Purpose: Determine the best method to help patients understand their preferences and apply information about risks and benefits to a high-stakes decision about prostate cancer treatment. Methods: We created a computer-based interactive decision aid (DA) to help men participate in decisions about treatment choice for localized prostate cancer, which is common among men over the age of 50. Localized prostate cancer usually is asymptomatic and is detected through routine screening. The most commonly used treatments are radical prostatectomy (RP) and radiation therapy (RT). However, because the cancer often grows slowly, a strategy of no initial active treatment is a reasonable alternative for some men. In this case, active surveillance (monitoring for signs of tumor growth; also known as watchful waiting) is undertaken. The DA includes evidence on survival and treatment-related harms for watchful waiting, RP, and RT. All evidence was derived from a comparative effectiveness review published by the Agency for Healthcare Research and Quality in 2008. The DA helps users estimate their preferences about each of three important harms (erectile dysfunction, urinary incontinence, and bowel problems). Using a method based on the analytic hierarchy process, the user of the DA then revises these preference estimates after reviewing data about rates of the three harms among men who were treated with RP or RT. The DA provides feedback on these preferences to facilitate the patient’s discussion with providers on the choice and priorities of a treatment. We conducted individual structured interviews with prostate cancer survivors. In these interviews, the men reviewed successive drafts of the DA and described their understanding and intent to use the included information. Result: In this Resources for Research session, we will demonstrate the decision aid and discuss the strategies for helping users understand evidence and formulate their preferences. We will review the process used to refine the decision aid with each set of interviews. Conclusion: The iterative process of interviewing and refining proved effective for creating a user-friendly decision aid that helped patients understand their preferences. The tactic of testing the decision aid with men who had already made prostate cancer decisions helped in designing a decision aid that safely addressed emotionally-packed aspects of a preference-setting activity.
Candidate for the Lee B. Lusted Student Prize Competition