Valuing Treatments for Parkinson Disease Incorporating Process Utility: Performance of Best-Worst Scaling, Time Trade-Off, and Visual Analogue Scales

An Overview of Data Collection in Health Preference Research

This paper focuses on survey administration and data collection methods employed for stated-preference studies in health applications. First, it describes different types of survey administration methods, encompassing web-based surveys, face-to-face (in-person) surveys, and mail surveys. Second, the concept of sampling frames is introduced, clarifying distinctions between the target population and survey frame population. The discussion then extends to different types of sampling methods, such as probability and non-probability sampling, along with an evaluation of potential issues associated with different sampling methods within the context of health preference research. Third, the paper provides information about different recruitment methods, including web-surveys, leveraging patient groups, and in-clinic recruitment. Fourth, a crucial aspect addressed is the calculation of response rate, with insights into determining an adequate response rate and strategies to improve response rates in stated-preference surveys. Lastly, the paper concludes by discussing data management plans and suggesting insights for future research in this field. In summary, this paper examines the nuanced aspects of survey administration and data collection methods in stated-preference studies, offering valuable guidance for researchers and practitioners in the health domain.

Preferences for Monitoring Comprehensive Heart Failure Care: A Latent Class Analysis

OBJECTIVE

To measure preference heterogeneity for monitoring systems among patients with a chronic heart failure.

METHODS

A best-worst scaling experiment (BWS case 3) was conducted among patients with chronic heart failure to assess preferences for hypothetical monitoring care scenarios. These were characterized by the attributes mobility, risk of death, risk of hospitalization, type and frequency of monitoring, risk of medical device, and system-relevant complications. A latent class analysis (LCA) was used to analyze and interpret the data. In addition, a market simulator was used to examine which treatment configurations participants in the latent classes preferred.

RESULTS

Data from 278 respondents were analyzed. The LCA identified four heterogeneous classes. For class 1, the most decisive factor was mobility with a longer distance covered being most important. Class 2 respondents directed their attention toward attribute "monitoring," with a preferred monitoring frequency of nine times per year. The attribute risk of hospitalization was most important for respondents of class 3, closely followed by risk of death. For class 4, however, risk of death was most important. A market simulation showed that, even with high frequency of monitoring, most classes preferred therapy with high improvement in mobility, mortality, and hospitalization.

CONCLUSION

Using LCA, variations in preferences among different groups of patients with chronic heart failure were examined. This allows treatment alternatives to be adapted to individual needs of patients and patient groups. The findings of the study enhance clinical and allocative decision-making while elevating the quality of clinical data interpretation.

Which body functions and activities matter for stroke patients? Study protocol for best-Worst scalings to value core elements of the International Classification of Functioning, Disability and Health

BACKGROUND

Stroke is a common, serious, and disabling healthcare problem with increasing incidence and prevalence. Following a stroke, identifying the factors associated with decisions about rehabilitation interventions is important to assess rehabilitation after stroke. The aim is to guide clinical staff to make patient-centered decisions. Fundamentally, decision makers cannot draw on evidence to consider the relevance of distinct functions and activities from the patient's perspective. Until now, outcomes of rehabilitation are generally categorized using the International Classification of Functioning, Disability and Health (ICF). This can be seen as a conceptual basis for the assessment of health and disability. Since the ICF does not distinguish importance between these aspects there is a need to value the most important clinical factors as well as related activities from a patients and public perspective to help guide therapists in effectively designing post-acute rehabilitation care for individuals following stroke. The research question is which ICF body functions and activities are of value to stroke patients? Which trade-offs are patients willing to make within the core elements? Health preference research (HPR) answers the need to develop additional preference weights for certain ICF dimensions. Patient preference information (PPI) values health conditions based on the ICF from a patient perspective.

