Thromboprophylaxis in lower limb immobilisation after injury (TiLLI).

Venous thromboembolic disease is a major global cause of morbidity and mortality. An estimated 10 million episodes are diagnosed yearly; over half of these episodes are provoked by hospital admission/procedures and result in significant loss of disability adjusted life years. Temporary lower limb immobilisation after injury is a significant contributor to the overall burden of venous thromboembolism (VTE). Existing evidence suggests that pharmacological prophylaxis could reduce overall VTE event rates in these patients, but the proportional reduction of symptomatic events remains unclear. Recent studies have used different pharmacological agents, dosing regimens and outcome measures. Consequently, there is wide variation in thromboprophylaxis strategies, and international guidelines continue to offer conflicting advice for clinicians. In this review, we provide a summary of recent evidence assessing both the clinical and cost effectiveness of thromboprophylaxis in patients with temporary immobilisation after injury. We also examine the evidence supporting stratified thromboprophylaxis and the validity of widely used risk assessment methods.

Rheumatoid arthritis treated with 6-months of first-line biologic or biosimilar therapy: an updated systematic review and network meta-analysis.

OBJECTIVES: The aim of this study was to estimate the effectiveness of first-line biologic disease modifying drugs(boDMARDs), and their approved biosimilars (bsDMARDs), compared with conventional (csDMARD) treatment, in terms of ACR (American College of Rheumatology) and EULAR (European League against Rheumatism) responses. METHODS: Systematic literature search, on eight databases to January 2017, sought ACR and EULAR data from randomized controlled trials (RCTs) of boDMARDs / bsDMARDs (in combination with csDMARDs, or monotherapy). Two adult populations: methotrexate (MTX)-naïve patients with severe active RA; and csDMARD-experienced patients with moderate-to-severe active RA. Network meta-analyses (NMA) were conducted using a Bayesian Markov chain Monte Carlo simulation using a random effects model with a probit link function for ordered categorical. RESULTS: Forty-six RCTs met the eligibility criteria. In the MTX-naïve severe active RA population, no biosimilar trials meeting the inclusion criteria were identified. MTX plus methylprednisolone (MP) was most likely to achieve the best ACR response. There was insufficient evidence that combination boDMARDs was superior to intensive (two or more) csDMARDs. In the csDMARD-experienced, moderate-to-severe RA population, the greatest effects for ACR responses were associated with tocilizumab (TCZ) monotherapy, and combination therapy (plus MTX) with bsDMARD etanercept (ETN) SB4, boDMARD ETN and TCZ. These treatments also had the greatest effects on EULAR responses. No clear differences were found between the boDMARDs and their bsDMARDs. CONCLUSIONS: In MTX-naïve patients, there was insufficient evidence that combination boDMARDs was superior to two or more csDMARDs. In csDMARD-experienced patients, boDMARDs and bsDMARDs were comparable and all combination boDMARDs / bsDMARDs were superior to single csDMARD.

Estimating Future Health Technology Diffusion Using Expert Beliefs Calibrated to an Established Diffusion Model.

OBJECTIVES: Estimates of future health technology diffusion, or future uptake over time, are a requirement for different analyses performed within health technology assessments. Methods for obtaining such estimates include constant uptake estimates based on expert opinion or analogous technologies and on extrapolation from initial data points using parametric curves-but remain divorced from established diffusion theory and modeling. We propose an approach to obtaining diffusion estimates using experts' beliefs calibrated to an established diffusion model to address this methodologic gap. METHODS: We performed an elicitation of experts' beliefs on future diffusion of a new preterm birth screening illustrative case study technology. The elicited quantities were chosen such that they could be calibrated to yield the parameters of the Bass model of new product growth, which was chosen based on a review of the diffusion literature. RESULTS: With the elicitation of only three quantities per diffusion curve, our approach enabled us to quantify uncertainty about diffusion of the new technology in different scenarios. Pooled results showed that the attainable number of adoptions was predicted to be relatively low compared with what was thought possible. Further research evidence improved the attainable number of adoptions only slightly but resulted in greater speed of diffusion. CONCLUSIONS: The proposed approach of eliciting experts' beliefs about diffusion and informing the Bass model has the potential to fill the methodologic gap evident in value of implementation and research, as well as budget impact and some cost-effectiveness analyses.

