Chris Sampson’s journal round-up for 13th January 2020

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 vision ‘bolt-on’ increases the responsiveness of EQ-5D: preliminary evidence from a study of cataract surgery. The European Journal of Health Economics [PubMed] Published 4th January 2020

The EQ-5D is insensitive to differences in how well people can see, despite this seeming to be an important aspect of health. In contexts where the impact of visual impairment may be important, we could potentially use a ‘bolt-on’ item that asks about a person’s vision. I’m working on the development of a vision bolt-on at the moment. But ours won’t be the first. A previously-developed bolt-on has undergone some testing and has been shown to be sensitive to differences between people with different levels of visual function. However, there is little or no evidence to support its responsiveness to changes in visual function, which might arise from treatment.

For this study, 63 individuals were recruited prior to receiving cataract surgery in Singapore. Participants completed the EQ-5D-3L and EQ-5D-5L, both with and without a vision bolt-on, which matched the wording of other EQ-5D dimensions. Additionally, the SF-6D, HUI3, and VF-12 were completed along with a LogMAR assessment of visual acuity. The authors sought to compare the responsiveness of the EQ-5D with a vision bolt-on compared with the standard EQ-5D and the other measures. Therefore, all measures were completed before and after cataract surgery. Preference weights can be generated for the EQ-5D-3L with a vision bolt-on, but they can’t for the EQ-5D-5L, so the authors looked at rescaled sum scores to compare across all measures. Responsiveness was measured using indicators such as standardised effect size and response mean.

Visual acuity changed dramatically before and after surgery, for almost everybody. The authors found that the vision bolt-on does seem to provide a great deal more in the way of response to this, compared to the EQ-5D without the bolt-on. For instance, the mean change in the EQ-5D-3L index score was 0.018 without the vision bolt-on, and 0.031 with it. The HUI3 came out with a mean change of 0.105 and showed the highest responsiveness across all analyses.

Does this mean that we should all be using a vision bolt-on, or perhaps the HUI3? Not exactly. Something I see a lot in papers of this sort – including in this one – is the framing of a “superior responsiveness” as an indication that the measure is doing a better job. That isn’t true if the measure is responding to things to which we don’t want it to respond. As the authors point out, the HUI3 has quite different foundations to the EQ-5D. We also don’t want a situation where analysts can pick and choose measures according to which ever is most responsive to the thing to which they want it to be most responsive. In EuroQol parlance, what goes into the descriptive system is very important.

The causal effect of social activities on cognition: evidence from 20 European countries. Social Science & Medicine Published 9th January 2020

Plenty of studies have shown that cognitive abilities are correlated with social engagement, but few have attempted to demonstrate causality in a large sample. The challenge, of course, is that people who engage in more social activities are likely to have greater cognitive abilities for other reasons, and people’s decision to engage in social activities might depend on their cognitive abilities. This study tackles the question of causality using a novel (to me, at least) methodology.

The analysis uses data from five waves of SHARE (the Survey of Health, Ageing and Retirement in Europe). Survey respondents are asked about whether they engage in a variety of social activities, such as voluntary work, training, sports, or community-related organisations. From this, the authors generate an indicator for people participating in zero, one, or two or more of these activities. The survey also uses a set of tests to measure people’s cognitive abilities in terms of immediate recall capacity, delayed recall capacity, fluency, and numeracy. The authors look at each of these four outcomes, with 231,407 observations for the first three and 124,381 for numeracy (for which the questions were missing from some waves). Confirming previous findings, a strong positive correlation is found between engagement in social activities and each of the cognition indicators.

The empirical strategy, which I had never heard of, is partial identification. This is a non-parametric method that identifies bounds for the average treatment effect. Thus, it is ‘partial’ because it doesn’t identify a point estimate. Fewer assumptions means wider and less informative bounds. The authors start with a model with no assumptions, for which the lower bound for the treatment effect goes below zero. They then incrementally add assumptions. These include i) a monotone treatment response, assuming that social participation does not reduce cognitive abilities on average; ii) monotone treatment selection, assuming that people who choose to be socially active tend to have higher cognitive capacities; iii) a monotone instrumental variable assumption that body mass index is negatively associated with cognitive abilities. The authors argue that their methodology is not likely to be undermined by unobservables, as previous studies might.

