The cost-effectiveness of risk-stratified breast cancer screening in the UK.

BACKGROUND: There has been growing interest in the UK and internationally of risk-stratified breast screening whereby individualised risk assessment may inform screening frequency, starting age, screening instrument used, or even decisions not to screen. This study evaluates the cost-effectiveness of eight proposals for risk-stratified screening regimens compared to both the current UK screening programme and no national screening. METHODS: A person-level microsimulation model was developed to estimate health-related quality of life, cancer survival and NHS costs over the lifetime of the female population eligible for screening in the UK. RESULTS: Compared with both the current screening programme and no screening, risk-stratified regimens generated additional costs and QALYs, and had a larger net health benefit. The likelihood of the current screening programme being the optimal scenario was less than 1%. No screening amongst the lowest risk group, and triannual, biennial and annual screening amongst the three higher risk groups was the optimal screening strategy from those evaluated. CONCLUSIONS: We found that risk-stratified breast cancer screening has the potential to be beneficial for women at the population level, but the net health benefit will depend on the particular risk-based strategy.

A Systematic Review and Statistical Analysis of Factors Influencing the Cost-Effectiveness of Transcatheter Aortic Valve Implantation for Symptomatic Severe Aortic Stenosis.

Objective: Transcatheter aortic valve implantation (TAVI) is a disruptive technology recommended for patients with symptomatic severe aortic stenosis (sSAS). Despite being available for over 15 years in Europe, with an extensive volume of clinical and economic evaluations across all surgical risk groups, there is little evidence on the identification of the key drivers of TAVI's cost-effectiveness. This study sought to identify these factors and quantify their role. Methods: A systematic literature review was conducted to identify published economic evaluations of TAVI. This was supplemented by health technology assessment reports. The primary outcome was the likelihood of TAVI being found cost-effective. Secondary outcomes of TAVI being dominant, and the incremental health benefits of TAVI were also explored. Results: Forty-two studies, reporting 65 unique analyses, were identified. TAVI was found to be cost-effective and dominant in 74% and 20% of analyses, respectively. The latest generation balloon-expandable TAVI device (SAPIEN 3) was more likely to be found cost-effective, as was TAVI use in low-risk populations and when performed via transfemoral access route. There was heterogeneity in the approach taken to economic modelling, which may also influence estimates of cost-effectiveness. Analyses that found TAVI to be dominant always compared it to surgery and usually considered the latest generation balloon-expandable TAVI device. Largest health benefits were observed for the inoperable risk group. Conclusion: For patients with sSAS, TAVI is typically a cost-effective treatment option. There are important differences by device generation, risk group and access route. It is crucial to consider these differences when appraising the health economic evidence-base for TAVI.

A Guide to Selecting Flexible Survival Models to Inform Economic Evaluations of Cancer Immunotherapies.

OBJECTIVES: Parametric models are routinely used to estimate the benefit of cancer drugs beyond trial follow-up. The advent of immune checkpoint inhibitors has challenged this paradigm, and emerging evidence suggests that more flexible survival models, which can better capture the shapes of complex hazard functions, might be needed for these interventions. Nevertheless, there is a need for an algorithm to help analysts decide whether flexible models are required and, if so, which should be chosen for testing. This position article has been produced to bridge this gap. METHODS: A virtual advisory board comprising 7 international experts with in-depth knowledge of survival analysis and health technology assessment was held in summer 2021. The experts discussed 24 questions across 6 topics: the current survival model selection procedure, data maturity, heterogeneity of treatment effect, cure and mortality, external evidence, and additions to existing guidelines. Their responses culminated in an algorithm to inform selection of flexible survival models. RESULTS: The algorithm consists of 8 steps and 4 questions. Key elements include the systematic identification of relevant external data, using clinical expert input at multiple points in the selection process, considering the future and the observed hazard functions, assessing the potential for long-term survivorship, and presenting results from all plausible models. CONCLUSIONS: This algorithm provides a systematic, evidence-based approach to justify the selection of survival extrapolation models for cancer immunotherapies. If followed, it should reduce the risk of selecting inappropriate models, partially addressing a key area of uncertainty in the economic evaluation of these agents.

Optimizing the Design of a Repeated Fecal Immunochemical Test Bowel Cancer Screening Programme With a Limited Endoscopy Capacity From a Health Economic Perspective.

