Background: A systematic review and meta-analysis of real-world observational studies was conducted to summarize the impact of letermovir cytomegalovirus (CMV) primary prophylaxis (PP) among adult allogeneic hematopoietic cell transplant (allo-HCT) recipients. Methods: Systematic searches in Medline/PubMed, Embase, and conferences (from database inception to October 2021) were conducted to identify studies for inclusion. Random-effects models were used to derive pooled estimates on the relative effectiveness of letermovir PP compared to controls. Results: Forty-eight unique studies (N = 7104 patients) were included, most of which were comparative, single-center, and conducted in the United States. Letermovir PP was associated with statistically significant reduction in odds of CMV reactivation (pooled odds ratio [pOR], 0.13 and 0.24; P < .05), clinically significant CMV infection (pOR, 0.09 and 0.19; P < .05), and CMV disease (pOR, 0.31 and 0.35; P < .05) by day +100 and day +200 after allo-HCT, respectively. Letermovir PP was associated with significantly lower odds of all-cause (pOR, 0.73; P < .01) and nonrelapse mortality (pOR, 0.65; P = .01) beyond day 200 after allo-HCT. Conclusions: Letermovir for CMV PP was effective in reducing the risk of CMV-related complications overall and mortality beyond day 200 among adult allo-HCT recipients.

Background: Data on trends of diabetes medications use are sparse, outdated, and limited to prescription data. We determined trends in diabetes medication use among US individuals with diabetes during 2008-2015. Methods: We used 2008-2015 Medical Expenditure Panel Survey to examine diabetes medication utilization among individuals aged ≥18 years with diabetes. Prescription medications were classified based on therapeutic class and subclass using Multum Lexicon database. Results: From 2008 to 2015, use of any diabetes medication (81.4% vs. 87%), metformin (47.8% vs. 59.0%), and insulin (23.0% vs. 31.0%) increased, whereas, use of sulfonylurea (36.0% vs. 29.0%) and thiazolidinedione (21% vs. 9.0%) declined. A linear increase was observed in the uptake of dipeptidyl peptidase-4 (DPP-4) inhibitors from 6.2% in 2008 to 12.4% in 2015; glucagon-like peptide-1 (GLP-1) receptor agonists from 2.5% in 2008 to 4.4% in 2015 and sodium glucose transporter-2 (SGLT2) inhibitors from 0.8% in 2014 (the first SGLT2 inhibitors approval year) to 4.4% in 2015. Monotherapy use increased from 50.6% to 56.4% during 2008-2015, while triple therapy use declined. Conclusions: Metformin, insulin and sulfonylureas remained the top-three prescribed classes of diabetes medications. Increased use of DPP-4 inhibitors, GLP-1 receptor agonists and SGLT2 inhibitors was offset by decline in TZDs use.

BACKGROUND: Various factors, including patient demographic and socioeconomic characteristics, patient out-of-pocket (OOP) costs, therapy-related factors, clinical characteristics, and health-system factors, can affect patient adherence to oral anticancer medications (OAMs). OBJECTIVE: To determine the proportion of patients initiating oral anticancer therapy who were adherent to OAMs and to identify significant predictors of adherence to OAMs, including patient OOP costs and patient demographics. METHODS: A retrospective cohort study was conducted using data from Optum Clinformatics Data Mart commercial claims database for 2010-2018. Patients with a new pharmacy claim for an OAM between July 1, 2010, and December 31, 2017, were followed for 6 months to ascertain their medication adherence, which was defined as a proportion of days covered value of at least 0.8. Average monthly patient OOP costs for OAM prescriptions were categorized as lower OOP costs (quartiles 1-3) and higher OOP costs (quartile 4). Separate multivariable logistic regressions were conducted to identify predictors of OAM nonadherence for each cancer type. RESULTS: Out of 37,938 patients with cancer, 51.9% were adherent to OAMs, with adherence ranging from 32.8% among those with liver cancer to 70.4% among those with brain tumor. The average monthly OOP costs of OAMs also differed by cancer type, ranging from 5749 (SD=S1,014) among patients with blood cancer to $106 (SD=$439) among those with prostate cancer. Higher patient OOP costs were associated with higher odds of OAM nonadherence for many cancer types, including renal cancer (adjusted odds ratio [AOR]=3.91; 95% CI=2.80-5.47) and breast cancer (AOR=1.26; 95% CI =1.13-1.41). Additionally, patients with inpatient hospitalizations during the 6 months following OAM initiation had significantly higher odds of OAM nonadherence for all cancer types except for stomach cancer. Among patients with stomach cancer, male sex was associated with lower odds of OAM nonadherence (AOR =0.60; 95% CI =0.37-0.97). Among patients with renal or stomach cancer, those who had Medicare low-income subsidy had higher odds of OAM nonadherence compared with those with commercial insurance coverage. Among patients with blood cancers, Black and Hispanic patients had higher odds of OAM nonadherence compared with White patients (AOR=1.48; 95% CI =1.25-1,75 and AOR=1,38; 95% CI =1.13-1,68, respectively). CONCLUSIONS: Overall adherence to OAMs was suboptimal, and for several cancer types, adherence was worse among patients with higher OOP costs, those who were hospitalized, and those who received Medicare low-income subsidy. Policies addressing cost and access to OAMs and health-system strategies to address barriers to the effective use of OAMs are needed to improve patient access to these vital medications.