A Bayesian model that jointly considers comparative effectiveness research and patients’ preferences may help inform GRADE recommendations: an application to rheumatoid arthritis treatment recommendations

Preferences for risks and benefits of treatment outcomes for chronic low back pain: Choice-based conjoint measure development and discrete choice experiment

INTRODUCTION

Understanding individual patient preferences for chronic low back pain (cLBP) outcomes is essential for targeting available therapeutic options; yet tools to elicit patient outcome preferences are limited.

OBJECTIVE

To develop and test a choice-based conjoint (CBC) measure, commonly used in behavioral economics research, to elicit what outcomes patients with cLBP want to achieve and avoid.

DESIGN

We developed a survey-based CBC measure to allow patients to make risk/benefit trade-off choices between possible treatment outcomes. After extensive literature, clinician, and patient input, our measure included seven attributes: fatigue, anxiety/depression, difficulty thinking/making decisions, pain intensity, physical abilities, change in pain, and ability to enjoy life despite pain. Random-parameters logit models were used to estimate strength of preferences, and latent class analysis was used to identify patient characteristics associated with distinct preference.

SETTING

Online study using the Sawtooth web-based platform.

PARTICIPANTS

Two hundred eleven individuals with cLBP recruited from online advertising as well as at clinical sites across multiple academic and private institutions.

INTERVENTIONS

Not applicable.

RESULTS

The most valued outcome was the highest level of physical activity (β = 1.6-1.98; p < .001), followed by avoiding cognitive difficulties (β = -1.48; p < .001). Avoidance of severe pain was comparable to avoiding constant fatigue and near-constant depression/anxiety (β = -0.99, -1.02); p < .001). There was an association between preferences and current pain/disability status; patients with higher pain had a stronger preference to avoid severe pain, whereas those with higher disability have stronger preferences for achieving physical activity. The latent class analysis identified two distinct groups: (1) more risk-seeking and willing to accept worse outcomes (56%); and (2) more risk-averse with a stronger preference for achieving maximum benefits (44%).

CONCLUSIONS

Our study illuminated cLBP patient preferences for treatment outcomes and heterogeneity in these preferences. Patients stressed the importance of reaching high physical activity and avoiding cognitive declines, even over a desire to avoid pain. More work is needed to understand patient preferences to aid informed, shared decisions.

Using Twitter Data Analysis to Understand the Perceptions, Beliefs, and Attitudes about Pharmacotherapy Used in Rheumatology: An Observational Study

Twitter has become an important platform for disseminating information about rheumatology drugs by patients, health professionals, institutions, and other users. The aim of this study was to analyze tweets related to 16 drugs used in rheumatology, including their volume, content, and type of user (patients, patients' relatives, health professionals, health institutions, pharmaceutical industry, general press, scientific journals and patients' associations), and to detect inappropriate medical content. A total of 8829 original tweets were obtained, with a random sample of 25% of the total number of tweets for each drug (at least 100 tweets) analyzed. Methotrexate (MTX) accounted for a quarter of all tweets, and there were significant differences in the proportion of tweets issued according to the type of user. Patients and their relatives mainly tweeted about MTX, while professionals, institutions, and patient associations posted more about TNF inhibitors. In contrast, the pharmaceutical industry focused on IL-17 inhibitors. Medical content prevailed in all drugs except anti-CD20 and IL-1 inhibitors and the most discussed medical topic was efficacy, followed by posology and adverse effects. Inappropriate or fake content was found to be very low. In conclusion, the majority of the tweets were about MTX, which is a first-line treatment for several diseases. The distribution of medical content varied according to the type of user. In contrast to other studies, the amount of medically inappropriate content was very low.

