Biochemical Recurrence-Free Conditional Probability After Radical Prostatectomy: A Dynamic Prognosis

Objective To estimate the conditional biochemical recurrence-free probability and to develop a predictive model according to the disease-free interval for men with clinically localized prostate cancer treated with minimally invasive radical prostatectomy. Methods The study population consisted of 3576 consecutive patients who underwent laparoscopic radical prostatectomy and 2619 men treated with robotic radical prostatectomy in the past 15 years at Institute Mutualiste Montsouris, Paris, France. Biochemical recurrence was defined as serum prostate-specific antigen >= 0.2 ng/dL. Univariable and multivariable survival analyses were carried out to identify the prognostic factors for overall free-of-biochemical recurrence probability and conditional survival with respect to the years from surgery without recurrence. A detailed nomogram for the static and dynamic prognosis of biochemical recurrence was developed and internally validated. Results The median follow-up period was 8.49 years (interquartile range 4.01-12.97), and 1148 (19%) patients experienced biochemical recurrence. Significant variables associated with biochemical recurrence in the multivariable model included preoperative prostate-specific antigen, positive surgical margins, extracapsular extension, pathological Gleason >= 4 + 3 and laparoscopic surgery (all P < 0.001). Conditional survival probability decreased with increasing time without biochemical recurrence from surgery. When stratified by prognosis factors, the 5- and 10-year conditional survival improved in all cases, especially in men with worse prognosis factors. The concordance index of the nomogram was 0.705. Conclusions Conditional survival provides relevant information on how prognosis evolves over time. The risk of recurrence decreases with increasing number of years without disease. An easy-to-use nomogram for conditional survival estimates can be useful for patient counseling and also to optimize postoperative follow-up strategies.