Abstract B053: Factors that influence prostate cancer treatment decisions: A qualitative study among a diverse, population-based sample of men with low-risk prostate cancer in Northern California
Authors: Shariff-Marco Salma , Shim Janet , Allen Laura , Kuo Mei-Chin , Lau Kathie , Golden Todd , Loya Zinnia , Guan Alice , DeRouen Mindy C. , Oh Debora , Lichtensztajn Daphne ,   TAP Study Team, Gomez Scarlett Lin 
Published: September 2020

Background: Most men diagnosed with prostate cancers of low grade and low potential for progression are expected to have comparable survival as other men their age without prostate cancer. Thus, active surveillance (i.e., closely monitoring the course of disease with the expectation to intervene given evidence of cancer progression) is universally recommended as a viable management option for men with these tumors. However, men may not be adequately informed about their treatment options; for example, there is evidence that active surveillance is less frequently discussed with underserved men, such as minorities, those of low socioeconomic status, or those with limited English proficiency. Methods: This study is the first (qualitative) phase of a sequential mixed-methods study to explore factors that influence prostate cancer treatment among a diverse group of men with low risk disease. We conducted 43 in-depth interviews with patients diagnosed within the prior 24 months with low-risk prostate cancer recruited from the Greater Bay Area Cancer Registry (13 Asian Americans, 10 African Americans, 10 Latinos, and 10 Non-Hispanic Whites). Interviews were conducted in English, Spanish, Cantonese, or Mandarin. To date, 38 interviews have been transcribed, and coded in Dedoose using 29 codes. Three study staff reviewed all interview excerpts tagged with each code to identify factors that played a role in patients’ decision-making. These factors were then incorporated into an epidemiologic survey being developed for the second (quantitative) phase of the study. Results: Themes related to treatment decision-making include: concern for and obligation to partner/family, others’ experiences with treatment, clinical factors (grade/stage), health insurance, medical mistrust, cancer-related anxiety, comorbidities, race/ethnicity/culture, and religion/spirituality. We incorporated these themes into the quantitative survey by drafting survey items on: burden on family members, experiences of family/friends with cancer, avoidance of repeated tests, anxiety related to anticipation of test results, preference for immediate action rather than waiting to see whether the cancer progresses, personality and coping preferences, cultural factors (e.g., stigma regarding cancer, norms/expectations regarding manhood), and life stage and lifestyle. Most of these items have not been included in prior surveys of prostate cancer treatment decision-making. Conclusions: We identified many novel factors influencing treatment decisions among a diverse group of prostate cancer patients in the Greater San Francisco Bay Area, illustrating how a mixed-method approach can be used to augment knowledge regarding treatment decision-making in diverse populations. Ongoing quantitative work will examine the importance of these factors among a larger study population. This work will assist providers to better support patients with low risk prostate cancer as they go through the treatment decision-making process.

Citation Format: Salma Shariff-Marco, Janet Shim, Laura Allen, Mei-Chin Kuo, Kathie Lau, Todd Golden, Zinnia Loya, Alice Guan, Mindy C. DeRouen, Debora Oh, Daphne Lichtensztajn, TAP Study Team, Scarlett Lin Gomez. Factors that influence prostate cancer treatment decisions: A qualitative study among a diverse, population-based sample of men with low-risk prostate cancer in Northern California [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr B053.