Systematic review of quantitative preference studies of treatments for rheumatoid arthritis among patients and at-risk populations

Treatments used for rheumatoid arthritis (RA) are under investigation for their efficacy to prevent RA in at risk groups. It is therefore important to understand treatment preferences of those at risk. We systematically reviewed quantitative preference studies of drugs to treat, or prevent RA, to inform the design of further studies and trials of RA prevention. Stated preference studies for RA treatment or prevention were identified through a search of five databases. Study characteristics and results were extracted, and the relative importance of different types of treatment attributes was compared across populations. Twenty three studies were included 20 of RA treatments (18 of patients; 2 of the general public) and 3 prevention studies with first-degree relatives (FDRs). Benefits, risks, administration method and cost (when included) were important determinants of treatment choice. A benefit was more important than a risk attribute in half of the studies of RA treatment that included a benefit attribute and 2/3 studies of RA prevention. There was variability in the relative importance of attributes across the few prevention studies. In studies with non-patient participants, attributes describing confidence in treatment effectiveness/safety were more important determinants of choice than in studies with patients. Most preference studies relating to RA are of treatments for established RA. Few studies examine preferences for treatments to prevent RA. Given intense research focus on RA prevention, additional preference studies in this context are needed. Variation in treatment preferences across different populations is not well understood and direct comparisons are needed.

Heterogeneity in patient characteristics and differences in treatment across four Canadian rheumatoid arthritis cohorts

OBJECTIVE

To compare clinical characteristics and treatment of patients with rheumatoid arthritis (RA) across 4 Canadian cohorts.

METHODS

The four longitudinal cohorts included: The Canadian Early Arthritis Cohort (CATCH) (n=2878); Ontario Best Practices Research Initiative (OBRI) (n=3734); RHUMADATA® (Quebec, n=2890), and the Rheum4U Precision Health Registry (Calgary, n=709). Data were from cohort inception (range 1998-2016) to 2020. Clinical characteristics and drug treatments were summarized descriptively.

RESULTS

10,211 patients with RA were included. The percentage of patients who entered the cohort with early RA ( ≤ 2 years of disease at enrolment) ranged from 29% (Rheum4U) to 100% (CATCH). Mean age (55 years), sex (74% female) and seropositivity (69%) were similar between cohorts. At the time of initial disease modifying anti-rheumatic drug (DMARD) use, median disease activity scores (DAS-28) varied, ranging from 2.99 (Rheum4U) to 5.19 (CATCH), but were more similar at the time of the first DMARD switch (range:3.57-5.03), first biologic or targeted synthetic DMARD (bDAMRD, tsDMARD) use (range:4.01-4.67) and second bDAMRD or tsDMARD (range:3.71-4.39). The initial DMARD was most commonly methotrexate, either in monotherapy (32%, range:18%-40%) or dual therapy (34%, range:29%- 42%). The first DMARD switch was to another DMARD monotherapy in 20% (range:10%- 32%), dual therapy in 49% (range:39%-56%), and bDMARD or tsDMARD in 24% (range:15%- 28%). The first bDMARD was an anti-TNF in 79% (range:78%-85%).

CONCLUSION

Canadian RA cohorts demonstrate some heterogeneity in treatment which could reflect differences in inclusion criteria, calendar year, or regional differences. This project is a first step towards conducting harmonized analyses across Canadian RA cohorts.

Patient preferences for rheumatoid arthritis treatment

PURPOSE OF REVIEW

To provide an overview of recent articles discussing patient preferences for rheumatoid arthritis (RA) treatment.

RECENT FINDINGS

Recent studies examined patient preferences for RA treatment in several populations, finding that most participants were willing to accept certain risks of adverse effects to gain potential benefits. Perspectives regarding cannabis were studied, with patients describing medical marijuana as an alternative therapy to be used with prescription medications or as means of tapering off these medications. Treatment preferences for different RA therapies were explored using a conjoint analysis survey and five distinct preference phenotypes emerged, with members of the largest group most concerned with the cost of medications. Other discrete choice studies demonstrated route of administration as an important attribute influencing treatment preferences, with patients expressing preference for various modes in different studies. Patient preferences for route of administration have demonstrated preference for newer autoinjectors over prefilled syringes as well as currently marketed autoinjectors. Incorporating patient preferences in clinical practice recommendations was described in the development of the 2015 American College of Rheumatology (ACR) RA treatment guidelines as well as the 2017 ACR/American Association of Hip and Knee Surgeons guidelines for perioperative management of antirheumatic medications. In addition, other studies explored preferences with regard to predictive testing, medication intensification and tapering, treatment goals, and psychological support.