The various models show that engaging in social activities has a positive impact on all four of the cognitive indicators. The assumption of monotone treatment response had the highest identifying power. For all models that included this, the 95% confidence intervals in the estimates showed a statistically significant positive impact of social activities on cognition. What is perhaps most interesting about this approach is the huge amount of uncertainty in the estimates. Social activities might have a huge effect on cognition or they might have a tiny effect. A basic OLS-type model, assuming exogenous selection, provides very narrow confidence intervals, whereas the confidence intervals on the partial identification models are almost as wide as the lower and upper band themselves.

One shortcoming of this study for me is that it doesn’t seek to identify the causal channels that have been proposed in previous literature (e.g. loneliness, physical activity, self-care). So it’s difficult to paint a clear picture of what’s going on. But then, maybe that’s the point.

Do research groups align on an intervention’s value? Concordance of cost-effectiveness findings between the Institute for Clinical and Economic Review and other health system stakeholders. Applied Health Economics and Health Policy [PubMed] Published 10th January 2020

Aside from having the most inconvenient name imaginable, ICER has been a welcome edition to the US health policy scene, appraising health technologies in order to provide guidance on coverage. ICER has become influential, with some pharmacy benefit managers using their assessments as a basis for denying coverage for low value medicines. ICER identify technologies as falling in one of three categories – high, low, or intermediate long-term value – according to whether the ICER (grr) falls below, above, or between the threshold range of $50,000-$175,000 per QALY. ICER conduct their own evaluations, but so do plenty of other people. This study sought to find out whether other analyses in the literature agree with ICER’s categorisations.

The authors consider 18 assessments by ICER, including 76 interventions, between 2015 and 2017. For each of these, the authors searched the literature for other comparative studies. Specifically, they went looking for cost-effectiveness analyses that employed the same perspectives and outcomes. Unfortunately, they were only able to identify studies for six disease areas and 14 interventions (of the 76), across 25 studies. It isn’t clear whether this is because there is a lack of literature out there – which would be an interesting finding in itself – or because their search strategy or selection criteria weren’t up to scratch. Of the 14 interventions compared, 10 get a more favourable assessment in the published studies than in their corresponding ICER evaluations, with most being categorised as intermediate value instead of low value. The authors go on to conduct one case study, comparing an ICER evaluation in the context of migraine with a published study by some of the authors of this paper. There were methodological differences. In some respects, it seems as if ICER did a more thorough job, while in other respects the published study seemed to use more defensible assumptions.

I agree with the authors that these kinds of comparisons are important. Not least, we need to be sure that ICER’s approach to appraisal is valid. The findings of this study suggest that maybe ICER should be looking at multiple studies and combining all available data in a more meaningful way. But the authors excluded too many studies. Some imperfect comparisons would have been more useful than exclusion – 14 of 76 is kind of pitiful and probably not representative. And I’m not sure why the authors set out to identify studies that are ‘more favourable’, rather than just different. That perspective seems to reveal an assumption that ICER are unduly harsh in their assessments.

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Rita Faria’s journal round-up for 30th December 2019

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 in hepatitis C virus treatment: a patient-centered cost-effectiveness analysis. PharmacoEconomics [PubMed] Published 2nd December 2019

There have been many economic evaluations of treatments for viral hepatitis C. The usual outcomes are costs and a measure of quality-adjusted survival, such as QALYs. But health-related quality of life and life expectancy may not be the only important outcomes for patients. This fascinating paper by Joe Mattingly II and colleagues fills in the gap by collaborating with patients in the development of an economic evaluation of treatments for viral hepatitis C.

