Identification of Preference "Phenotypes" in Men With Prostate Cancer.

INTRODUCTION: Patient preference assessment is key to high-quality decision-making in men with prostate cancer. We aimed to determine if "phenotypes" could be identified among men with prostate cancer, with each phenotype representing a cohort with a distinct combination of preferences. We wished to learn if there was an association between phenotype and treatment selection. METHODS: A prospective cohort of men with prostate cancer received a pre-visit decision aid. This software used conjoint analysis to quantify relative patient preferences for treatment-associated survival, quality of life outcomes, and recovery time. We collected patient clinical data, physician recommendation for active treatment or surveillance, and treatments received. Preferences were analyzed using latent class analysis to identify distinct classes of preference phenotypes. We compared patient characteristics and treatment choice across phenotypes, both univariately and in a multivariable logistic regression. RESULTS: In 250 men who used the decision aid as part of routine care, latent class analysis revealed 3 phenotypic classes. Men in Class 1 had the highest concerns around recovery time and the lowest value on improving lifespan. Men in Class 2 had relatively evenly distributed concerns. Men in Class 3 had the lowest concerns around recovery time and risk of surgical complications. On multivariate analysis, treatment choice was not associated with preference-based phenotype. Only physician recommendation was associated with choice of active treatment. CONCLUSIONS: We identified the existence of 3 patient preference-based phenotypes in men with prostate cancer. Each phenotype had a unique combination of trade-offs when considering competing treatment outcomes. These phenotypes were not associated with treatment. Physician recommendation was the only factor determining treatment choice.

Comparison of Rating Scale, Time Tradeoff, and Conjoint Analysis Methods for Assessment of Preferences in Prostate Cancer.

Background. Conjoint analysis is widely used in studies of consumer preference but has only recently been applied to measure patient utilities for health outcomes. We compared the reliability, feasibility, and internal and predictive validity of conjoint scaling methods against better established rating scale and time tradeoff methods for assessing prostate cancer utilities in men at risk for prostate cancer. Methods. In total, 194 men who were biopsy negative for prostate cancer were randomly assigned to complete 2 preference assessment modules, either conjoint analysis and a rating scale module or conjoint analysis and a time tradeoff module. Each participant's most important attribute was identified and evaluated in relation to age group (age <65, age 65 and older), education (high school, some college, college graduate), race/ethnicity (white, black, Latino), and relationship status (in significant relationship v. not). The methods were also evaluated in terms of ease of use and satisfaction. Results. Rating scales were rated as easiest to use and respondents were more satisfied with rating scales and conjoint in comparison to time tradeoffs. Rating scales and conjoint measures demonstrated significantly higher internal validity compared to time tradeoff when evaluated through R2 of the fitted utility function. The 3 methods were similar in terms of predictive validity, but conjoint analysis outperformed the rating scale method when patients were presented with novel combinations of attribute levels (68% correct v. 43%, P = 0.003). Conclusions. Rating scales and conjoint analysis exercises offer greater ease of use and higher satisfaction when measuring patient preferences in men biopsied for prostate cancer in comparison to time tradeoff exercises. Conjoint analysis may be a more robust approach to preference measurement for men at risk for prostate cancer.

Outcomes of an Integrated Urology-Palliative Care Clinic for Patients With Advanced Urological Cancers: Maintenance of Quality of Life and Satisfaction and High Rate of Hospice Utilization Through End of Life.

INTRODUCTION: Systematic integration of palliative care in a surgical setting is important, but has yet to be achieved. Despite evidence of early palliative care improving patients' quality of life, hospice utilization remains low. Through an integrated palliative care-urology clinic, we aim to assess the effect of early outpatient palliative care on hospice utilization, health-related quality of life (HRQOL) and satisfaction in patients with advanced urological cancers. METHODS: Participants were recruited from 2012 through 2016 in the Greater Los Angeles Veterans Affairs Hospital. We partnered with palliative care clinicians to develop an integrated urology-palliative care clinic, where participants were seen by the palliative care team on the same day as their urological visit. The 12-item Short-Form Survey, Patient Satisfaction Questionnaire Short-Form, Patient Health Questionnaire, and Brief Pain Inventory were administered at initial and subsequent visits. Follow-up questionnaire results were compared between baseline and the 2 follow-up visits, and hospice utilization rates were assessed. RESULTS: Fifty-three participants completed baseline questionnaires. Of those 22 (42%) patients completed at least one follow-up assessment. The median time for the first and second follow-up visits was 2.9 and 7.8 months, respectively. There were no significant differences in HRQOL and satisfaction between baseline and subsequent follow-up visits. A total of 36 (68%) of 53 participants who were enrolled at the start of the study were deceased. Of those, 29 (81%) expired within a home or inpatient hospice. CONCLUSIONS: Rates of hospice use were high in an integrated palliative care-urology model. Health-related quality of life and satisfaction did not worsen over time.