When Future Change Matters: Modeling Future Price and Diffusion in Health Technology Assessments of Medical Devices.

BACKGROUND: Health technology assessments (HTAs) that take account of future price changes have been examined in the literature, but the important issue of price reductions that are generated by the reimbursement decision has been ignored. OBJECTIVES: To explore the impact of future price reductions caused by increasing uptake on HTAs and decision making for medical devices. METHODS: We demonstrate the use of a two-stage modeling approach to derive estimates of technology price as a consequence of changes in technology uptake over future periods on the basis of existing theory and supported by empirical studies. We explore the impact on cost-effectiveness and expected value of information analysis in an illustrative example on the basis of a technology in development for preterm birth screening. RESULTS: The application of our approach to the case study technology generates smaller incremental cost-effectiveness ratios compared with the commonly used single cohort approach. The extent of this reduction in the incremental cost-effectiveness ratio depends on the magnitude of the modeled price reduction, the speed of diffusion, and the length of the assumed technology life horizon. Results of value of information analysis are affected through changes in the expected net benefit calculation, the addition of uncertain parameters, and the diffusion-adjusted estimate of the affected patient population. CONCLUSIONS: Because modeling future changes in price and uptake has the potential to affect HTA outcomes, modeling techniques that can address such changes should be considered for medical devices that may otherwise be rejected.

Heart-type fatty acid binding protein as an early marker for myocardial infarction: systematic review and meta-analysis.

BACKGROUND: Heart-type fatty acid binding protein (H-FABP) has been proposed as an early biomarker of myocardial infarction (MI). The authors aimed to undertake a systematic review and meta-analysis to estimate the early sensitivity and specificity of quantitative and qualitative H-FABP assays. METHODS: The authors undertook a systematic search using electronic databases, citation lists and expert contacts to identify all diagnostic cohort studies of patients presenting with suspected acute coronary syndrome that compared H-FABP at presentation to a reference standard based on the Universal definition of MI. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Meta-analysis was conducted using Bayesian Markov chain Monte Carlo simulation. RESULTS: The authors included eight studies of quantitative H-FABP and nine studies of qualitative H-FABP. The summary estimates of sensitivity and specificity were 81% (95% prediction interval 50% to 95%) and 80% (26% to 98%) respectively for the quantitative assays and 68% (11% to 97%) and 92% (20% to 100%) respectively for the qualitative assays. Four studies reported the sensitivity of troponin and H-FABP at presentation in which the combination was considered positive if either test was positive. The addition of H-FABP to troponin increased sensitivity from 42-75% to 76-97% but decreased specificity from 94-100% to 65-93%. CONCLUSION: H-FABP has modest sensitivity and specificity for MI at presentation but estimates are subject to substantial uncertainty and primary data are subject to substantial heterogeneity. H-FABP may have a role alongside troponin in improving early sensitivity but comparison with high sensitivity troponin assays is required.

A note on dealing with missing standard errors in meta-analyses of continuous outcome measures in WinBUGS.

A meta-analysis of a continuous outcome measure may involve missing standard errors. This is not a problem depending on assumptions made about the population standard deviation. Multiple imputation can be used to impute missing values while allowing for uncertainty in the imputation. Markov chain Monte Carlo simulation is a multiple imputation technique for generating posterior predictive distributions for missing data. We present an example of imputing missing variances using WinBUGS. The example highlights the importance of checking model assumptions, whether for missing or observed data.

Worldwide relative smoking prevalence among people living with and without HIV.

