Prostate-specific antigen doubling time (PSADT) holds great promise for the prediction of cancer characteristics, such as stage and probability of progression before the delivery of definitive therapy [1–4]. Similarly, PSADT appears to have the ability to predict the probability of prostate cancer (PCa) diagnosis, especially after a previously negative biopsy. Moreover, PSADT was shown to predict progression towards lethal PCa phenotypes after radiation or surgery. Finally, PSADT represents one of the most powerful predictors of PCa-specific mortality in men with androgeninsensitive prostate cancer (AIPC) [5]. PSADT calculators are available at several PCa-oriented Web sites, such as the MSKCC site (www.nomograms.org) or the University of Montreal site (www.nomogram.org). The PSADT calculators allow the clinician to define the PSADT value of the individual patient at a given time. This metric showed promise as an independent predictor of cancer outcomes at different stages of the natural history of treated prostate cancer. Unfortunately, the current reports which showcase the value of PSADT might at times be difficult to interpret and even more difficult to implement. The problem relates to different PSADT cut-offs that are suggested as ‘‘ideal’’ predictors of unfavorable outcome. As a result, the clinician might not be able to derive the full benefit of the information contained within this powerful marker. Svatek et al circumvented the problem related to the interpretation of various PSADT cut-offs and integrated PSADT within a prognostic nomogram for men with AIPC [5]. Of all predictors, PSADT was the most informative, and accomplished its prognostic role for prediction of PCa-specific mortality in noncategorized format. Svatek et al demonstrated that this powerful predictor can result in most accurate predictions and can yield the best calibration, when it was combined with three other informative and significant variables [5]. Most importantly, these researchers proved that PSADT can be used to provide individualized predictions, which can be easily interpreted (prognosis expressed as a probability from 0–100% of dying from PCa at different time points) and can be equally easily accessed by patients and/or physicians (www.nomogram.org). Hopefully, more researchers will reexamine their valuable findings and will attempt to integrate PSADT within prognostic models capable of providing evidence-based, individualized prognostic information. Such measures would certainly result in much wider use of PSADT and would possibly improve patient care.