OBJECTIVES: In 2016, it was announced that the fecal immunochemical test (FIT) would replace the guaiac fecal occult blood test in the UK Bowel Cancer Screening Programme. England has limited endoscopy capacity. This study informed decision making by determining the most cost-effective FIT screening strategy (age range, frequency, and FIT threshold) under a constrained endoscopy capacity. METHODS: An economic model with a colorectal cancer natural history component was used to model 60 221 screening strategies with first screening at age 50 to 60 years, screening interval of 1 to 6 years, 3+ screening episodes, and FIT integer threshold of 20 to 180 µg hemoglobin/g feces. Screening strategies requiring the same endoscopy capacity were compared to determine the characteristics of the most cost-effective strategies. RESULTS: With 50 000 annual screening referral colonoscopies, the 20 most cost-effective strategies had a starting age of 50 to 53 years, 2-yearly screening, 7 or 8 rounds of screening, and FIT threshold of 127 to 166. Compared with a 2-yearly screening interval, screening less frequently (3-, 4-, 5-, or 6-yearly) with a more sensitive FIT was less cost-effective. CONCLUSIONS: The UK Bowel Cancer Screening Programme should use a 2-yearly FIT screening interval. When endoscopy capacity increases, the screening starting age should be reduced first followed by reducing the FIT threshold. These findings are relevant for other colorectal cancer screening programs with constrained endoscopy capacity.

How Uncertain is the Survival Extrapolation? A Study of the Impact of Different Parametric Survival Models on Extrapolated Uncertainty About Hazard Functions, Lifetime Mean Survival and Cost Effectiveness.

BACKGROUND AND OBJECTIVE: The extrapolation of estimated hazard functions can be an important part of cost-effectiveness analyses. Given limited follow-up time in the sample data, it may be expected that the uncertainty in estimates of hazards increases the further into the future they are extrapolated. The objective of this study was to illustrate how the choice of parametric survival model impacts on estimates of uncertainty about extrapolated hazard functions and lifetime mean survival. METHODS: We examined seven commonly used parametric survival models and described analytical expressions and approximation methods (delta and multivariate normal) for estimating uncertainty. We illustrate the multivariate normal method using case studies based on four representative hypothetical datasets reflecting hazard functions commonly encountered in clinical practice (constant, increasing, decreasing, or unimodal), along with a hypothetical cost-effectiveness analysis. RESULTS: Depending on the survival model chosen, the uncertainty in extrapolated hazard functions could be constant, increasing or decreasing over time for the case studies. Estimates of uncertainty in mean survival showed a large variation (up to sevenfold) for each case study. The magnitude of uncertainty in estimates of cost effectiveness, as measured using the incremental cost per quality-adjusted life-year gained, varied threefold across plausible models. Differences in estimates of uncertainty were observed even when models provided near-identical point estimates. CONCLUSIONS: Survival model choice can have a significant impact on estimates of uncertainty of extrapolated hazard functions, mean survival and cost effectiveness, even when point estimates were similar. We provide good practice recommendations for analysts and decision makers, emphasizing the importance of considering the plausibility of estimates of uncertainty in the extrapolated period as a complementary part of the model selection process.

A Review of Survival Analysis Methods Used in NICE Technology Appraisals of Cancer Treatments: Consistency, Limitations, and Areas for Improvement.

Objectives. In June 2011, the National Institute for Health and Care Excellence (NICE) Decision Support Unit published a Technical Support Document (TSD) providing recommendations on survival analysis for NICE technology appraisals (TAs). Survival analysis outputs are influential inputs into economic models estimating the cost-effectiveness of new cancer treatments. Hence, it is important that systematic and justifiable model selection approaches are used. This study investigates the extent to which the TSD recommendations have been followed since its publication. Methods. We reviewed NICE cancer TAs completed between July 2011 and July 2017. Information on survival analyses undertaken and associated critiques for overall survival (OS) and progression-free survival were extracted from the company submissions, Evidence Review Group (ERG) reports, and final appraisal determination documents. Results. Information was extracted from 58 TAs. Only 4 (7%) followed all TSD recommendations for OS outcomes. The vast majority (91%) compared a range of common parametric models and assessed their fit to the data (86%). Only a minority of TAs included an assessment of the shape of the hazard function (38%) or proportional hazards assumption (40%). Validation of the extrapolated portion of the survival function using external data was attempted in a minority of TAs (40%). Extrapolated survival functions were frequently criticized by ERGs (71%). Conclusions. Survival analysis within NICE TAs remains suboptimal, despite publication of the TSD. Model selection is not undertaken in a systematic way, resulting in inconsistencies between TAs. More attention needs to be given to assessing hazard functions and validation of extrapolated survival functions. Novel methods not described in the TSD have been used, particularly in the context of immuno-oncology, suggesting that an updated TSD may be of value.