METHODS

In this study we conduct three best-worst scaling (BWS) experiments to value body function and activities from patients' and public perspective. Out of all ICF dimensions this research covers health conditions relevant to stroke patients in terms of body function, perception, and activities of daily living. Stroke patients as well as members of the general population will be recruited to participate in the online BWS surveys. Fractional, efficient designs are applied regarding the survey design. Conditional and multinominal logit analyses will be used as the main analysis method, with the best-worst count analysis as a secondary analysis. The survey is being piloted prior to commencing the process of data collection. Results are expected by the autumn of 2023.

DISCUSSION

The research will add to the current literature on clinical decision-making in stroke rehabilitation and the value of certain body functions as well as related activities in neurorehabilitation. Moreover, the study will show whether body functions and activities that are currently equally weighted in international guidelines are also equally important from the point of view of those affected, or whether there are disconcordances in terms of differences between public judgements and patients' preferences.

Assessment of patients' preferences for new anticancer drugs in China: a best-worst discrete choice experiment on three common cancer types

OBJECTIVES

Despite the advancement in anticancer drug therapies, cancer treatment decisions are often complex and preference-sensitive, making them well suited for studying shared decision-making (SDM). Our study aimed to assess preferences for new anticancer drugs among three common types of patients with cancer to inform SDM.

DESIGN

We identified five attributes of new anticancer drugs and used a Bayesian-efficient design to generate choice sets for a best-worst discrete choice experiment (BWDCE). The mixed logit regression model was applied to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity.

SETTING

The BWDCE was conducted in Jiangsu province and Hebei province in China.

PARTICIPANTS

Patients aged 18 years or older, who had a definite diagnosis of lung cancer, breast cancer or colorectal cancer were recruited.

RESULTS

Data from 468 patients were available for analysis. On average, the most valued attribute was the improvement in health-related quality of life (HRQoL) (p<0.001). The low incidence of severe to life-threatening side effects, prolonged progression-free survival and the low incidence of mild to moderate side effects were also positive predictors of patients' preferences (p<0.001). Out-of-pocket cost was a negative predictor of their preferences (p<0.001). According to subgroup analysis by type of cancer, the improvement in HRQoL remained the most valuable attribute. However, the relative importance of other attributes varied by type of cancer. Whether patients were newly diagnosed or previously diagnosed cancer cases played a dominant role in the preference heterogeneity within each subgroup.

CONCLUSIONS

Our study can assist in the implementation of SDM by providing evidence on patients' preferences for new anticancer drugs. Patients should be informed of the multiattribute values of new drugs and encouraged to make decisions reflecting their values.

Best-worst scaling preferences among patients with well-controlled epilepsy: Pilot results

Epilepsy is a common, serious condition. Fortunately, seizure risk decreases with increasing seizure-free time on antiseizure medications (ASMs). Eventually, patients may consider whether to stop ASMs, which requires weighing treatment benefit versus burden. We developed a questionnaire to quantify patient preferences relevant to ASM decision-making. Respondents rated how concerning they would finding relevant items (e.g., seizure risks, side effects, cost) on a Visual Analogue Scale (VAS, 0-100) and then repeatedly chose the most and least concerning item from subsets (best-worst scaling, BWS). We pretested with neurologists, then recruited adults with epilepsy who were seizure-free at least one year. Primary outcomes were recruitment rate, and qualitative and Likert-based feedback. Secondary outcomes included VAS ratings and best-minus-worst scores. Thirty-one of 60 (52%) contacted patients completed the study. Most patients felt VAS questions were clear (28; 90%), easy to use (27; 87%), and assessed preferences well (25; 83%). Corresponding results for BWS questions were 27 (87%), 29 (97%), and 23 (77%). Physicians suggested adding a 'warmup' question showing a completed example and simplifying terminology. Patients suggested ways to clarify instructions. Cost, inconvenience of taking medication, and laboratory monitoring were the least concerning items. Cognitive side effects and a 50% seizure risk in the next year were the most concerning items. Twelve (39%) of patients made at least one 'inconsistent choice' for example ranking a higher seizure risk as lower concern compared with a lower seizure risk, though 'inconsistent choices' represented only 3% of all question blocks. Our recruitment rate was favorable, most patients agreed the survey was clear, and we describe areas for improvement. 'Inconsistent' responses may lead us to collapse seizure probability items into a single 'seizure' category. Evidence regarding how patients weigh benefits and harms may inform care and guideline development.

