Being Transparent About Brilliant Failures: An Attempt to Use Real-World Data in a Disease Model for Patients with Castration-Resistant Prostate Cancer.

BACKGROUND: Real-world disease models spanning multiple treatment lines can provide insight into the (cost) effectiveness of treatment sequences in clinical practice. OBJECTIVE: Our objective was to explore whether a disease model based solely on real-world data (RWD) could be used to estimate the effectiveness of treatments for patients with castration-resistant prostate cancer (CRPC) that could then be suitably used in a cost-effectiveness analysis. METHODS: We developed a patient-level simulation model using patient-level data from the Dutch CAPRI registry as input parameters. Time to event (TTE) and overall survival (OS) were estimated with multivariate regression models, and type of event (i.e., next treatment or death) was estimated with multivariate logistic regression models. To test internal validity, TTE and OS from the simulation model were compared with the observed outcomes in the registry. RESULTS: Although patient characteristics and survival outcomes of the simulated data were comparable to those in the observed data (median OS 20.6 vs. 19.8 months, respectively), the disease model was less accurate in estimating differences between treatments (median OS simulated vs. observed population: 18.6 vs. 17.9 [abiraterone acetate plus prednisone], 24.0 vs. 25.0 [enzalutamide], 20.2 vs. 18.7 [docetaxel], and 20.0 vs. 23.8 months [radium-223]). CONCLUSIONS: Overall, the disease model accurately approximated the observed data in the total CRPC population. However, the disease model was unable to predict differences in survival between treatments due to unobserved differences. Therefore, the model is not suitable for cost-effectiveness analysis of CRPC treatment. Using a combination of RWD and data from randomised controlled trials to estimate treatment effectiveness may improve the model.

Model-based cost-effectiveness analyses comparing combinations of urate lowering therapy and anti-inflammatory treatment in gout patients.

OBJECTIVES: To assess the cost-effectiveness of various combinations of urate lowering therapy (ULT) and anti-inflammatory treatment in the management of newly diagnosed gout patients, from the Dutch societal perspective. METHODS: A probabilistic patient-level simulation estimating costs and quality-adjusted life years (QALYs) comparing gout and hyperuricemia treatment strategies was performed. ULT options febuxostat, allopurinol and no ULT were considered. Flare treatments naproxen, colchicine, prednisone, and anakinra were considered. A Markov Model was constructed to simulate gout disease. Health states were no flare, and severe pain, mild pain, moderate pain, or no pain in the presence of a flare. Model input was derived from patient level clinical trial data, meta-analyses or from previously published health-economic evaluations. The results of probabilistic sensitivity analyses were presented using incremental cost-effectiveness ratios (ICERs), and summarized using cost-effectiveness acceptability curves (CEACs). Scenario analyses were performed. RESULTS: The ICER for allopurinol versus no ULT was €1,381, when combined with naproxen. Febuxostat yielded the highest utility, but also the highest costs (€4,385 vs. €4,063 for allopurinol), resulting in an ICER of €25,173 when compared to allopurinol. No ULT was not cost-effective, yielding the lowest utility. For the gout flare medications, comparable effects on utility were achieved. Combined with febuxostat, naproxen was the cheapest option (€4,404), and anakinra the most expensive (€4,651). The ICER of anakinra compared to naproxen was €818,504. Colchicine and prednisone were dominated by naproxen. CONCLUSION: Allopurinol and febuxostat were both cost-effective compared to No ULT. Febuxostat was cost-effective in comparison with allopurinol at higher willingness-to-pay thresholds. For treating gout flares, colchicine, naproxen and prednisone offered comparable health economic implications, although naproxen was the favoured option.

Impact of hospitalisation on health-related quality of life in patients with chronic heart failure.

