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INTRODUCTION: Despite decades of research on risk-communication approaches, questions remain about the optimal methods for conveying risks for different outcomes across multiple time points, which can be necessary in applications such as discrete choice experiments (DCEs). We sought to compare the effects of 3 design factors: 1) separated versus integrated presentations of the risks for different outcomes, 2) use or omission of icon arrays, and 3) vertical versus horizontal orientation of the time dimension. METHODS: We conducted a randomized study among a demographically diverse sample of 2,242 US adults recruited from an online panel (mean age 59.8 y, s = 10.4 y; 21.9% African American) that compared risk-communication approaches that varied in the 3 factors noted above. The primary outcome was the number of correct responses to 12 multiple-choice questions asking survey respondents to identify specific numbers, contrast options to recognize dominance (larger v. smaller risks), and compute differences. We used linear regression to test the effects of the 3 design factors, controlling for health literacy, graph literacy, and numeracy. We also measured choice consistency in a subsequent DCE choice module. RESULTS: Mean comprehension varied significantly across versions (P < 0.001), with higher comprehension in the 3 versions that provided separated risk information for each risk. In the multivariable regression, separated risk presentation was associated with 0.58 more correct responses (P < 0.001; 95% confidence interval: 0.39, 0.77) compared with integrated risk information. Neither providing icon arrays nor using vertical versus horizontal time formats affected comprehension rates, although participant understanding did correlate with DCE choice consistency. CONCLUSIONS: In presentations of multiple risks over multiple time points, presenting risk information separately for each health outcome appears to increase understanding. HIGHLIGHTS: When conveying information about risks of different outcomes at multiple time points, separate presentations of single-outcome risks resulted in higher comprehension than presentations that combined risk information for different outcomes.We also observed benefits of presenting single-outcome risks separately among respondents with lower numeracy and graph literacy.Study participants who scored higher on risk understanding were more internally consistent in their responses to a discrete choice experiment.
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BACKGROUND: Transcatheter edge-to-edge repair (TEER) of mitral regurgitation is less invasive than surgery but has greater 5-year mortality and reintervention risks, and leads to smaller improvements in physical functioning. The study objective was to quantify patient preferences for risk-benefit trade-offs associated with TEER and surgery. METHODS AND RESULTS: A discrete choice experiment survey was administered to patients with mitral regurgitation. Attributes included procedure type; 30-day mortality risk; 5-year mortality risk and physical functioning for 5 years; number of hospitalizations in the next 5 years; and risk of additional surgery in the next 5 years. A mixed-logit regression model was fit to estimate preference weights. Two hundred one individuals completed the survey: 63% were female and mean age was 74 years. On average, respondents preferred TEER over surgery. To undergo a less invasive procedure (ie, TEER), respondents would accept up to a 13.3% (95% CI, 8.7%-18.5%) increase in reintervention risk above a baseline of 10%, 4.6 (95% CI, 3.1-6.2) more hospitalizations above a baseline of 1, a 10.7% (95% CI, 6.5%-14.5%) increase in 5-year mortality risk above a baseline of 20%, or more limited physical functioning representing nearly 1 New York Heart Association class (0.7 [95% CI, 0.4-1.1]) over 5 years. CONCLUSIONS: Patients in general preferred TEER over surgery. When holding constant all other factors, a functional improvement from New York Heart Association class III to class I maintained over 5 years would be needed, on average, for patients to prefer surgery over TEER.
