Disease Progression Modeling: Key Concepts and Recent Developments

Abstract

Disease modeling involves the use of mathematical functions to describe quantitatively the time course of disease progression. In order to characterize the natural progression of disease, these models generally incorporate longitudinal data for some biomarker(s) of disease severity or can incorporate more direct measures of disease severity. Disease models are also often linked to pharmacokinetic–pharmacodynamic models so that the influence of drug treatment on disease progression can be quantified and evaluated. Regulatory agencies have embraced disease progression models as powerful tools that can be used to improve drug development productivity. This article provides a brief overview of key concepts in disease progression modeling followed by illustrative examples from models for Alzheimer’s disease. Finally, recent novel applications in which disease progression models have been linked to cost-effectiveness analysis and genomic analysis are described.

Disease Progression Modeling Analysis of the Change of Bone Mineral Density by Postoperative Hormone Therapies in Postmenopausal Patients With Early Breast Cancer

“…We used first‐order conditional estimation with INTERACTION in NONMEM subroutines ADVAN6. In this study we implemented empirical models used in previous studies for a disease progression model . Because BMD decreases with age, a first‐order deterioration model was used as the base model.…”

“…We applied tamoxifen and AI to the base model using a disease‐modifying model and a symptomatic model. A symptomatic effect model is defined when a drug effect provides a transient bad effect by offsetting the severity of the disease during drug use, and a disease‐modifying model is defined when a drug affects the disease progression rate …”

“…In this study we implemented empirical models used in previous studies for a disease progression model. 7 Because BMD decreases with age, a firstorder deterioration model was used as the base model. The base model is described by the following equation:…”

“…A symptomatic effect model is defined when a drug effect provides a transient bad effect by offsetting the severity of the disease during drug use, and a disease-modifying model is defined when a drug affects the disease progression rate. 8 The base structures of symptomatic model (2) and disease-modifying model (3) tested in this study are as follows:…”

Using medical claims database to develop a population disease progression model for leuprorelin-treated subjects with hormone-sensitive prostate cancer

“…Quantitative population-based disease progression modeling uses mathematical functions and statistical models to describe quantitatively the time course of disease progression in individuals and the entire patient population with or without drug treatment [13,14]. This modeling approach can trace disease progression over time, and quantify the effects of drug treatment and disease-and patient-specific factors on disease progression to optimize clinical trial design and guide personalized treatment strategies [13]. For example, quantitative disease progression modeling has been applied to clinical data to allow estimation of tumor growth and regression rates in metastatic castration-resistant PCa [14].…”