Characteristics Associated With Physician Bias in Contraceptive Recommendations.

OBJECTIVE: We aimed to examine associations between obstetrician-gynecologist (OBGYN) contraceptive recommendations and sociodemographic characteristics of patients and recommending physicians. METHODS: OBGYNs affiliated with residency programs across the United States were recruited via email to participate in an online exploratory survey depicting scenarios of reproductive-age women of differing race and socioeconomic status, all other factors identical, and were asked to provide contraceptive recommendations. The χ2 test, Fisher's exact tests, and logistic regression were used to analyze recommendation differences based on physician and patient characteristics. RESULTS: Of 172 physician respondents, large proportions self-identified as white (74%) and attending physicians (56%) from the Mid-Atlantic (42%). In multivariate logistic regression, self-administered methods (odds ratio [OR], 0.5; 95% confidence interval [CI], 0.2-0.8) and condoms (OR, 0.5; 95% CI, 0.3-0.9) were recommended significantly less to Black high SES patients compared with white high SES patients. Non-white physicians recommended tubal ligation (OR, 0.7; 95% confidence interval [CI], 0.5-0.9) significantly less than white physicians, and recommended long-acting reversible contraception (OR, 3.3, CI 2.2-5.2) and condoms (OR, 1.4; 95% CI, 1.1-1.9) significantly more. Trainee physicians recommended self-administered methods (OR, 0.3; 95% CI, 0.2-0.4), condoms (OR, 0.2; 95% CI, 0.2-0.3), and tubal ligation (OR, 0.4; 95% CI, 0.3-0.6) significantly less than attending physicians. CONCLUSIONS: OBGYN contraceptive recommendations differed based on patients' perceived race and SES. Recommendations also differed based on race, training level, and geographic location of the recommending physician. Results suggest that physician bias contributes to contraceptive recommendations. OBGYNs should receive education about contraceptive coercion and patient-centered decision-making so that they provide high-quality counseling to all patients.

Assessment of personal care product use and perceptions of use in a sample of US adults affiliated with a university in the Northeast.

Evidence supports unequal burdens of chemical exposures from personal care products (PCPs) among some groups, namely femme-identifying and racial and ethnic minorities. In this study, we implemented an online questionnaire to assess PCP purchasing and usage behaviors and perceptions of use among a sample of US adults recruited at a Northeastern university. We collected PCP use across seven product categories (hair, beauty, skincare, perfumes/colognes, feminine hygiene, oral care, other), and behaviors, attitudes, and perceptions of use and safety across sociodemographic factors to evaluate relationships between sociodemographic factors and the total number of products used within the prior 24-48 h using multivariable models. We also summarized participants' perceptions and attitudes. Among 591 adults (20.0% Asian American/Pacific Islander [AAPI], 5.9% Hispanic, 9.6% non-Hispanic Black [NHB], 54.6% non-Hispanic White [NHW], and 9.9% multiracial or other), the average number of PCPs used within the prior 24-48 h was 15.6 ± 7.7. PCP use was greater among females than males (19.0 vs. 7.9, P < 0.01) and varied by race and ethnicity among females. Relative to NHWs, AAPI females used fewer hair products (2.5 vs. 3.1) and more feminine hygiene products (1.5 vs. 1.1), NHB females used more hair products (3.8 vs. 3.1), perfumes (1.0 vs. 0.6), oral care (2.3 vs. 1.9), and feminine hygiene products (1.8 vs. 1.1), and multiracial or other females used more oral care (2.2 vs. 1.9) and feminine hygiene products (1.5 vs. 1.1) (P-values <0.05). Generally, study participants reported moderate concern about exposures and health effects from using PCPs, with few differences by gender, race, and ethnicity. These findings add to the extant literature on PCP use across sociodemographic characteristics. Improving the understanding of patterns of use for specific products and their chemical ingredients is critical for developing interventions to reduce these exposures, especially in vulnerable groups with an unequal burden of exposure.

Protective role of the placental efflux transporter BCRP/ABCG2 in the relationship between prenatal cadmium exposure, placenta weight, and size at birth.

