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Racial disparities exist in cancer patients both in incidence and death rates. In endometrial cancer, Black patients are reported to have higher incidence of aggressive endometrial cancer subtypes and higher death rates than White women. To date, diagnostic and prognostic biomarkers associated with race-specific methylation driven genes have yet to be identified. The objective of this study was to explore DNA methylation patterns in endometrial tumor samples from White and Black women.Differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs) were identified in White tumor samples compared to Black tumor samples using Endometrial Carcinoma (EC) methylation and clinical data from The Cancer Genome Atlas (TCGA). Survival analysis was performed using survival R package and results were visualized using Kaplan-Meier plots. To access the correlation between changes in methylation and gene expression, we downloaded raw RNA-sequencing by Expectation-Maximization (RSEM) counts data from The Cancer Genome Atlas (TCGA) using TCGABiolinks package (v2.18.0).Our analysis revealed 704 differentially methylated CpGs in tumors from Black and White women. These differentially methylated genes showed strong negative correlation with gene expression and statistically significant enrichment in regulatory regions such as DNase I hypersensitivity sites (DHSs) and transcription factor binding sites (TFBSs). Increased variability in methylation occurred in genes such as the insulin signaling pathway in Black tumor samples.By using two independent statistical method based on means (DMR, DMCs) and variances (DVCs) on the endometrial carcinoma TCGA data, we showed that endometrial tumors from Black women are hypomethylated and more hypervariable than tumors from White women. In-depth investigation of these methylation driven markers can aid in successful management of endometrial cancer disparities and improved overall survival in Black and White populations.

The spectrum of bladder health and the factors that promote bladder health and prevent lower urinary tract symptoms (LUTS) among women are not well understood. This manuscript describes the rationale, aims, study design, sampling strategy, and data collection for the RISE FOR HEALTH (RISE) study, a novel study of bladder health in women conducted by the Prevention of Lower Urinary Tract Symptom (PLUS) Research Consortium.RISE is a population-based, multicenter, prospective longitudinal cohort study of community-dwelling, English- and Spanish-speaking adult women based in the United States. Its goal is to inform the distribution of bladder health and the individual factors (biologic, behavioral, and psychosocial) and multilevel factors (interpersonal, institutional, community, and societal) that promote bladder health and/or prevent LUTS in women across the life course. Key study development activities included the: (1) development of a conceptual framework and philosophy to guide subsequent activities, (2) creation of a study design and sampling strategy, prioritizing diversity, equity, and inclusion, and (3) selection and development of data collection components. Community members and cross-cultural experts shaped and ensured the appropriateness of all study procedures and materials. RISE participants will be selected by simple random sampling of individuals identified by a marketing database who reside in the 50 counties surrounding nine PLUS clinical research centers. Participants will complete self-administered surveys at baseline (mailed paper or electronic) to capture bladder health and LUTS, knowledge about bladder health, and factors hypothesized to promote bladder health and prevent LUTS. A subset of participants will complete an in-person assessment to augment data with objective measures including urogenital microbiome specimens. Initial longitudinal follow-up is planned at 1 year.Findings from RISE will begin to build the necessary evidence base to support much-needed, new bladder health promotion and LUTS prevention interventions in women.

