Role of Patient Characteristics and Insurance Type in Newly Diagnosed Multiple Myeloma Care Disparities.

PURPOSE: Little is known about the role of social determinants of health (SDOH) in the utilization of novel treatments among patients with newly diagnosed multiple myeloma (NDMM). METHODS: This retrospective cohort study used Taussig Cancer Center's Myeloma Patient Registry to identify adults with NDMM between January 1, 2017, and December 31, 2021. Electronic health records data captured treatment with (1) triplet or quadruplet regimen and (2) lenalidomide during the first year after NDMM, and (3) stem-cell transplant (SCT) through December 31, 2022. Multivariable logistic regression models examined associations of demographic/clinical characteristics and SDOH with care patterns. RESULTS: We identified 569 patients with median age at diagnosis of 66 years (IQR, 59-73); 55% were male, 76% White, 23% Black, 1.1% other races, insured by Medicare (51%), private payer (38%), Medicaid (8.3%), and self-pay/other (1.8%). In the multivariable models, self-pay/other payers (adjusted odds ratio [AOR], 0.15 [95% CI, 0.03 to 0.54]) was associated with lower odds of triplet or quadruplet regimen, compared with Medicare. Private insurance (AOR, 0.48 [95% CI, 0.27 to 0.86]) and self-pay/other payers (AOR, 0.16 [95% CI, 0.04 to 0.74]) had lower odds of lenalidomide. Black patients (v White; AOR, 0.47 [95% CI, 0.26 to 0.85]) and patients treated at regional hospitals (v Taussig Cancer Center; AOR, 0.27 [95% CI, 0.12 to 0.57]) had lower odds of SCT. The odds of receiving triplet or quadruplet regimen, lenalidomide, and SCT also varied by the year of NDMM. CONCLUSION: Care for NDMM varied based on race, insurance type, year of diagnosis, and treatment facility. It may be useful to examine the impact of insurance-related characteristics and recent policy initiatives on care disparities.

Clinician use of the Statin Choice Shared Decision-making Encounter Tool in a Major Health System.

BACKGROUND: Effective shared decision-making (SDM) tools for use during clinical encounters are available, but, outside of study settings, little is known about clinician use of these tools in practice. OBJECTIVE: To describe real-world use of an SDM encounter tool for statin prescribing, Statin Choice, embedded into the workflow of an electronic health record. DESIGN: Cross-sectional study. PARTICIPANTS: Clinicians and their statin-eligible patients who had outpatient encounters between January 2020 and June 2021 in Cleveland Clinic Health System. MAIN MEASURES: Clinician use of Statin Choice was recorded within the Epic record system. We categorized each patient's 10-year atherosclerotic cardiovascular disease risk into low (< 5%), borderline (5-7.5%), intermediate (7.5-20%), and high (≥ 20%). Other patient factors included age, sex, insurance, and race. We used mixed effects logistic regression to assess the odds of using Statin Choice for statin-eligible patients, accounting for clustering by clinician and site. We generated a residual intraclass correlation coefficient (ICC) to characterize the impact of the clinician on Statin Choice use. KEY RESULTS: Statin Choice was used in 7% of 68,505 eligible patients. Of 1047 clinicians, 48% used Statin Choice with ≥ 1 patient, and these clinicians used it with a median 9% of their patients (interquartile range: 3-22%). In the mixed effects logistic regression model, patient age (adjusted OR per year: 1.04; 95%CI 1.03-1.04) and 10-year ASVCD risk (aOR for 5-7.5% versus < 5% risk: 1.28; 95%CI: 1.14-1.44) were associated with use of Statin Choice. Black versus White race was associated with a lower odds of Statin Choice use (aOR: 0.83; 95%CI: 0.73-0.95), as was female versus male sex (aOR: 0.83; 95%CI: 0.76-0.90). The model ICC demonstrated that 53% of the variation in use of Statin Choice was clinician-driven. CONCLUSIONS: Patient factors, including race and sex, were associated with clinician use of Statin Choice; half the variation in use was attributable to individual clinicians.

Investigation of a cluster of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in a hospital administration building.

OBJECTIVE: To investigate a cluster of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in employees working on 1 floor of a hospital administration building. METHODS: Contact tracing was performed to identify potential exposures and all employees were tested for SARS-CoV-2. Whole-genome sequencing was performed to determine the relatedness of SARS-CoV-2 samples from infected personnel and from control cases in the healthcare system with coronavirus disease 2019 (COVID-19) during the same period. Carbon dioxide levels were measured during a workday to assess adequacy of ventilation; readings >800 parts per million (ppm) were considered an indication of suboptimal ventilation. To assess the potential for airborne transmission, DNA-barcoded aerosols were released, and real-time polymerase chain reaction was used to quantify particles recovered from air samples in multiple locations. RESULTS: Between December 22, 2020, and January 8, 2021, 17 coworkers tested positive for SARS-CoV-2, including 13 symptomatic and 4 asymptomatic individuals. Of the 5 cluster SARS-CoV-2 samples sequenced, 3 were genetically related, but these employees denied higher-risk contacts with one another. None of the sequences from the cluster were genetically related to the 17 control sequences of SARS-CoV-2. Carbon dioxide levels increased during a workday but never exceeded 800 ppm. DNA-barcoded aerosol particles were dispersed from the sites of release to locations throughout the floor; 20% of air samples had >1 log10 particles. CONCLUSIONS: In a hospital administration building outbreak, sequencing of SARS-CoV-2 confirmed transmission among coworkers. Transmission occurred despite the absence of higher-risk exposures and in a setting with adequate ventilation based on monitoring of carbon dioxide levels.

