Collaborative Grant, VINCI, Innovative Medicines Initiative 2 Joint Undertaking, EU's Horizon 2020 research and innovation programme, and European Federation of Pharmaceutical Industries and Associations.

Deep phenotyping of 34,128 patients hospitalised with COVID-19 and a comparison with 81,596 influenza patients in America, Europe and Asia: an international network study.

Background In this study we phenotyped individuals hospitalised with coronavirus disease 2019 (COVID-19) in depth, summarising entire medical histories, including medications, as captured in routinely collected data drawn from databases across three continents. We then compared individuals hospitalised with COVID-19 to those previously hospitalised with influenza. Methods We report demographics, previously recorded conditions and medication use of patients hospitalised with COVID-19 in the US (Columbia University Irving Medical Center [CUIMC], Premier Healthcare Database [PHD], UCHealth System Health Data Compass Database [UC HDC], and the Department of Veterans Affairs [VA OMOP]), in South Korea (Health Insurance Review & Assessment [HIRA]), and Spain (The Information System for Research in Primary Care [SIDIAP] and HM Hospitales [HM]). These patients were then compared with patients hospitalised with influenza in 2014-19. Results 34,128 (US: 8,362, South Korea: 7,341, Spain: 18,425) individuals hospitalised with COVID-19 were included. Between 4,811 (HM) and 11,643 (CUIMC) unique aggregate characteristics were extracted per patient, with all summarised in an accompanying interactive website (http://evidence.ohdsi.org/Covid19CharacterizationHospitalization/). Patients were majority male in the US (CUIMC: 52%, PHD: 52%, UC HDC: 54%, VA OMOP: 94%,) and Spain (SIDIAP: 54%, HM: 60%), but were predominantly female in South Korea (HIRA: 60%). Age profiles varied across data sources. Prevalence of asthma ranged from 4% to 15%, diabetes from 13% to 43%, and hypertensive disorder from 24% to 70% across data sources. Between 14% and 33% were taking drugs acting on the renin-angiotensin system in the 30 days prior to hospitalisation. Compared to 81,596 individuals hospitalised with influenza in 2014-19, patients admitted with COVID-19 were more typically male, younger, and healthier, with fewer comorbidities and lower medication use. Conclusions We provide a detailed characterisation of patients hospitalised with COVID-19. Protecting groups known to be vulnerable to influenza is a useful starting point to minimize the number of hospital admissions needed for COVID-19. However, such strategies will also likely need to be broadened so as to reflect the particular characteristics of individuals hospitalised with COVID-19.

Criteria2Query: a natural language interface to clinical databases for cohort definition.

OBJECTIVE: Cohort definition is a bottleneck for conducting clinical research and depends on subjective decisions by domain experts. Data-driven cohort definition is appealing but requires substantial knowledge of terminologies and clinical data models. Criteria2Query is a natural language interface that facilitates human-computer collaboration for cohort definition and execution using clinical databases. MATERIALS AND METHODS: Criteria2Query uses a hybrid information extraction pipeline combining machine learning and rule-based methods to systematically parse eligibility criteria text, transforms it first into a structured criteria representation and next into sharable and executable clinical data queries represented as SQL queries conforming to the OMOP Common Data Model. Users can interactively review, refine, and execute queries in the ATLAS web application. To test effectiveness, we evaluated 125 criteria across different disease domains from ClinicalTrials.gov and 52 user-entered criteria. We evaluated F1 score and accuracy against 2 domain experts and calculated the average computation time for fully automated query formulation. We conducted an anonymous survey evaluating usability. RESULTS: Criteria2Query achieved 0.795 and 0.805 F1 score for entity recognition and relation extraction, respectively. Accuracies for negation detection, logic detection, entity normalization, and attribute normalization were 0.984, 0.864, 0.514 and 0.793, respectively. Fully automatic query formulation took 1.22 seconds/criterion. More than 80% (11+ of 13) of users would use Criteria2Query in their future cohort definition tasks. CONCLUSIONS: We contribute a novel natural language interface to clinical databases. It is open source and supports fully automated and interactive modes for autonomous data-driven cohort definition by researchers with minimal human effort. We demonstrate its promising user friendliness and usability.

Liver Test Monitoring: Real-World Compliance for Drugs with Monitoring Requirements at 2-Week Intervals or More Frequently.

BACKGROUND: Monitoring risk is often an important component of therapy. Some compounds require liver test (LT) monitoring, with the frequency detailed in the product label. Compliance with these instructions is generally unknown. OBJECTIVE: The goal of this short study was to describe LT compliance for compounds with monitoring recommended at 2-week intervals or more frequently in three US administrative claims databases. METHODS: The sample was drawn from three US claims databases during the period 1 January 2015 through 30 June 2018. This study examined nine compounds and five types of LTs. We looked at compounds in a published list of drugs requiring LTs at 2-week intervals or more frequently. Descriptive statistics about the days between tests were reported, as were the number and proportion of tests associated with each drug that met the recommended frequency. RESULTS: Compliance was < 33% with four drugs (ketoconazole, succimer, pentamidine, and felbamate) and > 60% with five drugs (oxaliplatin, rifampin, tolcapone, albendazole, and azathioprine). Among drugs with more than 1000 drug eras observed (all but succimer and tolcapone), LT compliance was highest for oxaliplatin (75.3%) and lowest for pentamidine (20.6%), with little difference in overall compliance by type of test (range 41-46). CONCLUSION: Compliance with frequent LT monitoring differed for the drugs examined. Two strata were found: compliance > 60% (oxaliplatin, rifampin, tolcapone, albendazole, and azathioprine) and compliance 20-30% (ketoconazole, succimer, pentamidine, and felbamate). No drug reached 80% compliance.