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Cardiac Surgical Procedures , Heart Valve Prosthesis Implantation , Mitral Valve Insufficiency , Humans , Female , Aged , Male , Mitral Valve/surgery , Mitral Valve Insufficiency/surgery , Patient Preference , Cardiac Surgical Procedures/adverse effects , Hospitalization , Treatment Outcome , Heart Valve Prosthesis Implantation/adverse effectsABSTRACT
Following the conceptualization of a well-formulated and relevant research question, selection of an appropriate stated-preference method, and related methodological issues, researchers are tasked with developing a survey instrument. A major goal of designing a stated-preference survey for health applications is to elicit high-quality data that reflect thoughtful responses from well-informed respondents. Achieving this goal requires researchers to design engaging surveys that maximize response rates, minimize hypothetical bias, and collect all the necessary information needed to answer the research question. Designing such a survey requires researchers to make numerous interrelated decisions that build upon the decision context, selection of attributes, and experimental design. Such decisions include considering the setting(s) and study population in which the survey will be administered, the format and mode of administration, and types of contextual information to collect. Development of a survey is an interactive process in which feedback from respondents should be collected and documented through qualitative pre-test interviews and pilot testing. This paper describes important issues to consider across all major steps required to design and test a stated-choice survey to elicit patient preferences for health preference research.
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OBJECTIVE: In this study, we aimed to develop education to assist BRCA mutation carriers in making informed decisions about HRT in the context of risk-reducing surgery, while simultaneously clarifying their treatment-specific values and reducing decisional conflict. METHODS: We enrolled premenopausal BRCA mutation carriers ages 19-49 without prior cancer or risk-reducing salpingo-oophorectomy to structured interviews in which they reviewed education about the risks and benefits of HRT. Materials included literature-derived data demonstrating associations between HRT and commonly considered health outcomes (breast cancer, vasomotor symptoms, sexual functioning, cardiovascular disease, osteoporosis, and blood clots). Participants completed the 16-item Decisional Conflict Scale (DCS) before and after education, communicated their preferences by rating and ranking the six outcomes, and provided feedback to inform iterative revisions of the educational content. RESULTS: 25 participants completed interviews. DCS scores decreased significantly from 54.6 to 22.8 following education (p < 0.001); sub-scores for uncertainty (71.7 to 37.3), informed (71.7 to 15.3), values clarity (53.7 to 17.0), effective decision (44.2 to 25.5), and support (35.0 to 17.7) also decreased significantly. Participants ranked cardiovascular disease as the most important outcome to consider, followed by breast cancer, osteoporosis, blood clots, decline in sexual function, and hot flashes. Participants with prior mastectomy (N = 10) ranked breast cancer as the most important outcome 25% of the time, compared to 80% in participants without mastectomy (N = 15). CONCLUSION: Following education, BRCA mutation carriers had significantly less decisional conflict regarding the choice to use HRT. This pilot study was successful in generating a prototype educational aid for further testing.
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Breast Neoplasms , Cardiovascular Diseases , Osteoporosis , Ovarian Neoplasms , Thrombosis , Female , Humans , Breast Neoplasms/genetics , Breast Neoplasms/surgery , Pilot Projects , Mastectomy , Hormone Replacement Therapy , Ovarian Neoplasms/genetics , Ovarian Neoplasms/prevention & control , Ovarian Neoplasms/surgery , Thrombosis/surgery , Patient-Centered Care , Mutation , OvariectomyABSTRACT
Background The REHAB-HF (Rehabilitation Therapy in Older Acute Heart Failure Patients) randomized trial demonstrated that a 3-month transitional, tailored, progressive, multidomain physical rehabilitation intervention improves physical function, frailty, depression, and health-related quality of life among older adults with acute decompensated heart failure. Whether there is differential intervention efficacy by race is unknown. Methods and Results In this prespecified analysis, differential intervention effects by race were explored at 3 months for physical function (Short Physical Performance Battery [primary outcome], 6-Minute Walk Distance), cognition, depression, frailty, health-related quality of life (Kansas City Cardiomyopathy Questionnaire, EuroQoL 5-Dimension-5-Level Questionnaire) and at 6 months for hospitalizations and death. Significance level for interactions was P≤0.1. Participants (N=337, 97% of trial population) self-identified in near equal proportions as either Black (48%) or White (52%). The Short Physical Performance Battery intervention effect size was large, with values of 1.3 (95% CI, 0.4-2.1; P=0.003]) and 1.6 (95% CI, 0.8-2.4; P<0.001) in Black and White participants, respectively, and without significant interaction by race (P=0.56). Beneficial effects were also demonstrated in 6-Minute Walk Distance, gait speed, and health-related quality of life scores without significant interactions by race. There was an association between intervention and reduced all-cause rehospitalizations in White participants (rate ratio, 0.73 [95% CI, 0.55-0.98]; P=0.034) that appears attenuated in Black participants (rate ratio, 1.06 [95% CI, 0.81-1.41]; P=0.66; interaction P=0.067). Conclusions The intervention produced similarly large improvements in physical function and health-related quality of life in both older Black and White patients with acute decompensated heart failure. A future study powered to determine how the intervention impacts clinical events is required. REGISTRATION URL: https://www.clinicaltrials.gov. Identifier: NCT02196038.
