Cost-effectiveness of nirsevimab and palivizumab for respiratory syncytial virus prophylaxis in preterm infants 29-34 6/7 weeks' gestation in the United States.

BACKGROUND: Respiratory syncytial virus (RSV) hospitalizations have increased since the 2014 guideline update recommended against the use of palivizumab for preterm infants born ≥29 0/7 weeks' gestational age (GA) without additional risk factors. A novel drug candidate, nirsevimab, has been developed for this population. We analyzed the cost-effectiveness of palivizumab/nirsevimab vs. no prophylaxis in this population. METHODS: A hybrid-Markov model predicted the RSV clinical course in the first year of life and sequelae in the subsequent four years for preterm infants from the healthcare and societal perspectives. Model parameters were derived from the literature. We calculated costs and quality-adjusted life-years (QALYs) to produce an incremental cost-effectiveness ratio (ICER) evaluated at a willingness-to-pay threshold of $150,000/QALY. Sensitivity analyses assessed model robustness. A threshold analysis examined nirsevimab pricing uncertainty. RESULTS: Compared to no prophylaxis, palivizumab costs $9572 and $9584 more from the healthcare and societal perspectives, respectively, with 0.0019 QALYs gained per patient over five years, resulting in ICERs >$5 million per QALY from each perspective. Results were robust to parameter uncertainties; probabilistic sensitivity analysis revealed that no prophylaxis had a 100% probability of being cost-effective. The threshold analysis suggested that nirsevimab is not cost-effective when compared to no prophylaxis if the price exceeds $1962 from a societal perspective. CONCLUSION: Palivizumab is dominated by no prophylaxis for preterm infants 29 0/7-34 6/7 weeks' GA with no additional risk factors. Relevant stakeholders should consider alternatives to palivizumab for this population that are both effective and economical.

Cost-effectiveness of second-line lisocabtagene maraleucel in relapsed or refractory diffuse large B-cell lymphoma.

ABSTRACT: Lisocabtagene maraleucel (liso-cel), a chimeric antigen receptor (CAR) T-cell therapy, received the US Food and Drug Administration approval in 2022 for second-line treatment of diffuse large B-cell lymphoma (DLBCL) for patients with refractory disease or early relapse after first-line chemoimmunotherapy. This decision was based on the TRANSFORM study demonstrating improvements in event-free survival with liso-cel compared with standard care. Given the high costs of CAR T-cell therapies, particularly as they transition to second-line treatment, a cost-effectiveness analysis is essential to determine their economic viability. The study used a partitioned survival model with standard parametric functions to evaluate the cost-effectiveness of liso-cel aganist platinum-based chemotherapy followed by high-dose chemotherapy and autologous hematopoietic stem cell transplantation over a lifetime horizon The analysis relied on data from the TRANSFORM and TRANSCEND trials, established literature, and public data sets to calculate the incremental cost-effectiveness ratio (ICER). For a representative cohort of US adults aged 60 years, ICER of liso-cel was $99 669 per quality-adjusted life-year (QALY) from a health care sector perspective and $68 212 per QALY from a societal perspective, confirming its cost-effectiveness at the $100 000 per QALY threshold. Nonetheless, under certain scenarios, liso-cel surpasses this benchmark but remains within the US acceptable range of $150 000 per QALY. A key finding underlines the importance of incorporating productivity losses into such analyses to capture the broader societal values of novel therapies. Although these therapies offer substantial clinical benefits, their high acquisition costs and limited long-term data critically challenge their economic sustainability.

Factors Associated with Biosimilar Exclusions and Step Therapy Restrictions Among US Commercial Health Plans.

BACKGROUND: Biosimilars have been introduced with the goal of competing with high-priced biologic therapies, yet their adoption has been slower than expected and resulted in limited efficiency gains. We aimed to explore factors associated with biosimilar coverage relative to their reference products by commercial plans in the United States (US). METHODS AND DATA: We identified 1181 coverage decisions for 19 commercially available biosimilars, corresponding to 7 reference products and 28 indications from the Tufts Medical Center Specialty Drug Evidence and Coverage database. We also drew on the Tufts Medical Center Cost-Effectiveness Analysis Registry for cost-effectiveness evidence, and the Merative™ Micromedex® RED BOOK® for list prices. We summarized the coverage restrictiveness as a binary variable based on whether the product is covered by the health plan, and if covered, the difference of payers' line of therapy between the biosimilar and its reference product. We used a multivariate logistic regression to examine the association between coverage restrictiveness and a number of potential drivers of coverage. RESULTS: Compared with reference products, health plans imposed coverage exclusions or step therapy restrictions on biosimilars in 229 (19.4%) decisions. Plans were more likely to restrict biosimilar coverage for the pediatric population (odds ratio [OR] 11.558, 95% confidence interval [CI] 3.906-34.203), in diseases with US prevalence higher than 1,000,000 (OR 2.067, 95% CI 1.060-4.029), and if the plan did not contract with one of the three major pharmacy benefit managers (OR 1.683, 95% CI 1.129-2.507). Compared with the reference product, plans were less likely to impose restrictions on the biosimilar-indication pairs if the biosimilar was indicated for cancer treatments (OR 0.019, 95% CI 0.008-0.041), if the product was the first biosimilar (OR 0.225, 95% CI 0.118-0.429), if the biosimilar had two competitors (reference product included; OR 0.060, 95% CI 0.006-0.586), if the biosimilar could generate annual list price savings of more than $15,000 per patient (OR 0.171, 95% CI 0.057-0.514), if the biosimilar's reference product was restricted by the plan (OR 0.065, 95% CI 0.038-0.109), or if a cost-effectiveness measure was not available (OR 0.066, 95% CI 0.023-0.186). CONCLUSION: Our study offered novel insights on the factors associated with biosimilar coverage by commercial health plans in the US relative to their reference products. Cancer treatment, pediatric population, and coverage restriction of the reference products are some of the most significant factors that are associated with biosimilar coverage decisions.