The cost-effectiveness of changes to the care pathway used to identify depression and provide treatment amongst people with diabetes in England: a model-based economic evaluation.

BACKGROUND: Diabetes is associated with premature death and a number of serious complications. The presence of comorbid depression makes these outcomes more likely and results in increased healthcare costs. The aim of this work was to assess the health economic outcomes associated with having both diabetes and depression, and assess the cost-effectiveness of potential policy changes to improve the care pathway: improved opportunistic screening for depression, collaborative care for depression treatment, and the combination of both. METHODS: A mathematical model of the care pathways experienced by people diagnosed with type-2 diabetes in England was developed. Both an NHS perspective and wider social benefits were considered. Evidence was taken from the published literature, identified via scoping and targeted searches. RESULTS: Compared with current practice, all three policies reduced both the time spent with depression and the number of diabetes-related complications experienced. The policies were associated with an improvement in quality of life, but with an increase in health care costs. In an incremental analysis, collaborative care dominated improved opportunistic screening. The incremental cost-effectiveness ratio (ICER) for collaborative care compared with current practice was £10,798 per QALY. Compared to collaborative care, the combined policy had an ICER of £68,017 per QALY. CONCLUSIONS: Policies targeted at identifying and treating depression early in patients with diabetes may lead to reductions in diabetes related complications and depression, which in turn increase life expectancy and improve health-related quality of life. Implementing collaborative care was cost-effective based on current national guidance in England.

Cost-effectiveness of screening for ovarian cancer amongst postmenopausal women: a model-based economic evaluation.

BACKGROUND: The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) was the biggest ovarian cancer screening trial to date. A non-significant effect of screening on ovarian cancer was reported, but the authors noted a potential delayed effect of screening, and suggested the need for four years further follow-up. There are no UK-based cost-effectiveness analyses of ovarian cancer screening. Hence we assessed the lifetime outcomes associated with, and the cost-effectiveness of, screening for ovarian cancer in the UK, along with the value of further research. METHODS: We performed a model-based economic evaluation. Effectiveness data were taken from UKCTOCS, which considered strategies of multimodal screening (MMS), ultrasound screening (USS) and no screening. We conducted systematic reviews to identify the remaining model inputs, and performed a rigorous and transparent prospective evaluation of different methods for extrapolating the effect of screening on ovarian cancer mortality. We considered costs to the UK healthcare system and measured effectiveness using quality-adjusted life years (QALYs). We used value of information methods to estimate the value of further research. RESULTS: Over a lifetime, MMS and USS were estimated to be both more expensive and more effective than no screening. USS was dominated by MMS, being both more expensive and less effective. Compared with no screening, MMS cost on average £419 more (95% confidence interval £255 to £578), and generated 0.047 more QALYs (0.002 to 0.088). The incremental cost-effectiveness ratio (ICER) comparing MMS with no screening was £8864 per QALY (£2600 to £51,576). Alternative extrapolation methods increased the ICER, with the highest value being £36,769 (£13,888 to dominated by no screening). Using the UKCTOCS trial horizon, both MMS and USS were dominated by no screening, as they produced fewer QALYs at a greater cost. The value of research into eliminating all uncertainty in long-term effectiveness was estimated to be worth up to £20 million, or approximately £5 million for four years follow-up. CONCLUSIONS: Screening for ovarian cancer with MMS is both more effective and more expensive than not screening. Compared to national willingness to pay thresholds, lifetime cost-effectiveness is promising, but there remains considerable uncertainty regarding extrapolated long-term effectiveness.

Patterns of multimorbidity and their association with health outcomes within Yorkshire, England: baseline results from the Yorkshire Health Study.