OBJECTIVE AND DESIGN: People living with HIV (PLH) suffer disproportionately from the chronic diseases exacerbated by smoking tobacco. We performed a systematic review and meta-analysis to establish the relative prevalence of smoking among PLH. METHODS: We included observational studies reporting current smoking rates among PLH and comparators without HIV. We searched Medline, EMBASE, LILACS and SciELO from inception to 31 August 2019. We excluded studies that recruited participants with smoking related illness. We used a random effects model to estimate the odds ratio for current smoking in PLH and people without HIV. We used the Newcastle--Ottawa scale to assess methodological bias. We performed subgroup analysis based on sex and WHO region. We quantified heterogeneity with meta-regression and predictive distributions. PROSPERO registration:CRD42016052608. RESULTS: We identified 6116 studies and included 37. Of 111 258 PLH compared with 10 961 217 HIV-negative participants pooled odds of smoking were 1.64 [(95% confidence interval, 95% CI: 1.45-1.85) (95% prediction interval: 0.66-4.10, I2 = 98.1%)]. Odds for men and women living with HIV were 1.68 [(95% CI: 1.44-1.95) (95% prediction interval: 0.71-3.98, I2 = 91.1%)] and 2.16 [(95% CI: 1.77-2.63) (95% prediction interval: 0.92-5.07, I2 = 81.7%)] respectively. CONCLUSION: PLH are more likely to be smokers than people without HIV. This finding was true in subgroup analyses of men, women and in four of five WHO regions from which data were available. Meta-regression did not explain heterogeneity, which we attribute to the diversity of PLH populations worldwide. Smoking is a barrier to PLH achieving parity in life expectancy and an important covariate in studies of HIV-associated multimorbidity.

Pharmacological thromboprophylaxis to prevent venous thromboembolism in patients with temporary lower limb immobilization after injury: systematic review and network meta-analysis.

BACKGROUND: Thromboprophylaxis has the potential to reduce venous thromboembolism (VTE) following lower limb immobilization resulting from injury. OBJECTIVES: We aimed to estimate the effectiveness of thromboprophylaxis, compare different agents, and identify any factors associated with effectiveness. METHODS: We undertook a systematic review and network meta-analysis (NMA) of randomized trials reporting VTE or bleeding outcomes that compared thromboprophylactic agents with each other or to no pharmacological prophylaxis, for this indication. An NMA was undertaken for each outcome or agent used, and a series of study-level network meta-regressions examined whether population characteristics, type of injury, treatment of injury, or duration of thromboprophylaxis were associated with treatment effect. RESULTS: Data from 6857 participants across 13 randomized trials showed that, compared with no treatment, low molecular weight heparin (LMWH) reduced the risk of any VTE (odds ratio [OR]: 0.52; 95% credible interval [CrI]: 0.37-0.71), clinically detected deep vein thrombosis (DVT) (OR: 0.39; 95% CrI: 0.12-0.94) and pulmonary embolism (PE) (OR: 0.16; 95% CrI: 0.01-0.74), whereas fondaparinux reduced the risk of any VTE (OR: 0.13; 95% CrI: 0.05-0.30) and clinically detected DVT (OR: 0.10; 95% CrI: 0.01-0.86), with inconclusive results for PE (OR: 0.40; 95% CrI: 0.01-7.53). CONCLUSIONS: Thromboprophylaxis with either fondaparinux or LMWH appears to reduce the odds of both asymptomatic and clinically detected VTE in people with temporary lower limb immobilization following an injury. Treatment effects vary by outcome and are not always conclusive. We were unable to identify any treatment effect modifiers other than thromboprophylactic agent used.

Identification and Characterization of a DmoB Flavin Oxidoreductase from a Putative Two-Component DMS C-Monooxygenase.

