Variation in Model-Based Economic Evaluations of Low-Dose Computed Tomography Screening for Lung Cancer: A Methodological Review.

OBJECTIVES: There is significant heterogeneity in the results of published model-based economic evaluations of low-dose computed tomography (LDCT) screening for lung cancer. We sought to understand and demonstrate how these models differ. METHODS: An expansion and update of a previous systematic review (N = 19). Databases (including MEDLINE and Embase) were searched. Studies were included if strategies involving (single or multiple) LDCT screening were compared with no screening or other imaging modalities, in a population at risk of lung cancer. More detailed data extraction of studies from the previous review was conducted. Studies were critically appraised using the Consensus Health Economic Criteria list. RESULTS: A total of 16 new studies met the inclusion criteria, giving a total of 35 studies. There are geographic and temporal differences and differences in screening intervals and eligible populations. Studies varied in the types of models used, for example, decision tree, Markov, and microsimulation models. Most conducted a cost-effectiveness analysis (using life-years gained) or cost-utility analysis. The potential for overdiagnosis was considered in many models, unlike with other potential consequences of screening. Some studies report considering lead-time bias, but fewer mention length bias. Generally, the more recent studies, involving more complex modeling, tended to meet more of the critical appraisal criteria, with notable exceptions. CONCLUSIONS: There are many differences across the economic evaluations contributing to variation in estimates of the cost-effectiveness of LDCT screening for lung cancer. Several methodological factors and evidence needs have been highlighted that will require consideration in future economic evaluations to achieve better agreement.

Symptom scores in the diagnosis of pediatric cow's milk protein allergy: A systematic review.

BACKGROUND: Cow's milk protein allergy (CMPA) is an immune-mediated allergic response to proteins in milk that is common in infants. Broad CMPA symptoms make diagnosis a challenge, particularly in primary care. Symptom scores may improve a clinician's awareness of symptoms, indicating a need for further testing. This systematic review examined the development and evaluation of such symptom scores for use in infants. METHODS: CENTRAL, MEDLINE, EMBASE and CINAHL databases were searched from inception to 3 December 2019 (Updated 14 November 2020) for diagnostic accuracy studies, randomised controlled trials, observational studies, economic evaluations, qualitative studies and studies reporting development of the tools. Data were not suitable for meta-analysis due to clinical and methodological heterogeneity, so were narratively synthesised. RESULTS: We found two symptom scores evaluated in one and fourteen studies, respectively. Estimated sensitivity and specificity ranged from 37% to 98% and 38% to 93%. The evaluations of each tool were at high risk of bias or failed to address issues such as clinical and cost-effectiveness. CONCLUSIONS: Estimates of accuracy of symptom scores for CMPA offered so far should be interpreted cautiously. Rigorous, conflict-free research based on well-defined roles for the tools is urgently required.

At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR-based tests? A systematic review of individual participant data.

BACKGROUND: Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA) using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity. METHODS: We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv, and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites. RESULTS: Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from - 6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 and 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset. CONCLUSIONS: RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated.

Development, validation and effectiveness of diagnostic prediction tools for colorectal cancer in primary care: a systematic review.

BACKGROUND: Tools based on diagnostic prediction models are available to help general practitioners (GP) diagnose colorectal cancer. It is unclear how well they perform and whether they lead to increased or quicker diagnoses and ultimately impact on patient quality of life and/or survival. The aim of this systematic review is to evaluate the development, validation, effectiveness, and cost-effectiveness, of cancer diagnostic tools for colorectal cancer in primary care. METHODS: Electronic databases including Medline and Web of Science were searched in May 2017 (updated October 2019). Two reviewers independently screened titles, abstracts and full-texts. Studies were included if they reported the development, validation or accuracy of a prediction model, or assessed the effectiveness or cost-effectiveness of diagnostic tools based on prediction models to aid GP decision-making for symptomatic patients presenting with features potentially indicative of colorectal cancer. Data extraction and risk of bias were completed by one reviewer and checked by a second. A narrative synthesis was conducted. RESULTS: Eleven thousand one hundred thirteen records were screened and 23 studies met the inclusion criteria. Twenty-studies reported on the development, validation and/or accuracy of 13 prediction models: eight for colorectal cancer, five for cancer areas/types that include colorectal cancer. The Qcancer models were generally the best performing. Three impact studies met the inclusion criteria. Two (an RCT and a pre-post study) assessed tools based on the RAT prediction model. The third study looked at the impact of GP practices having access to RAT or Qcancer. Although the pre-post study reported a positive impact of the tools on outcomes, the results of the RCT and cross-sectional survey found no evidence that use of, or access to, the tools was associated with better outcomes. No study evaluated cost effectiveness. CONCLUSIONS: Many prediction models have been developed but none have been fully validated. Evidence demonstrating improved patient outcome of introducing the tools is the main deficiency and is essential given the imperfect classification achieved by all tools. This need is emphasised by the equivocal results of the small number of impact studies done so far.

