Patient-Patient Centered Outcomes Research最新文献

Background: The stage of the pandemic significantly affects people's preferences for (the societal impacts of) COVID-19 policies. No discrete choice experiments were conducted when the COVID-19 pandemic was in a transition phase.

Objectives: This is the first study to empirically investigate how citizens weigh the key societal impacts of pandemic policies when the COVID-19 pandemic transitions into an endemic.

Methods: We performed two discrete choice experiments among 2181 Dutch adults that included six attributes: COVID-19 deaths, physical health problems, mental health problems, financial problems, surgery delays and the degree to which individual liberties are restricted. We used latent class choice models to identify heterogeneous preferences for the impacts of COVID-19 measures across different groups of respondents.

Results: A large majority of the participants in this study was willing to accept deaths to avoid that citizens experience physical complaints, mental health issues, financial problems and the postponement of surgeries. The willingness to tolerate COVID-19 deaths to avoid these societal impacts differed substantially between participants. When participants were provided with information about the stringency of COVID-19 measures, they assigned relatively less value to preventing the postponement of non-urgent surgeries for 1-3 months across all classes.

Conclusions: Having gone through a pandemic, most Dutch citizens clearly prefer pandemic policies that consider citizens' financial situations, physical problems, mental health problems and individual liberties, alongside the effects on excess mortality and pressure on healthcare.

Objective: We aimed to synthesize the evidence on the construct validity and responsiveness of the EQ-5D and compare them with asthma-specific health-related quality-of-life scales, to guide further research and clinical applications in asthma.

Methods: We searched key databases from inception to 1 June, 2024 and used the COnsensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) method to appraise the evidence. The effect size estimates were aggregated using the inverse variance method to evaluate the relative efficiency of EQ-5D measures against the Asthma Quality of Life Questionnaire (AQLQ) and/or its corresponding preference-based index, Asthma Quality of Life-5 Dimensions (AQL-5D).

Results: There were 493 tests (construct validity: 428; responsiveness: 65) drawn from 37 selected articles (validation: 7; clinical: 30). Overall, 78.4% and 76.9% of the a priori hypotheses for assessing construct validity (convergent validity: 56.4%; known groups: 88.5%) and responsiveness, respectively, were satisfied. The methodological quality was "very good" or "adequate" in 78.2% of construct validity tests and 92.3% of responsiveness tests. The pooled correlation coefficient between EQ-5D index and AQLQ total scores was 0.52 (95% confidence interval 0.43-0.59), and between EQ visual analog scale and AQLQ total scores was 0.53 (95% confidence interval 0.34-0.69). The Cohen's d ratios for the index, level sum scores, and visual analog scale compared to AQLQ were 0.56 (n = 27), 1.16 (n = 16), and 0.75 (n = 37). The EQ-5D index's Cohen's d ratio compared to AQL-5D was 0.49 (n = 5). The standardized response mean ratios for the index and visual analog scale compared to AQLQ were 0.26 (n = 11) and 0.63 (n = 9).

Conclusions: The EQ-5D demonstrated overall good validity and responsiveness in the adult asthma population. However, a comparison against disease-specific instruments suggested scope for improvement in its psychometric performance for this population.

Background: Individual preferences for treatment options for major depressive disorder can impact therapeutic decision making, adherence, and ultimately outcomes.

Objectives: This systematic review of discrete choice experiments (DCEs) on patient preferences for major depressive disorder treatment assessed the range of DCE applications in major depressive disorder to document patient stakeholder involvement in DCE development and to identify the relative importance of treatment attributes.

Methods: We searched MEDLINE via Ovid (1946-present), EMBASE (Elsevier interface), Cochrane Central Register of Controlled Trials (Wiley interface), and PsycINFO (EBSCO interface) databases on 29 May, 2024. Covidence software facilitated the review, which four members completed independently. The review was conducted in two phases: title and abstract and then a full-text review. We used an established quality reporting tool to evaluate selected articles. The Covidence extraction tool was adapted for this study.

Results: A total of 19 articles were included in this review. Most studies elicited preferences for depression treatment (63.2%) and care delivery (10.5%). Two assessed willingness to pay. Individuals prefer a combination of medicine and counseling over each treatment alone. Treatment efficacy, relapse prevention, and symptom relief were among the most important attributes. Individuals were willing to accept larger risks to achieve symptom improvement. Few studies examined preference heterogeneity with latent subgroups.

Conclusions: Discrete choice experiments for major depressive disorder treatment preferences enable an assessment of trade-offs for first-line therapeutic options. Patient stakeholders are infrequently involved as collaborators in the DCE development. Few examined preference heterogeneity among subgroups.

Background: Several sphingosine-1-phosphate receptor (S1PR) modulators are available in the US for treating relapsing forms of multiple sclerosis (RMS). Given that these S1PR modulators have similar efficacy and safety, patients may consider the clinical management characteristics of the S1PR modulators when deciding among treatments. However, none of the S1PR modulators is clearly superior in every aspect of clinical management, and for some treatments, clinical management varies based on a patient's comorbid health conditions (e.g., heart conditions [HC]).

Objectives: This study aimed to determine which S1PR modulator patients with relapsing-remitting multiple sclerosis (RRMS) would prefer based on clinical management considerations, and to estimate how different clinical management considerations might drive these preferences. Preferences were explored separately for patients with and without comorbid HC.