Does Patient Preference Measurement in Decision Aids Improve Decisional Conflict? A Randomized Trial in Men with Prostate Cancer.

BACKGROUND: Shared decision making (SDM) has been advocated as an approach to medical decision making that can improve decisional quality. Decision aids are tools that facilitate SDM in the context of limited physician time; however, many decision aids do not incorporate preference measurement. OBJECTIVES: We aim to understand whether adding preference measurement to a standard patient educational intervention improves decisional quality and is feasible in a busy clinical setting. METHODS: Men with incident localized prostate cancer (n = 122) were recruited from the Greater Los Angeles Veterans Affairs (VA) Medical Center urology clinic, Olive View UCLA Medical Center, and Harbor UCLA Medical Center from January 2011 to May 2015 and randomized to education with a brochure about prostate cancer treatment or software-based preference assessment in addition to the brochure. Men undergoing preference assessment received a report detailing the relative strength of their preferences for treatment outcomes used in review with their doctor. Participants completed instruments measuring decisional conflict, knowledge, SDM, and patient satisfaction with care before and/or after their cancer consultation. RESULTS: Baseline knowledge scores were low (mean 62%). The baseline mean total score on the Decisional Conflict Scale was 2.3 (±0.9), signifying moderate decisional conflict. Men undergoing preference assessment had a significantly larger decrease in decisional conflict total score (p = 0.023) and the Perceived Effective Decision Making subscale (p = 0.003) post consult compared with those receiving education only. Improvements in satisfaction with care, SDM, and knowledge were similar between groups. CONCLUSIONS: Individual-level preference assessment is feasible in the clinic setting. Patients with prostate cancer who undergo preference assessment are more certain about their treatment decisions and report decreased levels of decisional conflict when making these decisions.

Community-Partnered Collaboration to Build an Integrated Palliative Care Clinic: The View From Urology.

BACKGROUND: We partnered with patients, families, and palliative care clinicians to develop an integrated urology-palliative care clinic for patients with metastatic cancer. We assessed clinician satisfaction with a multidisciplinary palliative care clinic model. METHODS: We conducted semi-structured interviews with 18 clinicians who practice in our integrated clinic. We analyzed transcripts using a multistage, cutting-and-sorting technique in an inductive approach based on grounded theory analysis. Finally, we administered a validated physician job satisfaction survey. RESULTS: Clinicians found that referring a patient to palliative care in the urology clinic was feasible and appropriate. Patients were receptive to supportive care, and clinicians perceived that quality of care improved following the intervention. CONCLUSION: An integrated, patient-centered model for individuals with advanced urologic malignancies is feasible and well received by practitioners.

Decisional conflict in economically disadvantaged men with newly diagnosed prostate cancer: baseline results from a shared decision-making trial.

BACKGROUND: Decisional conflict is a source of anxiety and stress for men diagnosed with prostate cancer given uncertainty surrounding myriad treatment options. Few data exist to help clinicians identify which patients are at risk for decisional conflict. The purpose of this study was to examine factors associated with decisional conflict in economically disadvantaged men diagnosed with prostate cancer before any treatment choices were made. METHODS: A total of 70 men were surveyed at a Veterans Administration clinic with newly diagnosed localized prostate cancer enrolled in a randomized trial testing a novel shared decision-making tool. Baseline demographic, clinical, and functional data were collected. Independent variables included age, race, education, comorbidity, relationship status, urinary/sexual dysfunction, and prostate cancer knowledge. Tested outcomes were Decisional Conflict Scale, Uncertainty Subscale, and Perceived Effectiveness Subscale. Multiple linear regression modeling was used to identify factors associated with decisional conflict. RESULTS: Mean age was 63 years, 49% were African American, and 70% reported an income less than $30,000. Poor prostate cancer knowledge was associated with increased decisional conflict and higher uncertainty (P < .001 and P = 0.001, respectively). Poor knowledge was also associated with lower perceived effectiveness (P = 0.003) whereas being in a relationship was associated with higher decisional conflict (P = 0.03). CONCLUSIONS: Decreased patient knowledge about prostate cancer is associated with increased decisional conflict and lower perceived effective decision-making. Interventions to increase comprehension of prostate cancer and its treatments may reduce decisional conflict. Further work is needed to better characterize this relationship and identify effective targeted interventions.