State-level disparities in cervical cancer prevention and impact on outcomes in the U.S.: A modeling study.

Background: Despite the availability of HPV vaccines for over a decade, coverage across the United States (US) is varied. While some states have made concerted efforts to increase HPV vaccination coverage, most model-based analyses have estimated vaccine impact on the US. We estimated the impact of hypothetical changes in HPV vaccination coverage at the state level for three states with varying levels of HPV vaccination coverage and cervical cancer incidence (California, New York, Texas) using a mathematical model. Methods: We developed a new mathematical model of HPV transmission and cervical cancer tailored to state-level cancer incidence and mortality. We quantified the public health impact of increasing HPV vaccination coverage to 80% by 2025 or 2030 and the effect on time to elimination in the three states. Results: Increasing vaccination coverage to 80% in Texas in 10 years could reduce cervical cancer incidence by 50.9% (95%-CrI: 46.6-56.1%) by 2100. In New York and California, achieving the same coverage could reduce incidence by 27.3% (95%-CrI: 23.9-31.5%) and 24.4% (95%-CrI: 20.0-30.0%), respectively. Achieving 80% coverage in 5 years will slightly increase the reduction. If 2019 vaccination coverage continues, cervical cancer elimination would be reached in the US by 2051 (95%-Crl: 2034-2064). However, the timeline by which individual states reach elimination could vary by decades. Conclusion: Achieving an HPV vaccination coverage target of 80% by 2030 will benefit states with low vaccination coverage and high cervical cancer incidence the most. Our results highlight the value of more geographically focused analyses to inform priorities.

North Carolina Medicaid System Perspectives on Substance Use Disorder Treatment Policy Changes During the COVID-19 Pandemic.

OBJECTIVE: This study aimed to describe perspectives from stakeholders involved in the Medicaid system in North Carolina regarding substance use disorder (SUD) treatment policy changes during the coronavirus disease 2019 pandemic. METHODS: We conducted semistructured interviews in early 2022 with state agency representatives, Medicaid managed care organizations, and Medicaid providers (n = 22) as well as 3 focus groups of Medicaid beneficiaries with SUD (n = 14). Interviews and focus groups focused on 4 topics: policies, meeting needs during COVID, demand for SUD services, and staffing. RESULTS: Overall, policy changes, such as telehealth and take-home methadone, were considered beneficial, with participants displaying substantial support for both policies. Shifting demand for services, staffing shortages, and technology barriers presented significant challenges. Innovative benefits and services were used to adapt to these challenges, including the provision of digital devices and data plans to improve access to telehealth. CONCLUSIONS: Perspectives from Medicaid stakeholders, including state organizations to beneficiaries, support the continuation of SUD policy changes that occurred. Staffing shortages remain a substantial barrier. Based on the participants' positive responses to the SUD policy changes made during the coronavirus disease 2019 pandemic, such as take-home methadone and telehealth initiation of buprenorphine, these changes should be continued. Additional steps are needed to ensure payment parity for telehealth services.

LGBTQ+ inequity in crowdfunding cancer costs: The influence of online reach and LGBTQ+ state policy.

