The Cost-Effectiveness of Preventing AIDS Complications (CEPAC) model is a computer-based, state-transition, Monte Carlo simulation model of the progression and outcomes of HIV disease.
A state transition model characterizes each patient’s progression as a sequence of monthly transitions from one “health state” to another. A “Monte Carlo” simulation uses a random number generator and probability distributions to generate one unique, hypothetical patient at a time; it then draws from a set of transition probabilities to determine the occurrence of clinical events and health state transitions experienced by that patient.
At the outset of any simulation, the initial cohort size and characteristics are defined, including distributions of age, sex, HIV prevalence, CD4 count (a measure of immunologic function), and HIV RNA (a measure of HIV viral load, which influences immunologic decline). Also defined are probability distributions for various clinical events such as opportunistic infection and entrance to or dropping out of care for different patient health states.
Health states are descriptive of the patient’s current health, relevant history, quality of life, and resource utilization patterns. They are designed to be predictive of clinical prognosis, including disease progression, immunologic deterioration, development and relapse of opportunistic infections, medication toxicity, response to antiretroviral therapy (ART), and mortality.
The model defines four general categories of HIV health states:
- Primary infection
- Chronic infection
- Acute event
Patients usually reside in the chronic state, where immunologic deterioration occurs. Successful treatment with ART reverses this decline. Patients who develop an acute event (either an opportunistic infection or medication toxicity) temporarily move to an acute health state, where resource consumption and mortality rates increase while quality of life decreases.
While death may occur in any health state, mortality rates from a given health state are based upon acute event history, CD4 cell count, as well as age-, gender-, and race-specific non-HIV causes.
The model uses a 1-month cycle length to reflect a realistic duration in which important HIV-associated events occur. Clinical events (e.g., acute opportunistic infections) and health-state transitions (e.g., changes in CD4 count or HIV RNA levels) are governed by probabilities estimated from clinical trials and epidemiologic datasets.
From the distributions of demographic and clinical data, each patient’s clinical course is tracked from entry into the model until death. A running tally is maintained of all clinical events and of the cumulative cost and health-related quality of life (or “utility”) associated with the months in each health state. This process is repeated until the entire cohort has passed through the model, at which point overall outcome measures such as average survival, quality-adjusted life expectancy, and per-patient cost are computed.
A more detailed look at the CEPAC model can be found in the following PDFs: