Disease system analysis: basic disease progression models in degenerative disease.
OBJECTIVE
To describe the disease status of degenerative diseases (i.e., type 2 diabetes mellitus, Parkinson's disease) as function of disease process and treatment effects, a family of disease progression models is introduced.


METHODS
Disease progression is described using a progression rate (Rdp) acting on the synthesis or elimination parameters of the indirect response model. Symptomatic effects act as disease-dependent or -independent effects on the synthesis or elimination parameters. Protective drug effects act as disease dependent or -independent effects on Rdp.


RESULTS
Simulations with the ten disease models show distinctly different signature profiles of treatment effects on disease status. Symptomatic effects result in improvement of disease status with a subsequent deterioration. Treatment cessation results in a disease status equal to the situation where treatment had not been applied. Protective effects result in a lasting reduction, or even reversal, of the disease progression rate and the resulting disease status during the treatment period. After cessation of treatment the natural disease course will continue from the disease status at that point.


CONCLUSIONS
Disease system analysis constitutes a scientific basis for the distinction between symptomatic versus protective drug effects in relation to specific disease processes as well as the identification of the exposure-response relationship during the time-course of disease.
Post
Teun M
TM
Leiden Experts on Advanced Pharmacokinetics and Pharmacodynamics, Leiden, The Netherlands.
Freijer
Jan I
JI
DeJongh
Joost
J
Danhof
Meindert
M
D015415:Biomarkers; D002908:Chronic Disease; D003198:Computer Simulation; D018450:Disease Progression; D006706:Homeostasis; D006801:Humans; D008954:Models, Biological; D019636:Neurodegenerative Diseases / Q000175:diagnosis* / Q000188:drug therapy; D020011:Protective Agents / Q000627:therapeutic use
D015415:Biomarkers; D020011:Protective Agents