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The EQ-5D is a preference based instrument which provides a description of a respondent's health status, and an empirically derived value for that health state often from a representative sample of the general population. It is commonly used to derive Quality Adjusted Life Year calculations (QALY) in economic evaluations. However, values for health states have been found to differ between countries. The objective of this study was to develop a set of values for the EQ-5D health states for use in Canada. Values for 48 different EQ-5D health states were elicited using the Time Trade Off (TTO) via a web survey in English. A random effect model was fitted to the data to estimate values for all 243 health states of the EQ-5D. Various model specifications were explored. Comparisons with EQ-5D values from the UK and US were made. Sensitivity analysis explored different transformations of values worse than dead, and exclusion criteria of subjects. The final model was estimated from the values of 1145 subjects with socio-demographics broadly representative of Canadian general population with the exception of Quebec. This yielded a good fit with observed TTO values, with an overall R2 of 0.403 and a mean absolute error of 0.044. A preference-weight algorithm for Canadian studies that include the EQ-5D is developed. The primary limitations regarded the representativeness of the final sample, given the language used (English only), the method of recruitment, and the difficulty in the task. Insights into potential issues for conducting valuation studies in countries as large and diverse as Canada are gained.

Background Overweight and obese persons are at risk of a number of medical conditions which can lead to further morbidity and mortality. The primary objective of this study is to provide an estimate of the incidence of each co-morbidity related to obesity and overweight using a meta-analysis. Methods A literature search for the twenty co-morbidities identified in a preliminary search was conducted in Medline and Embase (Jan 2007). Studies meeting the inclusion criteria (prospective cohort studies of sufficient size reporting risk estimate based on the incidence of disease) were extracted. Study-specific unadjusted relative risks (RRs) on the log scale comparing overweight with normal and obese with normal were weighted by the inverse of their corresponding variances to obtain a pooled RR with 95% confidence intervals (CI). Results A total of 89 relevant studies were identified. The review found evidence for 18 co-morbidities which met the inclusion criteria. The meta-analysis determined statistically significant associations for overweight with the incidence of type II diabetes, all cancers except esophageal (female), pancreatic and prostate cancer, all cardiovascular diseases (except congestive heart failure), asthma, gallbladder disease, osteoarthritis and chronic back pain. We noted the strongest association between overweight defined by body mass index (BMI) and the incidence of type II diabetes in females (RR = 3.92 (95% CI: 3.10–4.97)). Statistically significant associations with obesity were found with the incidence of type II diabetes, all cancers except esophageal and prostate cancer, all cardiovascular diseases, asthma, gallbladder disease, osteoarthritis and chronic back pain. Obesity defined by BMI was also most strongly associated with the incidence of type II diabetes in females (12.41 (9.03–17.06)). Conclusion Both overweight and obesity are associated with the incidence of multiple co-morbidities including type II diabetes, cancer and cardiovascular diseases. Maintenance of a healthy weight could be important in the prevention of the large disease burden in the future. Further studies are needed to explore the biological mechanisms that link overweight and obesity with these co-morbidities.

Evaluating precision oncology outcomes requires access to real-world and clinical trial data. Access is based on consent, and consent is based on patients' informed preferences when deciding to share their data. Decision-making is often modeled using utility theory, but a complex decision context calls for a consideration of how heuristic, intuitive thought processes interact with rational utility maximization. Data-sharing decision-making has been studied using heuristic theory, but almost no heuristic research exists in the health data context. This study explores this evidence gap, applying a qualitative approach to probe for evidence of heuristic mechanisms behind the health data-sharing preferences of those who have experienced cancer. Exploring qualitative decision-making reveals the types of heuristics used and how they are related to the process of decision-making to better understand whether consent mechanisms should consider nonrational processes to better serve patient decision-making. This study aimed to explore how patients with cancer use heuristics when deciding whether to share their data for research. The researchers conducted a focus group study of Canadians who have experienced cancer. We recruited participants through an online advertisement, screening individuals based on their ability to increase demographic diversity in the sample. We reviewed the literature on data-sharing platforms to develop a semistructured topic guide on concerns about data sharing, incentives to share, and consent and control. Focus group facilitators led the open-ended discussions about data-sharing preferences that revealed underlying heuristics. Two qualitative analysts coded transcripts using a heuristic framework developed from a review of the literature. Transcripts were analyzed for heuristic instances which were grouped according to sociocultural categories. Using thematic analysis, the analysts generated reflexive themes through norming sessions and consultations. A total of 3 focus groups were held with 19 participants in total. The analysis identified 12 heuristics underlying intentions to share data. From the thematic analysis, we identified how the heuristics of social norms and community building were expressed through altruism; the recognition, reputation, and authority heuristics led to (dis)trust in certain institutions; the need for security prompted the illusion of control and transparency heuristics; and the availability and affect heuristics influenced attitudes around risk and benefit. These thematic relationships all had impacts on the participants' intentions to share their health data. The findings provide a novel qualitative understanding of how health data-sharing decisions and preferences may be based on heuristic processing. As patients consider the extent of risks and benefits, heuristic processes influence their assessment of anticipated outcomes, which may not result in rational, truly informed consent. This study shows how considering heuristic processing when designing current consent mechanisms opens up the opportunity for more meaningful and realistic interactions with the complex decision-making context.

