Cost-effectiveness analysis in colorectal cancer using a semi-Markov model.
Cost and effectiveness are usually modeled according to one studied event or one health state with parametric or non-parametric methods. In this paper, we propose an original method for assessing total costs while incorporating the dynamics of change in the health status of patients. A semi-Markov model in which the distributions of sojourn times are explicitly defined is developed. The hazard function of sojourn times is modeled by Weibull distributions specific to each transition. A vector of covariates is incorporated into the hazard function of each transition. From a regression model for costs, a cumulative cost function is derived. An estimation of the mean cost per patient in each state defined in the semi-Markov model could thus be made, and this enables us to identify the determinants of direct costs. The results of incremental net benefit (INB) are assessed using the bootstrap method. A cost-effectiveness analysis is performed in order to compare two strategies of follow-up in the colorectal cancer study. Two hundred and forty patients were enrolled in this study. Three health states are defined for patients with curative resection of colorectal cancer: alive without relapse, alive with relapse, and dead. The mean survival is 4.35 and 4.12 years, respectively, in the standard and moderate follow-up groups. We show that mean cost differs significantly by follow-up strategy and Dukes stage. Finally, the INB is assessed and this indicates that neither of the strategies compared was more cost-effective than the other.
Institut Universitaire de Recherche Clinique, Laboratoire de Biostatistique, 641 av. du doyen Gaston Giraud, 34093 Montpellier, France. Castelli@iurc.montp.inserm.fr
Christel
C
Castelli
Christophe
C
Combescure
Yohann
Y
Foucher
Jean-Pierre
JP
Daures
D000368:Aged; D000369:Aged, 80 and over; D015179:Colorectal Neoplasms / Q000191:economics* / Q000534:rehabilitation / Q000601:surgery; D003107:Colorectal Surgery / Q000534:rehabilitation; D003362:Cost-Benefit Analysis / Q000379:methods*; D018450:Disease Progression; D018572:Disease-Free Survival; D005240:Feasibility Studies; D005260:Female; D005500:Follow-Up Studies; D017048:Health Care Costs / Q000706:statistics & numerical data; D006304:Health Status; D006801:Humans; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D009367:Neoplasm Staging; D010548:Personal Health Services / Q000191:economics / Q000706:statistics & numerical data; D011184:Postoperative Period; D011338:Probability Theory; D012008:Recurrence; D012044:Regression Analysis; D015203:Reproducibility of Results