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Frailty , Heart Failure , Humans , Aged , Quality of Life , Hospitalization , Patient ReadmissionABSTRACT
Objective of this study is to quantify benefit-risk tradeoffs pertaining to potential gene therapies among adults and parents/caregivers of children with sickle cell disease (SCD). A discrete-choice experiment survey was developed in which respondents selected their preferred treatment alternatives in a series of experimentally controlled pairs of hypothetical gene therapies and a "no gene therapy" option. Gene therapy alternatives were defined based on the chance of eliminating SCD symptoms, expected increases in life expectancy they could offer, treatment-related risk of death, and potential increases in lifetime cancer risk. Respondents made selections based on their current disease severity and in the context of expectations of worsened disease. Three clinical sites and 1 patient organization recruited 174 adult patients and 109 parents of children with SCD to complete the survey. Adult and parent respondents were generally willing to choose gene therapies, but the adults required higher expected levels of efficacy (ie, higher chance of eliminating symptoms) than parents to choose gene therapies that conferred mortality risks of ≥10%. When adults and parents of children with less severe symptoms were asked to consider scenarios of higher levels of disease severity, the increased risk tolerance, and the lowest acceptable level of efficacy for gene therapies with mortality risks dropped by >50%. Baseline SCD symptoms are a major driver of gene therapy acceptability. Adults and parents of patients with milder symptoms may prefer other treatment options; however, an expectation of symptoms deterioration triggers strong reassessment of the acceptable benefit-risk balance of this novel technology.
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Anemia, Sickle Cell , Adult , Child , Humans , Anemia, Sickle Cell/genetics , Anemia, Sickle Cell/therapy , Risk Assessment , Parents , Surveys and Questionnaires , Genetic Therapy/adverse effectsABSTRACT
PURPOSE: Several novel therapies for castration-resistant prostate cancer (CRPC) have been approved with randomized phase III studies with continuing observational research either planned or ongoing. Accurately identifying patients with CRPC in electronic health care data is critical for quality observational research, resource allocation, and quality improvement. Previous work in this area has relied on either structured laboratory results and medication data or natural language processing (NLP) methods. However, a computable phenotype using both structured data and NLP identifies these patients with more accuracy. METHODS: The Corporate Data Warehouse (CDW) of the Veterans Health Administration (VHA) was used to collect PCa diagnoses, prostate-specific antigen test results, and information regarding patient characteristics and medication use. The final system used for validation and subsequent analysis combined the NLP system and an algorithm of structured laboratory and medication data to identify patients as being diagnosed with CRPC. Patients with both a documented diagnosis of CRPC and a documented diagnosis of metastatic PCa were classified as having mCRPC by this system. RESULTS: Among 1.2 million veterans with PCa, the International Classification of Diseases (ICD)-10 diagnosis code for CRPC (Z19.2) identifies 3,791 patients from 2016 when the code was created until 2022, compared with the combined algorithm which identifies 14,103, 10,312 more than ICD-10 codes alone, from 2016 to 2022. The combined algorithm showed a sensitivity of 97.9% and a specificity of 99.2%. CONCLUSION: ICD-10 codes proved to be insufficient for capturing CRPC in the VHA CDW data. Using both structured and unstructured data identified more than double the number of patients compared with ICD-10 codes alone. Application of this combined approach drastically improved identification of real-world patients and enables high-quality observational research in mCRPC.