Biologics represent a large segment of drug spending in Canada: although they constituted just 1.5% of prescription volumes, biologics accounted for 27.3% of expenditures in 2018. As of 2018, the price of biologics in Canada, including spending per capita, was second only to that in the US among the Organisation for Economic Cooperation and Development countries. Here, McClean et al evaluate the current state of biosimilar policies and use across Canada. They also discuss interchangeability and indication extrapolation before making suggestions for enhancing the market through harmonization of biosimilar policies, patient and prescriber education, and manufacturer collaboration.

Quantifying the contribution of rheumatoid arthritis to the acquisition of subsequent health care costs is an emerging focus of the rheumatologic community and payers of health care. Our objective was to determine the healthcare costs before and after diagnosis of rheumatoid arthritis (RA) from the public payer’s perspective. The study design was a longitudinal observational administrative data-based cohort with RA cases from Ontario Canada (n = 104,933) and two control groups, matched 1:1 on year of cohort entry from 2001 to 2016. The first control group was matched on age, sex and calendar year of cohort entry (diagnosis year for those with RA); the second group added medical history to the match before RA diagnosis year. The main exposure was new onset RA. The secondary exposure was calendar year of RA diagnosis to compare attributable costs over the study observation window. Main outcomes were health care costs in 2015 Canadian dollars, overall and by cost category. We used attribution methods to classify costs into those associated with RA, those associated with comorbidities, and age/sex-related underlying costs. Health care costs associated with RA increased up to the year of diagnosis, where they reached$8,591: $ 4,142 in RA associated costs;$1,242 in RA comorbidity associated costs; and $ 3,207 in underlying costs. In the eighth-year post diagnosis, the RA costs declined to$2,567 while the RA comorbidity associated costs remained relatively constant at $ 1,142, and the underlying age/sex related cost increased to $4,426. RA patients had lower costs when diagnosed in later calendar years. Our results suggest a large proportion of disease related health care costs are a result of costs associated with RA comorbidities, which may appear many years before diagnosis.

To understand preferences for and estimate the likely uptake of preventive treatments currently being evaluated in randomized controlled trials with individuals at increased risk of developing rheumatoid arthritis (RA). Focus groups were used to identify key attributes of potential preventive treatment for RA (reduction in risk of RA, how treatment is taken, chance of side effects, certainty in estimates, health care providers opinion). A web-based discrete choice experiment (DCE) was administered to people at-risk of developing RA, asking them to first choose their preferred of two hypothetical preventive RA treatments, and then between their preferred treatment and 'no treatment for now.' DCE data was analyzed using conditional logit regression to estimate the significance and relative importance of attributes in influencing preferences. Two-hundred and eighty-eight first-degree relatives (60% female; 66% aged 18-39 years) completed all tasks in the survey. Fourteen out of fifteen attribute levels significantly influenced preferences for treatments. How treatment is taken (oral vs. infusion β0.983, p<0.001), increasing reduction in risk of RA (β0.922, p<0.001), health care professional preference (β0.900, p<0.001), and avoiding irreversible (β0.839, p<0.001) or reversible serious side effects (β0.799, p<0.001) were most influential. Predicted uptake was high for non-biologic drugs (e.g. 84% hydroxycholoroquine), but very low for atorvastatin (8%) and biologics (<6%). Decisions to take preventative treatments are complex, and uptake depends on how treatments can compromise on convenience, potential risks and benefits, and recommendations/preferences of health care professionals. This evidence contributes to understanding whether different preventative treatment strategies are likely to be acceptable to target populations.

