Monday, October 20, 2014: 10:45 AM

Jingyu Zhang, PhD1, Pavan Dadlani, PDEng2, Jente de Pee, MSc2 and Chris H. Bagma, MD3, (1)Philips Research North America, Briarcliff Manor, NY, (2)Philips Research, Eindhoven, Netherlands, (3)Erasmus MC, Rotterdam, Netherlands
Purpose: Prostate cancer is the most common solid tumor in American and western European men. Most of the new diagnoses are localized prostate cancers. Primary treatment options such as radical prostatectomy (RP), external beam radiation therapy (EBRT), brachytherapy (BT), and active surveillance (AS) have comparable survival outcomes and various degrees of side effects. The best treatment option could be different from patient to patient depending on patient’s disease profile including age, tumor stage, Gleason score, pre-existing symptoms, and comorbidities, and patient’s own preferences on how to tradeoff longer survival and quality-of-life (QoL) impact after treatment. We developed a decision support system to facilitate share decision making and help choosing primary treatment option for localized prostate cancer patients. The system takes into account the patient’s disease profile, matching evidences from literature, and patient’s preferences on side effects. This paper focuses on how patients’ primary treatment choices shift with different preferences on QoL tradeoffs.

Method: A Markovian model is utilized to estimate survival and quality adjusted life years (QALYs) for different treatments. Stochastic sensitivity analysis is done to obtain confidence intervals of the estimates. Since the confidence intervals for different treatments could overlap for most of the patients, we estimate the probability of being the best treatment option for each treatment. We simulate newly-diagnosed patients to get population-based results.

Result: Our initial computational experiments focus on patients’ preferences about erectile dysfunction. Assuming other side effects has no QoL impact on patients, when erectile dysfunction doesn’t matter to the patients (QALY decrement is 0), more than 99% of the simulated patients’ best choice is RP or EBRT. When QALY decrement for erectile dysfunction increases to 0.2 QALYs each year, 47% of the simulated patient’s best choice is AS, while 12%, 21%, and 20% should choose RP, EBRT, and BT, respectively.

Conclusion: Patients’ preferences on QoL tradeoffs about side effects after treatment is could significantly shift their choice of primary treatment. Therefore, it is very important to help patients understand their own preferences during the shared decision making process for localized prostate cancer patients. Further experiments are needed to uncover how other side effects and their combinations could shift patient’s treatment choices.