Chris Sampson’s journal round-up for 19th February 2018

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function. BMC Medical Research Methodology [PubMed] Published 8th February 2018

Statistical significance – whatever you think of it – and the ‘power’ of clinical trials to detect change, is an important decider in clinical decision-making. Trials are designed to be big enough to detect ‘statistically significant’ differences. But in the context of rare diseases, this can be nigh-on impossible. In theory, the required sample size could exceed the size of the whole population. This paper describes an alternative method for determining sample sizes for trials in this context, couched in a value of information framework. Generally speaking, power calculations ignore the ‘value’ or ‘cost’ associated with errors, while a value of information analysis would take this into account and allow accepted error rates to vary accordingly. The starting point for this study is the notion that sample sizes should take into account the size of the population to which the findings will be applicable. As such, sample sizes can be defined on the basis of maximising the expected (societal) utility associated with the conduct of the trial (whether the intervention is approved or not). The authors describe the basis for hypothesis testing within this framework and specify the utility function to be maximised. Honestly, I didn’t completely follow the stats notation in this paper, but that’s OK – the trial statisticians will get it. A case study application is presented from the context of treating children with severe haemophilia A, which demonstrates the potential to optimise utility according to sample size. The key point is that the power is much smaller than would be required by conventional methods and the sample size accordingly reduced. The authors also demonstrate the tendency for the optimal trial sample size to increase with the size of the population. This Bayesian approach at least partly undermines the frequentist basis on which ‘power’ is usually determined. So one issue is whether regulators will accept this as a basis for defining a trial that will determine clinical practice. But then regulators are increasingly willing to allow for special cases, and it seems that the context of rare diseases could be a way-in for Bayesian trial design of this sort.

EQ-5D-5L: smaller steps but a major step change? Health Economics [PubMed] Published 7th February 2018

This editorial was doing the rounds on Twitter last week. European (and Canadian) health economists love talking about the EQ-5D-5L. The editorial features in the edition of Health Economics that hosts the 5L value set for England, which – 2 years on – has finally satisfied the vagaries of academic publication. The authors provide a summary of what’s ‘new’ with the 5L, and why it matters. But we’ve probably all figured that out by now anyway. More interestingly, the editorial points out some remaining concerns with the use of the EQ-5D-5L in England (even if it is way better than the EQ-5D-3L and its 25-year old value set). For example, there is some clustering in the valuations that might reflect bias or problems with the technique and – even if they’re accurate – present difficulties for analysts. And there are also uncertain implications for decision-making that could systematically favour or disfavour particular treatments or groups of patients. On this basis, the authors support NICE’s decision to ‘pause’ and await independent review. I tend to disagree, for reasons that I can’t fit in this round-up, so come back tomorrow for a follow-up blog post.

Factors influencing health-related quality of life in patients with Type 1 diabetes. Health and Quality of Life Outcomes [PubMed] Published 2nd February 2018

Diabetes and its complications can impact upon almost every aspect of a person’s health. It isn’t clear what aspects of health-related quality of life might be amenable to improvement in people with Type 1 diabetes, or which characteristics should be targeted. This study looks at a cohort of trial participants (n=437) and uses regression analyses to determine which factors explain differences in health-related quality of life at baseline, as measured using the EQ-5D-3L. Age, HbA1c, disease duration and being obese all significantly influenced EQ-VAS values, while self-reported mental illness and unemployment status were negatively associated with EQ-5D index scores. People who were unemployed were more likely to report problems in the mobility, self-care, and pain/discomfort domains. There are some minor misinterpretations in the paper (divining a ‘reduction’ in scores from a cross-section, for example). And the use of standard linear regression models is questionable given the nature of EQ-5D-3L index values. But the findings demonstrate the importance of looking beyond the direct consequences of a disease in order to identify the causes of reduced health-related quality of life. Getting people back to work could be more effective than most health care as a means of improving health-related quality of life.