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Prostatic Neoplasms, Castration-Resistant , Male , Humans , Prostatic Neoplasms, Castration-Resistant/therapy , Prostatic Neoplasms, Castration-Resistant/drug therapy , Natural Language ProcessingABSTRACT
BACKGROUND: Many patients with advanced cancer describe pain as a debilitating symptom that greatly interferes with daily activities and enjoyment of life. Psychosocial interventions can improve cancer-related pain but rarely address spiritual concerns (e.g., loss of meaning, peace), which can influence the pain experience for those facing life-threatening illness. To address these needs, we systematically developed and pilot tested a novel psychosocial intervention called Meaning-Centered Pain Coping Skills Training (MCPC). In this randomized controlled trial, we aim to determine MCPC's efficacy for reducing pain interference (primary outcome) and improving secondary outcomes. We will also estimate MCPC's cost-effectiveness. METHOD/DESIGN: Patients (target N = 210) with advanced solid tumor malignancies (Stage IV) and clinically-elevated pain interference will be enrolled and block randomized with equal allocation to MCPC + enhanced usual care or enhanced usual care alone. MCPC's four, videoconferenced, 45-60 min weekly sessions will be individually delivered by trained study therapists. Primary (pain interference) and secondary (pain severity, anxiety and depressive symptoms, pain self-efficacy, social support, spiritual well-being) patient-reported outcomes will be assessed at baseline, and 8-weeks (primary endpoint) and 12-weeks after baseline. CONCLUSION: Our MCPC intervention is the first to systematically address the biopsychosocial-spiritual aspects of pain in patients with advanced cancer. If MCPC demonstrates efficacy, next steps will involve hybrid efficacy-effectiveness and implementation work to broaden access to this brief, manualized, remotely-delivered intervention, with the goal of reducing suffering in patients with life-threatening illness.
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Neoplasms , Quality of Life , Humans , Neoplasms/complications , Neoplasms/therapy , Neoplasms/pathology , Pain , Anxiety/etiology , Anxiety/therapy , Adaptation, Psychological , Randomized Controlled Trials as TopicABSTRACT
Importance: Up to 40% of women experience dissatisfaction after breast reconstruction due to unexpected outcomes that are poorly aligned with personal preferences. Identifying what attributes patients value when considering surgery could improve shared decision-making. Adaptive choice-based conjoint (ACBC) analysis can elicit individual-level treatment preferences. Objectives: To identify which attributes of breast reconstruction are most important to women considering surgery and to describe how these attributes differ by those who prefer flap vs implant reconstruction. Design, Setting, and Participants: This web-based, cross-sectional study was conducted from March 1, 2022, to January 31, 2023, at Duke University and between June 1 and December 31, 2022, through the Love Research Army with ACBC analysis. Participants were 105 women at Duke University with a new diagnosis of or genetic predisposition to breast cancer who were considering mastectomy with reconstruction and 301 women with a history of breast cancer or a genetic predisposition as identified through the Love Research Army registry. Main Outcomes and Measures: Relative importance scores, part-worth utility values, and maximum acceptable risks were estimated. Results: Overall, 406 women (105 from Duke University [mean (SD) age, 46.3 (10.5) years] and 301 from the Love Research Army registry [mean (SD) age, 59.2 (11.9) years]) participated. The attribute considered most important was the risk of abdominal morbidity (mean [SD] relative importance [RI], 28% [11%]), followed by chance of major complications (RI, 25% [10%]), number of additional operations (RI, 23% [12%]), appearance of the breasts (RI, 13% [12%]), and recovery time (RI, 11% [7%]). Most participants (344 [85%]) preferred implant-based reconstruction; these participants cared most about abdominal morbidity (mean [SD] RI, 30% [11%]), followed by the risk of complications (mean [SD], RI, 26% [11%]) and additional operations (mean [SD] RI, 21% [12%]). In contrast, participants who preferred flap reconstruction cared most about additional operations (mean [SD] RI, 31% [15%]), appearance of the breasts (mean [SD] RI, 27% [16%]), and risk of complications (mean [SD] RI, 18% [6%]). Factors independently associated with choosing flap reconstruction included being married (odds ratio [OR], 2.30 [95% CI, 1.04-5.08]; P = .04) and higher educational level (college education; OR, 2.43 [95% CI, 1.01-5.86]; P = .048), while having an income level of greater than $75â¯000 was associated with a decreased likelihood of choosing the flap profile (OR, 0.45 [95% CI, 0.21-0.97]; P = .01). Respondents who preferred flap appearance were willing to accept a mean (SD) increase of 14.9% (2.2%) chance of abdominal morbidity (n = 113) or 6.4% (4.8%) chance of complications (n = 115). Conclusions and Relevance: This study provides information on how women value different aspects of their care when making decisions for breast reconstruction. Future studies should assess how decision aids that elicit individual-level preferences can help tailor patient-physician discussions to focus preoperative counseling on factors that matter most to each patient and ultimately improve patient-centered care.
