Patient-Centered Clinical Trial Design for Heart Failure Devices via Bayesian Decision Analysis.

BACKGROUND: The statistical significance of clinical trial outcomes is generally interpreted quantitatively according to the same threshold of 2.5% (in one-sided tests) to control the false-positive rate or type I error, regardless of the burden of disease or patient preferences. The clinical significance of trial outcomes-including patient preferences-are also considered, but through qualitative means that may be challenging to reconcile with the statistical evidence. OBJECTIVE: We aimed to apply Bayesian decision analysis to heart failure device studies to choose an optimal significance threshold that maximizes the expected utility to patients across both the null and alternative hypotheses, thereby allowing clinical significance to be incorporated into statistical decisions either in the trial design stage or in the post-trial interpretation stage. In this context, utility is a measure of how much well-being the approval decision for the treatment provides to the patient. METHODS: We use the results from a discrete-choice experiment study focusing on heart failure patients' preferences, questioning respondents about their willingness to accept therapeutic risks in exchange for quantifiable benefits with alternative hypothetical medical device performance characteristics. These benefit-risk trade-off data allow us to estimate the loss in utility-from the patient perspective-of a false-positive or false-negative pivotal trial result. We compute the Bayesian decision analysis-optimal statistical significance threshold that maximizes the expected utility to heart failure patients for a hypothetical two-arm, fixed-sample, randomized controlled trial. An interactive Excel-based tool is provided that illustrates how the optimal statistical significance threshold changes as a function of patients' preferences for varying rates of false positives and false negatives, and as a function of assumed key parameters. RESULTS: In our baseline analysis, the Bayesian decision analysis-optimal significance threshold for a hypothetical two-arm randomized controlled trial with a fixed sample size of 600 patients per arm was 3.2%, with a statistical power of 83.2%. This result reflects the willingness of heart failure patients to bear additional risks of the investigational device in exchange for its probable benefits. However, for increased device-associated risks and for risk-averse subclasses of heart failure patients, Bayesian decision analysis-optimal significance thresholds may be smaller than 2.5%. CONCLUSIONS: A Bayesian decision analysis is a systematic, transparent, and repeatable process for combining clinical and statistical significance, explicitly incorporating burden of disease and patient preferences into the regulatory decision-making process.

Leveraging Patient Preference Information in Medical Device Clinical Trial Design.

Use of robust, quantitative tools to measure patient perspectives within product development and regulatory review processes offers the opportunity for medical device researchers, regulators, and other stakeholders to evaluate what matters most to patients and support the development of products that can best meet patient needs. The medical device innovation consortium (MDIC) undertook a series of projects, including multiple case studies and expert consultations, to identify approaches for utilizing patient preference information (PPI) to inform clinical trial design in the US regulatory context. Based on these activities, this paper offers a cogent review of considerations and opportunities for researchers seeking to leverage PPI within their clinical trial development programs and highlights future directions to enhance this field. This paper also discusses various approaches for maximizing stakeholder engagement in the process of incorporating PPI into the study design, including identifying novel endpoints and statistical considerations, crosswalking between attributes and endpoints, and applying findings to the population under study. These strategies can help researchers ensure that clinical trials are designed to generate evidence that is useful to decision makers and captures what matters most to patients.

Quantifying Benefit-Risk Preferences for Heart Failure Devices: A Stated-Preference Study.

BACKGROUND: Regulatory and clinical decisions involving health technologies require judgements about relative importance of their expected benefits and risks. We sought to quantify heart-failure patients' acceptance of therapeutic risks in exchange for improved effectiveness with implantable devices. METHODS: Individuals with heart failure recruited from a national web panel or academic medical center completed a web-based discrete-choice experiment survey in which they were randomized to one of 40 blocks of 8 experimentally controlled choice questions comprised of 2 device scenarios and a no-device scenario. Device scenarios offered an additional year of physical functioning equivalent to New York Heart Association class III or a year with improved (ie, class II) symptoms, or both, with 30-day mortality risks ranging from 0% to 15%, in-hospital complication risks ranging from 0% to 40%, and a remote adjustment device feature. Logit-based regression models fit participants' choices as a function of health outcomes, risks and remote adjustment. RESULTS: Latent-class analysis of 613 participants (mean age, 65; 49% female) revealed that two-thirds were best represented by a pro-device, more risk-tolerant class, accepting up to 9% (95% CI, 7%-11%) absolute risk of device-associated mortality for a one-year gain in improved functioning (New York Heart Association class II). Approximately 20% were best represented by a less risk-tolerant class, accepting a maximum device-associated mortality risk of 3% (95% CI, 1%-4%) for the same benefit. The remaining class had strong antidevice preferences, thus maximum-acceptable risk was not calculated. CONCLUSIONS: Quantitative evidence on benefit-risk tradeoffs for implantable heart-failure device profiles may facilitate incorporating patients' views during product development, regulatory decision-making, and clinical practice.

Early Feasibility Studies for Cardiovascular Devices in the United States: JACC State-of-the-Art Review.