BACKGROUND: Empirical identification of the direct impact of hospitalisation in the change in utility could provide an interpretation for some of the unexplained variance in quality of life responses in clinical practice and clinical trials and provide assistance to researchers in assessing the impact of a hospitalisation in the context of economic evaluations. This study had the goal of determining the impact of nonfatal hospitalisations on the quality of life of a cohort of patients previously diagnosed with heart failure by using their quality of life measurements before and after hospitalisation. METHODS: The impact of hospitalisation on health-related quality of life was estimated by calculating the difference in utility measured using the EQ-5D-3L in patients that were hospitalised and had records of utility before and after hospitalisation. The variation in differences between the utilities pre and post hospitalisation was explained through two multiple linear regression models using (1) the individual patient characteristics and (2) the hospitalisation characteristics as explanatory variables. RESULTS: The mean difference between health-related quality of life measurement pre and post hospitalisation was found to be 0.020 [95% CI: - 0.020, 0.059] when measured with the EQ-5D index, while there was a mean decrease of - 0.012 [95% CI: - 0.043, 0.020] in the utility measured with the visual analogue scale. Differences in utility variation according to the primary cause for hospitalisation were found. Regression models showed a statistically significant impact of body mass index and serum creatinine in the index utility differences and of serum creatinine for utilities measured with the visual analogue scale. CONCLUSIONS: Knowing the impact of hospitalisation on health-related quality of life is particularly relevant for informing cost-effectiveness studies designed to assess health technologies aimed at reducing hospital admissions. Through using patient-level data it was possible to estimate the variation in utilities before and after the average hospitalisation and for hospitalisations due to the most common causes for hospital admission. These estimates for (dis) utility could be used in the calculations of effectiveness on economic evaluations, especially when discrete event simulations are the employed modelling technique.

Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations.

OBJECTIVES: To compare the cost-effectiveness of first-line gefitinib, erlotinib, afatinib, and osimertinib in patients with non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. METHODS: A systematic review and network meta-analysis (NMA) were conducted to compare the relative efficacy of gefitinib, erlotinib, afatinib, and osimertinib in EGFR-mutated NSCLC. To assess the cost-effectiveness of these treatments, a Markov model was developed from Dutch societal perspective. The model was based on the clinical studies included in the NMA. Incremental costs per life-year (LY) and per quality-adjusted life-year (QALY) gained were estimated. Deterministic and probabilistic sensitivity analyses (PSA) were conducted. RESULTS: Total discounted per patient costs for gefitinib, erlotinib, afatinib, and osimertinib were €65,889, €64,035, €69,418, and €131,997, and mean QALYs were 1.36, 1.39, 1.52, and 2.01 per patient, respectively. Erlotinib dominated gefitinib. Afatinib versus erlotinib yielded incremental costs of €27,058/LY and €41,504/QALY gained. Osimertinib resulted in €91,726/LY and €128,343/QALY gained compared to afatinib. PSA showed that gefitinib, erlotinib, afatinib, and osimertinib had 13%, 19%, 43%, and 26% probability to be cost-effective at a threshold of €80,000/QALY. A price reduction of osimertinib of 30% is required for osimertinib to be cost-effective at a threshold of €80,000/QALY. CONCLUSIONS: Osimertinib has a better effectiveness compared to all other TKIs. However, at a Dutch threshold of €80,000/QALY, osimertinib appears not to be cost-effective.

Phase I/II Clinical Trial-Based Early Economic Evaluation of Acalabrutinib for Relapsed Chronic Lymphocytic Leukaemia.

OBJECTIVES: The objective of this study was to construct an early economic evaluation for acalabrutinib for relapsed chronic lymphocytic leukaemia (CLL) to assist early reimbursement decision making. Scenarios were assessed to find the relative impact of critical parameters on incremental costs and quality-adjusted life-years (QALYs). METHODS: A partitioned survival model was constructed comparing acalabrutinib and ibrutinib from a UK national health service perspective. This model included states for progression-free survival (PFS), post-progression survival (PPS) and death. PFS and overall survival (OS) were parametrically extrapolated from ibrutinib publications and a preliminary hazard ratio based on phase I/II data was applied for acalabrutinib. Deterministic and probabilistic sensitivity analyses were performed, and 1296 scenarios were assessed. RESULTS: The base-case incremental cost-effectiveness ratio (ICER) was £61,941/QALY, with 3.44 incremental QALYs and incremental costs of £213,339. Deterministic sensitivity analysis indicated that survival estimates, utilities and treatment costs of ibrutinib and acalabrutinib and resource use during PFS have the greatest influence on the ICER. Probabilistic results under different development scenarios indicated that greater efficacy of acalabrutinib would decrease the likelihood of cost effectiveness (from 63% at no effect to 2% at maximum efficacy). Scenario analyses showed that a reduction in PFS did not lead to great QALY differences (- 8 to - 14% incremental QALYs) although it did greatly affect costs (- 47 to - 122% incremental pounds). For OS, the opposite was true (- 89 to - 93% QALYs and - 7 to - 39% pounds). CONCLUSIONS: Acalabrutinib is not likely to be cost effective compared with ibrutinib under current development scenarios. The conflicting effects of OS, PFS, drug costs and utility during PFS show that determining the cost effectiveness of acalabrutinib without insight into all parameters complicates health technology assessment decision making. Early assessment of the cost effectiveness of new products can support development choices and reimbursement processes through effective early dialogues between stakeholders.