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Breast Neoplasms , Mammaplasty , Female , Humans , Middle Aged , Mastectomy/psychology , Breast Neoplasms/surgery , Breast Neoplasms/psychology , Patient Preference , Cross-Sectional Studies , Mammaplasty/psychology , Genetic Predisposition to DiseaseABSTRACT
BACKGROUND: Digital therapeutics are patient-facing digital health interventions that can significantly alter the health care landscape. Despite digital therapeutics being used to successfully treat a range of conditions, their uptake in health systems remains limited. Understanding the full spectrum of uptake factors is essential to identify ways in which policy makers and providers can facilitate the adoption of effective digital therapeutics within a health system, as well as the steps developers can take to assist in the deployment of products. OBJECTIVE: In this review, we aimed to map the most frequently discussed factors that determine the integration of digital therapeutics into health systems and practical use of digital therapeutics by patients and professionals. METHODS: A scoping review was conducted in MEDLINE, Web of Science, Cochrane Database of Systematic Reviews, and Google Scholar. Relevant data were extracted and synthesized using a thematic analysis. RESULTS: We identified 35,541 academic and 221 gray literature reports, with 244 (0.69%) included in the review, covering 35 countries. Overall, 85 factors that can impact the uptake of digital therapeutics were extracted and pooled into 5 categories: policy and system, patient characteristics, properties of digital therapeutics, characteristics of health professionals, and outcomes. The need for a regulatory framework for digital therapeutics was the most stated factor at the policy level. Demographic characteristics formed the most iterated patient-related factor, whereas digital literacy was considered the most important factor for health professionals. Among the properties of digital therapeutics, their interoperability across the broader health system was most emphasized. Finally, the ability to expand access to health care was the most frequently stated outcome measure. CONCLUSIONS: The map of factors developed in this review offers a multistakeholder approach to recognizing the uptake factors of digital therapeutics in the health care pathway and provides an analytical tool for policy makers to assess their health system's readiness for digital therapeutics.
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Delivery of Health Care , Telemedicine , Humans , Databases, Factual , Health Personnel , Therapeutics , Delivery of Health Care/trendsABSTRACT
Pain coping skills training (PCST) is efficacious in patients with cancer, but clinical access is limited. To inform implementation, as a secondary outcome, we estimated the cost-effectiveness of 8 dosing strategies of PCST evaluated in a sequential multiple assignment randomized trial among women with breast cancer and pain (N = 327). Women were randomized to initial doses and re-randomized to subsequent doses based on their initial response (ie, ≥30% pain reduction). A decision-analytic model was designed to incorporate costs and benefits associated with 8 different PCST dosing strategies. In the primary analysis, costs were limited to resources required to deliver PCST. Quality-adjusted life-years (QALYs) were modeled based on utility weights measured with the EuroQol-5 dimension 5-level at 4 assessments over 10 months. A probabilistic sensitivity analysis was performed to account for parameter uncertainty. Implementation of PCST initiated with the 5-session protocol was more costly ($693-853) than strategies initiated with the 1-session protocol ($288-496). QALYs for strategies beginning with the 5-session protocol were greater than for strategies beginning with the 1-session protocol. With the goal of implementing PCST as part of comprehensive cancer treatment and with willingness-to-pay thresholds ranging beyond $20,000 per QALY, the strategy most likely to provide the greatest number of QALYs at an acceptable cost was a 1-session PCST protocol followed by either 5 maintenance telephone calls for responders or 5 sessions of PCST for nonresponders. A PCST program with 1 initial session and subsequent dosing based on response provides good value and improved outcomes. PERSPECTIVE: This article presents the results of a cost analysis of the delivery of PCST, a nonpharmacological intervention, to women with breast cancer and pain. Results could potentially provide important cost-related information to health care providers and systems on the use of an efficacious and accessible nonmedication strategy for pain management. TRIALS REGISTRATION: ClinicalTrials.gov: NCT02791646, registered 6/2/2016.