BACKGROUND: Multimorbidity is increasingly being recognized as a serious public health concern. Research into its determinants, prevalence, and management is needed and as the risk of experiencing multiple chronic conditions increases over time, attention should be given to investigating the development of multimorbidity through prospective cohort design studies. Here we examine the baseline patterns of multimorbidity and their association with health outcomes for residents in Yorkshire, England using data from the Yorkshire Health Study. METHODS: Baseline data from the Yorkshire Health Study (YHS) was collected from 27,806 patients recruited between 2010 and 2012. A two-stage sampling strategy was implemented which first involved recruiting 43 general practice surgeries and then having them consent to mailing invitations to their patients to complete postal or online questionnaires. The questionnaire collected information on chronic health conditions, demographics, health-related behaviours, healthcare and medication usage, and a range of other health related variables. Descriptive statistics (chi-square and t tests) were used to examine associations between these variables and multimorbidity. RESULTS: In the YHS cohort, 10,332 participants (37.2 %) reported having at least two or more long-term health conditions (multimorbidity). Older age, BMI and deprivation were all positively associated with multimorbidity. Nearly half (45.7 %) of participants from the most deprived areas experienced multimorbidity. Based on the weighted sample, average health-related quality of life decreased with the number of health conditions reported; the mean EQ-5D score for participants with no conditions was 0.945 compared to 0.355 for participants with five or more. The mean number of medications used for those without multimorbidity was 1.81 (range 1-13, SD = 1.25) compared to 3.81 (range 1-14, SD = 2.44) for those with at least two long-term conditions and 7.47 (range 1-37, SD = 7.47) for those with 5+ conditions. CONCLUSION: Patterns of multimorbidity within the Yorkshire Health Study support research on multimorbidity within previous observational cross-sectional studies. The YHS provides both a facility for participant recruitment to intervention trials, and a large population-based longitudinal cohort for observational research. It is planned to continue to record chronic conditions and other health related behaviours in future waves which will be useful for examining determinants and trends in chronic disease and multimorbidity.

Predicting preference-based utility values using partial proportional odds models.

BACKGROUND: The majority of analyses on utility data have used ordinary least square (OLS) regressions to explore potential relationships. The aim of this paper is to explore the benefits of response mapping onto health dimension profiles to generate preference-based utility scores using partial proportional odds models (PPOM). METHODS: Models are estimated using EQ-5D data collected in the Health Survey for England and the predicted utility scores are compared with those obtained using OLS regressions. Explanatory variables include age, acute illness, educational level, general health, deprivation and survey year. The expected EQ-5D scores for the PPOMs are obtained by weighting the predicted probabilities of scoring one, two or three for the five health dimensions by the corresponding preference-weights. RESULTS: The EQ-5D scores obtained using the probabilities from the PPOMs characterise the actual distribution of EQ-5D preference-based utility scores more accurately than those obtained from the linear model. The mean absolute and mean squared errors in the individual predicted values are also reduced for the PPOM models. CONCLUSIONS: The PPOM models characterise the underlying distributions of the EQ-5D data better than models obtained using OLS regressions. Additional research exploring the effect of modelling conditional responses and two part models could potentially improve the results further.

Aripiprazole for the treatment and prevention of acute manic and mixed episodes in bipolar I disorder in children and adolescents: a NICE single technology appraisal.

As part of its single technology process, the National Institute for Health and Care Excellence (NICE) invited the manufacturers of aripiprazole (Otsuka Pharmaceutical Co. and Bristol Myers Squibb) to submit evidence of the clinical and cost effectiveness of aripiprazole for the treatment and prevention of acute manic and mixed episodes in bipolar I disorder in children and adolescents. The School of Health and Related Research Technology Appraisal Group at the University of Sheffield was commissioned to act as the independent Evidence Review Group (ERG). The ERG produced a critical review of the evidence for the clinical and cost effectiveness of the technology, based upon the manufacturers' submission to NICE. The evidence, which was derived mainly from a double-blind, phase III, placebo-controlled trial of aripiprazole in patients aged 10-17 years, showed that aripiprazole performed significantly better than placebo in reducing mania according to the primary outcome measurement (the Young Mania Rating Scale at 4 weeks). Safety outcomes indicated that aripiprazole was significantly more likely to cause extrapyramidal symptoms and somnolence than placebo. The manufacturers also presented a network meta-analysis of aripiprazole versus other atypical antipsychotics commonly used to treat manic episodes (olanzapine, quetiapine and risperidone) to show that aripiprazole performed similarly to the comparator drugs in terms of efficacy and safety. Aripiprazole was demonstrated to perform better in safety outcomes of (1) less weight gain than olanzapine and quetiapine; and (2) less prolactin increase than olanzapine, quetiapine and risperidone. Results from the manufacturers' economic evaluation showed that use of aripiprazole second-line dominated all of the other treatment strategies that were considered. However, there was considerable uncertainty in this result, and clinical advisors indicated that the actual treatment strategy employed in practice is likely to be dependent upon the patient's characteristics. The ERG demonstrated that if this personalised medicine resulted in improved cost effectiveness for any of the other treatment strategies, then they had the potential to dominate use of aripiprazole second-line. In conclusion, whilst a strategy including aripiprazole appeared to be cost effective relative to a strategy without it, there was not robust enough evidence to recommend a specific place for aripiprazole within the treatment pathway.

