A systematic literature review of the economic and healthcare resource burden of cytomegalovirus.

OBJECTIVE: Cytomegalovirus (CMV) can infect individuals at any age, including infants, who may contract it from infected mothers (congenital CMV [cCMV]). Whereas CMV infection is typically asymptomatic or causes mild illness in healthy individuals, infection can result in severe outcomes in immunocompromised individuals and in infants with cCMV. This systematic review aims to characterize the economic impact of CMV and cCMV infections. METHODS: Medline, Embase, and LILACS databases were searched for publications reporting the economic impact of cCMV and CMV infections across all age groups. Manuscripts published between 2010 and 2020 from Australia, Latin America, Canada, Europe, Israel, Japan, the United States, and global (international, worldwide) studies were included; congress materials were excluded. Outcomes of interest included cCMV- and CMV-attributable direct costs/charges, resource utilization, and indirect/societal costs. RESULTS: Of 751 records identified, 518 were excluded based on duplication, population, outcome, study design, or country. Overall, 55 articles were eligible for full-text review; 25 were further excluded due to population, outcome, study design, or congress abstract. Two publications were additionally identified, resulting in economic impact data compiled from 32 publications. Of these, 24 publications reported cost studies of cCMV or CMV, including evaluation of direct costs/charges, healthcare resource utilization, and indirect/societal costs, and 7 publications reported economic evaluations of interventions. The populations, methods and outcomes used across these studies varied widely. CONCLUSIONS: CMV and cCMV infections impose a considerable economic impact on different countries, populations, and outcomes. There are substantial evidence gaps where further research is warranted.

Description of a New Predictive Modeling Approach That Correlates the Risk and Associated Cost of Well-Defined Diabetes-Related Complications With Changes in Glycated Hemoglobin (HbA1c).

The modeling approach described here is designed to support the development of spreadsheet-based simple predictive models. It is based on 3 pillars: association of the complications with HbA1c changes, incidence of the complications, and average cost per event of the complication. For each pillar, the goal of the analysis was (1) to find results for a large diversity of populations with a focus on countries/regions, diabetes type, age, diabetes duration, baseline HbA1c value, and gender; (2) to assess the range of incidences and associations previously reported. Unlike simple predictive models, which mostly are based on only 1 source of information for each of the pillars, we conducted a comprehensive, systematic literature review. Each source found was thoroughly reviewed and only sources meeting quality expectations were considered. The approach allows avoidance of unintended use of extreme data. The user can utilize (1) one of the found sources, (2) the found range as validation for the found figures, or (3) the average of all found publications for an expedited estimate. The modeling approach is intended for use in average insulin-treated diabetes populations in which the baseline HbA1c values are within an average range (6.5% to 11.5%); it is not intended for use in individuals or unique diabetes populations (eg, gestational diabetes). Because the modeling approach only considers diabetes-related complications that are positively associated with HbA1c decreases, the costs of negatively associated complications (eg, severe hypoglycemic events) must be calculated separately.