Financial incentives for chronic disease management: results and limitations of 2 randomized clinical trials with New York Medicaid patients. American Journal of Health Promotion [PubMed] Published 1st February 2018

Chronic diseases require (self-)management, but it isn’t always easy to ensure that patients adhere to the medication or lifestyle changes that could improve health outcomes. This study looks at the effectiveness of financial incentives in the context of diabetes and hypertension. The data are drawn from 2 RCTs (n=1879) which, together, considered 3 types of incentive – process-based, outcome-based, or a combination of the two – compared with no financial incentives. Process-based incentives rewarded participants for attending primary care or endocrinologist appointments and filling their prescriptions, up to a maximum of $250. Outcome-based incentives rewarded up to $250 for achieving target reductions in systolic blood pressure or blood glucose levels. The combined arms could receive both rewards up to the same maximum of $250. In short, none of the financial incentives made any real difference. But generally speaking, at 6-month follow-up, the movement was in the right direction, with average blood pressure and blood glucose levels tending to fall in all arms. It’s not often that authors include the word ‘limitations’ in the title of a paper, but it’s the limitations that are most interesting here. One key difficulty is that most of the participants had relatively acceptable levels of the target outcomes at baseline, meaning that they may already have been managing their disease well and there may not have been much room for improvement. It would be easy to interpret these findings as showing that – generally speaking – financial incentives aren’t effective. But the study is more useful as a way of demonstrating the circumstances in which we can expect financial incentives to be ineffective, and support a better-informed targeting for future programmes.

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Alastair Canaway’s journal round-up for 29th January 2018

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Is “end of life” a special case? Connecting Q with survey methods to measure societal support for views on the value of life-extending treatments. Health Economics [PubMed] Published 19th January 2018

Should end-of-life care be treated differently? A question often asked and previously discussed on this blog: findings to date are equivocal. This question is important given NICE’s End-of-Life Guidance for increased QALY thresholds for life-extending interventions, and additionally the Cancer Drugs Fund (CDF). This week’s round-up sees Helen Mason and colleagues attempt to inform the debate around societal support for views of end-of-life care, by trying to determine the degree of support for different views on the value of life-extending treatment. It’s always a treat to see papers grounded in qualitative research in the big health economics journals and this month saw the use of a particularly novel mixed methods approach adding a quantitative element to their previous qualitative findings. They combined the novel (but increasingly recognisable thanks to the Glasgow team) Q methodology with survey techniques to examine the relative strength of views on end-of-life care that they had formulated in a previous Q methodology study. Their previous research had found that there are three prevalent viewpoints on the value of life-extending treatment: 1. ‘a population perspective: value for money, no special cases’, 2. ‘life is precious: valuing life-extension and patient choice’, 3. ‘valuing wider benefits and opportunity cost: the quality of life and death’. This paper used a large Q-based survey design (n=4902) to identify societal support for the three different viewpoints. Viewpoints 1 and 2 were found to be dominant, whilst there was little support for viewpoint 3. The two supported viewpoints are not complimentary: they represent the ethical divide between the utilitarian with a fixed budget (view 1), and the perspective based on entitlement to healthcare (view 2: which implies an expanding healthcare budget in practice). I suspect most health economists will fall into camp number one. In terms of informing decision making, this is very helpful, yet unhelpful: there is no clear answer. It is, however, useful for decision makers in providing evidence to balance the oft-repeated ‘end of life is special’ argument based solely on conjecture, and not evidence (disclosure: I have almost certainly made this argument before). Neither of the dominant viewpoints supports NICE’s End of Life Guidance nor the CDF. Viewpoint 1 suggests end of life interventions should be treated the same as others, whilst viewpoint 2 suggests that treatments should be provided if the patient chooses them; it does not make end of life a special case as this viewpoint believes all treatments should be available if people wish to have them (and we should expand budgets accordingly). Should end of life care be treated differently? Well, it depends on who you ask.