Patient engagement was guided by a stakeholder advisory board including health care professionals, four patients and a representative of a national patient advocacy organisation. This board reviewed the model design, model inputs and presentation of results. To ensure that the economic evaluation included what is important to patients, the team conducted a Delphi process with patients who had received treatment or were considering treatment. This is reported in a separate paper.

The feedback from patients led to the inclusion of two outcomes beyond QALYs and costs: infected life-years, which relate to the patient’s fear of infecting others, and workdays missed, which relate to financial issues and impact on work and career.

I was impressed with the effort put into engaging with patients and stakeholders. For example, there were 11 meetings with the stakeholder advisory board. This shows that engaging with stakeholders takes time and energy to do right! The challenge with the patient-centric outcome measures is in using them to make decisions. From an individual or an employer’s perspective, it may be useful to have results in terms of costs per workday missed avoided, for example, if these can then be compared to a maximum acceptable cost. As suggested by the authors, an interesting next step would be to seek feedback from managed care organisations. Whether such measures would be useful to inform decisions in publicly funded healthcare services is less clear.

Patient engagement is all the rage at present, but there’s not much guidance on how to do it in practice. This paper is a great example of how to go about it.

TECH-VER: a verification checklist to reduce errors in models and improve their credibility. PharmacoEconomics [PubMed] [RePEc] Published 8th November 2019

Looking for help in checking your decision model? Fear not, there’s a new tool on the block! The TECH-VER checklist lists a set of steps to assess the internal validity of your model.

I have to admit that I’m getting a bit weary of checklists, but this one is truly useful. It’s divided into five areas: model inputs, event/state calculations, results, uncertainty analysis, and overall validation and other supplementary checks. Each area includes an assessment of the completeness of the calculations in the electronic model, their consistency with the technical report, and then steps to check their correctness.

Correctness is assessed with a series of black-box, white-box, and replication-based tests. Black-box tests involve changing parameters in the model and checking if the results change as expected. For example, if the HRQOL weights=1 and decrements=0, the QALYs should be the same as the life years. White-box testing involves checking the calculations one by one. Replication-based tests involve redoing calculations independently.

The authors’ handy tip is to apply the checks in ascending order of effort and time: starting first with black-box tests, then conducting white-box tests only for priority calculations or if there are unexpected results. I recommend this paper to all cost-effectiveness modellers. TECH-VER will definitely feature in my toolbox!

Proposals on Kaplan-Meier plots in medical research and a survey of stakeholder views: KMunicate. BMJ Open [PubMed] Published 30th September 2019

What’s your view of the Kaplan-Meier plot? I find it quite difficult to explain to non-specialist audiences, particularly the uncertainty in the differences in survival time between treatment groups. It seems that I’m not the only one!

Tim Morris and colleagues agree that Kaplan-Meier can be difficult to interpret. To address this, they proposed improvements to better show the status of patients over time and the uncertainty around those estimates. They then assessed the proposed improvements with a survey of researchers. Similar to my own views, the majority of respondents preferred having a table with the number of patients who had the events and who were censored to show the status of patients over time, and confidence intervals to show the uncertainty.

The Kaplan-Meier plot with confidence intervals and the table would definitely help me to interpret and explain Kaplan-Meier plots. Also, the proposed improvements seem to be straightforward to implement. One way to make it easy for researchers to implement these plots in practice would be to publish the code to replicate the preferred plots.

There is a broader question, outside the scope of this project, about how to convey survival times and their uncertainty to untrained audiences, from health care professionals and managers to patients. Would audience-specific tools be the answer? Or should we try to up-skill the audience to understand a Kaplan-Meier plot?

Better communication is surely key if we want to engage stakeholders with research and if our research is to have an impact on policy. I, for one, would be grateful for more guidance on how to communicate research. This study is an excellent first step in making a specialist tool – the Kaplan-Meier plot – easier to understand.