SUMMARY

Our review of recent studies show variability in patient preferences for RA treatment, highlighting the importance of incorporating patient input into the treatment approach.

Patient preferences for maintenance therapy in Crohn's disease: A discrete-choice experiment

Objective

To quantify patient preferences for maintenance therapy of Crohn’s disease and understand the impact on treatment selection.

Methods

We conducted a discrete-choice experiment in patients with Crohn’s disease (n = 155) to measure the importance of attributes relevant to choosing between different medical therapies for maintenance of Crohn’s disease. The attributes included efficacy and withdrawals due to adverse events, as well as dosing and other rare risks of treatment. From the discrete-choice experiment we estimated the part-worth (importance) of each attribute level, and explored preference heterogeneity through latent class analysis. We then used the part-worths to apply weights across each outcome from a prior network meta-analysis to estimate patients’ preferred treatment in pairwise comparisons and for the overall group of treatments.

Results

The discrete-choice experiment revealed that maintaining remission was the most important attribute. Patients would accept a rare risk of infection or cancer for a 14% absolute increased chance of remission. Latent class analysis demonstrated that 45% of the cohort was risk averse, either to adverse events or requiring a course of prednisone. When these preferences were used in modelling studies to compare pairs of treatments, there was a ≥ 78% probability that all biologic treatments were preferred to azathioprine and methotrexate, based on the balance of benefits and harms. When comparing all treatments, adalimumab was preferred by 53% of patients, who were motivated by efficacy, and vedolizumab was preferred by 30% who were driven by the preference to avoid risks. However, amongst biologic treatment options, there was considerable uncertainty regarding the preferred treatment at the individual patient level.

Conclusion

Patients with Crohn’s disease from our population were, on average, focused on the benefits of treatment, supporting intensive treatment approaches aimed at maintaining remission. Important preference heterogeneity was identified, however, highlighting the importance of shared decision making when selecting treatments.

Using a Discrete-Choice Experiment in a Decision Aid to Nudge Patients Towards Value-Concordant Treatment Choices in Rheumatoid Arthritis: A Proof-of-Concept Study

PURPOSE

To evaluate, in a proof-of-concept study, a decision aid that incorporates hypothetical choices in the form of a discrete-choice experiment (DCE), to help patients with early rheumatoid arthritis (RA) understand their values and nudge them towards a value-centric decision between methotrexate and triple therapy (a combination of methotrexate, sulphasalazine and hydroxychloroquine).

PATIENTS AND METHODS

In the decision aid, patients completed a series of 6 DCE choice tasks. Based on the patient's pattern of responses, we calculated his/her probability of choosing each treatment, using data from a prior DCE. Following pilot testing, we conducted a cross-sectional study to determine the agreement between the predicted and final stated preference, as a measure of value concordance. Secondary outcomes including time to completion and usability were also evaluated.

RESULTS

Pilot testing was completed with 10 patients and adjustments were made. We then recruited 29 patients to complete the survey: median age 57, 55% female. The patients were all taking treatment and had well-controlled disease. The predicted treatment agreed with the final treatment chosen by the patient 21/29 times (72%), similar to the expected agreement from the mean of the predicted probabilities (68%). Triple therapy was the predicted treatment 24/29 times (83%) and chosen 20/29 (69%) times. Half of the patients (51%) agreed that completing the choice questions helped them to understand their preferences (38% neutral, 10% disagreed). The tool took an average of 15 minutes to complete, and median usability scores were 55 (system usability scale) indicating "OK" usability.

CONCLUSION

Using a DCE as a value-clarification task within a decision aid is feasible, with promising potential to help nudge patients towards a value-centric decision. Usability testing suggests further modifications are needed prior to implementation, perhaps by having the DCE exercises as an "add-on" to a simpler decision aid.

