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BACKGROUND: Selected molecular biomarkers were incorporated into the US cancer registry reporting for patients with brain tumors beginning in 2018. We investigated the completeness and validity of these variables and described the epidemiology of molecularly defined brain tumor types. METHODS: Brain tumor patients with histopathologically confirmed diagnosis in 2018 were identified within the Central Brain Tumor Registry of the United States and NCIs Surveillance, Epidemiology, and End Results Incidence databases. The brain molecular markers (BMM) site-specific data item was assessed for coding completeness and validity. 1p/19q status, MGMT promoter methylation, WHO grade data items, and new ICD-O-3 codes were additionally evaluated. These data were used to profile the characteristics and age-adjusted incidence rates per 100 000 population of molecularly defined brain tumors with 95% confidence intervals (95% CI). RESULTS: BMM completeness across the applicable tumor types was 75%-92% and demonstrated favorable coding validity. IDH-wildtype glioblastomas incidence rate was 1.74 (95% CI: 1.69-1.78), as compared to 0.14 for WHO grade 2 (95% CI: 0.12-0.15), 0.15 for grade 3 (95% CI: 0.14-0.16), and 0.07 for grade 4 (95% CI: 0.06-0.08) IDH-mutant astrocytomas. Irrespective of WHO grade, IDH mutation prevalence was highest in adolescent and young adult patients, and IDH-mutant astrocytomas were more frequently MGMT promoter methylated. Among pediatric-type tumors, the incidence rate was 0.06 for H3K27M-mutant diffuse midline gliomas (95% CI: 0.05-0.07), 0.03 for SHH-activated/TP53-wildtype medulloblastomas (95% CI: 0.02-0.03), and

The article presents a study which examined longitudinal trends in the living arrangements of persons living with dementia (PLWD) and the characteristics of PLWD in each care setting. Topics discussed include proportion of persons living with dementia in each living arrangement over time, and factors that may have altered where PLWD reside.

Objectives: Racial and ethnic minorities receive opioid prescriptions at lower rates and dosages than White patients. Though opioid stewardship interventions can improve or exacerbate these disparities, there is little evidence about these effects. We conducted a secondary analysis of a cluster‐randomized controlled trial conducted among 438 clinicians from 21 emergency departments and 27 urgent care clinics. Our objective was to determine whether randomly allocated opioid stewardship clinician feedback interventions that were designed to reduce opioid prescriptions had unintended effects on disparities in prescribing by patient race and ethnicity. Methods: The primary outcome was likelihood of receiving a low‐pill prescription (low ≤10 pills, medium 11–19 pills, high ≥20 pills). Generalized mixed‐effects models were used to determine patient characteristics associated with low‐pill prescriptions during the baseline period. These models were then used to determine whether receipt of a low‐pill prescription varied by patient race or ethnicity during the intervention period between usual care and three opioid stewardship interventions: (1) individual audit feedback, (2) peer comparison feedback, and (3) combined (individual audit + peer comparison) feedback. Results: Compared with White patients, Black patients were more likely to receive a low‐pill prescription during the baseline (adjusted odds ratio [OR] 1.18, 95% confidence interval [CI] 1.06–1.31, p = 0.002) and intervention (adjusted OR 1.43, 95% CI 1.07–1.91, p = 0.015). While combined feedback was associated with an overall increase in low‐pill prescriptions as intended (adjusted OR 1.89, 95% CI 1.28–2.78, p = 0.001), there were no significant differences in treatment effects of any of the interventions by patient race and ethnicity. Conclusions: Combined individual audit and peer comparison feedback was associated with fewer opioid pills per prescription equally by patient race and ethnicity. However, the intervention did not significantly close the baseline disparity in prescribing by race. [ABSTRACT FROM AUTHOR]

Peer comparison feedback is a promising strategy for reducing opioid prescribing and opioid-related harms. Such comparisons may be particularly impactful among underestimating clinicians who do not perceive themselves as high prescribers relative to their peers. But peer comparisons could also unintentionally increase prescribing among overestimating clinicians who do not perceive themselves as lower prescribers than peers. The objective of this study was to assess if the impact of peer comparisons varied by clinicians' preexisting opioid prescribing self-perceptions. Subgroup analysis of a randomized trial of peer comparison interventions among emergency department and urgent care clinicians was used. Generalized mixed-effects models were used to assess whether the impact of peer comparisons, alone or combined with individual feedback, varied by underestimating or overestimating prescriber status. Underestimating and overestimating prescribers were defined as those who self-reported relative prescribing amounts that were lower and higher, respectively, than actual relative baseline amounts. The primary outcome was pills per opioid prescription. Among 438 clinicians, 54% (n = 236) provided baseline prescribing self-perceptions and were included in this analysis. Overall, 17% (n = 40) were underestimating prescribers whereas 5% (n = 11) were overestimating prescribers. Underestimating prescribers exhibited a differentially greater decrease in pills per prescription compared to nonunderestimating clinicians when receiving peer comparison feedback (1.7 pills, 95% CI, -3.2 to -0.2 pills) or combined peer and individual feedback (2.8 pills, 95% CI, -4.8 to -0.8 pills). In contrast, there were no differential changes in pills per prescription for overestimating versus nonoverestimating prescribers after receiving peer comparison (1.5 pills, 95% CI, -0.9 to 3.9 pills) or combined peer and individual feedback (3.0 pills, 95% CI, -0.3 to 6.2 pills). Peer comparisons were more impactful among clinicians who underestimated their prescribing compared to peers. By correcting inaccurate self-perceptions, peer comparison feedback can be an effective strategy for influencing opioid prescribing., (Copyright © 2023 the American College of Medical Quality.)