Cost-effectiveness of strategies preventing late-onset infection in preterm infants. Archives of Disease in Childhood [PubMed] Published 13th December 2019

And lastly, a plug for my own paper! This article reports the cost-effectiveness analysis conducted for a ‘negative’ trial. The PREVAIL trial found that the experimental intervention – anti-microbial impregnated peripherally inserted central catheters (AM-PICCs) – had no effect compared to the standard PICCS, which are used in the NHS. AM-PICCs are more costly than standard PICCs. Clearly, AM-PICCs are not cost-effective. So, you may ask, why conduct a cost-effectiveness analysis and develop a new model?

Developing a model to evaluate the cost-effectiveness of AM-PICCs was one of the project’s objectives. We started the economic work pretty early on. By the time that the trial reported, the model was already built, tested with data from the literature, and all ready to receive the trial data. Wasted effort? Not at all!

Thanks to this cost-effectiveness analysis, we have concluded that avoiding neurodevelopmental impairment in children born preterm is very beneficial; hence warranting a large investment by the NHS. If we believe the observational evidence that infection causes neurodevelopmental impairment, interventions that reduce the risk of infection can be cost-effective.

The linkage to Hospital Episode Statistics, National Neonatal Research Database and Paediatric Intensive Care Audit Network allowed us to get a good picture of the hospital care and costs of the babies in the PREVAIL trial. This informed some of the cost inputs in the cost-effectiveness model.

If you’re planning a cost-effectiveness analysis of strategies to prevent infections and/or neurodevelopmental impairment in preterm babies, do feel free to get in touch!

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Meeting round-up: ISPOR Europe 2019

For many health economists, November is ISPOR Europe month, and this year was no exception! We gathered in the fantastic Bella Center in Copenhagen to debate, listen and breathe health economics and outcomes research from the 2nd to the 6th November. Missed it? Would like a recap? Stay tuned for the #ISPOREurope 2019 round-up!

Bella Center

My ISPOR week started with the fascinating course ‘Tools for reproducible real-world data analysis’ by Blythe Adamson and Rachael Sorg. My key take-home messages? Use an interface like R-markdown to produce a document with code and results automatically. Use a version control platform like Phabricator to make code review easy. Write a detailed protocol, write the code to follow the protocol, and then check the code side by side with the protocol.

Monday started with the impressive workshop on translating oncology clinical trial endpoints to real-world data (RWD) for decision making.

Keith Abrams set the scene. Electronic health records (EHRs) may be used to derive the overall survival (OS) benefit given the observed benefit on progression-free survival (PFS). Sylwia Bujkiewicz showed an example where a bivariate meta-analysis of RCTs was used to estimate the surrogate relationship between PFS and OS (paper here). Jessica Davies discussed some of the challenges, such as the lack of data on exposure to treatments in a way that matches the data recorded in trials. Federico Felizzi presented a method to determine the optimal treatment duration of a cancer drug (see here for the code).

Next up, the Women in HEOR session! Women in HEOR is an ISPOR initiative that aims to support the growth, development, and contribution of women. It included various initiatives at ISPOR Europe, such as dinners, receptions and, of course, this session.

Shelby Reed introduced, and Olivia Wu presented on the overwhelming evidence on the benefits of diversity and on how to foster it in our work environment. Nancy Berg presented on ISPOR’s commitment to diversity and equality. We then heard from Sabina Hutchison about how to network in a conference environment, how to develop a personal brand and present our pitch. Have a look at my twitter thread for the tips. For more information on the Women in HEOR activities at ISPOR Europe, search #WomenInHEOR on twitter. Loads of cool information!

My Monday afternoon started with the provocatively titled ‘Time for change? Has time come for the pharma industry to accept modest prices?’. Have a look here for my live twitter thread. Kate Dion started by noting that the pressure is on for the pharmaceutical industry to reduce drug prices. Sarah Garner argued that lower prices lead to more patients being able to access the drug, which in turn increases the company’s income. Michael Schröter argued that innovative products should have a premium price, such as with Hemlibra. Lastly, Jens Grueger supported the implementation of value-based price, given the cost-effectiveness threshold.