BACKGROUND AND AIM: Placental efflux transporter proteins, such as BCRP, reduce the placental and fetal toxicity of environmental contaminants but have received little attention in perinatal environmental epidemiology. Here, we evaluate the potential protective role of BCRP following prenatal exposure to cadmium, a metal that preferentially accumulates in the placenta and adversely impacts fetal growth. We hypothesized that individuals with a reduced function polymorphism in ABCG2, the gene encoding BCRP, would be most vulnerable to the adverse impacts of prenatal cadmium exposure, notably, smaller placental and fetal size. METHODS: We measured cadmium in maternal urine samples at each trimester and in term placentas from UPSIDE-ECHO study participants (NY, USA; n = 269). We fit adjusted multivariable linear regression and generalized estimating equation models to examine log-transformed urinary and placental cadmium concentrations in relation to birthweight, birth length, placental weight, and fetoplacental weight ratio (FPR) and stratified models by ABCG2 Q141K (C421A) genotype. RESULTS: Overall 17% of participants expressed the reduced-function ABCG2 C421A variant (AA or AC). Placental cadmium concentrations were inversely associated with placental weight (ß = -19.55; 95%CI: -37.06, -2.04) and trended towards higher FPR (ß = 0.25; 95%CI: -0.01, 0.52) with stronger associations in 421A variant infants. Notably, higher placental cadmium concentrations in 421A variant infants were associated with reduced placental weight (ß = -49.42; 95%CI: 98.87, 0.03), and higher FPR (ß = 0.85, 95%CI: 0.18, 1.52), while higher urinary cadmium concentration was associated with longer birth length (ß = 0.98; 95%CI: 0.37, 1.59), lower ponderal index (ß = -0.09; 95%CI: 0.15, -0.03), and higher FPR (ß = 0.42; 95%CI: 0.14, 0.71). CONCLUSIONS: Infants with reduced function ABCG2 polymorphisms may be particularly vulnerable to the developmental toxicity of cadmium as well as other xenobiotics that are BCRP substrates. Additional work examining the influence of placental transporters in environmental epidemiology cohorts is warranted.

Incidence and Predictors of COVID-19 Infection in Prison Healthcare Workers.

OBJECTIVE: The aim of the study is to assess the predictors of SARS-CoV-2 infection among correctional healthcare workers (HCWs). METHODS: We conducted a retrospective chart review to describe the demographic and workplace characteristics of New Jersey correctional HCWs between March 15, 2020, and August 31, 2020, using univariate and multivariable analysis. RESULTS: Among 822 HCWs, patient-facing staff had the highest incidence of infection (7.2%). Associated risk factors include being Black and working in a maximum-security prison. There were few statistically significant findings due to small total numbers ( n = 47) that tested positive. CONCLUSIONS: Correctional HCWs' challenging work environment creates unique risk factors for infection with the SARS-CoV-2 virus. Administrative measures taken by the department of corrections may have a significant role in curbing the spread of infection. The findings can help focus preventive measures for reducing the spread of COVID-19 in this unique population.

Performance of Multiple Imputation Using Modern Machine Learning Methods in Electronic Health Records Data.

BACKGROUND: Missing data are common in studies using electronic health records (EHRs)-derived data. Missingness in EHR data is related to healthcare utilization patterns, resulting in complex and potentially missing not at random missingness mechanisms. Prior research has suggested that machine learning-based multiple imputation methods may outperform traditional methods and may perform well even in settings of missing not at random missingness. METHODS: We used plasmode simulations based on a nationwide EHR-derived de-identified database for patients with metastatic urothelial carcinoma to compare the performance of multiple imputation using chained equations, random forests, and denoising autoencoders in terms of bias and precision of hazard ratio estimates under varying proportions of observations with missing values and missingness mechanisms (missing completely at random, missing at random, and missing not at random). RESULTS: Multiple imputation by chained equations and random forest methods had low bias and similar standard errors for parameter estimates under missingness completely at random. Under missingness at random, denoising autoencoders had higher bias than multiple imputation by chained equations and random forests. Contrary to results of prior studies of denoising autoencoders, all methods exhibited substantial bias under missingness not at random, with bias increasing in direct proportion to the amount of missing data. CONCLUSIONS: We found no advantage of denoising autoencoders for multiple imputation in the setting of an epidemiologic study conducted using EHR data. Results suggested that denoising autoencoders may overfit the data leading to poor confounder control. Use of more flexible imputation approaches does not mitigate bias induced by missingness not at random and can produce estimates with spurious precision.