Exploring the Cost-Effectiveness of Mechanical Thrombectomy Beyond 6 Hours Following Advanced Imaging in the United Kingdom.

Background and Purpose- In the United Kingdom, mechanical thrombectomy (MT) for acute ischemic stroke patients assessed beyond 6 hours from symptom onset will be commissioned up to 12 hours provided that advanced imaging (AdvImg) demonstrates salvageable brain tissue. While the accuracy of AdvImg differs across technologies, evidence is limited regarding the proportion of patients who would benefit from late MT. We compared the cost-effectiveness of 2 care pathways: (1) MT within and beyond 6 hours based on AdvImg selection versus (2) MT only within 6 hours based on conventional imaging selection. The impact of varying AdvImg accuracy and prior probability for acute ischemic stroke patients to benefit from late MT was assessed. Methods- A decision tree and a Markov trace were developed. A hypothetical United Kingdom cohort of suspected stroke patients aged 71 years with first event was modeled. Costs, health outcomes, and probabilities were obtained from the literature. Outcomes included costs, life years (LYs), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios. Probabilistic sensitivity analyses were performed. Various scenarios with prior probabilities of 10%, 20%, and 30%, respectively, for acute ischemic stroke patients to benefit from late MT, and with perfect accuracy, 80% sensitivity, and 70% specificity of AdvImg were studied. Results- Incremental cost-effectiveness ratios resulting from our deterministic analyses varied from $8199 (£6164) to $49 515 (£37 229) per QALY gained. AdvImg accuracy impacted the incremental cost-effectiveness ratio only when its specificity decreased. Over lifetime horizons, all scenarios including late MT improved QALYs and LYs. Depending on the scenario, the probabilistic sensitivity analyses showed probabilities varying between 46% and 93% for the late MT pathway to be cost-effective at a willingness to pay threshold of $39 900 (£30 000) per QALY. Conclusions- Late MT based on AdvImg selection may be good value for money. However, additional data regarding the implementation of AdvImg and prior probability to benefit from late MT are needed before its cost-effectiveness can be fully assessed.

A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification.

BACKGROUND: Computed tomography (CT) biomarkers claim to improve cardiovascular risk stratification. This review focuses on significant differences in incremental measures between adequate and inadequate reporting practise. METHODS: Studies included were those that used Framingham Risk Score as a baseline and described the incremental value of adding calcium score or CT coronary angiogram in predicting cardiovascular risk. Searches of MEDLINE, EMBASE, Web of Science and Cochrane Central were performed with no language restriction. RESULTS: Thirty five studies consisting of 206,663 patients (men = 118,114, 55.1%) were included. The baseline Framingham Risk Score included the 1998, 2002 and 2008 iterations. Selective reporting, inconsistent reference groupings and thresholds were found. Twelve studies (34.3%) had major and 23 (65.7%) had minor alterations and the respective Δ AUC were significantly different (p = 0.015). When the baseline model performed well, the Δ AUC was relatively lower with the addition of a CT biomarker (Spearman coefficient = - 0.46, p < 0.0001; n = 33; 76 pairs of data). Other factors that influenced AUC performance included exploration of data analysis, calibration, validation, multivariable and AUC documentation (all p < 0.05). Most studies (68.7%) that reported categorical NRI (n = 16; 46 pairs of data) subjectively drew strong conclusions along with other poor reporting practices. However, no significant difference in values of NRI was found between adequate and inadequate reporting. CONCLUSIONS: The widespread practice of poor reporting particularly association, discrimination, reclassification, calibration and validation undermines the claimed incremental value of CT biomarkers over the Framingham Risk Score alone. Inadequate reporting of discrimination inflates effect estimate, however, that is not necessarily the case for reclassification.