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Breast Neoplasms , Cost-Effectiveness Analysis , Humans , Female , Breast Neoplasms/complications , Adaptation, Psychological , Pain , Pain Management/methodsABSTRACT
While the quality-adjusted life-year construct has advantages of simplicity and consistency, simplicity requires strong assumptions. In particular, standard assumptions result in health-state utility functions that are unrealistically linear and separable in risk and duration. Consequently, sequencing of a series of health improvements has no effect on the total value of the sequence because each increment is assessed independently of previous increments. Utility functions in nearly all other areas of applied economics are assumed to be nonlinear with diminishing marginal utility so it matters where an improvement occurs in a sequence. We construct a conceptual framework that that demonstrates how diminishing marginal utility for health improvements could affect preferences for different sequence patterns. Using this framework, we derive conditions for which the sum of conventional health-state utilities understates, overstates, or approximates the sequence-sensitive value of health improvements. These patterns suggest the direction and magnitude of possible adjustments to conventional value calculations. We provide numerical examples and identify recent studies whose results are consistent with the conceptual model.
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Models, Statistical , Humans , Quality-Adjusted Life YearsABSTRACT
INTRODUCTION: In 2016, the Department of Veterans Affairs (VA) and Prostate Cancer Foundation (PCF) began a partnership to improve access to testing. The primary objective of this analysis was to describe the use of tumor testing and treatment patterns in Veterans who progressed to metastatic castration-resistant prostate cancer (mCRPC) from 2016 to 2021. Secondary objectives including identifying factors associated with receipt of tumor testing, and reporting HRR mutation results among a subset who were tested. METHODS AND MATERIALS: Natural language processing algorithms were applied to VA electronic health record data to identify a nationwide cohort of veterans with mCRPC. Tumor testing over time and by region were reported, alongside first-, second-, and third-line treatment patterns. Factors associated with receipt of tumor testing were identified using generalized linear mixed models with binomial distributions and logit links to account for clustering by VA facility. RESULTS: Of the 9,852 veterans analyzed, 1,972 (20%) received tumor testing, with 73% of testing occurring in 2020-2021. Factors associated with tumor testing included younger age, later diagnosis year, being treated in the Midwest, or Puerto Rico or other compared to the South, and being treated at a PCF-VA Center of Excellence. Fifteen percent of tests were positive for a pathogenic HRR mutation. Seventy-six percent of the study cohort received first-line treatment, and among those, a subsequent 52% received second-line treatment. A subsequent 46% received third-line treatment. CONCLUSION: After the VA-PCF partnership, one-fifth of veterans with mCRPC received tumor testing, with most tests occurring in 2020-2021.
Subject(s)
Prostatic Neoplasms, Castration-Resistant , Veterans , Male , Humans , Prostatic Neoplasms, Castration-Resistant/diagnosis , Prostatic Neoplasms, Castration-Resistant/genetics , Prostatic Neoplasms, Castration-Resistant/therapy , Retrospective StudiesABSTRACT
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.