Good practice guidelines for the use of statistical regression models in economic evaluations.

Decision-analytic models (DAMs) used to evaluate the cost effectiveness of interventions are pivotal sources of evidence used in economic evaluations. Parameter estimates used in the DAMs are often based on the results of a regression analysis, but there is little guidance relating to these. This study had two objectives. The first was to identify the frequency of use of regression models in economic evaluations, the parameters they inform, and the amount of information reported to describe and support the analyses. The second objective was to provide guidance to improve practice in this area, based on the review. The review concentrated on a random sample of economic evaluations submitted to the UK National Institute for Health and Clinical Excellence (NICE) as part of its technology appraisal process. Based on these findings, recommendations for good practice were drafted, together with a checklist for critiquing reporting standards in this area. Based on the results of this review, statistical regression models are in widespread use in DAMs used to support economic evaluations, yet reporting of basic information, such as the sample size used and measures of uncertainty, is limited. Recommendations were formed about how reporting standards could be improved to better meet the needs of decision makers. These recommendations are summarised in a checklist, which may be used by both those conducting regression analyses and those critiquing them, to identify what should be reported when using the results of a regression analysis within a DAM.

Innovation in health economic modelling of service improvements for longer-term depression: demonstration in a local health community.

BACKGROUND: The purpose of the analysis was to develop a health economic model to estimate the costs and health benefits of alternative National Health Service (NHS) service configurations for people with longer-term depression. METHOD: Modelling methods were used to develop a conceptual and health economic model of the current configuration of services in Sheffield, England for people with longer-term depression. Data and assumptions were synthesised to estimate cost per Quality Adjusted Life Years (QALYs). RESULTS: Three service changes were developed and resulted in increased QALYs at increased cost. Versus current care, the incremental cost-effectiveness ratio (ICER) for a self-referral service was £11,378 per QALY. The ICER was £2,227 per QALY for the dropout reduction service and £223 per QALY for an increase in non-therapy services. These results were robust when compared to current cost-effectiveness thresholds and accounting for uncertainty. CONCLUSIONS: Cost-effective service improvements for longer-term depression have been identified. Also identified were limitations of the current evidence for the long term impact of services.

Cabazitaxel for the second-line treatment of metastatic hormone-refractory prostate cancer: a NICE single technology appraisal.

The National Institute for Health and Clinical Excellence (NICE) invited the manufacturer of cabazitaxel (Jevtana®, sanofi-aventis, UK) to submit evidence of its clinical and cost effectiveness for the second-line treatment of metastatic hormone-refractory prostate cancer (mHRPC). The School of Health and Related Research Technology Appraisal Group (ScHARR-TAG) at the University of Sheffield was commissioned to act as the independent Evidence Review Group (ERG). The ERG produced a critical review of the evidence for the clinical and cost effectiveness of the technology based upon the manufacturer's submission to NICE. Clinical evidence was derived from a multinational randomized open-label phase III trial of cabazitaxel plus prednisone or prednisolone in men with mHRPC that had progressed during or following treatment with docetaxel. The comparator was mitoxantrone plus prednisone or prednisolone. Use of cabazitaxel was associated with a statistically significant improvement in overall survival, median progression-free survival and time to tumour progression. However, it was also associated with an increased incidence of adverse events such as neutropenia. Utility data were based on interim results from the early access programme for cabazitaxel. Data were only available for a small number of patients with stable disease, resulting in great uncertainty as to the effect of cabazitaxel on quality of life. For their economic evaluation, the manufacturer estimated that the use of cabazitaxel was associated with an incremental cost of £74,908 per QALY gained. However, the ERG disagreed with the manufacturer over two key methodological points. The first concerned modelling and extrapolating survival; the second point was concerned with the choice of patient population. The ERG altered the manufacturer's evaluation to take into account these two points of disagreement. The resulting cost per QALY gained was £82,950. The NICE Appraisal Committee believed the analysis presented by the ERG to be more plausible, and likely to be an underestimate of the cost per QALY. They concluded that whilst the clinical effectiveness of cabazitaxel had been proven, it was not likely to represent a cost-effective use of NHS resources and so its use could not be recommended.