Immunosuppressive agents in adult kidney transplantation in the National Health Service: a model-based economic evaluation.

BACKGROUND: Immunosuppression is required in kidney transplantation to prevent rejection and prolong graft survival. We conducted an economic evaluation to support England's National Institute for Health and Care Excellence in developing updated guidance on the use of immunosuppression, incorporating new immunosuppressive agents, and addressing changes in pricing and the evidence base. METHODS: A discrete-time state transition model was developed to simulate adult kidney transplant patients over their lifetime. A total of 16 different regimens were modelled to assess the cost-effectiveness of basiliximab and rabbit anti-thymocyte globulin (rabbit ATG) as induction agents (with no antibody induction as a comparator) and immediate-release tacrolimus, prolonged-release tacrolimus, mycophenolate mofetil, mycophenolate sodium, sirolimus, everolimus and belatacept as maintenance agents (with ciclosporin and azathioprine as comparators). Graft survival was extrapolated from acute rejection rates, graft function and post-transplant diabetes rates, all estimated at 12 months post-transplantation. National Health Service (NHS) and personal social services costs were included. Cost-effectiveness thresholds of £20 000 and £30 000 per quality-adjusted life year were used. RESULTS: Basiliximab was predicted to be more effective and less costly than rabbit ATG and induction without antibodies. Immediate-release tacrolimus and mycophenolate mofetil were cost-effective as maintenance therapies. Other therapies were either more expensive and less effective or would only be cost-effective if a threshold in excess of £100 000 per quality-adjusted life year were used. CONCLUSIONS: A regimen comprising induction with basiliximab, followed by maintenance therapy with immediate-release tacrolimus and mycophenolate mofetil, is likely to be effective for uncomplicated adult kidney transplant patients and a cost-effective use of NHS resources.

Systematic Review of Health Economic Impact Evaluations of Risk Prediction Models: Stop Developing, Start Evaluating.

BACKGROUND: Although health economic evaluations (HEEs) are increasingly common for therapeutic interventions, they appear to be rare for the use of risk prediction models (PMs). OBJECTIVES: To evaluate the current state of HEEs of PMs by performing a comprehensive systematic review. METHODS: Four databases were searched for HEEs of PM-based strategies. Two reviewers independently selected eligible articles. A checklist was compiled to score items focusing on general characteristics of HEEs of PMs, model characteristics and quality of HEEs, evidence on PMs typically used in the HEEs, and the specific challenges in performing HEEs of PMs. RESULTS: After screening 791 abstracts, 171 full texts, and reference checking, 40 eligible HEEs evaluating 60 PMs were identified. In these HEEs, PM strategies were compared with current practice (n = 32; 80%), to other stratification methods for patient management (n = 19; 48%), to an extended PM (n = 9; 23%), or to alternative PMs (n = 5; 13%). The PMs guided decisions on treatment (n = 42; 70%), further testing (n = 18; 30%), or treatment prioritization (n = 4; 7%). For 36 (60%) PMs, only a single decision threshold was evaluated. Costs of risk prediction were ignored for 28 (46%) PMs. Uncertainty in outcomes was assessed using probabilistic sensitivity analyses in 22 (55%) HEEs. CONCLUSIONS: Despite the huge number of PMs in the medical literature, HEE of PMs remains rare. In addition, we observed great variety in their quality and methodology, which may complicate interpretation of HEE results and implementation of PMs in practice. Guidance on HEE of PMs could encourage and standardize their application and enhance methodological quality, thereby improving adequate use of PM strategies.

