Chimeric antigen receptor T-cell treatment patterns in relapsed or refractory large B-cell lymphoma.

Aim: To investigate real-world chimeric antigen receptor (CAR) T-cell therapy treatment patterns. Patient & methods: Relapsed/refractory large B-cell lymphoma patients who received CAR T-cell therapy were identified. Patient characteristics, setting of CAR T-cell infusion, incidence of CAR T-cell therapy-associated adverse events and healthcare resource utilization were assessed. Results: Of 1175 patients, 83% were infused inpatient. Within three days postinfusion, inpatient-infused patients had a significantly higher risk of CAR T-associated adverse events (hazard ratio: 2.67; 95% CI: 2.09-3.42) compared with outpatient-infused patients. By day 30, 67% of outpatient-infused patients were hospitalized at least once. Conclusion: These findings suggest that physicians were able to select lower-risk patients for outpatient infusion, but postinfusion hospitalizations still occur.

This study tracks outcomes in patients with relapsed/refractory large B-cell lymphoma who received chimeric antigen receptor (CAR) T-cell therapy between 2017 and 2020. The authors used the Anlitiks All-Payor Claims (AAPC) database, which includes insurance claims of patients covered through Medicare, Medicaid or commercial insurance plans. AAPC includes over 80% of insured patients in the USA healthcare system. The study describes where patients received CAR T-cell therapy (inpatient/outpatient), rates of adverse events potentially related to CAR T-cell treatment and how much healthcare the patients received. In the 3 days after receiving CAR T-cell therapy, rates of CAR T-associated adverse events were significantly higher in patients who received CAR T-cell therapy in the inpatient setting, compared with outpatients. The findings suggest that lower-risk patients may receive CAR T-cell therapy as outpatients, but that most outpatient-infused patients will still require inpatient care.

Comparative Efficacy, Safety, and Acceptability of Pimavanserin and Other Atypical Antipsychotics for Parkinson's Disease Psychosis: Systematic Review and Network Meta-Analysis.

BACKGROUND: The current comparative efficacy, safety, and acceptability of atypical antipsychotics (AAPs) in treating Parkinson's Disease Psychosis (PDP) are not entirely understood. OBJECTIVE: To evaluate comparative efficacy, safety, and acceptability of AAPs in patients with PDP. METHODS: We conducted a systematic review and a network meta-analysis to compare the efficacy, safety, and acceptability of pimavanserin, quetiapine, olanzapine, clozapine, ziprasidone, and risperidone. We estimated relative standardized mean differences (SMDs) for continuous outcomes and odds ratios (OR) for binary outcomes, with their respective 95% confidence intervals (CIs). RESULTS: We included 19 unique studies evaluating AAPs in a total of 1,242 persons with PDP. Based on Clinical Global Impression Scale for Severity, pimavanserin (SMD, -4.81; 95% CI, -5.39, -4.24) and clozapine (SMD, -4.25; 95% CI, -5.24, -3.26) significantly improved symptoms compared with placebo. Also, compared to placebo, pimavanserin (OR, 1.16; 95% CI, 1.07, 1.24) significantly improved psychotic symptoms based on Scale for Assessment of Positive Symptoms for Parkinson's Disease Psychosis/Hallucinations and Delusions scores. In comparison to placebo, clozapine (SMD, -0.69; 95% CI, -1.35, -0.02), pimavanserin (SMD, -0.01; 95% CI, -0.56, 0.53), and quetiapine (SMD, 0.00; 95% CI, -0.68, 0.69) did not impair motor function per Unified Parkinson's Disease Rating scale. Based on Mini-Mental State Examination scale, quetiapine (SMD, 0.60; 95% CI, 0.07, 1.14) significantly impaired cognition compared to placebo. CONCLUSIONS: In patients with PDP, pimavanserin and clozapine demonstrated significant improvement in psychosis without affecting motor function. With quetiapine being associated with a significant decline in cognition and despite not impairing motor function, our findings suggest that it should be avoided in patients with PDP and reduced cognitive abilities.

Using Self-reports or Claims to Assess Disease Prevalence: It's Complicated.

BACKGROUND: Two common ways of measuring disease prevalence include: (1) using self-reported disease diagnosis from survey responses; and (2) using disease-specific diagnosis codes found in administrative data. Because they do not suffer from self-report biases, claims are often assumed to be more objective. However, it is not clear that claims always produce better prevalence estimates. OBJECTIVE: Conduct an assessment of discrepancies between self-report and claims-based measures for 2 diseases in the US elderly to investigate definition, selection, and measurement error issues which may help explain divergence between claims and self-report estimates of prevalence. DATA: Self-reported data from 3 sources are included: the Health and Retirement Study, the Medicare Current Beneficiary Survey, and the National Health and Nutrition Examination Survey. Claims-based disease measurements are provided from Medicare claims linked to Health and Retirement Study and Medicare Current Beneficiary Survey participants, comprehensive claims data from a 20% random sample of Medicare enrollees, and private health insurance claims from Humana Inc. METHODS: Prevalence of diagnosed disease in the US elderly are computed and compared across sources. Two medical conditions are considered: diabetes and heart attack. RESULTS: Comparisons of diagnosed diabetes and heart attack prevalence show similar trends by source, but claims differ from self-reports with regard to levels. Selection into insurance plans, disease definitions, and the reference period used by algorithms are identified as sources contributing to differences. CONCLUSIONS: Claims and self-reports both have strengths and weaknesses, which researchers need to consider when interpreting estimates of prevalence from these 2 sources.