Abstract Background The characterization of uncertainty is critical in cost-effectiveness analysis, particularly when considering whether additional evidence is needed. In addition to parameter and ...methodological uncertainty, there are other sources of uncertainty which include simplifications and scientific judgments that have to be made when constructing and interpreting a model of any sort. These have been classified in a number of different ways but can be referred to collectively as structural uncertainties. Materials and Methods Separate reviews were undertaken to identify what forms these other sources of uncertainty take and what other forms of potential methods to explicitly characterize these types of uncertainties in decision analytic models. These methods were demonstrated through application to four decision models each representing one of the four types of uncertainty. Results These sources of uncertainty fall into four general themes: 1) inclusion of relevant comparators; 2) inclusion of relevant events; 3) alternative statistical estimation methods; and 4) clinical uncertainty. Two methods to explicitly characterize such uncertainties were identified: model selection and model averaging. In addition, an alternative approach, adding uncertain parameters to represent the source of uncertainty was also considered. The applications demonstrate that cost-effectiveness may be sensitive to these uncertainties and the methods used to characterize them. The value of research was particularly sensitive to these uncertainties and the methods used to characterize it. It is therefore important, for decision-making purposes, to incorporate such uncertainties into the modeling process. Conclusion Only parameterizing the uncertainty directly in the model can inform the decision to conduct further research to resolve this source of uncertainty.
Decisions to adopt, reimburse or issue guidance on the use of health technologies are increasingly being informed by explicit cost-effectiveness analyses of the alternative interventions. Healthcare ...systems also invest heavily in research and development to support these decisions. However, the increasing transparency of adoption and reimbursement decisions, based on formal analysis, contrasts sharply with research prioritisation and commissioning. This is despite the fact that formal measures of the value of evidence generated by research are readily available. The results of two recent opportunities to apply value of information analysis to directly inform policy decisions about research priorities in the UK are presented. These include a pilot study for the UK National Co-ordinating Centre for Health Technology Assessment (NCCHTA) and a pilot study for the National Institute for Health and Clinical Excellence (NICE). We demonstrate how these results can be used to address a series of policy questions, including: is further research required to support the use of a technology and, if so, what type of research would be most valuable? We also show how the results can be used to address other questions such as, which patient subgroups should be included in subsequent research, which comparators and endpoints should be included, and what length of follow up would be most valuable.
A pressing need exists to develop vaccines for neglected diseases, including leishmaniasis. However, the development of new vaccines is dependent on their value to two key players-vaccine developers ...and manufacturers who need to have confidence in the global demand in order to commit to research and production; and governments (or other international funders) who need to signal demand based on the potential public health benefits of the vaccine in their local context, as well as its affordability. A detailed global epidemiological analysis is rarely available before a vaccine enters a market due to lack of resources as well as insufficient global data necessary for such an analysis. Our study seeks to bridge this information gap by providing a generalisable approach to estimating the commercial and public health value of a vaccine in development relying primarily on publicly available Global Burden of Disease (GBD) data. This simplified approach is easily replicable and can be used to guide discussions and investments into vaccines and other health technologies where evidence constraints exist. The approach is demonstrated through the estimation of the demand curve for a future leishmaniasis vaccine.
We project the ability to pay over the period 2030-2040 for a vaccine preventing cutaneous and visceral leishmaniasis (CL / VL), using an illustrative set of countries which account for most of the global disease burden. First, based on previous work on vaccine demand projections in these countries and CL / VL GBD-reported incidence rates, we project the potential long-term impact of the vaccine on disability-adjusted life years (DALYs) averted as a result of reduced incidence. Then, we apply an economic framework to our estimates to determine vaccine affordability based on the abilities to pay of governments and global funders, leading to estimates of the demand and market size. Based on our estimates, the maximum ability-to-pay of a leishmaniasis vaccine (per course, including delivery costs), given the current estimates of incidence and population at risk, is higher than $5 for 25-30% of the countries considered, with the average value-based maximum price, weighted by quantity demanded, being $5.7-6 $0.3 - $34.5, and total demand of over 560 million courses.