A bias-adjusted evidence synthesis of RCT and observational data: the case of total hip replacement.

Evaluation of clinical effectiveness of medical devices differs in some aspects from the evaluation of pharmaceuticals. One of the main challenges identified is lack of robust evidence and a will to make use of experimental and observational studies (OSs) in quantitative evidence synthesis accounting for internal and external biases. Using a case study of total hip replacement to compare the risk of revision of cemented and uncemented implant fixation modalities, we pooled treatment effect estimates from OS and RCTs, and simplified existing methods for bias-adjusted evidence synthesis to enhance practical application. We performed an elicitation exercise using methodological and clinical experts to determine the strength of beliefs about the magnitude of internal and external bias affecting estimates of treatment effect. We incorporated the bias-adjusted treatment effects into a generalized evidence synthesis, calculating both frequentist and Bayesian statistical models. We estimated relative risks as summary effect estimates with 95% confidence/credibility intervals to capture uncertainty. When we compared alternative approaches to synthesizing evidence, we found that the pooled effect size strongly depended on the inclusion of observational data as well as on the use bias-adjusted estimates. We demonstrated the feasibility of using observational studies in meta-analyses to complement RCTs and incorporate evidence from a wider spectrum of clinically relevant studies and healthcare settings. To ensure internal validity, OS data require sufficient correction for confounding and selection bias, either through study design and primary analysis, or by applying post-hoc bias adjustments to the results. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.

EXPLICIT: a feasibility study of remote expert elicitation in health technology assessment.

BACKGROUND: Expert opinion is often sought to complement available information needed to inform model-based economic evaluations in health technology assessments. In this context, we define expert elicitation as the process of encoding expert opinion on a quantity of interest, together with associated uncertainty, as a probability distribution. When availability for face-to-face expert elicitation with a facilitator is limited, elicitation can be conducted remotely, overcoming challenges of finding an appropriate time to meet the expert and allowing access to experts situated too far away for practical face-to-face sessions. However, distance elicitation is associated with reduced response rates and limited assistance for the expert during the elicitation session. The aim of this study was to inform the development of a remote elicitation tool by exploring the influence of mode of elicitation on elicited beliefs. METHODS: An Excel-based tool (EXPLICIT) was developed to assist the elicitation session, including the preparation of the expert and recording of their responses. General practitioners (GPs) were invited to provide expert opinion about population alcohol consumption behaviours. They were randomised to complete the elicitation by either a face-to-face meeting or email. EXPLICIT was used in the elicitation sessions for both arms. RESULTS: Fifteen GPs completed the elicitation session. Those conducted by email were longer than the face-to-face sessions (13 min 30 s vs 10 min 26 s, p = 0.1) and the email-elicited estimates contained less uncertainty. However, the resulting aggregated distributions were comparable. CONCLUSIONS: EXPLICIT was useful in both facilitating the elicitation task and in obtaining expert opinion from experts via email. The findings support the opinion that remote, self-administered elicitation is a viable approach within the constraints of HTA to inform policy making, although poor response rates may be observed and additional time for individual sessions may be required.

A comparison of two methods for expert elicitation in health technology assessments.

