Let’s pretend that you are a prostate cancer patient whose doctor, a well-known robotic surgeon, recommends robotic-assisted radical prostatectomy (RRP). He makes some very persuasive points:
- Based on the Partin tables you have less than a 12% chance of biochemical recurrence (rising PSA) in three years after treatment.
- He’ll “get it all out” and you won’t have to worry about it anymore.
- Since your cancer is only on one side, he can do nerve-sparing RRP on the opposite side.
- 95% of his patients are fully continent in less than 3 months after treatment.
- 90% of his patients return to baseline ED in 6-18 months, especially with his penile rehabilitation program.
- You’ll be back to work in less than 2 weeks, and full activity in 4-6 weeks.
- 90% of his patients are still cancer-free at 5 years.
This all sounds pretty safe, and you are leaning toward RRP.
But one thing bothers you: how accurate is that Partin table prediction? A little research tells you that Partin table is a nomogram, or risk calculation based on a set of scales, and it is the urological basis for predicting the probability of recurrence. How can you find out if that <12% chance of recurrence is reasonably correct? You’d feel better if there was some way to confirm it. You might be interested in a new study published in the Journal of Magnetic Resonance Imaging about a nomogram based on multiparametric MRI (mpMRI) before prostatectomy.[i] A team of Chinese radiologists published a study to evaluate the predictive performance of a nomogram they generated based on specific prostate tumor characteristics clearly detected by MRI, including
- Tumor location
- Tumor diameter
- Diffusion weighted imaging results (apparent diffusion coefficients or ADCs)
- PI-RADS v2 score (see my PI-RADS blog at https://sperlingprostatecenter.com/pi-rads-score/)
- Dynamic contrast-enhanced MRI
- MR T-stage
In order to achieve their purpose, they retrospectively evaluated the clinical records of 205 patients who each underwent mpMRI before having a prostatectomy. Patients were treated between 2009 and 2013, and follow up consisted of regular PSA tests during the first 3 years after RP. Treatment failure was defined as a PSA greater than 0.2 ng/mL after prostatectomy. For this study population the rate of biochemical recurrence within 3 years was 25.4%. Retrospective analysis of patient pre-treatment clinical factors allowed correlation-based analysis of the MRI features with the cases that failed and those that did not, allowing the researchers to create their MRI-bases nomogram. They compared how well their nomogram performed versus the D’Amico risk classification system and the CAPRA (Cancer of the Prostate Risk Assessment) scheme.
The authors found that the MRI nomogram offered better predictive performance than both the D’Amico classification and CAPRA. However, adding the MRI nomogram to the D’Amico stratification system significantly improved its performance. The authors concluded, “Multiparametric MRI, when converted into a prognostic nomogram, can predict the clinical outcome in patients with PCa after prostatectomy.”
[i] Zhang YD, Wu CJ, Bao ML, Li H et al. MR-based prognostic nomogram for prostate cancer after radical prostatectomy. J Magn Reson Imaging. 2016 Sep 21. doi: 10.1002/jmri.25441. [Epub ahead of print]
About Dr. Dan Sperling
Dan Sperling, MD, DABR, is a board certified radiologist who is globally recognized as a leader in multiparametric MRI for the detection and diagnosis of a range of disease conditions. As Medical Director of the Sperling Prostate Center, Sperling Medical Group and Sperling Neurosurgery Associates, he and his team are on the leading edge of significant change in medical practice. He is the co-author of the new patient book Redefining Prostate Cancer, and is a contributing author on over 25 published studies. For more information, contact the Sperling Prostate Center.