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Heart Failure , Humans , Bayes Theorem , Clinical Trials as Topic , Heart Failure/therapy , Decision Support Techniques , Patient-Centered CareABSTRACT
ABSTRACT: Behavioral pain management interventions are efficacious for reducing pain in patients with cancer. However, optimal dosing of behavioral pain interventions for pain reduction is unknown, and this hinders routine clinical use. A Sequential Multiple Assignment Randomized Trial (SMART) was used to evaluate whether varying doses of Pain Coping Skills Training (PCST) and response-based dose adaptation can improve pain management in women with breast cancer. Participants (N = 327) had stage I-IIIC breast cancer and a worst pain score of > 5/10. Pain severity (a priori primary outcome) was assessed before initial randomization (1:1 allocation) to PCST-Full (5 sessions) or PCST-Brief (1 session) and 5 to 8 weeks later. Responders ( > 30% pain reduction) were rerandomized to a maintenance dose or no dose and nonresponders (<30% pain reduction) to an increased or maintenance dose. Pain severity was assessed again 5 to 8 weeks later (assessment 3) and 6 months later (assessment 4). As hypothesized, PCST-Full resulted in greater mean percent pain reduction than PCST-Brief (M [SD] = -28.5% [39.6%] vs M [SD]= -14.8% [71.8%]; P = 0.041). At assessment 3 after second dosing, all intervention sequences evidenced pain reduction from assessment 1 with no differences between sequences. At assessment 4, all sequences evidenced pain reduction from assessment 1 with differences between sequences ( P = 0.027). Participants initially receiving PCST-Full had greater pain reduction at assessment 4 ( P = 0.056). Varying PCST doses led to pain reduction over time. Intervention sequences demonstrating the most durable decreases in pain reduction included PCST-Full. Pain Coping Skills Training with intervention adjustment based on response can produce sustainable pain reduction.
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Breast Neoplasms , Cancer Pain , Humans , Female , Cancer Pain/drug therapy , Adaptation, Psychological , Behavior Therapy/methods , PainABSTRACT
Background and Objectives. Risk-tolerance measures from patient-preference studies typically focus on individual adverse events. We recently introduced an approach that extends maximum acceptable risk (MAR) calculations to simultaneous maximum acceptable risk thresholds (SMART) for multiple treatment-related risks. We extend these methods to include the computation and display of confidence intervals and apply the approach to 3 published discrete-choice experiments to evaluate its utility to inform regulatory decisions. Methods. We generate MAR estimates and SMART curves and compare them with trial-based benefit-risk profiles of select treatments for depression, psoriasis, and thyroid cancer. Results. In the depression study, SMART curves with 70% to 95% confidence intervals portray which combinations of 2 adverse events would be considered acceptable. In the psoriasis example, the asymmetric confidence intervals for the SMART curve indicate that relying on independent MARs versus SMART curves when there are nonlinear preferences can lead to decisions that could expose patients to greater risks than they would accept. The thyroid cancer application shows an example in which the clinical incidence of each of 3 adverse events is lower than the single-event MARs for the expected treatment benefit, yet the collective risk profile surpasses acceptable levels when considered jointly. Limitations. Nonrandom sample of studies. Conclusions. When evaluating conventional MARs in which the observed incidences are near the estimated MARs or where preferences demonstrate diminishing marginal disutility of risk, conventional MAR estimates will overstate risk acceptance, which could lead to misinformed decisions, potentially placing patients at greater risk of adverse events than they would accept. Implications. The SMART method, herein extended to include confidence intervals, provides a reproducible, transparent evidence-based approach to enable decision makers to use data from discrete-choice experiments to account for multiple adverse events. Highlights: Estimates of maximum acceptable risk (MAR) for a defined treatment benefit can be useful to inform regulatory decisions; however, the conventional metric considers one adverse event at a time.This article applies a new approach known as SMART (simultaneous maximum acceptable risk thresholds) that accounts for multiple adverse events to 3 published discrete-choice experiments.Findings reveal that conventional MARs could lead decision makers to accept a treatment based on individual risks that would not be acceptable if multiple risks are considered simultaneously.