BACKGROUND: When data needed to inform parameters in decision models are lacking, formal elicitation of expert judgement can be used to characterise parameter uncertainty. Although numerous methods for eliciting expert opinion as probability distributions exist, there is little research to suggest whether one method is more useful than any other method. This study had three objectives: (i) to obtain subjective probability distributions characterising parameter uncertainty in the context of a health technology assessment; (ii) to compare two elicitation methods by eliciting the same parameters in different ways; (iii) to collect subjective preferences of the experts for the different elicitation methods used. METHODS: Twenty-seven clinical experts were invited to participate in an elicitation exercise to inform a published model-based cost-effectiveness analysis of alternative treatments for prostate cancer. Participants were individually asked to express their judgements as probability distributions using two different methods - the histogram and hybrid elicitation methods - presented in a random order. Individual distributions were mathematically aggregated across experts with and without weighting. The resulting combined distributions were used in the probabilistic analysis of the decision model and mean incremental cost-effectiveness ratios and the expected values of perfect information (EVPI) were calculated for each method, and compared with the original cost-effectiveness analysis. Scores on the ease of use of the two methods and the extent to which the probability distributions obtained from each method accurately reflected the expert's opinion were also recorded. RESULTS: Six experts completed the task. Mean ICERs from the probabilistic analysis ranged between £162,600-£175,500 per quality-adjusted life year (QALY) depending on the elicitation and weighting methods used. Compared to having no information, use of expert opinion decreased decision uncertainty: the EVPI value at the £30,000 per QALY threshold decreased by 74-86 % from the original cost-effectiveness analysis. Experts indicated that the histogram method was easier to use, but attributed a perception of more accuracy to the hybrid method. CONCLUSIONS: Inclusion of expert elicitation can decrease decision uncertainty. Here, choice of method did not affect the overall cost-effectiveness conclusions, but researchers intending to use expert elicitation need to be aware of the impact different methods could have.

First do no harm: pain relief for the peripheral venous cannulation of adults, a systematic review and network meta-analysis.

BACKGROUND: Peripheral venous cannulation is an everyday practice in hospitals, which many adults find painful. However, anaesthesia for cannulation is usually only offered to children. Inadequate pain relief is not only unpleasant for patients but may cause anxiety about further treatment and deter patients from seeking medical care in the future. The aim of this study is to discover the most effective local anaesthetic for adult peripheral venous cannulation and to find out how the pain of local anaesthetic application compares with that of unattenuated cannulation. METHODS: These aims are addressed through a systematic review, network meta-analysis and random-effects meta-analysis. Searching covered 12 databases including MEDLINE and EMBASE from 1990 to August 2015. The main included study design was RCTs. The primary outcome measure is self-reported pain, measured on a 100 mm visual analogue scale. RESULTS: The systematic review found 37 includable studies, 27 of which were suitable for network meta-analysis and two for random-effects meta-analysis. The results of the network meta-analysis indicate that none of the 17 anaesthetic considered had a very high probability of being the most effective when compared to each other; 2 % lidocaine had the highest probability (44 %). When the anaesthetics were compared to no treatment, the network meta-analysis showed that again 2 % lidocaine was estimated to be the most effective (mean difference -25.42 (95 % CI -32.25, -18.57). Other members of the 'caine' family were also estimated to be more effective than no treatment as were Ametop®, EMLA® and Rapydan® patch. The meta-analysis compared the pain of anaesthetic application with the unattenuated pain of cannulation. This found that all applications of local anaesthetic were less painful than cannulation without local anaesthetic. In particular a 1 % lidocaine injection was estimated to be -12.97 (95 % CI -15.71, -10.24) points (100 mm VAS) less painful than unattenuated cannulation. CONCLUSIONS: The pain of peripheral venous cannulation in adults can be successfully treated. The pain of application of any local anaesthetic is less than that of unattenuated cannulation. Local anaesthetic prior to cannulation should become normal practice and a marker of high quality care. PROTOCOL REGISTRATION: The protocol for the larger study was registered with PROSPERO no. CRD42012002093 .

Impact of the transparent reporting of evaluations with nonrandomized designs reporting guideline: ten years on.

OBJECTIVES: We assessed how the Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) reporting guideline was used by authors and journal editors in journals' instructions to authors. We also evaluated its impact on reporting completeness and study quality. METHODS: We extracted data from publications that cited TREND on how TREND was used in those reports; we also extracted information on journals' instructions to authors. We then undertook a case-control study of relevant publications to evaluate the impact of using TREND. RESULTS: Between 2004 and 2013, TREND was cited 412 times, but it was only evidently applied to study reports 47 times. TREND was specifically mentioned 14 times in the sample of 61 instructions to authors. Some evidence suggested that use of TREND was associated with more comprehensive reporting and higher study quality ratings. CONCLUSIONS: TREND appeared to be underutilized by authors and journal editors despite its potential application and benefits. We found evidence that suggested that using TREND could contribute to more transparent and complete study reports. Even when authors reported using TREND, reporting completeness was still suboptimal.