COVID-19 infection and transmission includes complex sequence diversity.

SARS-CoV-2 whole genome sequencing has played an important role in documenting the emergence of polymorphisms in the viral genome and its continuing evolution during the COVID-19 pandemic. Here we present data from over 360 patients to characterize the complex sequence diversity of individual infections identified during multiple variant surges (e.g., Alpha and Delta). Across our survey, we observed significantly increasing SARS-CoV-2 sequence diversity during the pandemic and frequent occurrence of multiple biallelic sequence polymorphisms in all infections. This sequence polymorphism shows that SARS-CoV-2 infections are heterogeneous mixtures. Convention for reporting microbial pathogens guides investigators to report a majority consensus sequence. In our study, we found that this approach would under-report sequence variation in all samples tested. As we find that this sequence heterogeneity is efficiently transmitted from donors to recipients, our findings illustrate that infection complexity must be monitored and reported more completely to understand SARS-CoV-2 infection and transmission dynamics. Many of the nucleotide changes that would not be reported in a majority consensus sequence have now been observed as lineage defining SNPs in Omicron BA.1 and/or BA.2 variants. This suggests that minority alleles in earlier SARS-CoV-2 infections may play an important role in the continuing evolution of new variants of concern.

Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in a Patient Transport Van.

We report 2 episodes of potential SARS-CoV-2 transmission from infected van drivers to passengers despite masking and physical distancing. Whole-genome sequencing confirmed relatedness of driver and passenger SARS-CoV-2. With the heater operating, fluorescent microspheres were transported by airflow >3 meters from the front to the back of the van.

A Schistosoma mansoni tri- and tetramer microsatellite catalog for genetic population diversity and differentiation.

All Schistosoma mansoni tri- and tetranucleotide repeat microsatellites published as of December 2018 were identified. All 52 were evaluated for autosomal location, strength of amplification, scorability and behavior as single-copy loci by polyacrylamide and capillary gel electrophoresis. Of these, 27 were unique, autosomal, polymorphic, easily scored and single copy as assessed on pooled adult worm DNA from two different continental origins and adult worm clones. These microsatellites were distributed across all seven autosomal chromosomes. On laboratory strains their heterozygosity ranged from 0.22 to 0.77. Individual markers had 5-13 alleles, allelic richness of 2-10 and an effective allele number of 1.3-8.14. Those infected by Schistosoma mansoni carry many genetically distinct, sexually reproducing parasites, therefore, for an individual infection the complete allele frequency profile of their progeny consists of a pool of DNA from multiple diploid eggs. Using a set of 25 microsatellites, we calculated allele frequency profiles of eggs in fecal samples from people in two Brazilian communities separated by 6 km: Jenipapo (n = 80) and Volta do Rio (n = 38). There were no a priori characteristics that could predict the performance of markers in natural infections based on their performance with laboratory strains. Increasing marker number did not change accuracy for differentiation and diversity but did improve precision. Our data suggest that using a random set of 10-20 microsatellites appears to result in values that exhibit low standard deviations for diversity and differentiation indices. All identified microsatellites as well as PCR conditions, allele size, primer sequences and references for all tri- and tetramer microsatellites markers presented in this work are available at: https://sites.google.com/case.edu/cwru-and-fiocruz-wdrc/home.

The changing profile of schistosomiasis in a changing urban landscape.

Since 2007, most of humanity resides in urban areas, a trend which continues worldwide. Diseases usually associated with rural contexts are now emerging or newly recognised in cities. In the neighbourhood of São Bartolomeu in Salvador, Brazil, the prevalence of Schistosoma mansoni infection in 2011 was >20%. Following enrollment and treatment of a portion of the community, ~25% of the area underwent urban renewal. In 2015, we returned to enrol individuals who had previously participated and a cohort that had not taken part in 2011. Thus, infected individuals in one group experienced specific drug treatment plus improved living conditions and the second group only improved living conditions. Between 2011 and 2015 there were no organised treatment programs, but adequate sanitation increased from 69% to 92% coverage, household flooding decreased, and the presence of indoor toilets increased to 99% of households. Ownership of household appliances also increased significantly. The overall prevalence of schistosome infections was 6.2%. In 2015, the cohort first seen in 2011 had a higher prevalence (8.7%) than those first seen in 2015 (4.8%) and showed a few demographic differences. The 2011 cohort was older, more likely born in Salvador, less likely to have lived outside of Salvador, spent a greater percentage of their lifetime in Salvador, but more likely to have travelled. The population structure of the parasites from both cohorts underwent a marked change with similar increased component and infrapopulation differentiation and >10 fold decrease in effective population size. There was a 4-5 year shift in age-specific prevalence in 2015 for all compared with 2011. While praziquantel may have helped reduce prevalence, our evidence suggests that the structural changes and improvements in living conditions had the biggest impact on schistosomiasis in this community.