Our results demonstrate that both the quantity of vaccines estimated to be required by the countries considered as well as their ability-to-pay could make a vaccine for leishmaniasis commercially attractive to potential manufacturers. The methodology used can be equally applied to other technology developments targeting health in developing countries.
Gestational diabetes mellitus (GDM) is associated with a higher risk of important adverse outcomes. Practice varies and the best strategy for identifying and treating GDM is unclear.
To estimate the ...clinical effectiveness and cost-effectiveness of strategies for identifying and treating women with GDM.
We analysed individual participant data (IPD) from birth cohorts and conducted systematic reviews to estimate the association of maternal glucose levels with adverse perinatal outcomes; GDM prevalence; maternal characteristics/risk factors for GDM; and the effectiveness and costs of treatments. The cost-effectiveness of various strategies was estimated using a decision tree model, along with a value of information analysis to assess where future research might be worthwhile. Detailed systematic searches of MEDLINE
and MEDLINE In-Process & Other Non-Indexed Citations
, EMBASE, Cumulative Index to Nursing and Allied Health Literature Plus, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database, Maternity and Infant Care database and the Cochrane Methodology Register were undertaken from inception up to October 2014.
We identified 58 studies examining maternal glucose levels and outcome associations. Analyses using IPD alone and the systematic review demonstrated continuous linear associations of fasting and post-load glucose levels with adverse perinatal outcomes, with no clear threshold below which there is no increased risk. Using IPD, we estimated glucose thresholds to identify infants at high risk of being born large for gestational age or with high adiposity; for South Asian (SA) women these thresholds were fasting and post-load glucose levels of 5.2 mmol/l and 7.2 mmol/l, respectively and for white British (WB) women they were 5.4 and 7.5 mmol/l, respectively. Prevalence using IPD and published data varied from 1.2% to 24.2% (depending on criteria and population) and was consistently two to three times higher in SA women than in WB women. Lowering thresholds to identify GDM, particularly in women of SA origin, identifies more women at risk, but increases costs. Maternal characteristics did not accurately identify women with GDM; there was limited evidence that in some populations risk factors may be useful for identifying low-risk women. Dietary modification additional to routine care reduced the risk of most adverse perinatal outcomes. Metformin (Glucophage,
Teva UK Ltd, Eastbourne, UK) and insulin were more effective than glibenclamide (Aurobindo Pharma - Milpharm Ltd, South Ruislip, Middlesex, UK). For all strategies to identify and treat GDM, the costs exceeded the health benefits. A policy of no screening/testing or treatment offered the maximum expected net monetary benefit (NMB) of £1184 at a cost-effectiveness threshold of £20,000 per quality-adjusted life-year (QALY). The NMB for the three best-performing strategies in each category (screen only, then treat; screen, test, then treat; and test all, then treat) ranged between -£1197 and -£1210. Further research to reduce uncertainty around potential longer-term benefits for the mothers and offspring, find ways of improving the accuracy of identifying women with GDM, and reduce costs of identification and treatment would be worthwhile.
We did not have access to IPD from populations in the UK outside of England. Few observational studies reported longer-term associations, and treatment trials have generally reported only perinatal outcomes.
Using the national standard cost-effectiveness threshold of £20,000 per QALY it is not cost-effective to routinely identify pregnant women for treatment of hyperglycaemia. Further research to provide evidence on longer-term outcomes, and more cost-effective ways to detect and treat GDM, would be valuable.
This study is registered as PROSPERO CRD42013004608.
The National Institute for Health Research Health Technology Assessment programme.
Abstract Background Until recently, purchasers' options regarding whether to pay for the use of medical technologies have been binary in nature: a treatment is either covered or not. Policies, ...however, have emerged that expand the decision options, for example, linking coverage to evidence development, an option increasingly used for treatments with limited/uncertain evidence. There has been little effort to reconcile the features of technologies with the available decision options. Methods We described a framework within which different decision options can be evaluated. We distinguished two sources of value in terms of health: the value of the technology per se and the value of reducing decision uncertainty. The costs of reversing decisions were also considered. Findings Purchasers should weigh the expected benefits of coverage against the possibility that the decision may need to be reversed and the chance that adoption will hinder evidence generation. Based on the purchaser's range of authority over access, research, and price and on the characteristics of the technology with regard to reversibility and evidence, different decisions may be appropriate. The framework clarified the assessments needed to establish the appropriateness of different decisions. A taxonomy of coverage decisions was suggested. Conclusions A range of decision options may facilitate paying for the use of promising medical technologies despite their uncertain evidence. It is important that the option be chosen on the basis of not only the expected value of a technology but also the value of further research, the anticipated effect of coverage on further research, and the costs associated with reversing the decision.