The compound dimethyl sulfide (DMS) links terrestrial and oceanic sulfur with the atmosphere because of its volatility. Atmospheric DMS is responsible for cloud formation and radiation backscattering and has been implicated in climate control mitigation. The enzyme DMS C-monooxygenase degrades DMS and has been classified as a two-component FMNH2-dependent monooxygenase. This enzyme requires a flavin reductase B subunit to supply electrons to the monooxygenase A subunit where DMS conversion occurs. One form of the enzyme from Hyphomicrobium sulfonivorans has been isolated and characterized. In this work, a putative DMS C-monooxygenase has been identified with bioinformatics in Arthrobacter globiformis. We report the expression, purification, and characterization of the DmoB flavin reductase subunit, termed DmoB, from A. globiformis. Data support DmoB preference and optimal activity for the cosubstrates flavin mononucleotide (FMN) and NADH. FMN binds at a 1:1 stoichiometry with high affinity (K d = 1.11 µM). The reductase is able to generate product with the A subunit from H. sulfonivorans expressed in Escherichia coli, albeit at a lower turnover than the natively expressed enzyme. No static protein-protein interactions were observed under the conditions tested between the two subunits. These results provide new details in the classification of enzymes involved in the sulfur cycling pathway and emerging forms of the enzyme DMS monooxygenase.

Using short-term evidence to predict six-month outcomes in clinical trials of signs and symptoms in rheumatoid arthritis.

A model is presented to generate a distribution for the probability of an ACR response at six months for a new treatment for rheumatoid arthritis given evidence from a one- or three-month clinical trial. The model is based on published evidence from 11 randomized controlled trials on existing treatments. A hierarchical logistic regression model is used to find the relationship between the proportion of patients achieving ACR20 and ACR50 at one and three months and the proportion at six months. The model is assessed by Bayesian predictive P-values that demonstrate that the model fits the data well. The model can be used to predict the number of patients with an ACR response for proposed six-month clinical trials given data from clinical trials of one or three months duration.

The Rheumatoid Arthritis Drug Development Model: a case study in Bayesian clinical trial simulation.

The development of a new drug is a major undertaking and it is important to consider carefully the key decisions in the development process. Decisions are made in the presence of uncertainty and outcomes such as the probability of successful drug registration depend on the clinical development programmme.The Rheumatoid Arthritis Drug Development Model was developed to support key decisions for drugs in development for the treatment of rheumatoid arthritis. It is configured to simulate Phase 2b and 3 trials based on the efficacy of new drugs at the end of Phase 2a, evidence about the efficacy of existing treatments, and expert opinion regarding key safety criteria.The model evaluates the performance of different development programmes with respect to the duration of disease of the target population, Phase 2b and 3 sample sizes, the dose(s) of the experimental treatment, the choice of comparator, the duration of the Phase 2b clinical trial, the primary efficacy outcome and decision criteria for successfully passing Phases 2b and 3. It uses Bayesian clinical trial simulation to calculate the probability of successful drug registration based on the uncertainty about parameters of interest, thereby providing a more realistic assessment of the likely outcomes of individual trials and sequences of trials for the purpose of decision making.In this case study, the results show that, depending on the trial design, the new treatment has assurances of successful drug registration in the range 0.044-0.142 for an ACR20 outcome and 0.057-0.213 for an ACR50 outcome.

Assessment-Schedule Matching in Unanchored Indirect Treatment Comparisons of Progression-Free Survival in Cancer Studies.

