Patient Heterogeneity in Health Economic Decision Models for Chronic Obstructive Pulmonary Disease: Are Current Models Suitable to Evaluate Personalized Medicine?

Abstract

Patient heterogeneity in health economic decision models for chronic obstructive pulmonary disease (COPD): are current models suitable to evaluate personalized medicine? 3 AbstractObjectives: To assess how suitable current COPD cost-effectiveness models are to evaluate personalized treatment options for COPD by exploring the type of heterogeneity included in current models and by validating outcomes for subgroups of patients.Methods: A consortium of COPD modelling groups completed three tasks. First, they reported all patient characteristics included in the model and provided the level of detail in which the input parameters were specified. Second, groups simulated disease progression, mortality, quality-adjusted life-years (QALYs) and costs for hypothetical subgroups of patients that differed in terms of gender, age, smoking status and lung function (FEV1% predicted). Finally, model outcomes for exacerbations and mortality for subgroups of patients were validated against published subgroup results of two large COPD trials.Results: Nine COPD modelling groups participated. Most models included gender (seven), age (nine), smoking status (six) and FEV1% predicted (nine), mainly to specify disease progression and mortality.Trial results showed higher exacerbation rates for females (found in one model), higher mortality rates for males (two models), lower mortality for younger patients (four models), and higher exacerbation and mortality rates in patients with severe COPD (four models).Conclusions: The majority of currently available COPD cost-effectiveness models are able to evaluate the cost-effectiveness of personalized treatment based on gender, age, smoking and FEV1% predicted. Treatment in COPD is however, more likely to be personalized based on clinical parameters. Two models include several clinical patient characteristics and are therefore most suitable to evaluate personalized treatment, although some important clinical parameters are still missing.4

Prediction models for exacerbations in different COPD patient populations: comparing results of five large data sources

“…Since 2011, a worldwide network of people involved in health economic modeling for COPD (ie, COPD modeling teams, employees of pharmaceutical companies interested in COPD modeling, clinicians, health economists, and epidemiologists) gathered together for three one-day meetings with the aim to discuss and compare the different available COPD models and share best practices about COPD modeling. 13 , 23 In May 2015 participants in this COPD modeling network were contacted to explore their interest in participating in a modeling exercise for the fourth COPD modeling meeting. To participate in this so-called modeling challenge, participants needed to have access to a database with patient-level data with the following characteristics: 1) a minimum of about 500 patients, 2) follow-up of at least 1 year, 3) moderate and severe exacerbations measured, and 4) several demographic and clinical patient characteristics available.…”

“…Accurate and precise estimation of the exacerbation risk in these models is very important because exacerbations are associated with high health care costs and therefore strongly influence the cost outcomes of the models. However, most of the currently available cost-effectiveness models include an exacerbation risk specified by degree of airflow obstruction 13 only and they are not able to distinguish high-risk patients based on other relevant predictors, such as previous exacerbations. 14 Therefore, the focus of the Fourth Annual Meeting of the International COPD Health Economic Modelling Network in 2015 was to develop prediction models for exacerbations including several relevant patient and disease characteristics as predictors.…”

The Future of Precision Medicine: Potential Impacts for Health Technology Assessment

“…For example, multi-parametric testing may lead to secondary findings unrelated to the original test, as well as spill-over effects on family members and future generations [ 48 ]. A number of studies concluded that more research is needed to establish best practice guidelines for modelling precision medicines [ 12 , 33 , 43 , 60 ], while others suggested approaches that could handle complex structures more adequately, such as microsimulation and discrete event simulations [ 12 , 35 , 62 ].…”

Development and Validation of the Evaluation Platform in COPD (EPIC): A Population-Based Outcomes Model of COPD for Canada

“…Recently, a convention of model developers assessed the consistency of 5 different models in COPD and their external validity. 18,50,51 Putting our developed model in the context of previous reference models is informative. Among the previously reviewed models, only the model by Hoogendoorn et al, 19 which was developed for the Netherlands, is a dynamic population model.…”