There is limited information on the costs and benefits of alternative adjunct non-pharmacological treatments for knee osteoarthritis and little guidance on which should be prioritised for ...commissioning within the NHS. This study estimates the costs and benefits of acupuncture, braces, heat treatment, insoles, interferential therapy, laser/light therapy, manual therapy, neuromuscular electrical stimulation, pulsed electrical stimulation, pulsed electromagnetic fields, static magnets and transcutaneous electrical nerve Stimulation (TENS), based on all relevant data, to facilitate a more complete assessment of value.
Data from 88 randomised controlled trials including 7,507 patients were obtained from a systematic review. The studies reported a wide range of outcomes. These were converted into EQ-5D index values using prediction models, and synthesised using network meta-analysis. Analyses were conducted including firstly all trials and secondly only trials with low risk of selection bias. Resource use was estimated from trials, expert opinion and the literature. A decision analytic model synthesised all evidence to assess interventions over a typical treatment period (constant benefit over eight weeks or linear increase in effect over weeks zero to eight and dissipation over weeks eight to 16).
When all trials are considered, TENS is cost-effective at thresholds of £20-30,000 per QALY with an incremental cost-effectiveness ratio of £2,690 per QALY vs. usual care. When trials with a low risk of selection bias are considered, acupuncture is cost-effective with an incremental cost-effectiveness ratio of £13,502 per QALY vs. TENS. The results of the analysis were sensitive to varying the intensity, with which interventions were delivered, and the magnitude and duration of intervention effects on EQ-5D.
Using the £20,000 per QALY NICE threshold results in TENS being cost-effective if all trials are considered. If only higher quality trials are considered, acupuncture is cost-effective at this threshold, and thresholds down to £14,000 per QALY.
Men with suspected prostate cancer usually undergo transrectal ultrasound (TRUS)-guided prostate biopsy. TRUS-guided biopsy can cause side effects and has relatively poor diagnostic accuracy. ...Multiparametric magnetic resonance imaging (mpMRI) used as a triage test might allow men to avoid unnecessary TRUS-guided biopsy and improve diagnostic accuracy.
To (1) assess the ability of mpMRI to identify men who can safely avoid unnecessary biopsy, (2) assess the ability of the mpMRI-based pathway to improve the rate of detection of clinically significant (CS) cancer compared with TRUS-guided biopsy and (3) estimate the cost-effectiveness of a mpMRI-based diagnostic pathway.
A validating paired-cohort study and an economic evaluation using a decision-analytic model.
Eleven NHS hospitals in England.
Men at risk of prostate cancer undergoing a first prostate biopsy.
Participants underwent three tests: (1) mpMRI (the index test), (2) TRUS-guided biopsy (the current standard) and (3) template prostate mapping (TPM) biopsy (the reference test).
Diagnostic accuracy of mpMRI, TRUS-guided biopsy and TPM-biopsy measured by sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using primary and secondary definitions of CS cancer. The percentage of negative magnetic resonance imaging (MRI) scans was used to identify men who might be able to avoid biopsy.
