A multicenter prospective cohort study, including 512 patients for whom date of HIV infection was known, showed that the use of an appropriate auxiliary event can improve the analysis of survival data and lead to an earlier detection of risk factors for HIV patients. Age at seroconversion and primary symptomatic infection were used as risk factors. Two age groups were defined as age at seroconversion >30 years (n = 203) and < or = 30 years (n = 309). Patients with primary symptomatic infection PSI (n = 215) were compared with patients without any clinical manifestation during primary infection (n = 297). Death was considered as the endpoint of primary interest and occurred in 76 patients in the study. Classical non-parametric methods (Kaplan-Meier estimate and long-rank test) and parametric regression model (Weibull model) were used for a standard analysis of survival data. A parametric approach using auxiliary information was used to estimate the survival function and to test the effect of age at seroconversion and PSI. We also applied a recently proposed distribution-free method to produce a non-parametric estimate of the survival function and to test age at seroconversion and PSI with respect to survival estimates. Both methods are compared for two distinct auxiliary events (Karnofsky score below 75 and a first drop of CD4 lymphocyte counts below 200 cells/MM3). The use of CD4 lymphocyte counts below 200 cells/MM3 as an auxiliary event improved the analysis of survival data available in December 1994. For both methods incorporating CD4 counts below 200 cells/mm3 in addition to survival data, the effect of age at seroconversion on survival was significant in April 1992 whereas it was not significant with standard methods. For PSI exposure group, results shown in this work do not indicate any improvement in using auxiliary information. Conditions for using an appropriate auxiliary event as well as advantages and shortcomings of both methods are discussed. Methods used in this work, with appropriate auxiliary information, are promising either through a reduction in the time to follow-up to detect risk factors for cohort studies or the time needed for drug development in clinical trials.