Defining certainty of net benefit: a GRADE concept paper

Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology is used to assess and report certainty of evidence and strength of recommendations. This GRADE concept article is not GRADE guidance but introduces certainty of net benefit, defined as the certainty that the balance between desirable and undesirable health effects is favourable. Determining certainty of net benefit requires considering certainty of effect estimates, the expected importance of outcomes and variability in importance, and the interaction of these concepts. Certainty of net harm is the certainty that the net effect is unfavourable. Guideline panels using or testing this approach might limit strong recommendations to actions with a high certainty of net benefit or against actions with a moderate or high certainty of net harm. Recommendations may differ in direction or strength from that suggested by the certainty of net benefit or harm when influenced by cost, equity, acceptability or feasibility.

Patient Preferences for Disease-modifying Antirheumatic Drug Treatment in Rheumatoid Arthritis: A Systematic Review

Objective.

To summarize patients’ preferences for disease-modifying antirheumatic drug (DMARD) therapy in rheumatoid arthritis (RA).

Methods.

We conducted a systematic review to identify English-language studies of adult patients with RA that measured patients’ preferences for DMARD or health states and treatment outcomes relevant to DMARD decisions. Study quality was assessed using a published quality assessment tool. Data on the importance of treatment attributes and associations with patient characteristics were summarized across studies.

Results.

From 7951 abstracts, we included 36 studies from a variety of countries. Most studies were in patients with established RA and were rated as medium- (n = 19) or high-quality (n = 12). The methods to elicit preferences varied, with the most common being discrete choice experiment (DCE; n = 13). Despite the heterogeneity of attributes in DCE studies, treatment benefits (disease improvement) were usually more important than both non-serious (6 of 8 studies) and serious adverse events (5 of 8), and route of administration (7 of 9). Among the non-DCE studies, some found that patients placed high importance on treatment benefits, while others (in patients with established RA) found that patients were quite risk averse. Subcutaneous therapy was often but not always preferred over intravenous therapy. Patient preferences were variable and commonly associated with the sociodemographic characteristics.

Conclusion.

Overall, the results showed that many patients place a high value on treatment benefits over other treatment attributes, including serious or minor side effects, cost, or route of administration. The variability in patient preferences highlights the need to individualize treatment choices in RA.

P values in display items are ubiquitous and almost invariably significant: A survey of top science journals

P values represent a widely used, but pervasively misunderstood and fiercely contested method of scientific inference. Display items, such as figures and tables, often containing the main results, are an important source of P values. We conducted a survey comparing the overall use of P values and the occurrence of significant P values in display items of a sample of articles in the three top multidisciplinary journals (Nature, Science, PNAS) in 2017 and, respectively, in 1997. We also examined the reporting of multiplicity corrections and its potential influence on the proportion of statistically significant P values. Our findings demonstrated substantial and growing reliance on P values in display items, with increases of 2.5 to 14.5 times in 2017 compared to 1997. The overwhelming majority of P values (94%, 95% confidence interval [CI] 92% to 96%) were statistically significant. Methods to adjust for multiplicity were almost non-existent in 1997, but reported in many articles relying on P values in 2017 (Nature 68%, Science 48%, PNAS 38%). In their absence, almost all reported P values were statistically significant (98%, 95% CI 96% to 99%). Conversely, when any multiplicity corrections were described, 88% (95% CI 82% to 93%) of reported P values were statistically significant. Use of Bayesian methods was scant (2.5%) and rarely (0.7%) articles relied exclusively on Bayesian statistics. Overall, wider appreciation of the need for multiplicity corrections is a welcome evolution, but the rapid growth of reliance on P values and implausibly high rates of reported statistical significance are worrisome.

Measuring Patient Preferences: An Overview of Methods with a Focus on Discrete Choice Experiments

There is increasing recognition of the importance of patient preferences and methodologies to measure them. In this article, methods to quantify patient preferences are reviewed, with a focus on discrete choice experiments. In a discrete choice experiment, patients are asked to choose between 2 or more treatments. The results can be used to quantify the relative importance of treatment outcomes and/or other considerations relevant to medical decision making. Conducting and interpreting a discrete choice experiment requires multiple steps and an understanding of the potential biases that can arise, which we review in this article with examples in rheumatic diseases.