First-line tyrosine kinase inhibitors in EGFR mutation-positive non-small-cell lung cancer: a network meta-analysis.

BACKGROUND: EGFR-tyrosine kinase inhibitors (EGFR-TKIs) including afatinib, dacomitinib, erlotinib, gefitinib, and osimertinib have proven efficacy in terms of progression-free survival (PFS) in patients with non-small-cell lung cancer (NSCLC) harboring EGFR mutations. However, an overall view for comparing efficacy and toxicity on a meta-level is lacking. This study compared efficacy and toxicity of first-line treatment with five different EGFR-TKIs by conducting a network meta-analysis (NMA). METHODS: A systematic review was performed, aiming to find eligible literature. Data of PFS, overall survival (OS), objective response rate (ORR), and adverse events were extracted. An NMA based on Bayesian statistics was established to synthesize the efficacy and toxicity of all treatments. RESULTS: Thirteen randomized controlled trials, including data from 3,539 patients with EGFR-mutated NSCLC, were analyzed. Rank probabilities showed that osimertinib had a potentially better efficacy in terms of PFS and OS compared to all other TKIs. For ORR, afatinib and osimertinib showed a trend of superiority compared to the other four TKIs. Furthermore, there was a high risk of diarrhea and rash for patients treated with afatinib or dacomitinib as well as a moderate risk for treatment with erlotinib, gefitinib, and osimertinib. CONCLUSION: Our study showed a favorable efficacy of osimertinib in terms of PFS and OS compared to all other EGFR-TKIs in patients with NSCLC harboring activating EGFR mutations. Furthermore, gefitinib, erlotinib, and osimertinib were associated with fewer toxicities compared to the other TKIs. Therefore, osimertinib is indicated as a preferable first-line TKI in patients with activating EGFR-mutated NSCLC.

Ribociclib with an Aromatase Inhibitor for Previously Untreated, HR-Positive, HER2-Negative, Locally Advanced or Metastatic Breast Cancer: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence, as part of the institute's single technology appraisal process, invited the manufacturer of ribociclib (Kisqali®, Novartis) to submit evidence regarding the clinical and cost effectiveness of the drug in combination with an aromatase inhibitor for the treatment of previously untreated, hormone receptor-positive, human epidermal growth factor receptor 2-negative, locally advanced or metastatic breast cancer. Kleijnen Systematic Reviews Ltd and Erasmus University Rotterdam were commissioned as the Evidence Review Group for this submission. The Evidence Review Group reviewed the evidence submitted by the manufacturer, corrected and validated the manufacturer's decision analytic model, and conducted exploratory analyses to assess the robustness and validity of the presented clinical and cost-effectiveness results. This article describes the company submission, the Evidence Review Group assessment and National Institute for Health and Care Excellence subsequent decisions. The main clinical effectiveness evidence was obtained from the MONALEESA-2 trial, a randomised controlled trial comparing ribociclib plus letrozole with placebo plus letrozole. Progression-free survival was significantly longer in the ribociclib group (95% confidence interval, 19.3-not reached) vs. 14.7 months (95% confidence interval 13.0-16.5) in the placebo group. To assess the cost effectiveness of ribociclib in combination with an aromatase inhibitor, the company developed an individual patient-level model using a discrete-event simulation approach in Microsoft® Excel. In the model, simulated patients move through a series of three health states until death, i.e. first-line progression-free survival, second-line progression-free survival and progressive disease. The length of progression-free survival during the first line was informed by the MONALEESA-2 trial. The benefit in progression-free survival in the first line was transferred to a benefit in overall survival assuming full progression-free survival to overall survival surrogacy (because of the immaturity of overall survival data from the MONALEESA-2 trial). Patient-level data from the BOLERO-2 trial, evaluating the addition of everolimus to exemestane in the second-line treatment of postmenopausal HR-positive advanced breast cancer, were used to inform the length of progression-free survival during the second line. Costs included in the model were treatment costs (e.g. technology acquisition costs of first, second, third and/or later line treatments), drug administration costs, monitoring costs and health state costs (including terminal care). Additionally, the costs of adverse events associated with the first-line treatment were incorporated. The Evidence Review Group recalculated the incremental cost-effectiveness ratio using data from a different data cut-off date from the MONALEESA-2 trial and by changing some assumptions (e.g. progression-free survival to overall survival surrogacy approach and post-progression third and/or later line treatment-related costs). After two appraisal committee meetings and a revised base case submitted by the company (including a second enhanced patient access scheme discount), the committee concluded that taking into account the uncertainties in the calculation of the cost effectiveness, there were plausible cost-effectiveness estimates broadly in the range that could be considered as a cost-effective use of National Health Service resources. Therefore, ribociclib was recommended as a treatment option for the first-line treatment of hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer, contingent on the company providing ribociclib with the discount agreed in the second enhanced patient access scheme.