Association of the OPRM1 Variant rs1799971 (A118G) with Non-Specific Liability to Substance Dependence in a Collaborative de novo Meta-Analysis of European-Ancestry Cohorts.

The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for "general" substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83-0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.

Longitudinal genetic analysis of brain volumes in normal elderly male twins.

This study investigated the role of genetic and environmental influences on individual differences in brain volumes measured at 2 time points in normal elderly males from the National Heart, Lung, and Blood Institute Twin Study. The magnetic resonance imaging (MRI) scans were conducted 4 years apart on 33 monozygotic and 33 dizygotic male twin pairs, aged 68 to 77 years when first scanned. Volumetric measures of total brain and total cerebrospinal fluid were significantly heritable at baseline (over 70%). For both volumes genetic influences at follow-up were entirely accounted for by genetic influences at baseline, suggesting that the same genetic factors influence variability in brain volume at each time of assessment. Variability in 4-year volume change was due to shared and individual-specific environmental influences. There was little evidence for heritable influences on change measures. These results suggest that variation in longitudinal change of some brain volume measures may have different underlying genetic and environmental architecture from variation in repeat cross-sectional measures, which could have implications for intervention strategies for age-related illness associated with brain morphology. The results of this study are discussed in the context of the small sample size and associated limitations of statistical power.

A genetic signature of spina bifida risk from pathway-informed comprehensive gene-variant analysis.

Despite compelling epidemiological evidence that folic acid supplements reduce the frequency of neural tube defects (NTDs) in newborns, common variant association studies with folate metabolism genes have failed to explain the majority of NTD risk. The contribution of rare alleles as well as genetic interactions within the folate pathway have not been extensively studied in the context of NTDs. Thus, we sequenced the exons in 31 folate-related genes in a 480-member NTD case-control population to identify the full spectrum of allelic variation and determine whether rare alleles or obvious genetic interactions within this pathway affect NTD risk. We constructed a pathway model, predetermined independent of the data, which grouped genes into coherent sets reflecting the distinct metabolic compartments in the folate/one-carbon pathway (purine synthesis, pyrimidine synthesis, and homocysteine recycling to methionine). By integrating multiple variants based on these groupings, we uncovered two provocative, complex genetic risk signatures. Interestingly, these signatures differed by race/ethnicity: a Hispanic risk profile pointed to alterations in purine biosynthesis, whereas that in non-Hispanic whites implicated homocysteine metabolism. In contrast, parallel analyses that focused on individual alleles, or individual genes, as the units by which to assign risk revealed no compelling associations. These results suggest that the ability to layer pathway relationships onto clinical variant data can be uniquely informative for identifying genetic risk as well as for generating mechanistic hypotheses. Furthermore, the identification of ethnic-specific risk signatures for spina bifida resonated with epidemiological data suggesting that the underlying pathogenesis may differ between Hispanic and non-Hispanic groups.

Impact of meat consumption, preparation, and mutagens on aggressive prostate cancer.

BACKGROUND: The association between meat consumption and prostate cancer remains unclear, perhaps reflecting heterogeneity in the types of tumors studied and the method of meat preparation--which can impact the production of carcinogens. METHODS: We address both issues in this case-control study focused on aggressive prostate cancer (470 cases and 512 controls), where men reported not only their meat intake but also their meat preparation and doneness level on a semi-quantitative food-frequency questionnaire. Associations between overall and grilled meat consumption, doneness level, ensuing carcinogens and aggressive prostate cancer were assessed using multivariate logistic regression. RESULTS: Higher consumption of any ground beef or processed meats were positively associated with aggressive prostate cancer, with ground beef showing the strongest association (OR = 2.30, 95% CI:1.39-3.81; P-trend = 0.002). This association primarily reflected intake of grilled or barbequed meat, with more well-done meat conferring a higher risk of aggressive prostate cancer. Comparing high and low consumptions of well/very well cooked ground beef to no consumption gave OR's of 2.04 (95% CI:1.41-2.96) and 1.51 (95% CI:1.06-2.14), respectively. In contrast, consumption of rare/medium cooked ground beef was not associated with aggressive prostate cancer. Looking at meat mutagens produced by cooking at high temperatures, we detected an increased risk with 2-amino-3,8-Dimethylimidazo-[4,5-f]Quinolaxine (MelQx) and 2-amino-3,4,8-trimethylimidazo(4,5-f)qunioxaline (DiMelQx), when comparing the highest to lowest quartiles of intake: OR = 1.69 (95% CI:1.08-2.64;P-trend = 0.02) and OR = 1.53 (95% CI:1.00-2.35; P-trend = 0.005), respectively. DISCUSSION: Higher intake of well-done grilled or barbequed red meat and ensuing carcinogens could increase the risk of aggressive prostate cancer.