Predicted vs. Actual Drug Spending for Interferon-Free Direct-Acting Antiviral Therapies in Hepatitis C: A Case Study on Drug Spending Forecasts
Author(s)
Natasha Kulkarni, BS1, John Jarvis, MBA2, Cheryl Steward, MPA2, Lufei Tu, MS2, Alexa Klimchak, MA1, Kathy Gooch, PhD1, Marjorie Crowell, MPA2.
1Sarepta Therapeutics., Inc., Cambridge, MA, USA, 2Medicus Economics, LLC, Milton, MA, USA.
1Sarepta Therapeutics., Inc., Cambridge, MA, USA, 2Medicus Economics, LLC, Milton, MA, USA.
Presentation Documents
OBJECTIVES: Forecast models are frequently used to predict drug spending in the U.S. and inform stakeholder decision-making, but few analyses have compared predictions to actual spending. This study uses interferon-free direct-acting antiviral (DAA) therapies approved to treat the hepatitis C virus (HCV) as a case study to investigate the accuracy of historical drug spending predictions.
METHODS: In June 2023, a targeted literature review (TLR) was conducted to identify publicly available analytical predictions of U.S. sales for interferon-free DAA therapies to treat HCV that were approved from 2013 to 2022. National sales predictions were compared to actual U.S. net sales over time. One hour in-depth interviews with U.S. payers were conducted in October 2023 to validate and further inform analysis findings.
RESULTS: Fourteen analytical predictions for total U.S. spending on HCV interferon-free DAA therapies were identified in the TLR. Spending predictions varied considerably. Base-case prediction estimates ranged from $53 billion to $310 billion, with nearly two-thirds predicting total U.S. spending greater than $200 billion. Between 2013 and 2022, total actual U.S. net sales summed to $54 billion which was substantially lower than most predictions. During the interviews with 10 U.S. payers, five factors were identified that may have resulted in differences between predicted and actual spending: 1) overestimating HCV prevalence; 2) not accounting for new (incident) HCV cases over time; 3) not limiting treatment eligibility to those aware of their HCV infection (i.e., diagnosed patients); 4) overestimating treatment uptake; and 5) overestimating net drug prices over time.
CONCLUSIONS: Most public predictions overestimated actual U.S. spending for interferon-free DAA therapies in HCV. While prediction models can be valuable in estimating the potential budget impact of therapies on future healthcare spending, this assessment highlights the challenges and importance of accounting for disease-, treatment-, and population-specific nuances when developing healthcare spending forecasts.
METHODS: In June 2023, a targeted literature review (TLR) was conducted to identify publicly available analytical predictions of U.S. sales for interferon-free DAA therapies to treat HCV that were approved from 2013 to 2022. National sales predictions were compared to actual U.S. net sales over time. One hour in-depth interviews with U.S. payers were conducted in October 2023 to validate and further inform analysis findings.
RESULTS: Fourteen analytical predictions for total U.S. spending on HCV interferon-free DAA therapies were identified in the TLR. Spending predictions varied considerably. Base-case prediction estimates ranged from $53 billion to $310 billion, with nearly two-thirds predicting total U.S. spending greater than $200 billion. Between 2013 and 2022, total actual U.S. net sales summed to $54 billion which was substantially lower than most predictions. During the interviews with 10 U.S. payers, five factors were identified that may have resulted in differences between predicted and actual spending: 1) overestimating HCV prevalence; 2) not accounting for new (incident) HCV cases over time; 3) not limiting treatment eligibility to those aware of their HCV infection (i.e., diagnosed patients); 4) overestimating treatment uptake; and 5) overestimating net drug prices over time.
CONCLUSIONS: Most public predictions overestimated actual U.S. spending for interferon-free DAA therapies in HCV. While prediction models can be valuable in estimating the potential budget impact of therapies on future healthcare spending, this assessment highlights the challenges and importance of accounting for disease-, treatment-, and population-specific nuances when developing healthcare spending forecasts.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
HPR122
Topic
Health Policy & Regulatory
Topic Subcategory
Public Spending & National Health Expenditures
Disease
SDC: Infectious Disease (non-vaccine)