How Primary Care Providers Talk to Patients about Genome Sequencing Results: Risk, Rationale, and Recommendation

Abstract

Background: Genomics will play an increasingly prominent role in clinical medicine.

Objective: To describe how primary care physicians (PCPs) discuss and make clinical recommendations about genome sequencing results.

Design: Qualitative analysis.

Participants: PCPs and their generally healthy patients undergoing genome sequencing.

Approach: Patients received clinical genome reports that included four categories of results: monogenic disease risk variants (if present), carrier status, five pharmacogenetics results, and polygenic risk estimates for eight cardiometabolic traits. Patients' office visits with their PCPs were audio-recorded, and summative content analysis was used to describe how PCPs discussed genomic results.

Key results: For each genomic result discussed in 48 PCP-patient visits, we identified a "take-home" message (recommendation), categorized as continuing current management, further treatment, further evaluation, behavior change, remembering for future care, or sharing with family members. We analyzed how PCPs came to each recommendation by identifying 1) how they described the risk or importance of the given result and 2) the rationale they gave for translating that risk into a specific recommendation. Quantitative analysis showed that continuing current management was the most commonly coded recommendation across results overall (492/749, 66%) and for each individual result type except monogenic disease risk results. Pharmacogenetics was the most common result type to prompt a recommendation to remember for future care (94/119, 79%); carrier status was the most common type prompting a recommendation to share with family members (45/54, 83%); and polygenic results were the most common type prompting a behavior change recommendation (55/58, 95%). One-fifth of recommendation codes associated with monogenic results were for further evaluation (6/24, 25%). Rationales for these recommendations included patient context, family context, and scientific/clinical limitations of sequencing.

Conclusions: PCPs distinguish substantive differences among categories of genome sequencing results and use clinical judgment to justify continuing current management in generally healthy patients with genomic results.

Keywords: genome sequencing; medical decision-making; physician communication.

Conflict of interest statement

Dr. Ubel is a consultant for Humana. Dr. Green receives compensation for speaking or consultation from AIA, GenePeeks, Helix, Illumina, Ohana, Prudential, and Veritas, and is co-founder, advisor, and equity holder in Genome Medical, Inc. The other authors declare that they do not have a conflict of interest.

Figures

Figure 1

Conceptual framework for summative content analysis of PCP-patient discussions about genome sequencing results. For each result discussed, one or more take-home messages, or recommendations, were identified. The discussion about each recommendation was further coded by the type of result (e.g. monogenic disease risk, carrier status, polygenic risk, or pharmacogenetic result), the risk the PCP ascribed to that result, and the rationale(s) given for the recommendation.

Figure 2

Proportions of codes in three distinct dimensions in 48 physician discussions about genome sequencing results: risk (or for pharmacogenetic results, importance), rationale, and recommendation. Codes are stratified into the five possible types of results, as shown in the legend. For some results, more than one rationale or recommendation code was identified. LP, likely pathogenic; P, pathogenic; VUS, variant of uncertain significance.

Figure 3

Sankey diagram mapping the combinations of risk/importance, rationale, and recommendation codes in physician discussions about genome sequencing results, presented by type of result. Percentages indicate the proportions of individual qualitative codes within each axis (risk/importance, rationale, and recommendation). The width of each pathway corresponds to the proportion of a given code combination (for example, a polygenic result described as uncertain risk, prompting a recommendation to continue current management, with no rationale given), relative to the total number of code combinations.