Primer on Simulation Modeling: Using Model-Based Analyses to Inform Health Policy and Research on HIV Prevention

Transcription

1 Primer on Simulation Modeling: Using Model-Based Analyses to Inform Health Policy and Research on HIV Prevention Caitlin Dugdale, MD Massachusetts General Hospital Global HIV Vaccine Enterprise Modeling Webinar October 31, 2017 Supported by NIAID T32 AI and the IMPAACT network 1

2 Disclosures I have no conflicts of interest to declare 2

3 Simulation Modeling Structured method for approaching medical decision making Compare two or more strategies for treatment, prevention, diagnosis, etc. Use short-term inputs to generate long-term projections of clinical and economic outcomes Simulate the natural history of a disease to estimate future infections or healthcare resource needs Combine multiple sources of data to create what-if scenarios of complex systems Marshall DA et al. Value in Health, Hunink MG et al. Decision Making in Health and Medicine, 2 nd Ed

4 Advantages of Simulation Models Compare scenarios that may be unethical or infeasible to evaluate in a formal clinical trial (e.g. long follow required, patients LTFU) Evaluate the feasibility and affordability of policy goals (e.g ) Inform trial design by identifying key parameters that may change the efficacy or value of an intervention in advance of a clinical trial Walensky RP et al. Ann Intern Med, Hunink MG et al. Decision Making in Health and Medicine, 2 nd Ed

5 Advantages of Simulation Models Assess the cost-effectiveness of interventions Inform use for general population vs. subpopulations Evaluate the relative clinical and economic impact of an intervention in specific settings (e.g. areas with high vs. low HIV incidence) Estimate the budget impact of policies Sanders GD et al. JAMA, Hunink MG et al. Decision Making in Health and Medicine, 2 nd Ed

6 Model Advantages: Example A new HIV vaccine has an 80% efficacy over a 2 year period after 3 doses at a cost of $200. Questions for a model-based analysis: Is the vaccine cost-effective for use in the general population, or would it be best targeted to high-risk individuals? Would that conclusion change if the vaccine efficacy were 90%? If it required only a two-dose series? If it lasted 5 or 10 years? For what populations would it be cost-effective to re-vaccinate 2 years later? Until what age should that continue? At what total cost would the vaccine be cost-effective for general use in the U.S.? In South Africa? In Mozambique? What financial impact would such a vaccine have on a given country s overall healthcare budget? 6

7 Model-Based Analyses: Design (PICO) Population - Define the cohort for evaluation Consider sub-cohorts for scenario/sensitivity analyses Intervention/Control - Identify two or more strategies for comparison Current practice (standard of care) vs. Intervention 1 vs. Intervention 2 vs. Intervention 1+2 Outcome - Choose an outcome measure Infections averted, quality-adjusted life years (QALYs) gained, disability-adjusted life years (DALYs) averted, overall costs, cost per year of life saved ($/YLS), etc. 7

8 Model-Based Analyses: Methods Select the model structure that will best evaluate the primary research question Monte Carlo model, Markov model, discrete-event simulation, dynamic transmission model, etc.* Populate the model with data/input parameters* Run the simulation à base case Perform sensitivity analyses Stochastic: Inputs = point estimates Probabilistic: Inputs = distributions around point estimates *Covered in detail in next two presentations 8

9 Model-Based Analyses: Results Example Inputs: Probability of incident infection or drug toxicity Retention/LTFU Adherence Efficacy of intervention Unit costs of intervention, medications, or events Example Outputs: # New infections # Adverse events Disease-related mortality at different time points Cohort or sub-group lifeexpectancy Overall and individual costs Clinical and cost results can be reported separately or interpreted together in the context of a formal cost-effectiveness analysis 9

10 Cost-Effectiveness Analysis One of many factors in decision making Clinical benefits usually take priority in guideline development Estimates tradeoffs in health by investing in one intervention compared to another Projected (modeled) outcomes: Cost (in dollars or other currency) Effectiveness Years of life saved, QALYs gained, or DALYs averted Infections averted, patients linked to care, cases detected, etc. Some outcomes allow for cross-analysis comparisons 10

11 Cost-Effectiveness Analysis Cost-effective saves money Cost-effective cheap A more effective intervention is often more expensive. Is the additional benefit worth the additional cost? Value for money: For any given health care budget, maximize benefits to patients 11