BACKGROUND Patient navigation (PN) programs have demonstrated efficacy in improving health outcomes for marginalized populations across a range of clinical contexts by addressing barriers to health care, including social determinants of health (SDoHs). However, it can be challenging for navigators to identify SDoHs by asking patients directly because of many factors, including patients’ reluctance to disclose information, communication barriers, and the variable resources and experience levels of patient navigators. Navigators could benefit from strategies that augment their ability to gather SDoH data. Machine learning can be leveraged as one of these strategies to identify SDoH-related barriers. This could further improve health outcomes, particularly in underserved populations. OBJECTIVE In this formative study, we explored novel machine learning–based approaches to predict SDoHs in 2 Chicago area PN studies. In the first approach, we applied machine learning to data that include comments and interaction details between patients and navigators, whereas the second approach augmented patients’ demographic information. This paper presents the results of these experiments and provides recommendations for data collection and the application of machine learning techniques more generally to the problem of predicting SDoHs. METHODS We conducted 2 experiments to explore the feasibility of using machine learning to predict patients’ SDoHs using data collected from PN research. The machine learning algorithms were trained on data collected from 2 Chicago area PN studies. In the first experiment, we compared several machine learning algorithms (logistic regression, random forest, support vector machine, artificial neural network, and Gaussian naive Bayes) to predict SDoHs from both patient demographics and navigator’s encounter data over time. In the second experiment, we used multiclass classification with augmented information, such as transportation time to a hospital, to predict multiple SDoHs for each patient. RESULTS In the first experiment, the random forest classifier achieved the highest accuracy among the classifiers tested. The overall accuracy to predict SDoHs was 71.3%. In the second experiment, multiclass classification effectively predicted a few patients’ SDoHs based purely on demographic and augmented data. The best accuracy of these predictions overall was 73%. However, both experiments yielded high variability in individual SDoH predictions and correlations that become salient among SDoHs. CONCLUSIONS To our knowledge, this study is the first approach to applying PN encounter data and multiclass learning algorithms to predict SDoHs. The experiments discussed yielded valuable lessons, including the awareness of model limitations and bias, planning for standardization of data sources and measurement, and the need to identify and anticipate the intersectionality and clustering of SDoHs. Although our focus was on predicting patients’ SDoHs, machine learning can have a broad range of applications in the field of PN, from tailoring intervention delivery (eg, supporting PN decision-making) to informing resource allocation for measurement, and PN supervision.

ImportanceAnticholinergic medications to treat overactive bladder (OAB) have been associated with increased risk of cognitive decline, whereas β3-adrenoceptor agonists (hereafter, β3-agonists) have comparable efficacy and do not carry the same risk. Yet, anticholinergics remain the predominant OAB medication prescribed in the US.ObjectiveTo evaluate whether patient race, ethnicity, and sociodemographic characteristics are associated with receipt of anticholinergic vs β3-agonist OAB medications.Design, Setting, and ParticipantsThis study is a cross-sectional analysis of the 2019 Medical Expenditure Panel Survey, a representative sample of US households. Participants included individuals with a filled OAB medication prescription. Data analysis was performed from March to August 2022.ExposureA prescription for medication to treat OAB.Main Outcomes and MeasuresThe primary outcomes were receipt of a β3-agonist or an anticholinergic OAB medication.ResultsAn estimated 2 971 449 individuals (mean age, 66.4 years; 95% CI, 64.8-68.2 years) filled prescriptions for OAB medications in 2019; 2 185 214 (73.5%; 95% CI, 62.6%-84.5%) identified as female, 2 326 901 (78.3%; 95% CI, 66.3%-90.3%) self-identified as non-Hispanic White, 260 685 (8.8%; 95% CI, 5.0%-12.5%) identified as non-Hispanic Black, 167 210 (5.6%; 95% CI, 3.1%-8.2%) identified as Hispanic, 158 507 (5.3%; 95% CI, 2.3%-8.4%) identified as non-Hispanic other race, and 58 147 (2.0%; 95% CI, 0.3%-3.6%) identified as non-Hispanic Asian. A total of 2 229 297 individuals (75.0%) filled an anticholinergic prescription, and 590 255 (19.9%) filled a β3-agonist prescription, with 151 897 (5.1%) filling prescriptions for both medication classes. β3-agonists had a median out-of-pocket cost of $45.00 (95% CI, $42.11-$47.89) per prescription compared with $9.78 (95% CI, $9.16-$10.42) for anticholinergics. After controlling for insurance status, individual sociodemographic factors, and medical contraindications, non-Hispanic Black individuals were 54% less likely than non-Hispanic White individuals to fill a prescription for a β3-agonist vs an anticholinergic medication (adjusted odds ratio, 0.46; 95% CI, 0.22-0.98). In interaction analysis, non-Hispanic Black women had an even lower odds of filing a β3-agonist prescription (adjusted odds ratio, 0.10; 95% CI, 0.04-0.27).Conclusions and RelevanceIn this cross-sectional study of a representative sample of US households, non-Hispanic Black individuals were significantly less likely than non-Hispanic White individuals to have filled a β3-agonist prescription compared with an anticholinergic OAB prescription. These differences may reflect an inequity in prescribing behaviors promulgating health care disparities. Targeted research should assess the relative contribution of a variety of individual and societal factors.