Cost-effectiveness of cetuximab, cetuximab plus irinotecan, and panitumumab for third and further lines of treatment for KRAS wild-type patients with metastatic colorectal cancer.

OBJECTIVES: To estimate the cost-effectiveness of cetuximab monotherapy, cetuximab plus irinotecan, and panitumumab monotherapy compared with best supportive care (BSC) for the third and subsequent lines of treatment of patients with Kirsten rat sarcoma wild-type metastatic colorectal cancer from the perspective of the UK National Health Service. METHODS: An "an area under the curve" cost-effectiveness model was developed. The clinical effectiveness evidence for both cetuximab and panitumumab was taken from a single randomized controlled trial (RCT) in each case and for cetuximab plus irinotecan from several sources. RESULTS: Patients are predicted to survive for approximately 6 months on BSC, 8.5 months on panitumumab, 10 months on cetuximab, and 16.5 months on cetuximab plus irinotecan. Panitumumab is dominated, and cetuximab is extended dominated. An incremental cost-effectiveness ratio (ICER) of £95,000 per quality-adjusted life-year (QALY) was estimated for cetuximab versus BSC and is likely to be relatively accurate, because the relevant clinical evidence is taken from a high-quality RCT. The estimated ICER for panitumumab versus BSC, at £187,000 per QALY, is less certain due to assumptions in the adjustment for the substantial crossing-over of patients in the RCT. The ICER for cetuximab plus irinotecan versus BSC, at £88,000 per QALY, is least certain due to substantial uncertainty about progression-free survival, treatment duration, and overall survival. Nonetheless, when key parameters are varied within plausible ranges, all three treatments always remain poor value for money. CONCLUSIONS: All three treatments are highly unlikely to be considered cost-effective in this patient population in the United Kingdom. We explain how the reader can adapt the model for other countries.

Evolution of the evidence on the effectiveness and cost-effectiveness of acetylcholinesterase inhibitors and memantine for Alzheimer's disease: systematic review and economic model.

INTRODUCTION: in 2007 the National Institute of Health and Clinical Excellence (NICE) restricted the use of acetylcholinesterase inhibitors and memantine. METHODS: we conducted a health technology assessment (HTA) of the effectiveness and cost-effectiveness of donepezil, galantamine, rivastigmine and memantine for the treatment of AD to re-consider and up-date the evidence base used to inform the 2007 NICE decision. The systematic review of effectiveness targeted randomised controlled trials. A comprehensive search, including MEDLINE, Embase and the Cochrane Library, was conducted from January 2004 to March 2010. All key review steps were done by two reviewers. Random effects meta-analysis was conducted. The cost-effectiveness was assessed using a cohort-based model with three health states: pre-institutionalised, institutionalised and dead. The perspective was NHS and Personal Social Services and the cost year 2009. RESULTS: confidence about the size and statistical significance of the estimates of effect of galantamine, rivastigmine and memantine improved on function and global impact in particular. Cost-effectiveness also changed. For donepezil, galantamine and rivastigmine, the incremental cost per quality-adjusted life year (QALY) in 2004 was above £50,000; in 2010 the same drugs 'dominated' best supportive care (improved clinical outcome at reduced cost). This was primarily because of changes in the modelled costs of introducing the drugs. For memantine, the cost-effectiveness also improved from a range of £37-53,000 per QALY gained to a base-case of £32,000. CONCLUSION: there has been a change in the evidence base between 2004 and 2010 consistent with the change in NICE guidance. Further evolution in cost-effectiveness estimates is possible particularly if there are changes in drug prices.

The cost-effectiveness of mandatory 20 mph zones for the prevention of injuries.