Identification of Relevant Attributes for Liver Cancer Therapies (IRALCT): a maximum-difference-scaling analysis

The Identification of Relevant Attributes for Liver Cancer Therapies (IRALCT) project is intended to provide new insights into the relevant utility attributes regarding therapy choices for malignant primary and secondary liver tumors from the perspective of those who are involved in the decision-making process. It addresses the potential value of taking patients' expectations and preferences into account during the decision-making and, when possible, adapting therapies according to these preferences. Specifically, it is intended to identify the relevant clinical attributes that influence the patients', medical laymen's, and medical professionals' decisions and compare the three groups' preferences. We conducted maximum difference (MaxDiff) scaling among 261 participants (75 physicians, 97 patients with hepatic malignancies, and 89 medical laymen) to rank the importance of 14 attributes previously identified through a literature review. We evaluated the MaxDiff data using count analysis and hierarchical Bayes estimation (HB). Physicians, patients, and medical laymen assessed the same 7 attributes as the most important: probability (certainty) of a complete removal of the tumor, probability of reoccurrence of the disease, pathological evidence of tumor removal, possible complications during the medical intervention, welfare after the medical intervention, duration and intensity of the pain, and degree of difficulty of the medical intervention. The cumulative relative importance of these 7 attributes was 88.3%. Our results show that the physicians', patients', and medical laymen's preferences were very similar and stable.Trial registration DRKS-ID of the study: DRKS00013304, Date of Registration in DRKS: 2017/11/16.

Value assessment frameworks: who is valuing the care in healthcare?

Many healthcare agencies are producing evidence-based guidance and policy that may determine the availability of particular healthcare products and procedures, effectively rationing aspects of healthcare. They claim legitimacy for their decisions through reference to evidence-based scientific method and the implementation of just decision-making procedures, often citing the criteria of 'accountability for reasonableness'; publicity, relevance, challenge and revision, and regulation. Central to most decision methods are estimates of gains in quality-adjusted life-years (QALY), a measure that combines the length and quality of survival. However, all agree that the QALY alone is not a sufficient measure of all relevant aspects of potential healthcare benefits, and a number of value assessment frameworks have been suggested. I argue that the practical implementation of these procedures has the potential to lead to a distorted assessment of value. Undue weight may be ascribed to certain attributes, particularly those that favour commercial or political interests, while other attributes that are highly valued by society, particularly those related to care processes, may be omitted or undervalued. This may be compounded by a lack of transparency to relevant stakeholders, resulting in an inability for them to participate in, or challenge, the decisions. The makes it likely that costly new technologies, for which inflated prices can be justified by the current value frameworks, are displacing aspects of healthcare that are highly valued by society.

Bias Investigation in Artificial Intelligence Systems for Early Detection of Parkinson's Disease: A Narrative Review

Background and Motivation: Diagnosis of Parkinson's disease (PD) is often based on medical attention and clinical signs. It is subjective and does not have a good prognosis. Artificial Intelligence (AI) has played a promising role in the diagnosis of PD. However, it introduces bias due to lack of sample size, poor validation, clinical evaluation, and lack of big data configuration. The purpose of this study is to compute the risk of bias (RoB) automatically.

METHOD

The PRISMA search strategy was adopted to select the best 39 AI studies out of 85 PD studies closely associated with early diagnosis PD. The studies were used to compute 30 AI attributes (based on 6 AI clusters), using AP(ai)Bias 1.0 (AtheroPointTM, Roseville, CA, USA), and the mean aggregate score was computed. The studies were ranked and two cutoffs (Moderate-Low (ML) and High-Moderate (MH)) were determined to segregate the studies into three bins: low-, moderate-, and high-bias.