Conceptual model for the health technology assessment of current and novel interventions in rheumatoid arthritis.

The objective of this study was to evaluate current approaches to economic modeling in rheumatoid arthritis (RA) and propose a new conceptual model for evaluation of the cost-effectiveness of RA interventions. We followed recommendations from the International Society of Pharmacoeconomics and Outcomes Research-Society of Medical Decision Making (ISPOR-SMDM) Modeling Good Research Practices Task Force-2. The process involved scoping the decision problem by a working group and drafting a preliminary cost-effectiveness model framework. A systematic literature review (SLR) of existing decision-analytic models was performed and analysis of an RA registry was conducted to inform the structure of the draft conceptual model. Finally, an expert panel was convened to seek input on the draft conceptual model. The proposed conceptual model consists of three separate modules: 1) patient characteristic module, 2) treatment module, and 3) outcome module. Consistent with the scope, the conceptual model proposed six changes to current economic models in RA. These changes proposed are to: 1) use composite measures of disease activity to evaluate treatment response as well as disease progression (at least two measures should be considered, one as the base case and one as a sensitivity analysis); 2) conduct utility mapping based on disease activity measures; 3) incorporate subgroups based on guideline-recommended prognostic factors; 4) integrate realistic treatment patterns based on clinical practice/registry datasets; 5) assimilate outcomes that are not joint related (extra-articular outcomes); and 6) assess mortality based on disease activity. We proposed a conceptual model that incorporates the current understanding of clinical and real-world evidence in RA, as well as of existing modeling assumptions. The proposed model framework was reviewed with experts and could serve as a foundation for developing future cost-effectiveness models in RA.

The increasing importance of a continence nurse specialist to improve outcomes and save costs of urinary incontinence care: an analysis of future policy scenarios.

BACKGROUND: In an ageing population, it is inevitable to improve the management of care for community-dwelling elderly with incontinence. A previous study showed that implementation of the Optimum Continence Service Specification (OCSS) for urinary incontinence in community-dwelling elderly with four or more chronic diseases results in a reduction of urinary incontinence, an improved quality of life, and lower healthcare and lower societal costs. The aim of this study was to explore future consequences of the OCSS strategy of various healthcare policy scenarios in an ageing population. METHODS: We adapted a previously developed decision analytical model in which the OCSS new care strategy was operationalised as the appointment of a continence nurse specialist located within the general practice in The Netherlands. We used a societal perspective including healthcare costs (healthcare providers, treatment costs, insured containment products, insured home care), and societal costs (informal caregiving, containment products paid out-of-pocket, travelling expenses, home care paid out-of-pocket). All outcomes were computed over a three-year time period using two different base years (2014 and 2030). Settings for future policy scenarios were based on desk-research and expert opinion. RESULTS: Our results show that implementation of the OSCC new care strategy for urinary incontinence would yield large health gains in community dwelling elderly (2030: 2592-2618 QALYs gained) and large cost-savings in The Netherlands (2030: health care perspective: €32.4 Million - €72.5 Million; societal perspective: €182.0 Million - €250.6 Million). Savings can be generated in different categories which depends on healthcare policy. The uncertainty analyses and extreme case scenarios showed the robustness of the results. CONCLUSIONS: Implementation of the OCSS new care strategy for urinary incontinence results in an improvement in the quality of life of community-dwelling elderly, a reduction of the costs for payers and affected elderly, and a reduction in time invested by carers. Various realistic policy scenarios even forecast larger health gains and cost-savings in the future. More importantly, the longer the implementation is postponed the larger the savings foregone. The future organisation of healthcare affects the category in which the greatest savings will be generated.

