Using a Patient-Centered Multicriteria Decision Analysis to Assess the Value of Multiple Sclerosis Treatments in the US: A Study Protocol.

OBJECTIVE: The engagement of patients and family caregivers in value assessment is pivotal since they provide valuable contributions to assessment acceptability and relevance. The proposed study aims to use patient-centered techniques and multicriteria decision analysis (MCDA) to evaluate the values of disease-modifying therapies (DMTs) for multiple sclerosis (MS) from the perspectives of patients and family caregivers living in three 'Deep South' States of the US-Alabama, Louisiana, and Mississippi. METHODS: This study will follow guidance from the Patient-Centered Outcomes Research Institute (PCORI) for patient engagement and two best practice reports for MCDA from the Professional Society for Health Economics and Outcomes Research (ISPOR) to complete value assessment. Throughout the study, we will engage multiple stakeholders, including patients, family caregivers, healthcare providers, and payers. Forty patients with MS and their family caregivers from Alabama, Louisiana, and Mississippi will be invited to participate in this study. We will intensively train them for value assessment knowledge and MCDA before we engage them in MCDA to determine the value of DMTs for MS. DISCUSSIONS: Our approach differs from common MCDA since we incorporated a patient-centered framework in this study. Unlike previous studies only briefly inform or prepare participants before the MCDA process, in this study, we will provide basic value assessment trainings for patients and family caregivers to ensure they can effectively engage throughout the patient-centered MCDA process. We expect this study will demonstrate that the patient-centered MCDA approach is feasible and likely leads to improved patients' and family caregivers' engagement in value assessment.

HIV testing and risk behaviors associated with depression in the United States.

Given the high correlation between depression and HIV infection rates, our objective was to assess national rates for HIV testing and HIV risk behaviors among U.S. adults stratified by self-reports of depression. We conducted a cross-sectional study using data from the 2018-2020 Behavioral Risk Factor Surveillance System (BRFSS). We included respondents aged 18 years old and above with self-reported depression status (Sample size = 1,228,405). The primary outcomes included HIV testing and HIV-related risk behaviors. For respondents with prior HIV testing experience, we estimated the duration since the last HIV test. We applied a multivariable logistic regression model to analyze the correlation between depression and HIV testing or risk behaviors. The results showed people with depression had 51% higher odds of receiving HIV testing [adjusted odds ratio (AOR) = 1.51, 95% CI = 1.48, 1.55] and 51% higher odds of involvement in HIV risk behaviors [AOR = 1.51, 95% CI = 1.44, 1.58] after adjusting for covariates. Various socio-demographics and healthcare access variables were significantly associated with HIV testing and HIV risk behaviors. When comparing the average time from the last HIV test, people with depression had a shorter period compared to those without depression [Median time in months: 27.1 ± 0.45 vs. 29.3 ± 0.34]. Even though people with depression had higher rates of HIV testing, they still experienced long time periods (median = 2 + years) between HIV testing, which exceeded the recommended annual HIV testing for people at high risk from the Centers for Disease Control and Prevention.

Reproducibility of the medical cost estimation from the Medicare Current Beneficiary Survey: Comparing claims and survey.

Background: The Medicare Current Beneficiary Survey (MCBS) limited-access data provides the unique opportunity to utilize administrative claims and adjusted survey data to investigate trends in utilization and medical expenditure across time. The adjusted survey data is a synthesized, matched version of the original survey data and claims. Researchers may choose adjusted survey data or original claims for cost evaluations according to their research purpose. However, limited research has examined methodological issues when estimating medical cost using different MCBS data sources. Objective: The study objective was to examine the reproducibility of individual-level medical cost using both MCBS data sources: adjusted survey and claims data. Methods: This serial cross-sectional study design analyzed 2006-2012 MCBS data. The sample included noninstitutionalized older Medicare beneficiaries (≥65 years old), with a cancer diagnosis and annually enrolled in Medicare Parts A, B, and D. The population was stratified by diabetes diagnosis. The primary outcome was annual medical cost. We investigated the discrepancies of medical cost estimated from the adjusted survey and original claims data. The agreement between cost estimates from the two sources in each year was determined using the Wilcoxon signed-rank test. Results: A total of 4918 eligible Medicare beneficiaries were included in this study, and 26% of beneficiaries also had diabetes (N = 1275). Significant disagreements in cost estimates between adjusted survey and claims data were present regardless of disease complexity (with or without diabetes). Significant disagreements in medical cost estimates were present in most years, except in 2010 (p = 0.467) and 2011 (p = 0.098), for beneficiaries with cancer and diabetes (p < 0.001 for all). Significant disagreements in medical cost estimates were present in all years for beneficiaries with cancer without diabetes (p < 0.001 for all). Conclusions: Based on discrepant cost estimates across data sources, researchers using MCBS to estimate costs should be cautious when using claims or adjusted survey data alone.