BACKGROUND: The timing of efficacy-related clinical events recorded at scheduled study visits in clinical trials are interval censored, with the interval duration pre-determined by the study protocol. Events may happen any time during that interval but can only be detected during a planned or unplanned visit. Disease progression in oncology is a notable example where the time to an event is affected by the schedule of visits within a study. This can become a source of bias when studies with varying assessment schedules are used in unanchored comparisons using methods such as matching-adjusted indirect comparisons. OBJECTIVE: We illustrate assessment-time bias (ATB) in a simulation study based on data from a recent study in second-line treatment for locally advanced or metastatic urothelial carcinoma, and present a method to adjust for differences in assessment schedule when comparing progression-free survival (PFS) against a competing treatment. METHODS: A multi-state model for death and progression was used to generate simulated death and progression times, from which PFS times were derived. PFS data were also generated for a hypothetical comparator treatment by applying a constant hazard ratio (HR) to the baseline treatment. Simulated PFS times for the two treatments were then aligned to different assessment schedules so that progression events were only observed at set visit times, and the data were analysed to assess the bias and standard error of estimates of HRs between two treatments with and without assessment-schedule matching (ASM). RESULTS: ATB is highly affected by the rate of the event at the first assessment time; in our examples, the bias ranged from 3 to 11% as the event rate increased. The proposed method relies on individual-level data from a study and attempts to adjust the timing of progression events to the comparator's schedule by shifting them forward or backward without altering the patients' actual follow-up time. The method removed the bias almost completely in all scenarios without affecting the precision of estimates of comparative effectiveness. CONCLUSIONS: Considering the increasing use of unanchored comparative analyses for novel cancer treatments based on single-arm studies, the proposed method offers a relatively simple means of improving the accuracy of relative benefits of treatments on progression times.

Different strategies for pharmacological thromboprophylaxis for lower-limb immobilisation after injury: systematic review and economic evaluation.

BACKGROUND: Thromboprophylaxis can reduce the risk of venous thromboembolism (VTE) during lower-limb immobilisation, but it is unclear whether or not this translates into meaningful health benefit, justifies the risk of bleeding or is cost-effective. Risk assessment models (RAMs) could select higher-risk individuals for thromboprophylaxis. OBJECTIVES: To determine the clinical effectiveness and cost-effectiveness of different strategies for providing thromboprophylaxis to people with lower-limb immobilisation caused by injury and to identify priorities for future research. DATA SOURCES: Ten electronic databases and research registers (MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, Database of Abstracts of Review of Effects, the Cochrane Central Register of Controlled Trials, Health Technology Assessment database, NHS Economic Evaluation Database, Science Citation Index Expanded, ClinicalTrials.gov and the International Clinical Trials Registry Platform) were searched from inception to May 2017, and this was supplemented by hand-searching reference lists and contacting experts in the field. REVIEW METHODS: Systematic reviews were undertaken to determine the effectiveness of pharmacological thromboprophylaxis in lower-limb immobilisation and to identify any study of risk factors or RAMs for VTE in lower-limb immobilisation. Study quality was assessed using appropriate tools. A network meta-analysis was undertaken for each outcome in the effectiveness review and the results of risk-prediction studies were presented descriptively. A modified Delphi survey was undertaken to identify risk predictors supported by expert consensus. Decision-analytic modelling was used to estimate the incremental cost per quality-adjusted life-year (QALY) gained of different thromboprophylaxis strategies from the perspectives of the NHS and Personal Social Services. RESULTS: Data from 6857 participants across 13 trials were included in the meta-analysis. Thromboprophylaxis with low-molecular-weight heparin reduced the risk of any VTE [odds ratio (OR) 0.52, 95% credible interval (CrI) 0.37 to 0.71], clinically detected deep-vein thrombosis (DVT) (OR 0.40, 95% CrI 0.12 to 0.99) and pulmonary embolism (PE) (OR 0.17, 95% CrI 0.01 to 0.88). Thromboprophylaxis with fondaparinux (Arixtra®, Aspen Pharma Trading Ltd, Dublin, Ireland) reduced the risk of any VTE (OR 0.13, 95% CrI 0.05 to 0.30) and clinically detected DVT (OR 0.10, 95% CrI 0.01 to 0.94), but the effect on PE was inconclusive (OR 0.47, 95% CrI 0.01 to 9.54). Estimates of the risk of major bleeding with thromboprophylaxis were inconclusive owing to the small numbers of events. Fifteen studies of risk factors were identified, but only age (ORs 1.05 to 3.48), and injury type were consistently associated with VTE. Six studies of RAMs were identified, but only two reported prognostic accuracy data for VTE, based on small numbers of patients. Expert consensus was achieved for 13 risk predictors in lower-limb immobilisation due to injury. Modelling showed that thromboprophylaxis for all is effective (0.015 QALY gain, 95% CrI 0.004 to 0.029 QALYs) with a cost-effectiveness of £13,524 per QALY, compared with thromboprophylaxis for none. If risk-based strategies are included, it is potentially more cost-effective to limit thromboprophylaxis to patients with a Leiden thrombosis risk in plaster (cast) [L-TRiP(cast)] score of ≥ 9 (£20,000 per QALY threshold) or ≥ 8 (£30,000 per QALY threshold). An optimal threshold on the L-TRiP(cast) receiver operating characteristic curve would have sensitivity of 84-89% and specificity of 46-55%. LIMITATIONS: Estimates of RAM prognostic accuracy are based on weak evidence. People at risk of bleeding were excluded from trials and, by implication, from modelling. CONCLUSIONS: Thromboprophylaxis for lower-limb immobilisation due to injury is clinically effective and cost-effective compared with no thromboprophylaxis. Risk-based thromboprophylaxis is potentially optimal but the prognostic accuracy of existing RAMs is uncertain. FUTURE WORK: Research is required to determine whether or not an appropriate RAM can accurately select higher-risk patients for thromboprophylaxis. STUDY REGISTRATION: This study is registered as PROSPERO CRD42017058688. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