(s): Existing bladder-specific measures lack ability to assess a range of bladder health from poor to optimal health. We report evidence for validity of the self-administered, multidimensional Bladder Health Scales and Function Indices for research in adult women.A cross-sectional population-based validation study with random assignment to paper or electronic administration was conducted using national address-based probability sampling supplemented by purposive sampling of women with lower urinary tract symptoms surrounding 7 clinical research centers. Construct validity of the Bladder Health Scales and Function Indices was guided by Multitrait-Multimethod approach using health and condition-specific questionnaires, bladder diaries, expert ratings of bladder health, and noninvasive bladder function testing. Internal dimensional validity was evaluated using factor analysis; internal reliability was assessed using paired t-tests and 2-way mixed effects Intraclass Correlation Coefficient models. Mode comparisons used chi-square, Fisher Exact or t-tests. Convergent validity was evaluated using Pearson correlations with the external construct measures and known-group validity was established with comparison of women known and unknown to be symptomatic with urinary conditions.The sample included 1,072 participants. Factor analysis identified ten scales with Cronbach's alpha ranging 0.74-0.94. Intraclass correlation coefficients of scales ranged from 0.55-0.94. Convergent validity of ten scales and six indices ranged from 0.52- 0.83. Known-group validity was confirmed for all scales and indices. Item distribution was similar by mode of administration.The paper and electronic forms of the Bladder Health Scales and Function Indices are reliable and valid measures of bladder health for use in women's health research.

Background: Low- and middle-income countries are facing a high health burden of cervical cancer (CC). The situation is worsened by a high prevalence of human immunodeficiency virus (HIV). We aim to identify epigenetic signatures to help understand the virus-associated pathways underlying CC development, which is fundamental to developing effective CC screening tools or therapeutic approaches for women living with HIV. Methods: We recruited a total of 365 Nigerian women with mean age of 52 (239 HIV+ and 126 HIV-; 98 without CC, 106 with cervical lesions, and 161 with CC). DNA methylation profiling in cervical tissue samples was performed using Illumina EPIC array covering over 860K methylation sites. The epigenetic signatures were identified among HIV+ women through epigenome-wide association study comparing CC vs. CC-free (Bonferroni adjusted p Results: We identified 46 differentially methylated markers (p-value ranging from 5.7e-8 to 2.4e-19) in HIV+ CC women. The effect sizes among the 46 markers in the paired tumor-normal analysis and the paired lesion-normal analysis were highly correlated with the CC vs. CC-free analysis (r=0.99 and r=0.95, respectively) with smaller magnitudes (1.8 and 4.3 times smaller, respectively). Gene ontology and Reactome pathway enrichment analysis revealed that these 46 markers were enriched in genes involving activation of PI3K/AKT/mTOR signaling network (e.g., RPTOR, HDAC3, MAPKAP1), which plays a crucial role in virus/host crosstalk and virus-induced carcinogenesis. The PI3K/AKT/mTOR signaling cascade suppressors, including gene PRDM8, were silenced by promoter hypermethylation among HIV+ CC women (p=4.3e-12). These epigenetic changes, however, were not observed in CC women without HIV. In an independent dataset, MRS was the lowest in women without CC (2.3±2.1), followed by women with cervical lesions (4.9±1.1), and the highest in CC women (9.6±3.9) (p-trend < 2e-16). The MRS achieved areas under the ROC curve = 0.93 and 0.88 in distinguishing CC and cervical lesions from CC-free among HIV+ women, respectively. Conclusion: HIV may communicate with cervical cells and promote CC through epigenetic activation of PI3K/AKT/mTOR signaling pathway. Our epigenetic signatures may serve as novel biomarkers for CC early detection and treatment for women living with HIV. Citation Format: Yinan Zheng, Olugbenga Silas, Jonah Musa, Yishu Qu, Tao Gao, Kyeezu Kim, Brian Joyce, Jun Wang, Demirkan Gursel, Abdulkareem Fatimah, Godwin Imade, Alani Akanmu, Jian-Jun Wei, Masha Kocherginsky, Kwang-Youn Kim, Firas Wehbe, Chad Achenbach, Rose Anorlu, Melissa Simon, Atiene Sagay, Folasade Ogunsola, Robert Murphy, Lifang Hou. Epigenetic signatures of virus-associated cervical cancer in women living with HIV [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3021.

Background: Lesbian, gay, bisexual, transgender and queer (LGBTQ) individuals experience health disparities at disproportionate rates that drive reduced cancer screenings and late-stage cancer diagnoses. Community health centers play critical roles in providing primary care services to LGBTQ+ patients with cancer. Patients diagnosed with cancer and referred to specialty care outside health centers, however, often experience disruptions to their primary care services due to gaps in communication between primary and oncology care providers. The © 4R Oncology Model (Right Information and Right Care for the Right Patient at the Right Time) is a novel, patient-centric care coordination tool developed to facilitate cancer planning and serves as a longitudinal primary care checklist for use by patients and their care team. Our project aims to assess the facilitators and barriers of 4R as a component of primary and specialized care delivered to LGBTQ+ cancer survivors. Methods: We conducted semi-structured interviews with patients and their caregivers (n =12) and stakeholders (n=12) to assess facilitators and barriers to 4R implementation as a component of care delivered to LGBTQ+ cancer survivors. Research team members deductively identified initial themes from interview transcripts. Preliminary coding schemes were compared among three team members and refined by inductive coding to produce a higher-level study codebook. With this codebook, team members ultimately utilized ATLAS.ti, a qualitative data analysis software, to independently analyze interview transcripts, with discrepancies in coding resolved through team-wide discussions. Results: Patients, their caregivers, and stakeholders agree that the 4R model shows potential for use as a first-step intervention to address primary care gaps caused by inadequate care coordination. Suggested improvements to the model include a reduction of textual information and an increased emphasis on mental and emotional support resources on the model’s sequence of care form. Conclusions: Interim findings indicate that a lack of adequate research on solutions to the disruption of primary care services caused by the initiation of cancer care for LGBTQ+ cancer survivors is a significant barrier for this patient population. The 4R Oncology Model thus shows promise as a solution for initiating and sustaining more continuous communication between primary care and cancer care delivery for LGBTQ+ cancer survivors. Continued analysis of study interviews will further elucidate facilitators and barriers to cancer care coordination for LGBTQ+ individuals, while further informing iterations to the 4R model for the development of a national protocol aimed at improving access to care and outcomes for LGBTQ+ individuals and other underserved groups. Citation Format: Nihmotallahi Adebayo, Will Dunne, Sankirtana Danner, Juan A. Rivera, Elena Molina, Abbey Ekong, Elizabeth Adetoro, Cori Blum, Cassandra Osei, Julia Trosman, Christine Weldon, Melissa Simon. Assessing the facilitators and barriers of a novel cancer care delivery model adapted for the care coordination of LGBTQ+ cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB169.

Background: Lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals experience health disparities at disproportionate rates which drive reduced cancer screenings and late-stage cancer diagnoses. These disparities are the result of barriers to care including a lack of LGBTQ-competent providers, lack of health insurance, unstable housing, and avoidance of care due to medical trauma and concerns about abuse and mistreatment. Community health centers are critical for providing primary care to LGBTQ+ patients with cancer. Unfortunately, once a patient is diagnosed with cancer and referred to specialty care outside the health center, primary care services are often disrupted or even discontinued as a result of gaps in communication between primary and oncological care providers. The © 4R Oncology Model (Right Information and Right Care for the Right Patient at the Right Time) is a novel, patient-centric care coordination tool developed to facilitate cancer planning and serve as a longitudinal primary care checklist for patients and their care team. Our project aims to assess the benefits and limitations of the 4R as a component of care delivered to LGBTQ cancer survivors. Methods: In collaboration with Howard Brown Health, we conducted semi-structured interviews with clinical care team members (N=10) to assess the benefits and limitations of the 4R implementation as a component of care delivered to LGBTQ cancer survivors. A Rapid analysis process, a method used when a quick analysis is required to adopt changes to ongoing processes, will be utilized. Results: Clinical care team members indicate that a lack of adequate research on solutions to the disruption of primary care services caused by cancer care for LGBTQ cancer patients is a significant barrier for this patient population. Team members agree that the 4R is a necessary intervention for addressing primary care gaps caused by inadequate care coordination. Conclusions: The 4R shows promise as a solution for initiating and sustaining more continuous communication between primary care and cancer care delivery for LGBTQ cancer survivors. Future interviews with patients, caregivers, and community organization members will further elucidate the barriers and facilitators to cancer care coordination for this population and how iterations of the 4R can improve access to care and outcomes. Citation Format: Nihmotallahi Adebayo, Will Dunne, Toni Madorsky, Sankirtana Danner, Juan Rivera, Elena Molina, Abbey Ekong, Elizabeth Adetoro, Cassandra Osei, Julia Trosman, Christine Weldon, Melissa Simon. LGBTQ cancer care: Assessing the benefits and limitations of a novel cancer care coordination tool [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-021.