The development of technology to treat unmet clinical patient needs in the United States has been an important focus for the U.S. Food and Drug Administration and the 2016 Congressional 21st Century Cures Act. In response, a program of early feasibility studies (EFS) has been developed. One of the important issues has been the outmigration of the development and testing of medical devices from the United States. The EFS committee has developed and implemented processes to address issues to develop strategies for early treatment of these patient groups. Initial implementation of the U.S. Food and Drug Administration EFS program has been successful, but residual significant problems have hindered the opportunity to take full advantage of the program. These include delays in gaining Institutional Review Board approval, timeliness of budget and contractual negotiations, and lack of access to and enrollment of study subjects. This paper reviews improvements that have been made to the U.S. EFS ecosystem and outlines potential approaches to address remaining impediments to program success.

Effects of vibrotactile feedback and grasp interface compliance on perception and control of a sensorized myoelectric hand.

Current myoelectric prosthetic limbs are limited in their ability to provide direct sensory feedback to users, which increases attentional demands and reliance on visual cues. Vibrotactile sensory substitution (VSS), which can be used to provide sensory feedback in a non-invasive manner has demonstrated some improvement in myoelectric hand control. In this work, we developed and tested two VSS configurations: one with a single burst-rate modulated actuator and another with a spatially distributed array of five coin tactors. We performed a direct comparative assessment of these two VSS configurations with able-bodied subjects to investigate sensory perception, myoelectric control of grasp force and hand aperture with a prosthesis, and the effects of interface compliance. Six subjects completed a sensory perception experiment under a stimulation only paradigm; sixteen subjects completed experiments to compare VSS performance on perception and graded myoelectric control during grasp force and hand aperture tasks; and ten subjects completed experiments to investigate the effect of mechanical compliance of the myoelectric hand on the ability to control grasp force. Results indicated that sensory perception of vibrotactile feedback was not different for the two VSS configurations in the absence of active myoelectric control, but it was better with feedback from the coin tactor array than with the single actuator during myoelectric control of grasp force. Graded myoelectric control of grasp force and hand aperture was better with feedback from the coin tactor array than with the single actuator, and myoelectric control of grasp force was improved with a compliant grasp interface. Further investigations with VSS should focus on the use of coin tactor arrays by subjects with amputation in real-world settings and on improving control of grasp force by increasing the mechanical compliance of the hand.

The proprioceptive map of the arm is systematic and stable, but idiosyncratic.

Visual and somatosensory signals participate together in providing an estimate of the hand's spatial location. While the ability of subjects to identify the spatial location of their hand based on visual and proprioceptive signals has previously been characterized, relatively few studies have examined in detail the spatial structure of the proprioceptive map of the arm. Here, we reconstructed and analyzed the spatial structure of the estimation errors that resulted when subjects reported the location of their unseen hand across a 2D horizontal workspace. Hand position estimation was mapped under four conditions: with and without tactile feedback, and with the right and left hands. In the task, we moved each subject's hand to one of 100 targets in the workspace while their eyes were closed. Then, we either a) applied tactile stimulation to the fingertip by allowing the index finger to touch the target or b) as a control, hovered the fingertip 2 cm above the target. After returning the hand to a neutral position, subjects opened their eyes to verbally report where their fingertip had been. We measured and analyzed both the direction and magnitude of the resulting estimation errors. Tactile feedback reduced the magnitude of these estimation errors, but did not change their overall structure. In addition, the spatial structure of these errors was idiosyncratic: each subject had a unique pattern of errors that was stable between hands and over time. Finally, we found that at the population level the magnitude of the estimation errors had a characteristic distribution over the workspace: errors were smallest closer to the body. The stability of estimation errors across conditions and time suggests the brain constructs a proprioceptive map that is reliable, even if it is not necessarily accurate. The idiosyncrasy across subjects emphasizes that each individual constructs a map that is unique to their own experiences.

Haptic interaction of touch and proprioception: implications for neuroprosthetics.

Somatosensation is divided into multiple discrete modalities that we think of separably: e.g., tactile, proprioceptive, and temperature sensation. However, in processes such as haptics,those modalities all interact. If one intended to artificially generate a sensation that could be used for stereognosis, for example, it would be crucial to understand these interactions. We are presently examining the relationship between tactile and proprioceptive modalities in this context. In this overview of some of our recent work, we show that signals that would normally be attributed to two of these systems separately, tactile contact and self-movement, interact both perceptually and physiologically in ways that complicate the understanding of haptic processing. In the first study described here, we show that a tactile illusion on the fingertips, the cutaneous rabbit effect, can be abolished by changing the posture of the fingers. We then discuss activity in primary somatosensory cortical neurons illustrating the interrelationship of tactile and postural signals. In this study, we used a robot-enhanced virtual environment to show that many neurons in primary somatosensory cortex with cutaneous receptive fields encode elements both of tactile contact and self-motion. We then show the results of studies examining the structure of the process which extracts the spatial location of the hand from proprioceptive signals. The structure of the spatial errors in these maps indicates that the proprioceptive-spatial map is stable but individually constructed.These seemingly disparate studies lead us to suggest that tactile sensation is encoded in a 2-D map, but one which undergoes continual dynamic modification by an underlying proprioceptive map. Understanding how the disparate signals that comprise the somatosensory system are processed to produce sensation is an important step in realizing the kind of seamless integration aspired to in neuroprosthetics.