Associations Between Medicaid Expansion and Mental Health Among U.S. Racial and Ethnic Groups.

OBJECTIVE: The authors examined associations between Medicaid expansion and self-reported mental health by race-ethnicity, focusing on lagged associations. METHODS: This retrospective, cross-sectional study used 2011-2019 data from the Behavioral Risk Factor Surveillance System. The sample included low-income, childless adults ages 25-64 years. Difference-in-differences (DID) analysis was used to estimate associations between Medicaid expansion and self-reported mental health. Lagged associations were examined by separating the postexpansion period into proximal (2014-2016) and distal (2017-2019) periods. RESULTS: In the overall sample (N=327,248), Medicaid expansion was associated with a reduction in the mean number of self-reported past-month poor mental health days (DID=-0.12, 95% CI=-0.21 to -0.03), after adjustment for covariates. The expansion was associated with significant reductions in past-month poor mental health days for the following groups: non-Hispanic White (DID=-0.18, 95% CI=-0.29 to -0.07), non-Hispanic Asian (DID=-1.15, 95% CI=-1.37 to -0.93), non-Hispanic other (DID=-0.62, 95% CI=-1.03 to -0.21), and Hispanic (DID=-0.48, 95% CI=-0.73 to -0.23). The non-Hispanic Black group had a significant increase in past-month poor mental health days (DID=0.27, 95% CI=0.06 to 0.49), and no significant change was noted for the American Indian or Alaska Native (AIAN) group. Improvements in mental health observed at the beginning of the policy implementation (proximal period) were not sustained over time for some racial-ethnic minority groups. CONCLUSIONS: Although Medicaid expansion improved mental health for the overall sample, some racial-ethnic disparities were detected. The negative and insignificant associations for the non-Hispanic Black and AIAN groups, respectively, highlight the need to better understand why the Medicaid expansion affected racial-ethnic groups differently.

Diabetes management behaviors associated with depression in the U.S.

BACKGROUND: There is a lack of nationally representative evidence from the U.S. investigating the relationships between depression and diabetes management behaviors. Our study aimed to assess the associations between diabetes management behaviors and depression status, and to compare U.S. population-level percentages of diabetes management behaviors among patients with and without depression. METHODS: A cross-sectional study was conducted using population-based survey data to assess patient-reported variables retrospectively. We used the Behavioral Risk Factor Surveillance System (BRFSS) data and included states in the U.S. that continuously adopted the diabetes optional modules in 2013, 2015, 2017, and 2019. We included U.S. adults (≥ 18 years old) with self-reported diabetes in our analysis. Main outcomes were diabetes management behaviors (i.e., self-check for blood glucose and feet sores/irritation, regular diabetes clinical visit, HbA1c check, professional feet check, and dilated eye examination) and lifestyle behaviors (i.e., exercise, smoking, and alcohol consumption). RESULTS: Among the 74,011 respondents with diabetes, patients with depression had a higher likelihood of performing routine HbA1c checks (adjusted odds ratio (AOR) = 1.12; 95% CI 1.01-1.23) but had a lower likelihood to perform regular self-check for blood glucose (AOR = 0.91; 95% CI 0.84-0.99), receive professional feet checks (AOR = 0.87; 95% CI 0.79-0.95), and receive a dilated eye examination (AOR = 0.89; 95% CI 0.82-0.98). For lifestyle behaviors, patients with depression were more likely to smoke (No smoking (AOR) = 0.65; 95% CI = 0.59-0.72) and less likely to engage in sufficient exercise time (AOR = 0.69; 95% CI 0.63-0.75). There were no significant associations between depression and other behaviors, including self-check for feet sores/irritation (AOR = 0.99; 95% CI 0.92-1.08), regular diabetes clinical visit (AOR = 1.03, 95% CI 0.94-1.13), and alcohol consumption (AOR = 1.01, 95% CI 0.92-1.10). CONCLUSIONS: The association between depression status and diabetes management behaviors varied. People with depression were positively associated with HbA1c checks. However, less uptake of other behaviors may indicate the needs for improvement in diabetes management.