RESULT

The ML and HM cutoffs were 3.50 and 2.33, respectively, which constituted 7, 13, and 6 for low-, moderate-, and high-bias studies. The best and worst architectures were "deep learning with sketches as outcomes" and "machine learning with Electroencephalography," respectively. We recommend (i) the usage of power analysis in big data framework, (ii) that it must undergo scientific validation using unseen AI models, and (iii) that it should be taken towards clinical evaluation for reliability and stability tests.

CONCLUSION

The AI is a vital component for the diagnosis of early PD and the recommendations must be followed to lower the RoB.

Patient-Centered Identification of Meaningful Regulatory Endpoints for Medical Devices to Treat Parkinson's Disease

Introduction. A growing literature has developed on identifying outcomes that matter to patients. This study demonstrates an approach involving patient and regulatory perspectives to identify outcomes that are meaningful in the context of medical devices for Parkinson’s disease (PD). Methods. A systematic process was used for specifying relevant regulatory endpoints by synthesizing inputs of various sources and stakeholders. First, a literature review was conducted to identify important benefits, risks, and other considerations for medical devices to treat PD; patient discussion groups (n = 6) were conducted to refine the list of considerations, followed by a survey (n = 29) to prioritize them; and patient and Food and Drug Administration (FDA) reviewers informed specification of the final endpoints. Two FDA clinicians gave clinical and regulatory perspectives at each step. Results. Movement symptoms were ranked as most important (ranked 1 or 2 by 72% of participants) and psychological and cognitive symptoms as the next most important (ranked 1 or 2 by 52% of participants). Within movement symptoms, falls, impaired movement, bradykinesia, resting tremor, stiffness, and rigidity were ranked highly. Overall, nine attributes were identified and prioritized as patient-centric for use in clinical trial design and quantitative patient preference studies. These attributes were benefits and risks related to therapeutics for PD as well as other considerations, including time until a medical device is available for patient use. Discussion. This prospective approach identified meaningful and relevant benefits, risks, and other considerations that may be used for clinical trial design and quantitative patient preference studies. Although PD was the focus of this study, the approach can be used to study patient perspectives about other disease or treatment areas.

Similar responses to EQ-5D-3L by two elicitation methods: visual analogue scale and time trade-off

Background

Health-related quality of life (HRQoL) is often measured using EQ-5D-3L by the elicitation methods of visual analogue scale (VAS) and time trade-off (TTO). Although many countries have constructed both national VAS and TTO value sets, the fact that VAS and TTO value sets produces different values bewilders researchers and policymakers. The aim of this study is to explore certain conditions which could yield similar value sets using VAS and TTO.

Methods

A homogeneous sample of medical school students was selected to value 18 hypothetical health states using VAS and TTO methods. The 18 hypothetical health states were produced by orthogonal design (L18, 2*3^7). The range of rescaled values was transformed into − 1 ~ 0 ~ 1. The investigations via different methods were carried out by computer-assisted personal interviewing with a wash-time interval of 72 h. Value sets for VAS and TTO were constructed using general least square regression models. Independent variables were composed of 10 dummy variables from 5 dimensions and including or omitting both constant and N3 terms.

Results

Three hundred thirteen medical students participated. The mean age was 21.03 ± 0.44 years and 56.2% were female. The four regression models (for each method with and without constant and N3 terms) were all statistically significant (P < 0.05) with high goodness-of-fit (Adj. R² > 0.94 and MAE < 0.033). Differences between the coefficients of the 10 dummy variables corresponding to each model were all less than 0.059. Pearson correlation coefficients between observed means and predicted values exceeded 0.981. Fitted curves of VAS and TTO largely coincided.