A systematic review and meta-analysis of childhood health utilities. Medical Decision Making [PubMed] Published 7th October 2017

If you’re working on an economic evaluation of an intervention targeting children then you are going to be thankful for this paper. The purpose of the paper was to create a compendium of utility values for childhood conditions. A systematic review was conducted which identified a whopping 26,634 papers after deduplication – sincere sympathy to those who had to do the abstract screening. Following abstract screening, data were extracted for the remaining 272 papers. In total, 3,414 utility values were included when all subgroups were considered – this covered all ICD-10 chapters relevant to child health. When considering only the ‘main study’ samples, 1,191 utility values were recorded and these are helpfully separated by health condition, and methodological characteristics. In short, the authors have successfully built a vast catalogue of child utility values (and distributions) for use in future economic evaluations. They didn’t, however, stop there, they then built on the systematic review results by conducting a meta-analysis to i) estimate health utility decrements for each condition category compared to general population health, and ii) to examine how methodological factors impact child utility values. Interestingly for those conducting research in children, they found that parental proxy values were associated with an overestimation of values. There is a lot to unpack in this paper and a lot of appendices and supplementary materials are included (including the excel database for all 3,414 subsamples of health utilities). I’m sure this will be a valuable resource in future for health economic researchers working in the childhood context. As far as MSc dissertation projects go, this is a very impressive contribution.

Estimating a cost-effectiveness threshold for the Spanish NHS. Health Economics [PubMed] [RePEc] Published 28th December 2017

In the UK, the cost-per-QALY threshold is long-established, although whether it is the ‘correct’ value is fiercely debated. Likewise in Spain, there is a commonly cited threshold value of €30,000 per QALY with a dearth of empirical justification. This paper sought to identify a cost-per-QALY threshold for the Spanish National Health Service (SNHS) by estimating the marginal cost per QALY at which the SNHS currently operates on average. This was achieved by exploiting data on 17 regional health services between the years 2008-2012 when the health budget experienced considerable cuts due to the global economic crisis. This paper uses econometric models based on the provoking work by Claxton et al in the UK (see the full paper if you’re interested in the model specification) to achieve this. Variations between Spanish regions over time allowed the authors to estimate the impact of health spending on outcomes (measured as quality-adjusted life expectancy); this was then translated into a cost-per-QALY value for the SNHS. The headline figures derived from the analysis give a threshold between €22,000 and €25,000 per QALY. This is substantially below the commonly cited threshold of €30,000 per QALY. There are, however (as to be expected) various limitations acknowledged by the authors, which means we should not take this threshold as set in stone. However, unlike the status quo, there is empirical evidence backing this threshold and it should stimulate further research and discussion about whether such a change should be implemented.

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Paul Mitchell’s journal round-up for 6th November 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

A longitudinal study to assess the frequency and cost of antivascular endothelial therapy, and inequalities in access, in England between 2005 and 2015. BMJ Open [PubMed] Published 22nd October 2017

I am breaking one of my unwritten rules in a journal paper round-up by talking about colleagues’ work, but I feel it is too important not to provide a summary for a number of reasons. The study highlights the problems faced by regional healthcare purchasers in England when implementing national guideline recommendations on the cost-effectiveness of new treatments. The paper focuses on anti-vascular endothelial growth factor (anti-VEGF) medicines in particular, with two drugs, ranibizumab and aflibercept, offered to patients with a range of eye conditions, costing £550-800 per injection. Another drug, bevacizumab, that is closely related to ranibizumab and performs similarly in trials, could be provided at a fraction of the cost (£50-100 per injection), but it is currently unlicensed for eye conditions in the UK. This study investigates how the regional areas in England have coped with trying to provide the recommended drugs using administrative data from Hospital Episode Statistics in England between 2005-2015 by tracking their use since they have been recommended for a number of different eye conditions over the past decade. In 2014/15 the cost of these two new drugs for treating eye conditions alone was estimated at £447 million nationally. The distribution of where these drugs are provided is not equal, varying widely across regions after controlling for socio-demographics, suggesting an inequality of access associated with the introduction of these high-cost drugs over the past decade at a time of relatively low growth in national health spending. Although there are limitations associated with using data not intended for research purposes, the study shows how the most can be made from data routinely collected for non-research purposes. On a public policy level, it raises questions over the provision of such high-cost drugs, for which the authors state the NHS are currently paying more for than US insurers. Although it is important to be careful when comparing to unlicensed drugs, the authors point to clear evidence in the paper as to why their comparison is a reasonable one in this scenario, with a large opportunity cost associated with not including this option in national guidelines. If national recommendations continue to insist that such drugs be provided, clearer guidance is also required on how to disinvest from existing services at a regional level to reduce further examples of inequality in access in the future.

