“The ultimate risk:” How clinicians assess the value and meaning of genetic data in cardiology

Introduction

Genetic testing is becoming a routine part of clinical care in the United States. One of the main goals of clinical genetic testing is to identify genetic predisposition to disease so that providers and patients can intervene earlier in the course of a disease and prevent future harm. But there is still considerable disagreement among providers about how to properly introduce genetic testing into clinical care. Providers are seeking to determine when genetic data will be useful for their patients, and when genetic data may either be irrelevant or lead to worse outcomes for patients. In this paper, I explore how clinicians navigate the tension between identifying real disease risks for their patients with concerns about overdiagnosis and overtreatment. I find that providers disagree about many aspects of clinical genetic testing, including: how much genetic data should be collected, whether to trust genetic information from commercial laboratories, how to interpret genetic information, and how to use genetic information to guide future interventions. I find that the collection of genetic information can serve both to increase and decrease uncertainty about medical risks. I focus on clinicians ordering genetic testing for inherited cardiovascular diseases. Of the genes determined to be “clinically actionable” by the American College of Medical Genetics and Genomics (ACMG), half are related to cardiovascular diseases. ¹ While debates about the utility of genetic testing are occurring in all areas of clinical genetics, they are perhaps most salient in cardiovascular genetics.

This case is important for medical ethicists because it helps theorize how medical fields are shifting their evaluation of the boundaries of responsible data collection and intervention. Medical institutions collect data about their patient populations at least in part because they hope this data can improve patient care. Clinicians and medical researchers often argue that more and better data on a given subject will make it easier to assess when and what kinds of clinical interventions are appropriate. A large literature has explored how medicine can make use of new data sources, and can embrace the turn towards big data and precision medicine. ² At the same time, many social scientists have questioned the implementation of big data in medicine. ³ Science and technology studies scholars have shown, for example, that new clinical or research data can have tremendous interpretive flexibility. ⁴ Epstein and others have shown that new health data and clinical evidence often propel controversies rather than settle them. ⁵ There is some evidence that the movement towards collecting less data is growing in medicine broadly. In 2012, a new initiative from the American Board of Internal Medicine called Choosing Wisely, in collaboration with professional medical societies, started publishing lists of “tests, treatments, or services that are commonly used in that specialty and for which the use should be reevaluated by patients and clinicians”. ⁶ The recommendations suggest that physicians should stop performing some screening tests on average-risk patients, and seem to indicate growing acceptance that more medical care and data collection is not an inherently good thing. The number of medical societies participating in Choosing Wisely has grown from nine to seventy over the past five years, and the initiative has been cited in nearly 300 journal articles and 10,000 popular media articles. ⁷ Calls for the collection of less medical data are surprising given prior theories of biomedicalization, ⁸ and deserve more attention from medical ethicists. Thus, this paper explores how clinicians make judgements about the value and utility of genetic data collection without presuming that more data is ethically or epistemically preferable.

Methods

The data for this study come primarily from semi-structured, in-depth interviews with twenty cardiologists, clinical geneticists, and genetic counselors across the United States. Potential participants were identified from cardiovascular genetics clinic websites, personal contacts in the field, and snowball sampling. All participants were employed by large academic medical centers, which is where the majority of cardiovascular genetic testing occurs. Interviews lasted approximately 30 minutes, and each participant was asked a series of questions about their views on genetic testing in cardiology and to describe interesting cases from their practice. Interviews were professionally transcribed and then coded using NVivo 12 software. Using a grounded theory approach, I developed an initial codebook based on the themes identified while conducting the interviews. I worked with a colleague to collectively code five interviews and reach agreement about relevant themes in an iterative process. After reaching consensus, I coded the other fifteen interviews myself. In addition to collecting interview data, I spent approximately 30 hours shadowing a variety of clinicians as they saw patients with existing or suspected inherited cardiovascular conditions. Finally, I conducted literature searches in PubMed to identify research articles and clinical case reports related to genetic testing in cardiology. This protocol was approved by the IRB at the University of Pennsylvania.

Background

In cardiology, genetic tests are used to diagnose a range of diseases and to screen individuals who may be at risk of developing future cardiovascular disease. One of the main goals of testing is to identify people at higher risk of sudden death from cardiac arrest. Inherited cardiomyopathies and arrhythmic diseases are a major cause of cardiac morbidity and mortality, especially in young people.⁸ Patients with Long QT syndrome, an inherited heart rhythm disorder, have a six to eight percent risk of sudden death before the age of forty.⁹ Another inherited cardiovascular condition called Brugada Syndrome is responsible for around four to twelve percent of all unexpected sudden deaths and for up to twenty percent of all sudden deaths in individuals with an apparently normal heart. ¹⁰ Because of the severe consequences of these cardiovascular conditions, many patients and providers are eager to utilize genetic testing to help prevent sudden cardiac death in predisposed individuals. As one cardiologist I interviewed said, bluntly:

If a genetic test indicates that a patient has an increased risk of sudden death, there are a few available interventions. First, patients can be monitored more closely through regularly-scheduled echocardiograms and/or electrocardiograms (EKGs). Providers may also suggest prescription medications such as beta blockers. Most dramatically, some providers may recommend patients receive an implantable defibrillator (ICD), which can send a shock to a patient’s heart if they seem to be entering cardiac arrest. In my interviews, providers had varying opinions about how burdensome ICDs can be for patients. Some strongly emphasized the downsides: shocks from an ICD are painful and may happen unnecessarily, ICDs can get infected, and the devices often need to be replaced. Other providers said that the devices went mostly unnoticed by their patients. No matter how burdensome these devices may be, providers agreed that it would be ideal to only implant an ICD in patients where the risk of sudden death is higher than the risk of infection and other side effects of the device. Unfortunately, these risks are difficult to predict. As this paper will later demonstrate, providers have conflicting views on when the placement of an ICD is an appropriate way to manage future health risks.