BACKGROUND: Emerging literature suggests that LGBTQ+ cancer survivors are more likely to experience financial burden than non-LGBTQ+ survivors. However, LGBTQ+ cancer survivors experience with cost-coping behaviors such as crowdfunding is understudied. METHODS: We aimed to assess LGBTQ+ inequity in cancer crowdfunding by combining community-engaged and technology-based methods. Crowdfunding campaigns were web-scraped from GoFundMe and classified as cancer-related and LGBTQ+ or non-LGBTQ+ using term dictionaries. Bivariate analyses and generalized linear models were used to assess differential effects in total goal amount raised by LGBTQ+ status. Stratified models were run by online reach and LGBTQ+ inclusivity of state policy. RESULTS: A total of N = 188,342 active cancer-related crowdfunding campaigns were web-scraped from GoFundMe in November 2022, of which N = 535 were LGBTQ+ and ranged from 2014 to 2022. In multivariable models of recent campaigns (2019-2022), LGBTQ+ campaigns raised $1608 (95% CI: -2139, -1077) less than non-LGBTQ+ campaigns. LGBTQ+ campaigns with low (26-45 donors), moderate (46-87 donors), and high (88-240 donors) online reach raised on average $1152 (95% CI: -$1589, -$716), $1050 (95% CI: -$1737, -$364), and $2655 (95% CI: -$4312, -$998) less than non-LGBTQ+ campaigns respectively. When stratified by LGBTQ+ inclusivity of state level policy states with anti-LGBTQ+ policy/lacking equitable policy raised on average $1910 (95% CI: -2640, -1182) less than non-LGBTQ+ campaigns from the same states. CONCLUSIONS AND RELEVANCE: Our findings revealed LGBTQ+ inequity in cancer-related crowdfunding, suggesting that LGBTQ+ cancer survivors may be less able to address financial burden via crowdfunding in comparison to non-LGBTQ+ cancer survivors-potentially widening existing economic inequities.

Exploring Online Crowdfunding for Cancer-Related Costs Among LGBTQ+ (Lesbian, Gay, Bisexual, Transgender, Queer, Plus) Cancer Survivors: Integration of Community-Engaged and Technology-Based Methodologies.

BACKGROUND: Cancer survivors frequently experience cancer-related financial burdens. The extent to which Lesbian, Gay, Bisexual, Transgender, Queer, Plus (LGBTQ+) populations experience cancer-related cost-coping behaviors such as crowdfunding is largely unknown, owing to a lack of sexual orientation and gender identity data collection and social stigma. Web-scraping has previously been used to evaluate inequities in online crowdfunding, but these methods alone do not adequately engage populations facing inequities. OBJECTIVE: We describe the methodological process of integrating technology-based and community-engaged methods to explore the financial burden of cancer among LGBTQ+ individuals via online crowdfunding. METHODS: To center the LGBTQ+ community, we followed community engagement guidelines by forming a study advisory board (SAB) of LGBTQ+ cancer survivors, caregivers, and professionals who were involved in every step of the research. SAB member engagement was tracked through quarterly SAB meeting attendance and an engagement survey. We then used web-scraping methods to extract a data set of online crowdfunding campaigns. The study team followed an integrated technology-based and community-engaged process to develop and refine term dictionaries for analyses. Term dictionaries were developed and refined in order to identify crowdfunding campaigns that were cancer- and LGBTQ+-related. RESULTS: Advisory board engagement was high according to metrics of meeting attendance, meeting participation, and anonymous board feedback. In collaboration with the SAB, the term dictionaries were iteratively edited and refined. The LGBTQ+ term dictionary was developed by the study team, while the cancer term dictionary was refined from an existing dictionary. The advisory board and analytic team members manually coded against the term dictionary and performed quality checks until high confidence in correct classification was achieved using pairwise agreement. Through each phase of manual coding and quality checks, the advisory board identified more misclassified campaigns than the analytic team alone. When refining the LGBTQ+ term dictionary, the analytic team identified 11.8% misclassification while the SAB identified 20.7% misclassification. Once each term dictionary was finalized, the LGBTQ+ term dictionary resulted in a 95% pairwise agreement, while the cancer term dictionary resulted in an 89.2% pairwise agreement. CONCLUSIONS: The classification tools developed by integrating community-engaged and technology-based methods were more accurate because of the equity-based approach of centering LGBTQ+ voices and their lived experiences. This exemplar suggests integrating community-engaged and technology-based methods to study inequities is highly feasible and has applications beyond LGBTQ+ financial burden research.

A Survey of Behavioral Health Care Providers on Use and Barriers to Use of Measurement-Based Care.