Single-cell analysis of a high-grade serous ovarian cancer cell line reveals transcriptomic changes and cell subpopulations sensitive to epigenetic combination treatment.

Ovarian cancer (OC) is a lethal gynecological malignancy with a five-year survival rate of only 46%. Development of resistance to platinum-based chemotherapy is a common cause of high mortality rates among OC patients. Tumor and transcriptomic heterogeneity are drivers of platinum resistance in OC. Platinum-based chemotherapy enriches for ovarian cancer stem cells (OCSCs) that are chemoresistant and contribute to disease recurrence and relapse. Studies examining the effect of different treatments on subpopulations of HGSOC cell lines are limited. Having previously demonstrated that combined treatment with an enhancer of zeste homolog 2 inhibitor (EZH2i) and a RAC1 GTPase inhibitor (RAC1i) inhibited survival of OCSCs, we investigated EZH2i and RAC1i combination effects on HGSOC heterogeneity using single cell RNA sequencing. We demonstrated that RAC1i reduced expression of stemness and early secretory marker genes, increased expression of an intermediate secretory marker gene and induced inflammatory gene expression. Importantly, RAC1i alone and in combination with EZH2i significantly reduced oxidative phosphorylation and upregulated Sirtuin signaling pathways. Altogether, we demonstrated that combining a RAC1i with an EZH2i promoted differentiation of subpopulations of HGSOC cells, supporting the future development of epigenetic drug combinations as therapeutic approaches in OC.

iLoci: robust evaluation of genome content and organization for provisional and mature genome assemblies.

We introduce a new framework for genome analyses based on parsing an annotated genome assembly into distinct interval loci (iLoci), available as open-source software as part of the AEGeAn Toolkit (https://github.com/BrendelGroup/AEGeAn). We demonstrate that iLoci provide an alternative coordinate system that is robust to changes in assembly and annotation versions and facilitates granular quality control of genome data. We discuss how statistics computed on iLoci reflect various characteristics of genome content and organization and illustrate how these statistics can be used to establish a baseline for assessment of the completeness and accuracy of the data. We also introduce a well-defined measure of relative genome compactness and compute other iLocus statistics that reveal genome-wide characteristics of gene arrangements in the whole genome context. Given the fast pace of assembly/annotation updates, our AEGeAn Toolkit fills a niche in computational genomics based on deriving persistent and species-specific genome statistics. Gene structure model-centric iLoci provide a precisely defined coordinate system that can be used to store assembly/annotation updates that reflect either stable or changed assessments. Large-scale application of the approach revealed species- and clade-specific genome organization in precisely defined computational terms, promising intriguing forays into the forces of shaping genome structure as more and more genome assemblies are being deposited.

Can the LACE index help identify uninsured patients at risk of loss to follow-up during a pharmacist-led transitions of care program?

