Genetics Adviser: Evaluating a Digital Decision Support Tool for Genetic Results

Official Title

Genetics Adviser: Evaluating a Digital Decision Support Tool for Genetic Results


Oncologists are increasingly using genomic sequencing to diagnose and optimize care for their patients. A consequence of this technology is its capacity to detect a patient's risk for thousands of current and future conditions or diseases. Guidelines recommend doctors allow patients to choose which results they wish to receive before ordering the test. It is not feasible to counsel patients on the thousands of possible results because of the limited clinical resources and genomics expertise. Decision aids (DAs) can fill this gap, however there are no DAs to guide patients' decisions about results from genomic sequencing. A DA prototype was developed (, the first DA of its kind. This study will transform the DA prototype into an interactive, adaptable and patient-centred digital decision support tool (Genetics ADvISER) via user-centred design methods. The objective of this study is to evaluate the effectiveness of Genetics ADvISER in an RCT with patients being offered results from genomic sequencing. Results of this trial will be used to establish whether the Genetics ADvISER is effective to use in practice. This could fill a critical clinical care gap, improve health outcomes and service use by reducing counselling burden as well as overuse, underuse and misuse - concerns of policy makers seeking to address the triple aims of health care.

Trial Description

Primary Outcome:

  • Decisional Conflict Scale (DCS)
Secondary Outcome:
  • Knowledge
  • Satisfaction with Decision Scale (SWD)
  • Preparation for Decision Making scale (PrepDM)
  • State-Trait Anxiety Inventory
  • Hospital Anxiety and Depression Scale (HADS)
  • Acceptability
  • Time
BACKGROUND: Genomic sequencing (GS) is a driver of precision oncology. Oncologists are increasingly using tumour GS for precision oncology care, which is often times accompanied by germline GS on normal control tissue. One complex feature of this technology is its capacity to generate incidental findings (IF). Guidelines recommend doctors inform patients of their incidental GS results. Yet there are limited tools to communicate the scope and implications of the thousands incidental results available to help guide patients' decisions about which results they wish to learn. RATIONALE: There are limited decision support tools in genetics. Despite the long-standing practice of medical genetics, there are relatively few decision support tools for genetic testing and very few that have been rigorously evaluated. Even fewer decision support tools exist on possible results from genomic sequencing; existing tools target pediatric contexts, focus on genomic sequencing education-only or on the return of results; they do not cover all possible results with decision support to simulate genetic counselling, limiting their use and applicability in clinical care. Thus, there are no decision support tools to guide patients about all results available from genomic sequencing. OBJECTIVES:
Evaluate the effectiveness of the Genetics ADvISER vs standard genetic counseling (GC) with patients receiving incidental findings. HYPOTHESIS: Use of the Genetics ADvISER will reduce patients' decisional conflict & anxiety, improve patient knowledge, satisfaction with decisions and preparedness for decision-making when selecting IF compared to GC alone. PHASE 1: RCT to evaluate the Decision Aid Methods: This is a mixed method, non-blinded randomized controlled superiority trial. We will evaluate whether use of the Genetics ADvISER followed by Genetic Counsellor (GC) reduces decisional conflict compared to GC alone in a RCT. As a part of this trial, patients will receive results from exome sequencing. Study population: Adult cancer patients who have had GS for their cancer (but did not receive incidental findings) or adult patients who have had a negative genetic panel test and may eligible for GS. Sample: The primary outcome is decisional conflict; the study requires 64 patients/arm (128 total) to detect the minimal clinically important difference (MCID) of 0.3 using the Decisional Conflict Scale (DCS), assuming a standard deviation of 0.6, an alpha of 0.05 (two-sided) and power of 0.8. Participants will be consecutively randomized and allocated from an existing list of eligible subjects using a computer-generated randomization in a 1:1 ratio with random permuted blocks of varying sizes. Patients from each clinic will be randomized separately to ensure we have an even distribution of this population in both arms of the study. Intervention: Participants in the intervention arm will use the Genetics ADviSER to learn about GS, select which results they would like to receive and to receive their GS results. Control: Participants in the control arm will speak with a genetic counsellor to learn about GS, select which results they would like to receive and to receive their GS results. Outcomes and measures: The primary outcome is decisional conflict, assessed via the validated Decisional Conflict Scale (DCS) consistent with the ODSF. Secondary outcomes: Knowledge, measured using an established questionnaire assessing benefits and limitations of genome sequencing and a set of internally developed knowledge questions on IF; Satisfaction with decision-making, measured using the Satisfaction with Decision scale and the Preparation for Decision Making scale; Anxiety, measured using the state subscale of the State-Trait Anxiety Inventory. All sessions will be recorded to assess the length of GC sessions. Quantitative Analysis: The analysis of outcomes will follow the intention-to-treat approach. Mean scores for decisional conflict, satisfaction with and preparation for decision-making, knowledge of IF and GC session length will be compared using a t-test. Anxiety, knowledge of sequencing benefits and sequencing limitations scores will be assessed by summing the number of correct responses to the questions, and compared adjusting for baseline score using analysis of covariance (ANCOVA). The primary time points of comparison will be (T1) for the control versus (T2) for the intervention group. Secondary exploratory analyses will examine the impact that the decision aid had alone (T1), without the addition of follow-up GC at T2 and at T3, after participants have received their IF on decision conflict, knowledge, anxiety, satisfaction and preparation with decision-making. Descriptive statistics will be used to describe participants' demographic characteristics (age, sex, education, etc.). PHASE 2: Qualitative study This study will explore the utility the of the Genetics ADvISER and incidental results via qualitative interviews with participants. After the study is completed, a subset set of participants (n = 40) will be selected to participate qualitative portion of the study. Participants approached to complete the qualitative portion of the study will determined by purposeful sampling, in order to get mix of participants across a range of experiences and demographic characteristics. Qualitative Analysis: The qualitative analyses will draw on grounded theory. Open coding, constant comparison and axial coding will be used to identify common and divergent themes to characterize the entire dataset. Interviews will consider participants' socio-demographic factors that may influence their informational and decisional needs as well as how they engage with genetic information and participate in shared decision making. Two researchers will code transcripts independently; consensus on codes will be reached through discussion. Validation methods may include triangulation and member checking. In keeping with qualitative methodology, data analysis will occur in conjunction with data collection. On-going analysis will inform the development of progressive iterations of the interview guides.

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