Conclusions

VAS and TTO can generate similar responses under certain conditions, suggesting that the two valuation methods could be equivalent intrinsically. The VAS method appears a more valid approach for valuation in the general population due to its greater simplicity and feasibility.

The Psychometric Properties of a Self-Administered, Open-Source Module for Valuing Metastatic Epidural Spinal Cord Compression Utilities

INTRODUCTION

Web surveys are often used for utility valuation. Typically, custom utility valuation tools that have not undergone psychometric evaluation are used.

OBJECTIVES

This study aimed to determine the psychometric properties of a metastatic epidural spinal cord compression (MESCC) module run on a customizable open-source, internet-based, self-directed utility valuation platform (Self-directed Online Assessment of Preferences [SOAP]).

METHODS

Individuals accompanying patients to the emergency department waiting room in Ottawa, Canada, were recruited. Participants made SOAP MESCC health state valuations in the waiting room and 48 h later at home. Validity, agreement reliability, and responsiveness were measured by logical consistency of responses, smallest detectable change, the interclass correlation coefficient, and Guyatt's responsiveness index, respectively.

RESULTS

Of 285 participants who completed utility valuations, only 113 (39.6%) completed the re-test. Of these 113 participants, 92 (81.4%) provided valid responses on the first test and 75 (66.4%) provided valid responses on the test and re-test. Agreement for all groups of health states was adequate, since their smallest detectable change was less than the minimal clinically important difference. The mean interclass correlation coefficients for all health states were > 0.8, indicating at least substantial reliability. Guyatt's responsiveness indices all exceeded 0.80, indicating a high level of responsiveness.

CONCLUSIONS

To our knowledge, this is the first validated open-source, web-based, self-directed utility valuation module. We have demonstrated the SOAP MESCC module is valid, reproducible, and responsive for obtaining ex ante utilities. Considering the successful psychometric validation of the SOAP MESCC module, other investigators can consider developing modules for other diseases where direct utility valuation is needed.

A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best-Worst Scaling for Eliciting Preferences in Healthcare

OBJECTIVE

The aim of this study was to compare the acceptability, validity and concordance of discrete choice experiment (DCE) and best-worst scaling (BWS) stated preference approaches in health.

METHODS

A systematic search of EMBASE, Medline, AMED, PubMed, CINAHL, Cochrane Library and EconLit databases was undertaken in October to December 2016 without date restriction. Studies were included if they were published in English, presented empirical data related to the administration or findings of traditional format DCE and object-, profile- or multiprofile-case BWS, and were related to health. Study quality was assessed using the PREFS checklist.

RESULTS

Fourteen articles describing 12 studies were included, comparing DCE with profile-case BWS (9 studies), DCE and multiprofile-case BWS (1 study), and profile- and multiprofile-case BWS (2 studies). Although limited and inconsistent, the balance of evidence suggests that preferences derived from DCE and profile-case BWS may not be concordant, regardless of the decision context. Preferences estimated from DCE and multiprofile-case BWS may be concordant (single study). Profile- and multiprofile-case BWS appear more statistically efficient than DCE, but no evidence is available to suggest they have a greater response efficiency. Little evidence suggests superior validity for one format over another. Participant acceptability may favour DCE, which had a lower self-reported task difficulty and was preferred over profile-case BWS in a priority setting but not necessarily in other decision contexts.

CONCLUSION

DCE and profile-case BWS may be of equal validity but give different preference estimates regardless of the health context; thus, they may be measuring different constructs. Therefore, choice between methods is likely to be based on normative considerations related to coherence with theoretical frameworks and on pragmatic considerations related to ease of data collection.

Association of Parkinson's disease-related pain with plasma interleukin-1, interleukin-6, interleukin-10, and tumour necrosis factor-α

OBJECTIVE

To study the association between Parkinson's disease (PD)-related pain and plasma interleukin (IL)‑1, IL‑6, IL‑10, and tumour necrosis factor (TNF)‑α levels.