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BACKGROUND: Hearing loss significantly impacts health-related quality of life (QoL), yet the effects of current treatments on QoL utility remain uncertain. Our objective was to describe the impact of untreated and treated hearing loss on QoL utility to inform hearing healthcare policy. METHODS: We searched databases for articles published through 02/01/2021. Two independent reviewers screened for articles that reported elicitation of general QoL utility values for untreated and treated hearing loss health states. We extracted data and quality indicators from 62 studies that met the inclusion criteria. RESULTS: Included studies predominately used observational pre/post designs (61%), evaluated unilateral cochlear implantation (65%), administered the Health Utilities Index 3 (HUI3; 71%), and were conducted in Europe and North America (84%). In general, treatment of hearing loss improved post-treatment QoL utility when measured by most methods except the Euro-QoL 5 dimension (EQ-5D). In meta-analysis, hearing aids for adult mild-to-moderate hearing loss compared to no treatment significantly improved HUI3-estimated QoL utility (3 studies; mean change=0.11; 95% confidence interval (CI): 0.07 to 0.14) but did not impact EQ-5D-estimated QoL (3 studies; mean change=0.0; 95% CI: -0.03 to 0.04). Cochlear implants improved adult QoL utility 1-year post-implantation when measured by the HUI3 (7 studies; mean change=0.17; 95% CI: 0.11 to 0.23); however, pediatric VAS-estimated QoL utility was non-significant (4 studies; mean change=0.12; 95% CI: -0.02 to 0.25). The quality of included studies was limited by failure to report missingness of data and low survey response rates. Our study was limited by heterogeneous study populations and designs. FINDINGS: Treatment of hearing loss significantly improves QoL utility, and the HUI3 and VAS were most sensitive to improvements in hearing. Improved access to hearing healthcare should be prioritized. SYSTEMATIC REVIEW REGISTRATION: PROSPERO: CRD42021253314.
Subject(s)
Cochlear Implantation , Cochlear Implants , Hearing Loss , Adult , Humans , Child , Quality of LifeABSTRACT
BACKGROUND: While clinical practice guidelines underscore the need to incorporate patient preferences in clinical decision making, incorporating meaningful assessment of patient preferences in clinical encounters is challenging. Structured approaches that combine quantitative patient preferences and clinical evidence could facilitate effective patient-provider communication and more patient-centric health care decisions. Adaptive conjoint or stated-preference approaches can identify individual preference parameters, but they can require a relatively large number of choice questions or simplifying assumptions about the error with which preferences are elicited. METHOD: We propose an approach to efficiently diagnose preferences of patients for outcomes of treatment alternatives by leveraging prior information on patient preferences to generate adaptive choice questions to identify a patient's proximity to known preference phenotypes. This information can be used for measuring sensitivity and specificity, much like any other diagnostic procedure. We simulated responses with varying levels of choice errors for hypothetical patients with specific preference profiles to measure sensitivity and specificity of a 2-question preference diagnostic. RESULTS: We identified 4 classes representing distinct preference profiles for patients who participated in a previous first-time anterior shoulder dislocation (FTASD) survey. Posterior probabilities of class membership at the end of a 2-question sequence ranged from 87% to 89%. We found that specificity and sensitivity of the 2-question sequences were robust to respondent errors. The questions appeared to have better specificity than sensitivity. CONCLUSIONS: Our results suggest that this approach could help diagnose patient preferences for treatments for a condition such as FTASD with acceptable precision using as few as 2 choice questions. Such preference-diagnostic tools could be used to improve and document alignment of treatment choices and patient preferences. HIGHLIGHTS: Approaches that combine patient preferences and clinical evidence can facilitate effective patient-provider communication and more patient-centric healthcare decisions. However, diagnosing individual-level preferences is challenging, and no formal diagnostic tools exist.We propose a structured approach to efficiently diagnose patient preferences based on prior information on the distribution of patient preferences in a population.We generated a 2-question test of preferences for the outcomes associated with the treatment of first-time anterior shoulder dislocation.The diagnosis of preferences can help physicians discuss relevant aspects of the treatment options and proactively address patient concerns during the clinical encounter.
Subject(s)
Decision Making, Shared , Shoulder Dislocation , Humans , Patient Preference , Surveys and Questionnaires , Delivery of Health Care , Decision Making , Choice BehaviorABSTRACT
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.