BACKGROUND: Uninsured patients are susceptible to being lost to follow-up (LTFU). In addition to being uninsured, follow-up is especially critical among this population during transitions of care when patients are discharged from the hospital setting back to home because follow-up care after discharge has been proven to prevent readmissions. The LACE tool has historically been used to predict readmissions, but the LACE tool has not been used to evaluate patients' risk of LTFU. OBJECTIVE: To understand the potential translation of the LACE tool for use in uninsured patients' follow-up care, we assessed the association between LACE index scores and patients' risk of LTFU during a pharmacist-led transitions of care program for uninsured patients. METHODS: Data were extracted from a randomized controlled trial implementing a pharmacist-led transitions of care program at an indigent care clinic. The study population included uninsured adult patients (>18 years old) who spoke English and attended a clinical visit with a pharmacist within 16 days after discharge from a community hospital. Analyses sought to determine factors associated with the patients' LTFU status. RESULTS: Among 88 enrolled participants, 29 participants (32.95%) were LTFU. Thirty-two patients (36.4%) had a high LACE index score at baseline, indicating an increased risk of 30-day readmission. Of the remaining 56 patients (63.6%) with low-to-moderate LACE index scores, 54 (61.4%) had a moderate LACE index score, and only 2 (2.3%) had a low LACE index score. Uninsured patients with high LACE index scores had 70% lower odds of being LTFU than uninsured patients with low-to-moderate LACE index scores (exact odds ratio 0.297 [95% CI 0.081-0.947]). CONCLUSION: The LACE index score was inversely related to the risk of LTFU during a pharmacist-led transitions of care program. Pharmacists may use the LACE tool to identify patients at high risk of LTFU.

Partial-field illumination ophthalmoscope: improving the contrast of a camera-based retinal imager.

Effective and accurate in vivo diagnosis of retinal pathologies requires high performance imaging devices, combining a large field of view and the ability to discriminate the ballistic signal from the diffuse background in order to provide a highly contrasted image of the retinal structures. Here, we have implemented the partial-field illumination ophthalmoscope, a patterned illumination modality, integrated to a high pixel rate adaptive optics full-field microscope. This non-invasive technique enables us to mitigate the low signal-to-noise ratio, intrinsic of full-field ophthalmoscopes, by partially illuminating the retina with complementary patterns to reconstruct a wide-field image. This new, to the best of our knowledge, modality provides an image contrast spanning from the full-field to the confocal contrast, depending on the pattern size. As a result, it offers various trade-offs in terms of contrast and acquisition speed, guiding the users towards the most efficient system for a particular clinical application.

LSD1 and Aberrant DNA Methylation Mediate Persistence of Enteroendocrine Progenitors That Support BRAF-Mutant Colorectal Cancer.

Despite the connection of secretory cells, including goblet and enteroendocrine (EEC) cells, to distinct mucus-containing colorectal cancer histologic subtypes, their role in colorectal cancer progression has been underexplored. Here, our analysis of The Cancer Genome Atlas (TCGA) and single-cell RNA-sequencing data demonstrates that EEC progenitor cells are enriched in BRAF-mutant colorectal cancer patient tumors, cell lines, and patient-derived organoids. In BRAF-mutant colorectal cancer, EEC progenitors were blocked from differentiating further by DNA methylation and silencing of NEUROD1, a key gene required for differentiation of intermediate EECs. Mechanistically, secretory cells and the factors they secrete, such as trefoil factor 3, promoted colony formation and activation of cell survival pathways in the entire cell population. Lysine-specific demethylase 1 (LSD1) was identified as a critical regulator of secretory cell specification in vitro and in a colon orthotopic xenograft model, where LSD1 loss blocks formation of EEC progenitors and reduces tumor growth and metastasis. These findings reveal an important role for EEC progenitors in supporting colorectal cancer. SIGNIFICANCE: This study establishes enteroendocrine progenitors as a targetable population that promotes BRAF-mutant colorectal cancer and can be blocked by LSD1 inhibition to suppress tumor growth.

Moment subset sums over finite fields.

The k-subset sum problem over finite fields is a classical NP-complete problem. Motivated by coding theory applications, a more complex problem is the higher m-th moment k-subset sum problem over finite fields. We show that there is a deterministic polynomial time algorithm for the m-th moment k-subset sum problem over finite fields for each fixed m when the evaluation set is the image set of a monomial or Dickson polynomial of any degree n. In the classical case m=1, this recovers previous results of Nguyen-Wang (the case m=1, p>2) [24] and the results of Choe-Choe (the case m=1, p=2) [3].

