Abstract
BackgroundDespite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy.MethodsWe engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme.ResultsThe majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model’s composite result of quality-adjusted life years.ConclusionsA range of stakeholders provided valuable insights regarding the design of a personalized decision aid program, based upon Markov modeling with individualized model inputs, to provide a patient-centered framework to support for genomic-based treatment decisions for cancer patients. The guidance provided by our stakeholders may be broadly applicable to the communication of genomic test results to patients in a patient-centered fashion that supports effective shared decision-making that represents a spectrum of personal factors such as age, medical comorbidities, and individual priorities and values.
Highlights
Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making
Much of the background information was based upon recent research using Markov decision analysis modeling that demonstrated that treatment choices that maximized length and quality of life for individual patients are dependent upon genomic classifier (GC)-based recurrence risk and risk of mortality from causes other than prostate cancer [17]
Emphasis was placed on the need to address the challenge of explaining quality-adjusted life years (QALYs) – a numerical measure of disease burden that incorporates length and quality of life – in decision aid materials, since the analytic framework of the personalized reports is based upon a Markov modeling approach that using individualized inputs [17]
Summary
Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. Research on the implementation of gene expression profiling for cancer treatment decisions has identified variable levels of understanding among patients, with misperceptions of test validity [4], and concerns among oncologists regarding patients’ understanding of test results [5] This suggests a need for decision aids to support communication of genomic expression profiling test results and informed decision-making. Many of the nearly half of patients with localized prostate cancer who undergo radical prostatectomy (RP) will either develop a biochemical recurrence, in the form of a rising prostate specific antigen (PSA) blood level, or will be considered to be at high risk of recurrence based on adverse pathological features [8,9,10] These men will face treatment decisions regarding the use of adjuvant RT (ART) after RP and/or close biochemical observation with salvage RT (SRT) for PSA recurrence. There is a relative lack of comparative data to evaluate the relative benefits of ART versus SRT, and joint guidelines from the American Urological Association (AUA) and the American Society for Radiation Oncology (ASTRO) recommend that clinicians presents both ART and SRT as reasonable treatment options and counsel patients appropriately for shared decisionmaking [16]
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