There are two main factors that help clinicians and laboratories assess whether a patient has an increased risk of harm from an inherited heart condition: the classification of the genetic variant, and the penetrance of the gene/disease pair. If a test result shows that a patient has a variant in a gene known to cause a particular disease, there are five standardized ways that variant can be classified: Pathogenic, Likely Pathogenic, Variant of Uncertain Significance, Likely Benign, and Benign. Laboratories and clinicians make these determinations based on both biological and clinical evidence. But, laboratories and physicians often disagree regarding the classification of genetic variants, despite guidelines from professional organizations. Providers also disagree about how results, particularly variants of uncertain significance, should be used to drive clinical decision-making.

The second main factor used to assess risk of sudden death from an inherited cardiovascular condition is the penetrance of the gene/disease pair. Penetrance refers to the proportion of people with a given variant (genotype) that express an associated health problem (phenotype). Cardiovascular conditions do not have full penetrance, meaning that some people with a pathogenic variant will not go on to experience symptoms of disease. Estimates of penetrance are debated and range widely, with most inherited cardiovascular conditions deemed low to moderate penetrance. ¹¹

Changing guidelines for variant classification and changing estimates of penetrance can make it difficult for providers to assess what a genetic test result means for their patients. The providers I spoke with rely more heavily on physical symptoms of disease than genetic testing to make risk decisions. For patients with existing heart problems, genetic testing may not affect their clinical care at all. Patients with thickened heart muscle or an arrhythmia will already be monitored or put on medication regardless of their genetic diagnosis. As one cardiologist noted:

I can manage your family without genetics…the role of genetics is to help us refine the management of you and your family … [and for] cascade screening and that kind of stuff. – Cardiologist

Results

I focus on three areas where clinicians make judgements about the value and utility of genetic information in cardiology. First, clinicians must decide how much genetic information to collect. Should they sequence a few genes that seem related to a patient’s phenotype? Or should they order a gene panel that would sequence dozens of genes? Second, clinicians must decide how much to trust the information provided in the report from a genetic testing laboratory. Do they trust how the laboratory summarizes or interprets the data they have provided? Finally, clinicians must decide how to properly communicate about genetic information with patients and their families.

Discussion

This research demonstrates that clinical geneticists, cardiologists, and genetic counselors face high levels of uncertainty regarding genetic testing in cardiology in three main categories. First, they hold different philosophies about what types of genetic tests to order, with some preferring large panels and others preferring narrow testing. Second, they often do not trust commercial laboratories to provide accurate interpretations of genomic data, preferring to perform their own secondary analyses. Third, they have different approaches to communicating about test results with patients, particularly surrounding variants of uncertain significance.

Most notably, some providers are so concerned about inappropriate treatment that they prefer to collect the least amount of genetic data as possible. While many providers currently preferred to collect less genetic data, they were hopeful that this data could be useful in the future as more clinical trials were conducted. As clinical evidence grows, they expect to see a similar decrease in the amount of uncertainty surrounding the interpretation of test results. But waiting for clinical research to solve the problem of uncertainty may ultimately lead to disappointment. Previous social science literature has argued that new clinical trials and medical experiments often propel controversies rather than settle them. ¹⁷ In addition to collecting clinical evidence when necessary, providers and researchers should also be engaging in discussions about how to evaluate the utility of medical information [some of these conversations are already happening, especially when researchers discuss the “actionability” of genetic and genomic testing. ¹⁸ ]. These are not just scientific conversations. Scientific ideas about knowledge and evidence are inevitably coproduced with social and cultural ideas about what medical care ought to be. ¹⁹

There is a long-standing tradition of accepting an individual’s right not to know their own medical information. ²⁰ I find, however, that clinical genetics providers are not just suggesting that patients have a right not to know their medical information, but that they sometimes have a moral obligation not to collect information in the first place. This positive reframing of ignorance suggests that knowledge doesn’t always carry a moral or epistemic superiority over non-knowledge. Finally, my research suggests that clinicians have variable ways of understanding and dealing with uncertainty in clinical genomics. These variations deserve further attention and empirical research because they could have a real impact on the types of care patients receive. And, further research on how the field of clinical genomics manages the uncertainty surrounding genomic data could be useful for many medical fields trying to assess the value of new data sources. As the amount of data available to medical providers and patients grows exponentially, it will continue to be important for medical ethicists to engage in debates about the utility of data collection.