Jointly super-resolved and optically sectioned Bayesian reconstruction method for structured illumination microscopy.

Structured Illumination Microscopy (SIM) is an imaging technique for achieving both super-resolution (SR) and optical sectioning (OS) in wide-field microscopy. It consists in illuminating the sample with periodic patterns at different orientations and positions. The resulting images are then processed to reconstruct the observed object with SR and/or OS. In this work, we present BOSSA-SIM, a general-purpose SIM reconstruction method, applicable to moving objects such as encountered in in vivo retinal imaging, that enables SR and OS jointly in a fully unsupervised Bayesian framework. By modeling a 2-layer object composed of an in-focus layer and a defocused layer, we show that BOSSA-SIM is able to jointly reconstruct them so as to get a super-resolved and optically sectioned in-focus layer. The achieved performance, assessed quantitatively by simulations for several noise levels, compares favorably with a state-of-the-art method. Finally, we validate our method on open-access experimental microscopy data.

Expanding the importance of HMERF titinopathy: new mutations and clinical aspects.

OBJECTIVE: Hereditary myopathy with early respiratory failure (HMERF) is caused by titin A-band mutations in exon 344 and considered quite rare. Respiratory insufficiency is an early symptom. A collection of families and patients with muscle disease suggestive of HMERF was clinically and genetically studied. METHODS: Altogether 12 new families with 19 affected patients and diverse nationalities were studied. Most of the patients were investigated using targeted next-generation sequencing; Sanger sequencing was applied in some of the patients and available family members. Histological data and muscle MRI findings were evaluated. RESULTS: Three families had several family members studied while the rest were single patients. Most patients had distal and proximal muscle weakness together with respiratory insufficiency. Five heterozygous TTN A-band mutations were identified of which two were novel. Also with the novel mutations the muscle pathology and imaging findings were compatible with the previous reports of HMERF. CONCLUSIONS: Our collection of 12 new families expands mutational spectrum with two new mutations identified. HMERF is not that rare and can be found worldwide, but maybe underdiagnosed. Diagnostic process seems to be complex as this study shows with mostly single patients without clear dominant family history.

Targeted sequencing of 179 genes associated with hereditary retinal dystrophies and 10 candidate genes identifies novel and known mutations in patients with various retinal diseases.

PURPOSE: Hereditary retinal dystrophies (HRDs) are a group of monogenic diseases characterized by an irreversible loss of photoreceptors. HRDs exhibit significant genetic and clinical heterogeneities challenging traditional techniques for determining disease-causal mutations. This study aims to develop an efficient molecular diagnostic platform for HRDs, and to determine the genetic basis for 25 randomly collected Chinese families with a variety of HRDs. METHODS: We designed a high throughput sequence capture microarray targeting 179 genes associated with HRDs and 10 candidate genes. We combined sequence capture with next-generation sequencing (NGS) to screen for mutations in the cohort of Chinese families. Variants detected by NGS were filtered, validated, and prioritized by pathogenicity analysis. Genotypes and phenotypes were correlated. RESULTS: We identified four recurrent single mutations, two compound mutations, and eight novel putative causative mutations, including five putative pathogenic alleles (e.g., premature stop codons and frame shifts) and three novel missense variants that are very likely pathogenic. These findings provided specific genetic diagnoses in 14 of 25 families (56%). Among these, identification of a mutation in VCAN in a family with a complicated phenotype helped to finalize the clinical diagnosis as Wagner syndrome. In another five families, 11 potential novel pathogenic variants were identified. CONCLUSIONS: A substantial number of potential new genes and new mutations associated with HRDs remain to be discovered. Identification of the novel HRDs-causing mutations in our study not only provides a better understanding of genotype-phenotype relationships in these diseases, but also demonstrates that the approach described herein is an effective method for large scale mutation detection among diverse and complicated HRDs cases.