Economic evaluations of predictive genetic testing: A scoping review.

Predictive genetic testing can provide information about whether or not someone will develop or is likely to develop a specific condition at a later stage in life. Economic evaluation can assess the value of money for such testing. Studies on the economic evaluation of predictive genetic testing have been carried out in a variety of settings, and this research aims to conduct a scoping review of findings from these studies. We searched the PubMed, Web of Science, Embase, and Cochrane databases with combined search terms, from 2019 to 2022. Relevant studies from 2013 to 2019 in a previous systematic review were also included. The study followed the recommended stages for undertaking a scoping review. A total of 53 studies were included, including 33 studies from the previous review and 20 studies from the search of databases. A significant number of studies focused on the US, UK, and Australia (34%, 23%, and 11%). The most frequently included health conditions were cancer and cardiovascular diseases (68% and 19%). Over half of the studies compared predictive genetic testing with no genetic testing, and the majority of them concluded that at least some type of genetic testing was cost-effective compared to no testing (94%). Some studies stated that predictive genetic testing is becoming more cost-effective with the trend of lowering genetic testing costs. Studies on predictive genetic testing covered various health conditions, particularly cancer and cardiovascular diseases. Most studies indicated that predictive genetic testing is cost-effective compared to no testing.

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.