OBJECTIVE: Cost-effectiveness analyses based on clinical trials, using life-years gained (LYG) or QALY as endpoints require survival estimates, which must account for event patterns and survival during the trial and patient characteristics. METHODS: Using data from Saskatchewan Health, two statistical approaches were developed to estimate the full survival curves applicable to patients in the CURE trial, categorized into: “survived with no further events”, “survived after myocardial infarction (MI)”, “survived after stroke”, “died”. One approach involved fitting four piecewise parametric functions per category to hazards observed in 15,590 patients with index MI (64% male, mean age 69 years, half died during ten-years follow-up). The other was to fit a single equation using fractional polynomials. Time-dependent Cox proportional hazards analyses were used to derive individual risk-adjustment scores. Resulting survival curves were integrated to obtain life expectancy (LE); LYG by avoiding non-fatal events were derived by subtracting event-specific LE from that of no events for each patient type. RESULTS: Patients (24% diabetic; 30% previous MI/stroke; 61% hypertensive) in first nine-months (corresponding to trial), suffered non-fatal MI (5%); non-fatal stroke (1%); 72% event-free. Both types of hazard functions indicate high risk immediately following index MI, dropping sharply with event-free time. Subsequent events renew the risk. Integrating survival curves yields estimates of impact of preventing events: e.g., 65 year-old, diabetic, hypertensive man with no previous events has LE=7.98 years immediately after MI. This increases to 9.4 years if he survives through nine-months with no further events; 3.62 years are lost with second MI, 5.08 years with a stroke. CONCLUSION: These techniques yield detailed survival functions enabling extensive customization to obtain life-years lost for any pattern of events in any given patient. A second event, even if not immediately fatal, further reduces life-expectancy and must be considered in economic analyses.