OBJECTIVE: Despite robust evidence for efficacy of measurement-based care (MBC) in behavioral health care, studies suggest that adoption of MBC is limited in practice. A survey from Blue Cross-Blue Shield of North Carolina was sent to behavioral health care providers (BHCPs) about their use of MBC, beliefs about MBC, and perceived barriers to its adoption. METHODS: The authors distributed the survey by using professional networks and snowball sampling. Provider and clinical practice characteristics were collected. Numerical indices of barriers to MBC use were created. Ordered logistic regression models were used to identify associations among practice and provider characteristics, barriers to MBC use, and level of MBC use. RESULTS: Of the 922 eligible BHCPs who completed the survey, 426 (46%) reported using MBC with at least half of their patients. Providers were more likely to report MBC use if they were part of a large group practice, had MBC training, had more weekly care hours, or practiced in nonmetropolitan settings. Physicians, self-reported generalists, more experienced providers, and those who did not accept insurance were less likely to report MBC use. Low perceived clinical utility was the barrier most strongly associated with less frequent use of MBC. CONCLUSIONS: Although evidence exists for efficacy of MBC in behavioral health care, less than half of BHCPs reported using MBC with at least half of their patients, and low perceived clinical utility of MBC was strongly associated with lower MBC use. Implementation strategies that attempt to change negative attitudes toward MBC may effectively target this barrier to use.

Precursor Intensity-Based Label-Free Quantification Software Tools for Proteomic and Multi-Omic Analysis within the Galaxy Platform.

For mass spectrometry-based peptide and protein quantification, label-free quantification (LFQ) based on precursor mass peak (MS1) intensities is considered reliable due to its dynamic range, reproducibility, and accuracy. LFQ enables peptide-level quantitation, which is useful in proteomics (analyzing peptides carrying post-translational modifications) and multi-omics studies such as metaproteomics (analyzing taxon-specific microbial peptides) and proteogenomics (analyzing non-canonical sequences). Bioinformatics workflows accessible via the Galaxy platform have proven useful for analysis of such complex multi-omic studies. However, workflows within the Galaxy platform have lacked well-tested LFQ tools. In this study, we have evaluated moFF and FlashLFQ, two open-source LFQ tools, and implemented them within the Galaxy platform to offer access and use via established workflows. Through rigorous testing and communication with the tool developers, we have optimized the performance of each tool. Software features evaluated include: (a) match-between-runs (MBR); (b) using multiple file-formats as input for improved quantification; (c) use of containers and/or conda packages; (d) parameters needed for analyzing large datasets; and (e) optimization and validation of software performance. This work establishes a process for software implementation, optimization, and validation, and offers access to two robust software tools for LFQ-based analysis within the Galaxy platform.

metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes.

Microbiome research offers promising insights into the impact of microorganisms on biological systems. Metaproteomics, the study of microbial proteins at the community level, integrates genomic, transcriptomic, and proteomic data to determine the taxonomic and functional state of a microbiome. However, standard metaproteomics software is subject to several limitations, commonly supporting only spectral counts, emphasizing exploratory analysis rather than hypothesis testing and rarely offering the ability to analyze the interaction of function and taxonomy - that is, which taxa are responsible for different processes.Here we present metaQuantome, a novel, multifaceted software suite that analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information, emphasizing label-free intensity-based methods. For experiments with multiple experimental conditions, metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition. We benchmark metaQuantome analysis against standard methods, using two previously published datasets: (1) an artificially assembled microbial community dataset (taxonomy benchmarking) and (2) a dataset with a range of recombinant human proteins spiked into an Escherichia coli background (functional benchmarking). Furthermore, we demonstrate the use of metaQuantome on a previously published human oral microbiome dataset.In both the taxonomic and functional benchmarking analyses, metaQuantome quantified taxonomic and functional terms more accurately than standard summarization-based methods. We use the oral microbiome dataset to demonstrate metaQuantome's ability to produce publication-quality figures and elucidate biological processes of the oral microbiome. metaQuantome enables advanced investigation of metaproteomic datasets, which should be broadly applicable to microbiome-related research. In the interest of accessible, flexible, and reproducible analysis, metaQuantome is open source and available on the command line and in Galaxy.