Cost-Effectiveness Analysis of Abatacept Compared with Adalimumab on Background Methotrexate in Biologic-Naive Adult Patients with Rheumatoid Arthritis and Poor Prognosis.

OBJECTIVES: To assess cost effectiveness of abatacept versus adalimumab, each administered with methotrexate, in treating patients with rheumatoid arthritis (RA) stratified according to baseline anticitrullinated protein antibody (ACPA) levels (marker of poor prognosis in RA). METHODS: A payer-perspective cost-effectiveness model simulated disease progression in patients with RA who had previously failed conventional disease-modifying antirheumatic drugs and were starting biologic therapy. Patients commenced treatment with abatacept or adalimumab plus methotrexate and were evaluated after 6 months. Therapy continuation was based on the European League Against Rheumatism treatment response; disease progression was based on the Health Assessment Questionnaire Disability Index score. These score changes were used to estimate health state utilities and direct medical costs. Quality-adjusted life-years (QALYs) and incremental cost per QALY gained were calculated by baseline ACPA groups (Q1, 28-234 AU/ml; Q2, 235-609 AU/ml; Q3, 613-1045 AU/ml; and Q4, 1060-4894 AU/ml). Scenario analysis and one-way and probabilistic sensitivity analyses were used to evaluate robustness of model assumptions. RESULTS: Abatacept resulted in QALY gain versus adalimumab in ACPA Q1, Q3, and Q4; between-treatment difference (difference: Q1, -0.115 Q2, -0.009 Q3, 0.045; and Q4, 0.279). Total lifetime discounted cost was higher for abatacept versus adalimumab in most quartiles (Q2, £77,612 vs. £77,546; Q3, £74,441 vs. £73,263; and Q4, £78,428 vs. £76,696) because of longer time on treatment. Incremental cost per QALY for abatacept (vs. adalimumab) was the lowest in the high ACPA titer group (Q4, £6200/QALY), followed by the next lowest titer group (Q3, £26,272/QALY). CONCLUSIONS: Abatacept is a cost effective alternative to adalimumab in patients with RA with high ACPA levels.

Pomalidomide with Dexamethasone for Treating Relapsed and Refractory Multiple Myeloma Previously Treated with Lenalidomide and Bortezomib: An Evidence Review Group Perspective of an NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE), as part of the institute's single technology appraisal (STA) process, invited the manufacturer of pomalidomide (POM; Imnovid®, Celgene) to submit evidence regarding the clinical and cost effectiveness of the drug in combination with dexamethasone (POM + LoDEX) for the treatment of relapsed and refractory multiple myeloma (RRMM) after at least two regimens including lenalidomide (LEN) and bortezomib (BOR). Kleijnen Systematic Reviews Ltd (KSR) and Erasmus University Rotterdam were commissioned as the Evidence Review Group (ERG) for this submission. The ERG reviewed the evidence submitted by the manufacturer, validated the manufacturer's decision analytic model, and conducted exploratory analyses in order to assess the robustness and validity of the presented clinical and cost-effectiveness results. This paper describes the company submission, the ERG assessment, and NICE's subsequent decisions. The company conducted a systematic review to identify studies comparing POM with comparators outlined in the NICE scope: panobinostat with bortezomib and dexamethasone (PANO + BOR + DEX), bendamustine with thalidomide and dexamethasone (BTD) and conventional chemotherapy (CC). The main clinical effectiveness evidence was obtained from MM-003, a randomized controlled trial (RCT) comparing POM + LoDEX with high-dose dexamethasone (HiDEX; used as a proxy for CC). Additional data from other studies were also used as nonrandomized observational data sources for the indirect treatment comparison of POM + LoDEX with BTD and PANO + BOR + DEX. Covariate or treatment switching adjustment methods were used for each comparison. The model developed in Microsoft® Excel 2010 using a semi-Markov partitioned survival structure, submitted in the original submission to NICE for TA338, was adapted for the present assessment of the cost effectiveness of POM + LoDEX. Updated evidence from the clinical-effectiveness part was used for the survival modelling of progression-free survival and overall survival. For POM + LoDEX, the patient access scheme (PAS) discount was applied to the POM price. Three separate comparisons were conducted for each comparator, each comparison using a different dataset and adjustment methods. The ERG identified and corrected some errors, and the corrected incremental cost-effectiveness ratios (ICERs) for POM + LoDEX versus each comparator were presented: approximately £45,000 per quality-adjusted life-year (QALY) gained versus BTD, savings of approximately £143,000 per QALY lost versus PANO + BOR + DEX, and approximately £49,000 per QALY gained versus CC. The ERG also conducted full incremental analyses, which revealed that CC, POM + LoDEX and PANO + BOR + DEX were on the cost-effectiveness frontier. The committee's decision on the technology under analysis deemed that POM + LoDEX should be recommended as an option for treating multiple myeloma in adults at third or subsequent relapse of treatments including both LEN and BOR, contingent on the company providing POM with the discount agreed in the PAS.