BACKGROUND: Traffic calming and speed limits are major public health strategies for further reducing road injuries, especially for vulnerable pedestrians such as children and the elderly. We conducted a cost-benefit analysis (CBA-favoured by transport economists) alongside a cost-utility analysis (CUA-favoured by health economists) of mandatory 20 mph zones, providing a unique opportunity to compare assumptions and results. METHODS: A CUA from the public sector perspective and a CBA from a broader societal perspective. One-way, threshold and probabilistic sensitivity analyses were undertaken. RESULTS: In low casualty areas the intervention was not cost-effective regardless of approach (CUA: cost per QALY = £429 800; CBA: net present value = -£25 500). In high casualty areas, the intervention was cost-effective from the CBA (a saving of £90 600), but not from the CUA [cost per quality-adjusted life year (QALY) = £86 500; assuming National Institute for Health and Clinical Excellence's benchmark for approving health technologies]. CONCLUSIONS: Mandatory 20 mph zones may be cost-effective in high casualty areas when a CBA from a societal perspective is considered. Although CBA may appear, in principle, more appropriate, the quality, age or absence of reliable data for many parameters means that there is a great deal of uncertainty and the results should be interpreted with caution.

Evolution of a cost-utility model of donepezil for Alzheimer's disease.

OBJECTIVES: The aim of this study was to describe the evolution of a cost-utility model used to inform the UK National Institute for Health and Clinical Excellence's (NICE) most recent decisions on the cost-utility of drug treatments for Alzheimer's disease (AD), and to explore the impact of structural assumptions on the cost-utility results. METHODS: Changes informed by noted limitations of the decision model used in NICE's previous decisions (in 2006) were made cumulatively to the original decision model for donepezil compared with best supportive care (for patients with mild to moderate AD). Deterministic and probabilistic analyses were undertaken for each cumulative change of the model. The expected value of perfect information (EVPI) of parameter estimates and structural assumptions was also calculated. RESULTS: Cumulative changes to the decision model highlighted how the results of the original model (incremental cost-effectiveness ratio of £81,000 per quality-adjusted life-year gained) related to those of the new model (where donepezil was estimated to be cost-saving), mainly due to uncertainty in the incremental cost of donepezil treatment over best supportive care (ranging from -£600 to £3,000 per patient). The partial EVPI analysis reflected this finding where further information on treatment discontinuations and cost parameter estimates were shown to be valuable in terms of reducing decision uncertainty. CONCLUSIONS: Assessing the evolution of the cost-utility model helped to identify and explore structural differences between cohort-based models and is likely to be useful for decision models in other disease areas. This approach makes the structural uncertainty explicit, forcing decision makers to address structural uncertainty in addition to parameter uncertainty.

Test accuracy of artificial intelligence-based grading of fundus images in diabetic retinopathy screening: A systematic review.

OBJECTIVES: To systematically review the accuracy of artificial intelligence (AI)-based systems for grading of fundus images in diabetic retinopathy (DR) screening. METHODS: We searched MEDLINE, EMBASE, the Cochrane Library and the ClinicalTrials.gov from 1st January 2000 to 27th August 2021. Accuracy studies published in English were included if they met the pre-specified inclusion criteria. Selection of studies for inclusion, data extraction and quality assessment were conducted by one author with a second reviewer independently screening and checking 20% of titles. Results were analysed narratively. RESULTS: Forty-three studies evaluating 15 deep learning (DL) and 4 machine learning (ML) systems were included. Nine systems were evaluated in a single study each. Most studies were judged to be at high or unclear risk of bias in at least one QUADAS-2 domain. Sensitivity for referable DR and higher grades was ≥85% while specificity varied and was <80% for all ML systems and in 6/31 studies evaluating DL systems. Studies reported high accuracy for detection of ungradable images, but the latter were analysed and reported inconsistently. Seven studies reported that AI was more sensitive but less specific than human graders. CONCLUSIONS: AI-based systems are more sensitive than human graders and could be safe to use in clinical practice but have variable specificity. However, for many systems evidence is limited, at high risk of bias and may not generalise across settings. Therefore, pre-implementation assessment in the target clinical pathway is essential to obtain reliable and applicable accuracy estimates.

Do we know enough about the effect of low-dose computed tomography screening for lung cancer on mortality to act? An updated systematic review, meta-analysis and network meta-analysis of randomised controlled trials 2017 to 2021.

