Physicians often fail to communicate important details about key risks and benefits of treatment in prostate cancer consultations, an information gap that may inhibit effective patient participation in care decisions. We developed a framework to assess detail and personalization of physician communication of key concepts, derived from observations of treatment consultations.
We recorded and transcribed treatment consultations of 50 men with newly diagnosed prostate cancer across 10 multidisciplinary providers. Using open coding, analysts identified statements related to guideline-endorsed SDM concepts and categorized the level of detail for each topic. Concept-specific hierarchies indicating increasing detail were integrated into a unified framework. We reported the highest observed level for each concept across consultations.
Across 19,388 statements, sentences addressing cancer severity (1,016; 5.2%), baseline function (186; 1.0%), oncologic endpoints (343; 1.8%), cancer prognosis (318; 1.6%), life expectancy (111; 0.57%), and treatment-related side effects (952; 4.9%) were extracted. Empirically derived frameworks for evaluating the level of detail and personalization for each concept consistently displayed parallel levels of detail. We created a unified framework, with each level providing more precise, patient-specific risk communication: (0) omission, (1) no quantification, (2) binary assessment, (3) imprecise quantification, (4) specific quantification, and (5) patient-specific estimate. The prevalence of the highest observed level of detail and personalization conveyed varied by concept, ranging from 4% to 84%, 0% to 47%, 0% to 42%, 2% to 8%, 0% to 48%, and 0% to 66% for levels 0 to 5, respectively.
Our framework introduces an empirically derived, structured foundation for characterizing the level of detail and personalization of physician risk communication of key concepts in prostate cancer consultations.
Medical decision making : an international journal of the Society for Medical Decision Making. 2026 Jul 16 [Epub ahead of print]
Alexander Hernandez-Tirado, Renning Zheng, Michael Luu, Nadine A Friedrich, Paul Kokorowski, Judy Tan, Timothy J Daskivich
Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA., School of Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China., Department of Biostatistics, Cedars-Sinai Medical Center, Los Angeles, CA, USA., Center for Health Equity Research, Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, CA, USA.