In search of a common currency: a comparison of seven EQ-5D-5L value sets. Health Economics [PubMed] Published 24th October 2017

For those of us out there who like a good valuation study, you will need to set yourself aside a good piece of time to work your way through this one. The new EQ-5D-5L measure of health status, with a primary purpose of generating quality-adjusted life years (QALYs) for economic evaluations, is now starting to have valuation studies emerging from different countries, whereby the relative importance of each of the measure dimensions and levels are quantified based on general population preferences. This study offers the first comparison of value sets across seven countries: 3 Western European (England, Netherlands, Spain), 1 North American (Canada), 1 South American (Uruguay), and two East Asian (Japan and South Korea). The authors in this paper aim to describe methodological differences between the seven value sets, compare the relative importance of dimensions, level decrements and scale length (i.e. quality/quantity trade-offs for QALYs), as well as developing a common (Western) currency across four of the value sets. In brief summary, there does appear to be similar trends across the three Western European countries: level decrements from levels 3 to 4 have the largest value, followed by levels 1 to 2. There is also a pattern in these three countries’ dimensions, whereby the two “symptom” dimensions (i.e. pain/discomfort, anxiety/depression) have equal importance to the other three “functioning” dimensions (i.e. mobility, self-care and usual activities). There are also clear differences with the other four value sets. Canada, although it also has the highest level decrements between levels 3 and 4 (49%), unusually has equal decrements for the remainder (17% x 3). For the other three countries, greater weight is attached to the three functioning dimensions relative to the two symptom dimensions. Although South Korea also has the greatest level decrements between level 3 and 4, it was greatest between level 4 and level 5 in Uruguay and levels 1 and 2 in Japan. Although the authors give a number of plausible reasons as to why these differences may occur, less justification is given in the choice of the four value sets they offer as a common currency, beyond the need to have a value set for countries that do not have one already. The most in-common value sets were the three Western European countries, so a Western European value set may have been more appropriate if the criterion was to have comparable values across countries. If the aim was really for a more international common currency, there are issues with the exclusion of non-Western countries’ value sets from their common currency version. Surely differences across cultures should be reflected in a common currency if they are apparent in different cultures and settings. A common currency should also have a better spread of regions geographically, with no country from Africa, the Middle East, Central and South Asia represented in this study, as well as no lower- and middle-income countries. Though this final criticism is out of the control of the authors based on current data availability.

Quantifying the relationship between capability and health in older people: can’t map, won’t map. Medical Decision Making [PubMed] Published 23rd October 2017

The EQ-5D is one of many ways quality of life can be measured within economic evaluations. A more recent way based on Amartya Sen’s capability approach has attempted to develop outcome measures that move beyond health-related aspects of quality of life captured by EQ-5D and similar measures used in the generation of QALYs. This study examines the relationship between the EQ-5D and the ICECAP-O capability measure in three different patient populations included in the Medical Crises in Older People programme in England. The authors propose a reasonable hypothesis that health could be considered a conversion factor for a person’s broader capability set, and so it is plausible to test how well the EQ-5D-3L dimension values and overall score can map onto the ICECAP-O overall score. Through numerous regressions performed, the strongest relationship between the two measures in this sample was an R-squared of 0.35. Interestingly, the dimensions on the EQ-5D that had a significant relationship with the ICECAP-O score were a mix of dimensions with a focus on functioning (i.e. self-care, usual activities) and symptoms (anxiety/depression), so overall capability on ICECAP-O appears to be related, at least to a small degree, to both health components of EQ-5D discussed in this round-up’s previous paper. The authors suggest it provides further evidence of the complementary data provided by EQ-5D and ICECAP-O, but the causal relationship, as the authors suggest, between both measures remains under-researched. Longitudinal data analysis would provide a more definitive answer to the question of how much interaction there is between these two measures and their dimensions as health and capability changes over time in response to different treatments and care provision.

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