Background The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. Methods Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. Results Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. Conclusions Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

BackgroundMany seriously ill hospitalized patients have cardiopulmonary resuscitation (CPR) as part of their care plan, but CPR is unlikely to achieve the goals of many seriously ill hospitalized patients.ObjectiveTo determine if a multicomponent decision support intervention changes documented orders for CPR in the medical record, compared to usual care.DesignOpen-label randomized controlled trial.PatientsPatients on internal medicine and neurology wards at two tertiary care teaching hospitals who had a 1-year mortality greater than 10% as predicted with a validated model and whose care plan included CPR, if needed.InterventionBoth the control and intervention groups received usual communication about CPR at the discretion of their care team. The intervention group participated in a values clarification exercise and watched a CPR video decision aid.Main MeasureThe primary outcome was the proportion of patients who had a no-CPR order at 14 days after enrollment.Key ResultsWe recruited 200 patients between October 2017 and October 2018. Mean age was 77 years. There was no difference between the groups in no-CPR orders 14 days after enrollment (17/100 (17%) intervention vs 17/99 (17%) control, risk difference, − 0.2%) (95% confidence interval − 11 to 10%; p = 0.98). In addition, there were no differences between groups in decisional conflict summary score or satisfaction with decision-making. Patients in the intervention group had less conflict about understanding treatment options (decisional conflict knowledge subscale score mean (SD), 17.5 (26.5) intervention arm vs 40.4 (38.1) control; scale range 0–100 with lower scores reflecting less conflict).ConclusionsAmong seriously ill hospitalized patients who had CPR as part of their care plan, this decision support intervention did not increase the likelihood of no-CPR orders compared to usual care.Primary Funding SourceCanadian Frailty Network, The Ottawa Hospital Academic Medical Organization.

ObjectiveTo elicit and compare preferences of patients and first-degree relatives and rheumatologists for preventive treatments for rheumatoid arthritis, understand the influence of shared decision-making, and predict the probability of uptake of the preventive treatments currently being studied.MethodsAn online discrete choice experiment was completed by patients and their first-degree relatives and rheumatologists. Results were analysed using mixed logit model to estimate preferences for the key features of treatments. Preferences for features of treatments were used to predict the probability of uptake of seven preventive treatment options.ResultsA total of 108 potential recipients (78 patients and 30 of their first-degree relatives) and 39 rheumatologists completed the survey. Preferences of patients/first-degree relatives and rheumatologists were similar (shared decision-making was most important, followed by the risk of side effects and potential benefit), but subtle differences existed; rheumatologists placed greater importance on certainty in evidence than patients/first-degree relatives, who felt that how a treatment was taken was more important. Predicted uptake suggested that 38% (95% CI 19%, 58%) of patients/first-degree relatives would not take a preventive treatment, compared with 12% (95% CI − 4%, 27%) of rheumatologists. A consistent finding across all groups was a preference for non-biologic disease-modifying anti-rheumatic drugs.ConclusionOnly relatively safe options for preventive treatment are likely to be acceptable to at-risk populations. This study of preventive treatments highlights that the preferences of physicians and recipients of treatment should take a central role in the design of clinical studies as well as in decisions to initiate treatments.Key Points• This paper is the first to compare preferences for preventive treatments between rheumatologists and patients and at-risk individuals.• The results of this study indicate that patients and at-risk individuals, as well as rheumatologists, are likely to prefer the safest options as preventive treatment, even if the potential benefit of these is lower.• Although preferences of patients and at-risk individuals are similar to those of rheumatologists, the choice of preventive treatment may differ between groups; this is important as shared decision-making was a critical factor in treatment decision-making.• Preferences of physicians and recipients of treatment should take a central role in the design of clinical studies as well as in decisions to initiate treatments.

Background While the rates of total knee arthroplasty (TKA) continue to rise worldwide, there are concerns about whether all surgeries are appropriate. Guidelines for appropriateness suggest that patients should have realistic expectations for total knee arthroplasty (TKA), and that the patient and their surgeon should agree that the potential benefits outweigh the potential harms. The objective of this study is to evaluate whether routinely collected pre- and post-TKA patient-reported outcome measures (PROMs) could be integrated into a patient decision aid to better inform these appropriateness criteria. This randomised trial will evaluate the preliminary efficacy of a tailored PROM-based patient decision aid and surgeon report (compared to usual care) for patients considering TKA on decision quality. Methods This is a pragmatic, randomised controlled trial conducted at one site in Alberta, Canada. Adults over the age of 30 years, who have been scheduled for a TKA consultation at the Edmonton Bone and Joint Centre with a participating surgeon, who understand, speak, and read English, and can provide informed consent, are eligible to participate. Participants will be randomised to receive a PROM-based patient decision aid and surgeon report before their surgical consultation or usual care. The decision aid will provide patients with information on their expected outcomes based on the EQ-5D-5L PROM, and these estimates are individualized based on clinical and demographic characteristics. The primary outcome of this trial is decision quality. Analysis will consider outcomes intention to treat, and feasibility outcomes for implementing the trial to routine practise. Discussion This patient decision aid and surgeon report intervention could contribute to improved treatment decision-making for patients considering total knee arthroplasty. Trial registration (registry and number) ClinicalTrials.gov : NCT03240913. Registered on August 1, 2017.