People who have their leg immobilised in a plaster cast or brace following an injury are at risk of developing a blood clot. Sometimes the clot can break up and lodge in the lungs, which can make the person seriously ill. Drugs that thin the blood (anticoagulants) can reduce the risk of blood clots, but they carry a small risk of serious bleeding. This study analysed all published trials of anticoagulants for people with leg immobilisation and found that, without treatment, there was a 1­2% risk of a serious blood clot. This risk was roughly halved by using anticoagulant treatment. These estimates were used in a simulation model of patient treatment and it was found that the benefit of anticoagulants in reducing blood clots (in terms of length and quality of life) outweighed the risks of bleeding. Next, all published studies of risk assessment tools were analysed. Risk assessment tools can be used to predict who is most likely to get a blood clot. There were only a few studies and they had significant weaknesses. The risk assessment tools in the simulation model were evaluated and it was found that the most cost-effective approach was to use a risk assessment tool to select approximately half of the patients for treatment (those at higher risk), while not treating those at lower risk. Treating only the higher-risk patients would be a cost-effective use of NHS resources, compared with treating nobody. Treating everybody, compared with just treating higher-risk patients, would improve outcomes for some patients but would not be a cost-effective use of NHS resources. This study suggests that anticoagulant drugs are an effective and potentially cost-effective way of preventing blood clots in people with leg immobilisation due to injury. Research is needed to determine whether or not risk assessment tools can accurately predict who needs anticoagulant drugs and who does not.

Adalimumab for non-infectious uveitis: is it cost-effective?