Lay knowledge and practices of methamphetamine use to manage opioid-related overdose risks.

AIM: Methamphetamine use has increased among individuals with opioid use disorder. The key aims of this study are to detail and contextualise lay knowledge, attitudes, and behaviours related to methamphetamine use in relation to opioid overdose risks in an area dominated by non-pharmaceutical fentanyl-type drugs (NPF). METHODS: The study recruited 41 individuals in Dayton, Ohio, who reported past 30-day use of methamphetamine and heroin/fentanyl. Interviews included structured and qualitative questions. Urine toxicology analysis was conducted to identify NPFs and other drugs. Open-ended interview sections were audio-recorded, transcribed, and analysed qualitatively using NVivo. RESULTS: The mean age was 38.3 years, 51% were female, and 100% non-Hispanic white. Participants described an exceedingly unpredictable local opioid market that became saturated with NPFs. The sample tested positive for 10 NPFs, including fentanyl (100%), acetyl fentanyl (61%), tetrahydrofuran fentanyl (29%), and carfentanil (12%). Most participants believed that methamphetamine could help prevent and/or reverse an opioid-related overdose. Nearly half had personally used it to help manage overdose risks related to NPF. These beliefs were embedded in a lay understanding of how methamphetamine works to stimulate the cardiovascular system. They were acted upon in the context of last resort situations that were determined by a lack of immediate access to naloxone, ambiguities surrounding overdose symptomatology, and easy access to plentiful and inexpensive methamphetamine. CONCLUSION: Lay efforts to rely on methamphetamine to manage NPF-related overdose risks highlight the need for a continuing expansion of take-home-naloxone programs and implementation of other novel harm reduction approaches in communities affected by NPFs.

Integrating real world data and clinical trial results using survival data reconstruction and marginal moment-balancing weights.

Outcomes in electronic health records (EHR)-derived cohorts can be compared to similarly treated clinical trial cohorts to estimate the efficacy-effectiveness gap, the discrepancy in performance of an intervention in a trial compared to the real world. However, because clinical trial data may only be available in the form of published summary statistics and Kaplan-Meier curves, survival data reconstruction methods are needed to recreate individual-level survival data. Additionally, marginal moment-balancing weights can adjust for differences in the distributions of patient characteristics between the trial and EHR cohorts. We evaluated bias in hazard ratio (HR) estimates by comparing trial and EHR cohorts using survival data reconstruction and marginal moment-balancing weights through simulations and analysis of real-world data. This approach produced nearly unbiased HR estimates. In an analysis of overall survival for patients with metastatic urothelial carcinoma treated with gemcitabine-carboplatin captured in the nationwide Flatiron Health EHR-derived de-identified database and patients enrolled in a trial of the same therapy, survival was similar in the EHR and trial cohorts after using weights to balance age, sex, and performance status (HR = 0.93, 95% confidence interval (0.74, 1.18)). Overall, we conclude that this approach is feasible for comparison of trial and EHR cohorts and facilitates evaluation of outcome differences between trial and real-world populations.

Epigenetic Forensics for Suspect Identification and Age Prediction.