Diagnostic study - a total of 740 men were registered and 576 underwent all three tests. According to TPM-biopsy, the prevalence of any cancer was 71% 95% confidence interval (CI) 67% to 75%. The prevalence of CS cancer according to the primary definition (a Gleason score of ≥ 4 + 3 and/or cancer core length of ≥ 6 mm) was 40% (95% CI 36% to 44%). For CS cancer, TRUS-guided biopsy showed a sensitivity of 48% (95% CI 42% to 55%), specificity of 96% (95% CI 94% to 98%), PPV of 90% (95% CI 83% to 94%) and NPV of 74% (95% CI 69% to 78%). The sensitivity of mpMRI was 93% (95% CI 88% to 96%), specificity was 41% (95% CI 36% to 46%), PPV was 51% (95% CI 46% to 56%) and NPV was 89% (95% CI 83% to 94%). A negative mpMRI scan was recorded for 158 men (27%). Of these, 17 were found to have CS cancer on TPM-biopsy. Economic evaluation - the most cost-effective strategy involved testing all men with mpMRI, followed by MRI-guided TRUS-guided biopsy in those patients with suspected CS cancer, followed by rebiopsy if CS cancer was not detected. This strategy is cost-effective at the TRUS-guided biopsy definition 2 (any Gleason pattern of ≥ 4 and/or cancer core length of ≥ 4 mm), mpMRI definition 2 (lesion volume of ≥ 0.2 ml and/or Gleason score of ≥ 3 + 4) and cut-off point 2 (likely to be benign) and detects 95% (95% CI 92% to 98%) of CS cancers. The main drivers of cost-effectiveness were the unit costs of tests, the improvement in sensitivity of MRI-guided TRUS-guided biopsy compared with blind TRUS-guided biopsy and the longer-term costs and outcomes of men with cancer.
The PROstate Magnetic resonance Imaging Study (PROMIS) was carried out in a selected group and excluded men with a prostate volume of > 100 ml, who are less likely to have cancer. The limitations in the economic modelling arise from the limited evidence on the long-term outcomes of men with prostate cancer and on the sensitivity of MRI-targeted repeat biopsy.
Incorporating mpMRI into the diagnostic pathway as an initial test prior to prostate biopsy may (1) reduce the proportion of men having unnecessary biopsies, (2) improve the detection of CS prostate cancer and (3) increase the cost-effectiveness of the prostate cancer diagnostic and therapeutic pathway. The PROMIS data set will be used for future research; this is likely to include modelling prognostic factors for CS cancer, optimising MRI scan sequencing and biomarker or translational research analyses using the blood and urine samples collected. Better-quality evidence on long-term outcomes in prostate cancer under the various management strategies is required to better assess cost-effectiveness. The value-of-information analysis should be developed further to assess new research to commission.
Current Controlled Trials ISRCTN16082556 and NCT01292291.
This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in
; Vol. 22, No. 39. See the NIHR Journals Library website for further project information. This project was also supported and partially funded by the NIHR Biomedical Research Centre at University College London (UCL) Hospitals NHS Foundation Trust and UCL and by The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research Biomedical Research Centre and was co-ordinated by the Medical Research Council's Clinical Trials Unit at UCL (grant code MC_UU_12023/28). It was sponsored by UCL. Funding for the additional collection of blood and urine samples for translational research was provided by Prostate Cancer UK.
Abstract A growing number of jurisdictions now request economic data in support of their decision-making procedures for the pricing and/or reimbursement of health technologies. Because more ...jurisdictions request economic data, the burden on study sponsors and researchers increases. There are many reasons why the cost-effectiveness of health technologies might vary from place to place. Therefore, this report of an ISPOR Good Practices Task Force reviews what national guidelines for economic evaluation say about transferability, discusses which elements of data could potentially vary from place to place, and recommends good research practices for dealing with aspects of transferability, including strategies based on the analysis of individual patient data and based on decision-analytic modeling.
In recent years, Health Technology Assessment (HTA) processes specific to diagnostics and prognostic tests have been created in response to the increased pressure on health systems to decide not only ...which tests should be used in practice but also the best way to proceed, clinically, from the information they provide. These technologies differ in the way value is accrued to the population of users, depending critically on the value of downstream health care choices. This paper defines an analytical framework for establishing the value of diagnostic and prognostic tests for HTA in a way that is consistent with methods used for the evaluation of other health care technologies. It assumes a linked-evidence approach where modeling is required, and incorporates considerations regarding several different areas of policy, such as personalized medicine. We initially focus on diagnostic technologies with dichotomous results, and then extend the framework by considering diagnostic tests that provide more complex information, such as continuous measures (for example, blood glucose measurements) or multiple categories (such as tumor classification systems). We also consider how the methods of assessment differ for prognostic information or for diagnostics without a reference standard. Throughout, we propose innovative graphical ways of summarizing the results of such complex assessments of value.
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