Predicting panel attrition in longitudinal HRQoL surveys during the COVID-19 pandemic in the US.

BACKGROUND: Online longitudinal surveys may be subject to potential biases due to sample attrition. This study was designed to identify potential predictors of attrition using a longitudinal panel survey collected during the COVID-19 pandemic. METHODS: Three waves of data were collected using Amazon Mechanical Turk (MTurk), an online crowd-sourced platform. For each wave, the study sample was collected by referencing a US national representative sample distribution of age, gender, and race, based on US census data. Variables included respondents' demographics, medical history, socioeconomic status, COVID-19 experience, changes of health behavior, productivity, and health-related quality of life (HRQoL). Results were compared to pre-pandemic US norms. Measures that predicted attrition at different times of the pandemic were identified via logistic regression with stepwise selection. RESULTS: 1467 of 2734 wave 1 respondents participated in wave 2 and, 964 of 2454 wave 2 respondents participated in wave 3. Younger age group, Hispanic origin (p ≤ 0.001) and higher self-rated survey difficulty (p ≤ 0.002) consistently predicted attrition in the following wave. COVID-19 experience, employment, productivity, and limited physical activities were commonly observed variables correlated with attrition with specific measures varying by time periods. From wave 1, mental health conditions, average daily hours worked (p = 0.004), and COVID-19 impact on work productivity (p < 0.001) were associated with a higher attrition rate at wave 2, additional to the aforementioned factors. From wave 2, support of social distancing (p = 0.032), being Republican (p < 0.001), and having just enough money to make ends meet (p = 0.003) were associated with predicted attrition at wave 3. CONCLUSIONS: Attrition in this longitudinal panel survey was not random. Besides commonly identified demographic factors that contribute to panel attrition, COVID-19 presented novel opportunities to address sample biases by correlating attrition with additional behavioral and HRQoL factors in a constantly evolving environment. While age, ethnicity, and survey difficulty consistently predicted attrition, other factors, such as COVID-19 experience, changes of employment, productivity, physical health, mental health, and financial situation impacted panel attrition during the pandemic at various degrees.

Trends and disparities in the utilization of influenza vaccines among commercially insured US adults during the COVID-19 pandemic.

OBJECTIVES: Little is known about how the coronavirus disease 2019 (COVID-19) pandemic affected influenza vaccine utilization and disparities. We sought to estimate changes in the likelihood of receiving an influenza vaccine across different demographic subgroups during the COVID-19 pandemic. METHODS: In this cohort study, we analyzed influenza vaccine uptake from 2019 to 2020 using Optum commercial insurance claims data. Eligible individuals were aged 18 or above in 2018 and continuously enrolled from 08/01/2018 through 12/31/2020. Multivariable logistic regressions were fitted for the individual-level influenza vaccine uptake. Adjusting for demographic factors and medical histories, we estimated probabilities of receiving influenza vaccines before and after the COVID-19 pandemic across demographic subgroups. RESULTS: From August to December 2019, unadjusted influenza vaccination rate was 42.3%, while in the same period of 2020, the vaccination rate increased to 45.9%. Females had a higher vaccination rate in 2019 (OR: 1.16, 95% CI 1.15-1.16), but the increase was larger for males. Blacks and Hispanics had lower vaccination rates relative to whites in both flu seasons. Hispanics showed a greater increase in vaccination rate, increasing by 7.8 percentage points (p < .001) compared to 4.4 (p < .001) for whites. The vaccination rate for Blacks increased by 5.2 percentage points (p < .001). All income groups experienced vaccination improvements, but poorer individuals had lower vaccination rates in both seasons. The most profound disparities occurred when educational cohort were considered. The vaccination rate increased among college-educated enrollees by 8.8 percentage points (p < .001) during the pandemic compared to an increase of 2.8 percentage points (p < .001) for enrollees with less than a 12th grade education. Past influenza infections or vaccination increased the likelihood of vaccination (p < .001). CONCLUSIONS: The COVID-19 pandemic was associated with increased influenza vaccine utilization. Disparities persisted but narrowed with respect to gender and race but worsened with respect to income and educational attainment.