Background: Genetic testing at crime scenes is an instrumental molecular technique to identify or eliminate suspects, as well as to overturn wrongful convictions. Yet, genotyping alone cannot reveal the age of a sample, which could help advance the utility of crime scene samples for suspect identification. The distribution of cytosine methylation within a DNA sample can be leveraged to determine the epigenetic age of someone's blood. Methodology: We sought to demonstrate the ability of DNA methylation markers to accurately discern the age of blood spots from an actual crime scene, a "mock" crime scene, and also from a tube of blood stored in ethylenediaminetetraacetic acid for >20 years. This was achieved by quantifying methylation within known age-associated genetic loci across each DNA sample. We observed a strong linear coefficient (0.91) and high overall correlation (R 2 = 0.963) between the known age of a sample and the predicted age. Conclusion: We show that novel methods for targeted methylation and low-input whole-genome bisulfite sequencing can enable a novel and improved forensic profile of a crime scene that discerns not only who was present at the crime, but also their age. Finally, we use this model to discern the age and provenance of a blood sample that was used in a criminal investigation.

"It's Crazy What Meth Can Help You Do": Lay Beliefs, Practices, and Experiences of Using Methamphetamine to Self-Treat Symptoms of Opioid Withdrawal.

BACKGROUND: Across the U.S., methamphetamine use is expanding among people who use illicit opioids (PWUIO). Motives for methamphetamine use must be contextualized within the experiences of PWUIO, who may use methamphetamine not only to achieve euphoria, but also as a tactic of self-management. The overall aim of this study is to contextualize lay beliefs, practices, and experiences of methamphetamine use as a form of self-treatment of symptoms related to chronic opioid use among PWUIO in the Dayton Metro Area of Southwest Ohio, an epicenter of the ongoing opioid crisis. METHODS: This paper draws on two phases of interviews conducted with 38 individuals who use both heroin/fentanyl and methamphetamine. This paper primarily analyzes qualitative data but includes supplementary information from the structured interview component. Qualitative interview sections were transcribed in their entirety and thematically analyzed. RESULTS: Participants described learning about methamphetamine as a tactic to treat opioid withdrawal symptoms through social networks and through personal experimentation. Many participants suggested that methamphetamine was helpful in relieving exhaustion, alleviating some acute physical symptoms of opioid withdrawal, and providing a psychological distraction, although some admitted that methamphetamine use could incur additional health risks. To effectively use methamphetamine as a tactic of self-treatment, participants emphasized the importance of timing and dosing. DISCUSSION: Among PWUIO in the Dayton area, methamphetamine use as a tactic to self-manage opioid withdrawal must be studied in relation to historical and evolving patterns of illicit opioid use and associated risks. More research is needed to understand the long-term health impacts of this emergent practice of polydrug use.

Evolution of the Epigenetic Landscape in Childhood B Acute Lymphoblastic Leukemia and Its Role in Drug Resistance.

Although B-cell acute lymphoblastic leukemia (B-ALL) is the most common malignancy in children and while highly curable, it remains a leading cause of cancer-related mortality. The outgrowth of tumor subclones carrying mutations in genes responsible for resistance to therapy has led to a Darwinian model of clonal selection. Previous work has indicated that alterations in the epigenome might contribute to clonal selection, yet the extent to which the chromatin state is altered under the selective pressures of therapy is unknown. To address this, we performed chromatin immunoprecipitation, gene expression analysis, and enhanced reduced representation bisulfite sequencing on a cohort of paired diagnosis and relapse samples from individual patients who all but one relapsed within 36 months of initial diagnosis. The chromatin state at diagnosis varied widely among patients, while the majority of peaks remained stable between diagnosis and relapse. Yet a significant fraction was either lost or newly gained, with some patients showing few differences and others showing massive changes of the epigenetic state. Evolution of the epigenome was associated with pathways previously linked to therapy resistance as well as novel candidate pathways through alterations in pyrimidine biosynthesis and downregulation of polycomb repressive complex 2 targets. Three novel, relapse-specific superenhancers were shared by a majority of patients including one associated with S100A8, the top upregulated gene seen at relapse in childhood B-ALL. Overall, our results support a role of the epigenome in clonal evolution and uncover new candidate pathways associated with relapse. SIGNIFICANCE: This study suggests a major role for epigenetic mechanisms in driving clonal evolution in B-ALL and identifies novel pathways associated with drug resistance.