Methods: A multicriteria decision analysis was conducted on S1PR modulators approved to treat RMS: fingolimod, ozanimod, siponimod, and ponesimod. Clinical management preferences of patients with RRMS were elicited in a discrete choice experiment (DCE) in which participants repeatedly chose between hypothetical S1PR modulator profiles based on their clinical management attributes. Attributes included first-dose observations, genotyping, liver function tests, eye examinations, drug-drug interactions, interactions with antidepressants, interactions with foods high in tyramine, and immune system recovery time. Preferences were estimated separately for patients with HC and without HC (noHC). Marginal utilities were calculated from the DCE data for each attribute and level using a mixed logit model. In the multicriteria decision analysis, partial value scores were created by applying the marginal utilities for each attribute and level to the real-world profiles of S1PR modulators. Partial value scores were summed to determine an overall clinical management value score for each S1PR modulator.

Results: Four hundred patients with RRMS completed the DCE. Ponesimod had the highest overall value score for patients both without (n = 341) and with (n = 59) HC (noHC: 5.1; HC: 4.0), followed by siponimod (noHC: 4.9; HC: 3.3), fingolimod (noHC: 3.4; HC: 2.8), and ozanimod (noHC: 0.9; HC: 0.8). Overall, immune system recovery time contributed the highest partial value scores (noHC: up to 1.9 points; HC: up to 1.2 points), followed by the number of drug-drug interactions (noHC: up to 1.2 points; HC: up to 1.7 points).

Conclusions: When considering the clinical management of S1PR modulators, the average patient with RRMS is expected to choose a treatment with shorter immune system recovery time and fewer interactions with other drugs. Patients both with and without heart conditions are likely to prefer the clinical management profile of ponesimod ove

Treatment satisfaction is a person's rating of his or her treatment experience, including processes and outcomes. It is directly related to treatment adherence, which may be predictive of treatment effectiveness in clinical and real-world research. Consequently, patient-reported outcome (PRO) instruments have been developed to incorporate patient experience throughout various stages of drug development and routine care. PRO instruments enable clinicians and researchers to evaluate and compare treatment satisfaction data in different clinical settings. It is important to select fit-for-purpose PRO instruments that have demonstrated adequate levels of reliability, validity, and sensitivity to change to support their use. Some of these instruments are unidimensional while some are multidimensional; some are generic and can be applied across different therapeutic areas, while others have been developed for use in a specific treatment modality or condition. This article describes the role of treatment satisfaction in drug development as well as regulatory and Health Technology Assessment (HTA) decision making and calls for more widespread use of carefully selected treatment satisfaction PRO instruments in early- and late-phase drug development.

Background: Kaizen is a Japanese term for continuous improvement (kai ~ change, zen ~ good). In a kaizen task, a respondent makes sequential choices to improve an object's profile, revealing a preference path. Including kaizen tasks in a discrete choice experiment has the advantage of collecting greater preference evidence than pick-one tasks, such as paired comparisons. OBJECTIVE AND METHODS: So far, three online discrete choice experiments have included kaizen tasks: the 2020 US COVID-19 vaccination (CVP) study, the 2021 UK Children's Surgery Outcome Reporting (CSOR) study, and the 2023 US EQ-5D-Y-3L valuation (Y-3L) study. In this evidence synthesis, we describe the performance of the kaizen tasks in terms of response behaviors, conditional logit and Zermelo-Bradley-Terry (ZBT) estimates, and their standard errors in each of the surveys.

Results: Comparing the CVP and Y-3L, including hold-outs (i.e., attributes shared by all alternatives) seems to reduce positional behavior by half. The CVP tasks excluded multi-level improvements; therefore, we could not estimate logit main effects directly. In the CSOR, only 12 of the 21 logit estimates are significantly positive (p < 0.05), possibly due to the fixed attribute order. All Y-3L estimates are significantly positive, and their predictions are highly correlated (Pearson: logit 0.802, ZBT 0.882) and strongly agree (Lin: logit 0.744, ZBT 0.852) with the paired-comparison probabilities.

Conclusions: These discrete choice experiments offer important lessons for future studies: (1) include warm-up tasks, hold-outs, and multi-level improvements; (2) randomize the attribute order (i.e., up-down) at the respondent level; and (3) recruit smaller samples of respondents than traditional discrete choice experiments with only pick-one tasks.

Background and objectives: Pregnant women living in rural areas considering their preferred place of birth may have to 'trade-off' travel time/distance and other attributes of care (e.g. the full choice of birthplace options is rarely available locally). This study assesses the preferences and trade-offs of recent mothers who live in remote and rural areas of Great Britain.

Methods: An online survey, informed by qualitative research, was administered to women living in rural areas who had given birth in the preceding 3 years. The survey included a discrete choice experiment (DCE) to elicit women's preferences and trade-offs for place of birth. The DCE presented women with a series of eight choice tasks in which place of birth was defined by four attributes: (1) type of facility, (2) familiarity with staff, (3) understanding options and feel relaxed and reassured and (4) the travel time to the place of intrapartum care. DCE data were analysed using an error components logit model to identify preferences.

Results: Across 251 survey responses, holding everything else equal, respondents preferred: intrapartum care in locations with more specialist staff and equipment, locations where they understood their options and felt reassured and where travel time was minimal. Women were willing to travel (92-183 min) to a well-staffed and equipped facility if they understood their options and felt relaxed and reassured. Willingness to travel was reduced if the care received at the specialist facility was such that they did not understand their options and felt tense and powerless (41-132 min).

Conclusion: These insights into the preferences of recent mums from remote and rural areas could inform future planning of rural intrapartum care.