BACKGROUND/AIMS: Uveitis is inflammation inside the eye. Our objective was to assess the cost-effectiveness of adalimumab compared with current practice (immunosuppressants and systemic corticosteroids) in patients with non-infectious intermediate, posterior or panuveitis and to identify areas for future research. METHODS: A Markov model was built to estimate costs and benefits of the interventions. Systematic reviews were performed to identify the available relevant clinical and cost-effectiveness evidence. Data collected in two key randomised controlled trials (VISUAL I and VISUAL II) were used to estimate the interventions' effectiveness compared with the trials' comparator arms (placebo plus limited current practice (LCP)). The analysis was performed from the National Health Service and Personal Social Services perspective. Costs were calculated based on standard UK sources. RESULTS: The estimated incremental cost-effectiveness ratios (ICERs) of adalimumab versus LCP for the base case are £92 600 and £318 075 per quality-adjusted life year (QALY) gained for active and inactive uveitis, respectively. In sensitivity analyses, the ICER varied from £15 579 to £120 653 and £35 642 to £800 775 per QALY for active and inactive uveitis. CONCLUSION: The estimated ICERs of adalimumab versus LCP are above generally accepted thresholds for cost-effectiveness in the UK. Adalimumab may be more cost-effective in patients with active uveitis at greater risk of blindness. However, there is an unmet need for additional primary data to provide more reliable estimates in several important areas, including effectiveness of adalimumab versus current practice (instead of LCP), incidence of long-term blindness, adalimumab effectiveness in avoiding blindness, and rates and time to remission while on adalimumab.

Using Evidence from Randomised Controlled Trials in Economic Models: What Information is Relevant and is There a Minimum Amount of Sample Data Required to Make Decisions?

Evidence from randomised controlled trials (RCTs) is used to support regulatory approval and reimbursement decisions. I discuss how these decisions are typically made and argue that the amount of sample data and regulatory authorities' concerns over multiplicity are irrelevant when making reimbursement decisions. Decision analytic models (DAMs) are usually necessary to meet the requirements of an economic evaluation. DAMs involve inputs relating to health benefits and resource use that represent unknown true population parameters. Evidence about parameters may come from a variety of sources, including RCTs, and uncertainty about parameters is represented by their joint posterior distribution. Any impact of multiplicity is mitigated through the prior distribution. I illustrate my perspective with three examples: the estimation of a treatment effect on a rare event; the number of RCTs available in a meta-analysis; and the estimation of population mean overall survival. I conclude by recommending that reimbursement decisions should be followed by an assessment of the value of sample information and the DAM revised structurally as necessary and to include any new sample data that may be generated.

A review of methods for comparing treatments evaluated in studies that form disconnected networks of evidence.

A network meta-analysis allows a simultaneous comparison between treatments evaluated in randomised controlled trials that share at least one treatment with at least one other study. Estimates of treatment effects may be required for treatments across disconnected networks of evidence, which requires a different statistical approach and modelling assumptions to account for imbalances in prognostic variables and treatment effect modifiers between studies. In this paper, we review and discuss methods for comparing treatments evaluated in studies that form disconnected networks of evidence. Several methods have been proposed but assessing which are appropriate often depends on the clinical context as well as the availability of data. Most methods account for sampling variation but do not always account for others sources of uncertainty. We suggest that further research is required to assess the properties of methods and the use of approaches that allow the incorporation of external information to reflect parameter and structural uncertainty.

Incorporating Genuine Prior Information about Between-Study Heterogeneity in Random Effects Pairwise and Network Meta-analyses.

BACKGROUND: Pairwise and network meta-analyses using fixed effect and random effects models are commonly applied to synthesize evidence from randomized controlled trials. The models differ in their assumptions and the interpretation of the results. The model choice depends on the objective of the analysis and knowledge of the included studies. Fixed effect models are often used because there are too few studies with which to estimate the between-study SD from the data alone. OBJECTIVES: The aim of this study was to propose a framework for eliciting an informative prior distribution for the between-study SD in a Bayesian random effects meta-analysis model to genuinely represent heterogeneity when data are sparse. METHODS: We developed an elicitation method using external information, such as empirical evidence and expert beliefs, on the "range" of treatment effects to infer the prior distribution for the between-study SD. We also developed the method to be implemented in R. RESULTS: The 3-stage elicitation approach allows uncertainty to be represented by a genuine prior distribution to avoid making misleading inferences. It is flexible to what judgments an expert can provide and is applicable to all types of outcome measures for which a treatment effect can be constructed on an additive scale. CONCLUSIONS: The choice between using a fixed effect or random effects meta-analysis model depends on the inferences required and not on the number of available studies. Our elicitation framework captures external evidence about heterogeneity and overcomes the assumption that studies are estimating the same treatment effect, thereby improving the quality of inferences in decision making.