Keeping with the drug pricing theme, my next session was on indication-based pricing. Mireia Jofre Bonet tackled the question of whether a single price is stifling innovation. Adrian Towse was supportive of indication-based pricing because it allows for the price to depend on the value of each indication and expand access to the full licensed population. Andrew Briggs argued against indication-based pricing for three reasons. First, it would give companies the maximum value-based price across all indications. Second, it would lead to greater drug expenditure, leading to greater opportunity costs. Third, it would be difficult to enforce, given that it would require cooperation of all payers. Francis Arickx explained the pricing system in Belgium. Remarkably, prices can be renegotiated over time depending on new entrants to market and new evidence. Another excellent session at ISPOR Europe!

My final session on Monday was about the timely and important topic of approaches for OS extrapolation. Elisabeth Fenwick introduced the session by noting that innovations in oncology have given rise to different patterns of survival, with implications for extrapolation. Sven Klijn presented on the various available methods for survival extrapolation. John Whalen focused on mixture cure models for cost-effectiveness analysis. Steve Palmer argued that, although new methods, such as mixture cure models, may provide additional insight, the approach should be justified, evidence-based and alternatives explored. In sum, there is no single optimal method.

On Tuesday, my first session was the impressive workshop on estimating cost-effectiveness thresholds based on the opportunity cost (twitter thread). Nancy Devlin set the scene by explaining the importance of getting the cost-effectiveness threshold right. James Lomas explained how to estimate the opportunity cost to the health care system following the seminal work by Karl Claxton et al and also touching on some of James’s recent work. Martin Henriksson noted that, by itself, the opportunity cost is not sufficient to define the threshold if we wish to consider solidarity and need alongside cost-effectiveness. The advantage of knowing the opportunity cost is that we can make informed trade-offs between health maximisation and other elements of value. Danny Palnoch finished the panel by explaining the challenges when deciding what to pay for a new treatment.

Clearly there is a tension between the price that pharmaceutical companies feel is reasonable, the opportunity cost to the health care service, and the desire by stakeholders to use the drug. I feel this in every session of the NICE appraisal committee!

My next session was the compelling panel on the use of RWD to revisit the HTA decision (twitter thread). Craig Brooks-Rooney noted that, as regulators increasingly license technologies based on weaker evidence, HTA agencies are under pressure to adapt their methods to the available evidence. Adrian Towse proposed a conceptual framework to use RWD to revisit decisions based on value of information analysis. Jeanette Kusel went through examples where RWD has been used to inform NICE decisions, such as brentuximab vendotin. Anna Halliday discussed the many practical challenges to implement RWD collection to inform re-appraisals. Anna finished with the caution against prolonging negotiations and appraisals, which could lead to delays to patient access.

My Wednesday started with the stimulating panel on drugs with tumour agnostic indications. Clarissa Higuchi Zerbini introduced the panel and proposed some questions to be addressed. Rosa Giuliani contributed with the clinical perspective. Jacoline Bouvy discussed the challenges faced by NICE and ways forward in appraising tumour-agnostic drugs. Marc van den Bulcke finished the panel with an overview of how next generation sequencing has been implemented in Belgium.

My last session was the brilliant workshop on HTA methods for antibiotics.

Mark Sculpher introduced the topic. Antibiotic resistance is a major challenge for humanity, but the development of new antibiotics is declining. Beth Woods presented a new framework for HTA of antibiotics. The goal is to reflect the full value of antibiotics whilst accounting for the opportunity cost and uncertainties in the evidence (see this report for more details). Angela Blake offered the industry perspective. She argued that revenues should be delinked to volume, to be holistic in the value assessment, and to be mindful of the incentives faced by drug companies. Nick Crabb finished by introducing a new project, by NICE and NHS England, on the feasibility of innovative value assessments for antibiotics.

And this is the end of the absolutely outstanding ISPOR Europe 2019! If you’re eager for more, have a look at the video below with my conference highlights!