Evaluating the Impact of Predictive Variables on Individual Biosimilar US Market Share
Author(s)
Colleen Mueller, Master in Public Health1, Daniel Krieger, .2.
1Associate Consultant, Red Nucleus, Boston, MA, USA, 2Red Nucleus, Boston, MA, USA.
1Associate Consultant, Red Nucleus, Boston, MA, USA, 2Red Nucleus, Boston, MA, USA.
Presentation Documents
OBJECTIVES: Validating a predictive model developed in 2023 to examine the relative impact of factors influencing biosimilar US market share.
METHODS: We aimed to re-examine the relationship between predictor variables and the impact on originator market share using the multivariate regression model developed in 2023. The analysis included 9 originators with 38 approved biosimilars. Variables included aggregate biosimilar market share relative to each originator, number of biosimilars, duration of biosimilar competition, price differentials between originator and biosimilar(s), and payer management. An analysis of 15 health plans’ formulary documents as of 12/1/24 was conducted to identify step therapy requirements for each originator. Market share and model inputs were captured from FDA, NORD, Drugs.com, and other publicly available sources. The significance level was α=0.05.
RESULTS: The 5-variable model including all 38 products resulted in an R² of 0.653 (p<0.001). After adjusting for all variables in the model, multiple predictor variables achieved statistical significance, including payer management (p<0.001), duration of biosimilar competition (p=0.020), and number of biosimilars (p<0.001) and maintained significance when assessed independently from the other variables. The R² for this model indicates that over 65% of the variability in biosimilar market share was accounted for by the combination of other predictor variables included.
CONCLUSIONS: These results suggest a 1% increase in market share was associated with an aggregate of ~3 fewer steps. Outcomes from these models were similar to that of last year’s analysis with an increased R² and p-value, suggesting that this model is a more accurate representations of the factors influencing originator market share, likely due to greater sample size. Price differentials between originator and biosimilar(s) was not significant, suggesting that inclusion of list price likely minimizes the relationship given net price is more influential to payer access and subsequent market share.
METHODS: We aimed to re-examine the relationship between predictor variables and the impact on originator market share using the multivariate regression model developed in 2023. The analysis included 9 originators with 38 approved biosimilars. Variables included aggregate biosimilar market share relative to each originator, number of biosimilars, duration of biosimilar competition, price differentials between originator and biosimilar(s), and payer management. An analysis of 15 health plans’ formulary documents as of 12/1/24 was conducted to identify step therapy requirements for each originator. Market share and model inputs were captured from FDA, NORD, Drugs.com, and other publicly available sources. The significance level was α=0.05.
RESULTS: The 5-variable model including all 38 products resulted in an R² of 0.653 (p<0.001). After adjusting for all variables in the model, multiple predictor variables achieved statistical significance, including payer management (p<0.001), duration of biosimilar competition (p=0.020), and number of biosimilars (p<0.001) and maintained significance when assessed independently from the other variables. The R² for this model indicates that over 65% of the variability in biosimilar market share was accounted for by the combination of other predictor variables included.
CONCLUSIONS: These results suggest a 1% increase in market share was associated with an aggregate of ~3 fewer steps. Outcomes from these models were similar to that of last year’s analysis with an increased R² and p-value, suggesting that this model is a more accurate representations of the factors influencing originator market share, likely due to greater sample size. Price differentials between originator and biosimilar(s) was not significant, suggesting that inclusion of list price likely minimizes the relationship given net price is more influential to payer access and subsequent market share.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
EE339
Topic
Economic Evaluation
Topic Subcategory
Value of Information
Disease
SDC: Rare & Orphan Diseases, STA: Biologics & Biosimilars