Sorrel Wolowacz

Objective: The objective of this study was to assess the economic family spillover effects of childhood congenital cytomegalovirus (cCMV) in the US. Methods: This cross-sectional, Web-based study collected economic and health-state utility data between August 2024 and April 2025 using three surveys targeting caregivers of children with cCMV, children with cCMV, and their siblings. Results: Respondents included 227 caregivers, 211 children with cCMV, and 173 siblings. A high economic burden on families of children with cCMV was reported, including total mean annual costs (out-of-pocket medical and personal care expenses and work- or productivity-related costs) of $83,140 and lifetime out-of-pocket home adaptation/specialized schooling costs of $4713. The mean caregiver EQ-5D-5L utility score was 0.86, which is comparable to US general-population norms. Mean Health Utilities Indexes Mark 2 and 3 scores varied within the ranges of 0.38–0.83 and 0.03–0.73, respectively, among children with cCMV. Adult siblings reported a mean EQ-5D-5L utility of 0.90. Siblings aged 4–7 and 8–17 years reported mean EQ-5D-Y-3L utilities of 0.90 and 0.92, respectively. Conclusions: This is the first study to report the family spillover effects of caring for children with cCMV in the US. The results confirm a considerable, multifaceted burden experienced by children with cCMV and their families, spanning health-state utility and economic strains.

Including patient-reported outcome measures (PROMs) in cost-effectiveness models (CEMs) represents an important opportunity to reflect patients' perspectives in health technology assessments (HTAs). Beyond utility measures, little is known about how PROMs are used in CEMs and their acceptance by reviewers. We elucidated how PROMs were incorporated into CEMs submitted to the UK National Institute for Health and Care Excellence (NICE) for nononcology treatments and identified feedback from NICE and external assessment groups (EAGs). NICE HTAs for nononcology treatments from January 2016 to August 2022 which used a PROM (other than a generic utility measure) as a key element in the CEM were reviewed. Information on how PROMs were used, rationale for their use, and feedback from NICE and EAGs were summarized. Of 428 HTAs identified, 27 (6.3%) were included in our review. PROMs were included in the CEMs via treatment-effect parameters (n = 25/27, 92.6%), model structure (n = 25/27, 92.6%), treatment-stopping rules (n = 21/27, 77.8%), and/or condition-specific utility measures (n = 18/27, 66.7%). Of the 27 HTAs, 22 (81.5%) provided justification for using a PROM in the CEM, most frequently citing the PROM validation. NICE and/or the EAG raised concerns in 20 HTAs (74.1%) regarding the use of PROMs, most commonly regarding the data source, statistical methods, and implementation of the PROM in clinical practice. This review did not focus on ways the patient voice may be reflected in the NICE process beyond incorporation of PROMs in CEMs. Generalizability of the findings to other HTA settings may be limited. NICE accepted the use of PROMs in CEMs where high-quality data relevant to the target population and appropriate statistical methods were used. Few CEMs used PROMs other than utility measures. Further research is needed to understand the value of PROMs in CEMs for HTAs.

Selpercatinib and pralsetinib are approved for RET-rearranged non - small cell lung cancer. Efficacy and safety were compared using matching-adjusted indirect comparison. Median progression-free survival (PFS) was 22.1 and 13.3 months for selpercatinib and pralsetinib, respectively (HR = 0.67; 95% CI, 0.53-0.85). Objective response rate was 64.5% and 65.8%, and disease control rate was 92.1% and 90.4%, respectively. Median overall survival was not reached for selpercatinib and 43.9 months for pralsetinib (HR = 0.81; 95% CI, 0.60-1.09). Grade ≥ 3 treatment-related adverse events (TRAEs) were reported in 39.3% and 62.6% of patients, with discontinuations due to TRAEs in 3.6% and 10.0% of patients, respectively. Outcomes were similar; however, PFS was significantly prolonged with selpercatinib, with fewer grade ≥ 3 TRAEs.

Capture the economic and healthcare resource utilization (HCRU) burden in older adults due to respiratory syncytial virus (RSV) infection.An electronic literature search of PubMed, Embase, the Coch...

Aim: Evaluations of nonalcoholic steatohepatitis (NASH) treatments require predicting lifetime outcomes from short-term clinical trials. Materials & methods: A Markov model with NASH fibrosis stages F0–F3, NASH resolution, compensated cirrhosis (F4/CC), and liver-related complication (LRC) states was developed using literature-based standard of care (SoC) data. Hypothetical efficacy profiles were defined affecting resolution (100%-increase), fibrosis improvement (100% increase), or fibrosis worsening (50% decrease). Results: For the SoC, 10-year LRC rates increased with baseline fibrosis stage (F1: 3.0%; F2: 9.8%; F3: 27.2%; F4/CC: 64.9%). The fibrosis worsening profile reduced predicted 10-year LRC rates (F1: 1.9%; F2: 6.5%; F3: 19.1%; F4/CC: 55.0%) more than the resolution and fibrosis improvement profiles (F1: 2.6%/2.6%; F2: 8.5%/8.3%; F3: 23.3%/23.0%; F4/CC: NA/59.0%). Scenario analyses considered alternative SoC progression, treatment efficacy and treatment-stopping rules. Conclusion: Potential NASH efficacy profiles have differing impacts on predicted long-term outcomes, providing insights for future stakeholders.

Objective:Health utility estimates for children and adolescents are critical for cost-utility analyses informing health technology assessment (HTA) authorities' decisions governing access to pediatric treatments. However, in a recent review, only 29% of published pediatric cost-utility models used a utility measure validated for children. We examined utility estimates used in pediatric HTAs. Methods:A targeted review of pediatric HTAs was performed, focusing on agencies reporting utility estimate sources and methods. Results:Searches identified 11 HTAs in pediatric indications and five in mixed populations with separate analyses for adults and children. Among 13 appraisals reporting methodological detail, five used pediatric utility estimates (based on the Health Utilities Index [HUI],n = 3; Atopic Dermatitis Quality of Life [ADQoL],n = 1; or mapping,n = 1). Issues were identified with mapping, use of adult data for some health states, and assumptions about ADQoL responses. In the remaining eight appraisals, adult utility estimates were applied. Caregiver utility was included in two of 16 appraisals. Conclusions:Only 38% of pediatric HTAs reviewed used pediatric utility estimates, and HTA authorities raised concerns about these data in many cases; only 12% of HTAs included caregiver utility. Although several preference-based utility measures are available for pediatric populations, limited data and guidance on selection of measures are available. When estimating pediatric utility weights, alternative measures should be reviewed for suitability given the model population and health condition. Pediatric and adult utility estimates should be applied appropriately as patients age over time, and caregiver and/or family member utility should be included, where relevant. Gaps exist in utility measures for children aged <4 years and caregivers.