How do study design features and participant characteristics influence willingness to participate in clinical trials? Results from a choice experiment.

BACKGROUND: Research about the decision to participate in a clinical study has tended to be limited to single indications and has focused on narrow sets of study and participant characteristics. This study applied stated preference methods to understand the clinical trial design attributes that most influence willingness to participate and how this varied with participant characteristics. METHODS: Adults residing in the US, China, or Poland with a self-reported diagnosis of cancer, heart disease, migraine, rheumatoid arthritis, or multiple sclerosis completed an online survey. Participants were asked whether they would participate in clinical studies defined by seventeen attributes within five categories (payment/support, administration/procedures, treatment-related, study location/time commitment, and data collection/feedback). Participants saw six different hypothetical clinical study profiles. Depending on their participation decision to an initial clinical study profile, the subsequent five questions had one design attribute (randomly selected per question) consecutively improved or deteriorated to elicit preferences. A logistic regression was used to determine which participant characteristics influenced participation decisions. A latent class logit model was used to identify how the influence of study design features varied between participants and whether groups of participants with similar preferences could be identified. RESULTS: The survey was completed by 487 participants (32% China, 35% Poland, 33% US; 8%-19% per indication). Willingness to participate was found to be a function of participant age, certain elements of quality of life, and previous treatment experience, in particular number of lines of treatment received and experience of adverse events. Willingness to participate was influenced by study design features such as payment, study duration, and time commitment - both the overall time and whether the time was at home or away from home, with the latter being particularly relevant to participants experiencing fatigue due to their disease. CONCLUSIONS: This study quantifies how study designs influence willingness to participate and how this varies with participant types. These findings suggest that it is how an indication influences quality of life and treatment experience, rather than the indication alone, that impacts participation rates, opening the way for insights that are transferrable across indications, which may be particularly useful when considering rare diseases.

Use of LCP-Tacrolimus (LCPT) in Kidney Transplantation: A Delphi Consensus Survey of Expert Clinicians.

BACKGROUND LCPT (Envarsus XR®) is a common once-daily, extended-release oral tacrolimus formulation used in kidney transplantation. However, there are minimal evidence-based recommendations regarding optimal dosing and treatment in the de novo and conversion settings. MATERIAL AND METHODS Using Delphi methodology, 12 kidney transplantation experts with LCPT experience reviewed available data to determine potential consensus topics. Key statements regarding LCPT use were generated and disseminated to the panel in an online Delphi survey. Statements were either accepted, revised, or rejected based on the level of consensus, perceived strength of evidence, and alignment with clinical practice. Consensus was defined a priori as ≥75% agreement. RESULTS Twenty-three statements were generated: 14 focused on de novo LCPT use and 9 on general administration or LCPT conversion use. After 2 rounds, consensus was achieved for 11/14 of the former and 7/9 of the latter statements. In a de novo setting, LCPT was recognized as a first-line option based on its safety and efficacy compared to immediate-release tacrolimus. In particular, African Americans and rapid metabolizer populations were identified as preferred for first-line LCPT therapy. In a conversion setting, full consensus was achieved for converting to LCPT to address neurological adverse effects related to immediate-release tacrolimus and for the time required (approximately 7 days) for steady-state LCPT trough levels to be reached. CONCLUSIONS When randomized clinical trials do not replicate current utilization patterns, the Delphi process can successfully generate consensus statements by expert clinicians to inform clinical decision-making for the use of LCPT in kidney transplant recipients.

Treatment preferences of patients with relapsed or refractory multiple myeloma in the United States, United Kingdom, Italy, Germany, France, and Spain: results from a discrete choice experiment.