BACKGROUND: For people at high risk of lung cancer, low-dose computed tomography (LDCT) is proposed as a method to reduce mortality. METHODS: Our objective was to estimate the effect of LDCT lung cancer screening on mortality in high-risk populations. A systematic review of randomised controlled trials (RCTs) comparing LDCT screening programmes with usual care (no screening) or other imaging screening programme (such as chest X-ray (CXR)) was conducted. RCTs of CXR screening were additionally included in the network meta-analyses. Bibliographic sources including MEDLINE, Embase, Web of Science and the Cochrane Library were searched to January 2017, and then further extended to November 2021. All key review steps were done by two persons. Quality assessment used the Cochrane Risk of Bias tool. Meta-analyses were performed. RESULTS: Nine RCTs, with up to 12.3 years of follow-up from randomisation, were included in the direct meta-analysis, which showed that LDCT screening was associated with a statistically significant decrease in lung cancer mortality (pooled relative risk (RR) 0.86, 95% confidence interval [CI] 0.77 to 0.96). There was a statistically non-significant decrease in all-cause mortality (pooled RR 0.98, 95% CI 0.95 to 1.01). The statistical heterogeneity for both outcomes was minimal. Network meta-analysis including the nine RCTs in the direct meta-analysis plus two further RCTs comparing CXR with usual care confirmed the size of the effect of LDCT on lung cancer mortality and that this was very similar irrespective of whether the comparator was usual care or CXR screening. CONCLUSIONS: LDCT screening is effective in reducing lung cancer mortality in high-risk populations. The uncertainty of its effect on lung cancer mortality observed in 2018 has been much reduced with new trial results and updates to existing trials, emphasising the importance of updating systematic reviews. Although there are still a number of RCTs unreported or in progress, we predict that further evolution of summary mortality estimates is unlikely. The focus for debate now moves to resolving uncertainty about the cost-effectiveness of LDCT screening taking into account the balance between benefits and harms which occur in all screening programmes.

Cost-effectiveness analysis of degarelix for advanced hormone-dependent prostate cancer.

OBJECTIVE: To evaluate the cost-effectiveness of degarelix vs luteinizing hormone-releasing hormone analogue (triptorelin) plus short-term antiandrogen treatment for advanced prostate cancer. METHODS: We developed a decision analytic model based on a clinical trial and literature review. The two interventions evaluated were: (i) monthly injection of degarelix and (ii) 3-monthly triptorelin therapy plus short-term flutamide, cyproterone or bicalutamide treatment. The model consisted of a decision tree monitoring a hypothetical cohort of patients aged 70 years from the start of hormonal treatment to the end of the first month, and a Markov model monitoring patients from the end of month 1 for a time horizon of 10 years (i.e. when 96% of patients are assumed to have died). The base-case analysis assumed patients present with asymptomatic metastatic prostate cancer. Costs and outcomes were collected over the model time horizon. Outcome measures were quality-adjusted life years (QALYs), lifetime costs and incremental cost-effectiveness ratios. Sensitivity analyses (one-way and multi-way) and probabilistic sensitivity analyses were conducted to explore the uncertainties around the assumptions. RESULTS: In the base-case analysis, the incremental cost-effectiveness ratio (ICER) for degarelix vs triptorelin plus antiandrogen was £59,000 per QALY gained. The model was most sensitive to the rate of significant adverse events in the triptorelin plus antiandrogen group. The model was also sensitive to the assumed survival of patients with metastatic prostate cancer and the price of degarelix. The results of the probabilistic sensitivity analyses suggested that there was a low probability (9.6%) of degarelix being the most cost-effective treatment option when a willingness-to-pay threshold of £30,000 per QALY gained is assumed. CONCLUSION: Degarelix is unlikely to be cost-effective compared to triptorelin plus short-term antiandrogen in the management of advanced prostate cancer with respect to the usual thresholds of cost-effectiveness used in the UK: £20,000-30,000 per QALY gained (used by the National Institute for Health and Clinical Excellence).