October 1, 2021
Advances in precision medicine have given cancer clinicians new evaluative tools to improve individualization of treatments for patients with curable breast cancer. Incorporating these tools into the care continuum gives patients access to cutting-edge, multidisciplinary treatments. Although this development is a positive change in patient care, these treatments introduce patients to a highly complex health information environment, one that is fostered by myriad treatment decisions directed by multiple specialists.1 The timeline for decision-making often triggers powerful reactions to the disease threat.
Although having an accurate understanding about treatment trade-offs is a key component of an informed decision, patient knowledge remains low.2-3 In part, this is because of the complex and often overwhelming nature of the clinical information and treatment decisions the patient must make. Though the powerful role of emotion in decision-making has been well documented,4-6 few interventions have been deployed in the clinical setting to help patients manage these feelings. Research shows that patients may make decisions too quickly and may base decisions on emotions (including worry and anxiety), which also can drive them to select more extensive treatment options.7 In fact, failure to acknowledge emotion in decision-making may lead to suboptimal choices that, though anchored in facts, may be misaligned with the individual’s sense of self.8
FIGURE 1. iCanDecide EMOTIONAL SUPPORT ENHANCEMENT MODULE
Ensuring that patients and physicians can effectively communicate about both information and emotion during treatment decision-making remains an unaddressed gap. In this context, advances in precision medicine cannot optimally improve health without parallel progress in patient-centered communication (PCC). The National Cancer Institute (NCI) identifies key components of PCC as fostering relationships, managing emotions, exchanging information, and enabling patient self-management.9
To improve informed decision-making and prepare patients to make treatment decisions, a University of Michigan, Ann Arbor, team developed the iCanDecide breast cancer treatment decision-making tool (see Figure 1). This interactive, virtual tool is tailored to a patient’s desired amount of involvement and was designed to systematically build the patient knowledge base. The tool was evaluated in a randomized pilot study of 540 patients from 22 community-based surgical practices in four states.10 The study showed promise for improving aspects of decision quality,10 but also revealed the need to enhance high-quality decision tools focused on improving additional key aspects of PCC. The successes and lessons learned from the iCanDecide trial led to the development of the Improving Patient-Centered Communication in Breast Cancer: A RCT (Randomized Control Trial) of a Shared Decision Engagement System (SharES) (A231901CD). This is an Alliance for Clinical Trials in Oncology (Alliance)/American College of Surgeons (ACS) Cancer Care Delivery Research trial, funded by the NCI.9 The SharES trial was activated January 15, 2021, at 25 National Community Oncology Research Program sites. More than 40 surgeons are leading their teams in pursuit of the collective accrual goal of 700 patients.
FIGURE 2. CONCEPTUAL FRAMEWORKS: SUMMARY OF HOW SharES WILL IMPACT PRIMARY AND SECONDARY OUTCOMES
SharES uses two interventions to address key gaps identified in the iCanDecide study. It will test the intervention efficacy by adding an emotional support enhancement module. This module will help patients manage the anxiety and worry associated with a new diagnosis, make treatment decisions, and link the patient experience with the tool to that of their surgeon and clinicians via a clinician dashboard (CDB), so they can circle back to support PCC. A screenshot of some of the components of the enhancement tool is provided in Figure 1.
SharES is based on conceptual and underlying frameworks11,12 that describe the process by which the intervention components will affect key aspects of PCC and the endpoints that will be achieved if successful (see Figure 2).
FIGURE 3. STEPPED-WEDGE CLUSTER TRIAL DESIGN OF SharES (A231901CD)
SharES uses a crossed multilevel trial design in which the patient-level intervention (iCanDecide-ESE versus the original) occurs within a stepped-wedge cluster trial to evaluate the CDB (see Figure 3). Each surgery clinic must enroll at least one surgeon who agrees to use the CDB. The surgeon also may invite advanced practice providers to view the CDB. All participating surgical practices enroll patients into the patient-level intervention regardless of the step to which their practice is randomized to the dashboard.
The key endpoints are knowledge of treatment risks and benefits, patient-reported worry, and self-efficacy to manage worry, and these factors are assessed at five weeks after surgery. Secondary outcomes related to decision appraisal are assessed at five weeks after surgery and nine months after registration.
The Cancer Care Delivery Research Committee of the Alliance/ACS Cancer Research Program (CRP) was developed to lead the expansion of cooperative group research activities to include health services, comparative effectiveness, and patient-centered outcomes research with a focus on community-based research. The ACS CRP works closely with the Commission on Cancer (CoC) and the National Cancer Database to inform design of Alliance clinical trials and engage in comparative effectiveness research activities. The unique co-location of the ACS CRP and the CoC within the ACS provides an opportunity for strong collaboration through the College’s Cancer Programs.
For more information about the SharES study, contact UM-SharES@umich.edu or Sarah Hawley, PhD, MPH, at sarahawl@umich.edu.
Dr. Hawley would like to recognize the contributions of the University of Michigan and Alliance/ACS Cancer Care Delivery Research study team and all the community practices that have SharES trials open; their collaboration and support has been critical to the ongoing success of the SharES study.
The authors also would like to thank the NCI for their funding of this work through grant R01 CA237046.
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