METHODS

Sixty-seven participants were enrolled. Plasma inflammatory cytokine levels of IL-1, IL-6, IL-10, and TNF-α were measured with enzyme-linked immunosorbent assay. We additionally administered the third part of the Unified Parkinson's Disease Rating Scale (UPDRS III) and Hoehn and Yahr (H-Y) scale stage and recorded the course of the disease, the type and location of the pain, and the use of drugs.

RESULTS

The level of IL-1 was significantly higher in the PD-with-pain than in the healthy-control group (P < 0.05). There was no significant difference among groups in the other examined cytokine levels. There was a statistically significant difference between the PD-with-pain and the PD-without-pain groups in UPDRS III and H-Y stage. Additionally, the IL-1 level was significantly higher in patients who received a levodopa dosage of >250 mg than in their counterparts who received ≤250 mg, and the IL-1 level was higher in patients with an H-Y stage of >2 and UPDRS III of >27 than in their counterparts with an H-Y stage of ≤2 and UPDRS III of ≤27. The expression of TNF-α was higher in patients aged ≥70 years than in their counterparts aged <70 years. The level of IL-10 was significantly lower in the patients with an H-Y stage of >2 than in their counterparts with an H-Y stage of ≤2.

CONCLUSION

The elevated level of IL-1 and the depressed level of IL-10 in the peripheral blood of patients with PD-related pain suggests that certain inflammatory cytokines may be implicated in the occurrence and clinical symptoms of PD-related pain.

Patient Preferences Regarding Surgical Interventions for Knee Osteoarthritis

Surgical interventions for knee osteoarthritis (OA) have markedly different procedure attributes and may have dramatic differences in patient desirability. A total of 323 patients with knee OA were included in a dual response, choice-based conjoint analysis to identify the relative preference of 9 different procedure attributes. A model was also developed to simulate how patients might respond if presented with the real-world knee OA procedures, based on conservative assumptions regarding their attributes. The “amount of cutting and removal of the existing bone” required for a procedure had the highest preference score, indicating that these patients considered it the most important attribute. More specifically, a procedure that requires the least amount of bone cutting or removal would be expected to be the most preferred surgical alternative. The model also suggested that patients who are younger and report the highest pain levels and greatest functional limitations would be more likely to opt for surgical intervention.

Patient and Public Preferences for Treatment Attributes in Parkinson's Disease

Background

Patient and public preferences for therapeutic outcomes or medical technologies are often elicited, and discordance between the two is frequently reported.

Objective

Our main objective was to compare patient and public preferences for treatment attributes in Parkinson’s disease (PD).

Methods

A representative sample from Dutch PD patients and the general public were invited to complete a best–worst scaling case 2 experiment consisting of six health-related outcomes and one attribute describing the specific treatment (brain surgery, pump, oral medication). Data were analyzed using mixed logit models, and attribute impact was estimated and compared between populations (and population subgroups).

Results

Both the public (N = 276) and patient (N = 198) populations considered treatment modality the most important attribute, although patients assigned higher relative importance. Both groups assigned high disutility to pump infusion and brain surgery and preferred drug treatment. Most health outcomes were valued equally by patients and the public, with the exception of reducing dizziness (more important to the public) and improving slow movement (more important to patients).

Discussion

Although these data do not support definite conclusions on whether patients are less likely to undergo invasive treatments, the (predicted) choice probability of undergoing brain surgery or having pump infusion technology would be low based on the (un)desirability of the attribute levels. Patients with PD might have adapted to their condition and are not willing to undergo advanced treatments in order to receive health improvements. Both public and patient preferences entail information that is potentially relevant for decision makers, and patient preferences can inform decision makers about the likelihood of adaptation to a specific condition.

Electronic supplementary material

The online version of this article (doi:10.1007/s40271-017-0247-7) contains supplementary material, which is available to authorized users.