Introduction: Newer treatment options for relapsed/refractory multiple myeloma (RRMM) with efficacy and safety profiles that differ from traditional therapies have facilitated personalized management strategies to optimize patient outcomes. In the context of such personalized management, understanding how treatment characteristics influence patients' preferences is essential. This study assessed patients' preferences for RRMM treatment attributes and determined trade-offs between potential benefits, administration procedures, and adverse effects. Methods: Patients' preferences were evaluated using a discrete choice experiment (DCE). Patients with RRMM who reported failing two lines of anti-myeloma treatment (immunomodulatory agent and a proteasome inhibitor [PI]) or ≥ 3 lines (including ≥1 PI, immunomodulatory agent, or anti-CD38 monoclonal antibody), were recruited across the US, UK, Italy, Germany, France, and Spain. DCE attributes and levels were identified using a targeted literature review, a review of clinical data for relevant RRMM treatments, qualitative patient interviews, and input from clinical and myeloma patient experts. The DCE was administered within an online survey from February-June 2022. Preference data were analyzed using an error-component logit model and willingness to make trade-offs for potential benefits, and relative attribute importance scores were calculated. Results: Overall, 296 patients from the US (n = 100), UK (n = 49), Italy (n = 45), Germany (n = 43), France (n = 39), and Spain (n = 20) participated in the DCE. Mean (standard deviation) age was 63.8 (8.0) years, 84% had a caregiver, and patients had a median of 3 (range: 2-8) prior lines of therapy. Efficacy attributes most influenced patients' preferences, with increasing overall response rate (25-85%) and overall survival (6 months to 2 years) contributing to ~50% of treatment decision-making. Administration procedures were also considered important to patients. Avoiding individual side effects was considered relatively less important, with patients willing to tolerate increases in side effects for gains in efficacy. Patient characteristics such as rate of disease progression, sociodemographics, or clinical characteristics also influenced treatment preferences. Conclusion: Patients with RRMM were willing to tolerate increased risk of side effects for higher efficacy. Preferences and risk tolerance varied between patients, with preference patterns differing by certain patient characteristics. This highlights the importance of shared decision-making for optimal treatment selection and patient outcomes.

A Systematic Review of Discrete Choice Experiments in Oncology Treatments.

BACKGROUND: As the number and type of cancer treatments available rises and patients live with the consequences of their disease and treatments for longer, understanding preferences for cancer care can help inform decisions about optimal treatment development, access, and care provision. Discrete choice experiments (DCEs) are commonly used as a tool to elicit stakeholder preferences; however, their implementation in oncology may be challenging if burdensome trade-offs (e.g. length of life versus quality of life) are involved and/or target populations are small. OBJECTIVES: The aim of this review was to characterise DCEs relating to cancer treatments that were conducted between 1990 and March 2020. DATA SOURCES: EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews were searched for relevant studies. STUDY ELIGIBILITY CRITERIA: Studies were included if they implemented a DCE and reported outcomes of interest (i.e. quantitative outputs on participants' preferences for cancer treatments), but were excluded if they were not focused on pharmacological, radiological or surgical treatments (e.g. cancer screening or counselling services), were non-English, or were a secondary analysis of an included study. ANALYSIS METHODS: Analysis followed a narrative synthesis, and quantitative data were summarised using descriptive statistics, including rankings of attribute importance. RESULT: Seventy-nine studies were included in the review. The number of published DCEs relating to oncology grew over the review period. Studies were conducted in a range of indications (n = 19), most commonly breast (n =10, 13%) and prostate (n = 9, 11%) cancer, and most studies elicited preferences of patients (n = 59, 75%). Across reviewed studies, survival attributes were commonly ranked as most important, with overall survival (OS) and progression-free survival (PFS) ranked most important in 58% and 28% of models, respectively. Preferences varied between stakeholder groups, with patients and clinicians placing greater importance on survival outcomes, and general population samples valuing health-related quality of life (HRQoL). Despite the emphasis of guidelines on the importance of using qualitative research to inform attribute selection and DCE designs, reporting on instrument development was mixed. LIMITATIONS: No formal assessment of bias was conducted, with the scope of the paper instead providing a descriptive characterisation. The review only included DCEs relating to cancer treatments, and no insight is provided into other health technologies such as cancer screening. Only DCEs were included. CONCLUSIONS AND IMPLICATIONS: Although there was variation in attribute importance between responder types, survival attributes were consistently ranked as important by both patients and clinicians. Observed challenges included the risk of attribute dominance for survival outcomes, limited sample sizes in some indications, and a lack of reporting about instrument development processes. PROTOCOL REGISTRATION: PROSPERO 2020 CRD42020184232.