Pertuzumab for the Neoadjuvant Treatment of Early-Stage HER2-Positive Breast Cancer: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

As part of its single technology appraisal process, the National Institute for Health and Care Excellence invited the manufacturer of pertuzumab (Perjeta®; Roche Products Limited) to submit evidence of its clinical and cost- effectiveness for the neoadjuvant treatment of women with high-risk, early-stage, HER2-positive breast cancer when used in combination with trastuzumab and chemotherapy. High-risk women included those with locally advanced (including inflammatory) breast cancer and women with high-risk early-stage breast cancer (classified as T2/3 or N1). 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. This article presents the critical review of the company's submission by the Evidence Review Group and the outcome of the National Institute for Health and Care Excellence guidance. The clinical data were mainly taken from a phase II, randomised, open-label, active controlled study (NeoSphere), which reported a significant advantage in terms of pathological complete response rates of pertuzumab in combination with trastuzumab and chemotherapy, compared with trastuzumab alone with chemotherapy (45.8 vs. 29.0%, p = 0.0141). The company did not make any indirect comparisons. A meta-analysis of 12 neoadjuvant studies investigating the relationship between pathological complete response and event-free survival was used to extrapolate the outcomes reported in the NeoSphere study. A cardiac safety study (TRYPHAENA) demonstrated the safety of pertuzumab. The company undertook a model-based economic evaluation of neoadjuvant pertuzumab plus trastuzumab and docetaxel compared with neoadjuvant trastuzumab and docetaxel over a lifetime horizon from the National Health Service and Personal Social Services perspective. The probabilistic incremental cost-effectiveness ratio was estimated to be £20,104 per quality-adjusted life-year gained for pertuzumab alongside trastuzumab and docetaxel compared with trastuzumab and docetaxel, which was revised to £21,869 per quality-adjusted life-year gained following the clarification process. The Evidence Review Group corrected an error in the digitisation of the survivor functions and modified the clinically inappropriate assumption that recurrence is zero after 7 years. The Evidence Review Group's probabilistic base case was £23,962 per quality-adjusted life-year gained. During the appraisal, to mitigate the uncertainties associated with the evidence, the company offered a patient access scheme, which led to the National Institute for Health and Care Excellence Appraisal Committee recommending pertuzumab in this patient group, subject to the company providing the agreed discount in the patient access scheme.

Obinutuzumab with Bendamustine for Treating Follicular Lymphoma Refractory to Rituximab: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

As part of its single technology appraisal process, the UK National Institute for Health and Care Excellence (NICE) invited the manufacturer of obinutuzumab (Roche) to submit evidence on its clinical and cost effectiveness when used in combination with bendamustine in patients with follicular lymphoma (FL) refractory to rituximab. The Evidence Review Group (ERG), the School of Health and Related Research Technology Appraisal Group at the University of Sheffield, produced a document summarising the key points from the company submission alongside a critical review. Efficacy for progression-free survival (PFS) and safety was positively demonstrated in the pivotal GADOLIN trial, which compared obinutuzumab in combination with bendamustine followed by obinutuzumab maintenance (O-Benda+O) against bendamustine monotherapy. Data on overall survival were immature. The company submitted a model-based economic analysis, including a patient access scheme. The ERG identified a number of limitations, in particular the absence of subgroup analysis and the approach used by the company to estimate overall survival (OS), which was more favourable to the intervention arm. The key uncertainty was the duration of the treatment effect on OS. This uncertainty is expected to be reduced when the final analysis of the GADOLIN trial is reported. Consequently, the NICE appraisal committee recommended O-Benda+O in the population covered by the marketing authorisation within the Cancer Drug Fund until NICE is able to review the guidance following publication of the final analysis of GADOLIN.