12 Cost-Effectiveness Analysis Compares two strategies using an incremental cost-effectiveness ratio (ICER): Additional resource use Additional health benefit in $ Year of life saved (YLS) Threshold to define cost-effectiveness is evolving ICER <1x per-capita GDP/YLS is cost-effective - Cost-effective = additional health benefit worth the additional cost 12

13 Example: HIV Vaccine Harmon TM et al., PLOS ONE

14 Analysis Overview Evaluated the potential impact of a future AIDS vaccine in low and middle income countries - Compared scale up of the UNAIDS Investment Framework Enhanced (IFE) goals to IFE + vaccine - IFE: Prevention strategies (PMTCT, condoms, VMMC, etc.) + ART scale-up (with treatment as prevention) Used Spectrum Goals model - Creates discrete behavioral subgroups with randomly assigned individual characteristics to simulate HIV transmission Harmon TM et al., PLOS ONE

15 Table 1. Assumptions. Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

16 Fig 3. Reduction of new annual HIV infections under Full Scale-up of IFE according to vaccine efficacy between 2025 and 2070 (vaccine introduced in 2027). Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

17 Fig 3. Reduction of new annual HIV infections under Full Scale-up of IFE according to vaccine efficacy between 2025 and 2070 (vaccine introduced in 2027). Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

18 Fig 3. Reduction of new annual HIV infections under Full Scale-up of IFE according to vaccine efficacy between 2025 and 2070 (vaccine introduced in 2027). Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

19 Fig 6. Cost per QALY gained ( ) according to vaccine efficacy under two cost scenarios in LICs (discounted at 3% per year) when a vaccine is added to Full Scale-up of IFE. Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

20 Fig 6. Cost per QALY gained ( ) according to vaccine efficacy under two cost scenarios in LICs (discounted at 3% per year) when a vaccine is added to Full Scale-up of IFE. Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

21 Fig 6. Cost per QALY gained ( ) according to vaccine efficacy under two cost scenarios in LICs (discounted at 3% per year) when a vaccine is added to Full Scale-up of IFE. Harmon TM, Fisher KA, McGlynn MG, Stover J, Warren MJ, et al. (2016) Exploring the Potential Health Impact and Cost-Effectiveness of AIDS Vaccine within a Comprehensive HIV/AIDS Response in Low- and Middle-Income Countries. PLOS ONE 11(1): e

22 Example: Long-acting PrEP Cost-Effectiveness of Preventing AIDS Complications (CEPAC) state-transition model Simulated PrEP-eligible, HIV-uninfected, high-risk South African women Walensky RP et al., J Infect Dis

23 Example: Long-acting PrEP Walensky RP et al., J Infect Dis

24 Example: Long-acting PrEP Walensky RP et al., J Infect Dis

25 Example: Long-acting PrEP Walensky RP et al., J Infect Dis

26 Example: Long-acting PrEP Walensky RP et al., J Infect Dis

27 Example: Long-acting PrEP Walensky RP et al., J Infect Dis

28 Example: Long-acting PrEP Walensky RP et al., J Infect Dis

29 Example: Long-acting PrEP 29

30 Example: Long-acting PrEP 30

31 Example: Long-acting PrEP 31

32 Conclusion Simulation models are useful tools to inform research design and guide health care policy Cost-effectiveness analyses gauge the value for money of a policy or intervention Prevention modeling can help prioritize research investment in high-yield areas, forecast future trends in the HIV epidemic, identify key parameters for further investigation in trials, and optimize implementation of novel prevention therapies 32

33 Thank you CEPAC-Pediatric Team: Elaine Abrams, Ingrid Bassett, Alex Bulteel, Andrea L. Ciaranello, Sophie Desmonde, Caitlin Dugdale, Lorna Dunning, Simone Frank, Emily P. Hyle, Taige Hou, Valeriane Leroy, Landon Myer, Anne Neilan, Robert Parker, Kunjal Patel, Martina Penazzato, George Seage, Djora Soeteman, Milton Weinstein, Rochelle P. Walensky, Kenneth A. Freedberg Supported by: NIAID T32 AI and the IMPAACT network CEPAC Supported by: NICHD (R01HD079214), NIAID (R01AI058736, R37AI093269), the World Health Organization, the Elizabeth Glaser Pediatric AIDS Foundation, the Adolescent Trials Network and the IMPAACT network 33