A New Statistical Method to Determine the Degree of Validity of Health Economic Model Outcomes against Empirical Data.

BACKGROUND: The validation of health economic (HE) model outcomes against empirical data is of key importance. Although statistical testing seems applicable, guidelines for the validation of HE models lack guidance on statistical validation, and actual validation efforts often present subjective judgment of graphs and point estimates. OBJECTIVES: To discuss the applicability of existing validation techniques and to present a new method for quantifying the degrees of validity statistically, which is useful for decision makers. METHODS: A new Bayesian method is proposed to determine how well HE model outcomes compare with empirical data. Validity is based on a pre-established accuracy interval in which the model outcomes should fall. The method uses the outcomes of a probabilistic sensitivity analysis and results in a posterior distribution around the probability that HE model outcomes can be regarded as valid. RESULTS: We use a published diabetes model (Modelling Integrated Care for Diabetes based on Observational data) to validate the outcome "number of patients who are on dialysis or with end-stage renal disease." Results indicate that a high probability of a valid outcome is associated with relatively wide accuracy intervals. In particular, 25% deviation from the observed outcome implied approximately 60% expected validity. CONCLUSIONS: Current practice in HE model validation can be improved by using an alternative method based on assessing whether the model outcomes fit to empirical data at a predefined level of accuracy. This method has the advantage of assessing both model bias and parameter uncertainty and resulting in a quantitative measure of the degree of validity that penalizes models predicting the mean of an outcome correctly but with overly wide credible intervals.

Ramucirumab for Treating Advanced Gastric Cancer or Gastro-Oesophageal Junction Adenocarcinoma Previously Treated with Chemotherapy: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE) invited the company that manufactures ramucirumab (Cyramza®, Eli Lilly and Company) to submit evidence of the clinical and cost effectiveness of the drug administered alone (monotherapy) or with paclitaxel (combination therapy) for treating adults with advanced gastric cancer or gastro-oesophageal junction (GC/GOJ) adenocarcinoma that were previously treated with chemotherapy, as part of the Institute's single technology appraisal (STA) process. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company's submission, the ERG review, and NICE's subsequent decisions. Clinical effectiveness evidence for ramucirumab monotherapy (RAM), compared with best supportive care (BSC), was based on data from the REGARD trial. Clinical effectiveness evidence for ramucirumab combination therapy (RAM + PAC), compared with paclitaxel monotherapy (PAC), was based on data from the RAINBOW trial. In addition, the company undertook a network meta-analysis (NMA) to compare RAM + PAC with BSC and docetaxel. Cost-effectiveness evidence of monotherapy and combination therapy relied on partitioned survival, cost-utility models. The base-case incremental cost-effectiveness ratio (ICER) of the company was £188,640 (vs BSC) per quality-adjusted life-year (QALY) gained for monotherapy and £118,209 (vs BSC) per QALY gained for combination therapy. The ERG assessment indicated that the modelling structure represented the course of the disease; however, a few errors were identified and some of the input parameters were challenged. The ERG provided a new base case, with ICERs (vs BSC) of £188,100 (monotherapy) per QALY gained and £129,400 (combination therapy) per QALY gained and conducted additional exploratory analyses. The NICE Appraisal Committee (AC), considered the company's decision problem was in line with the NICE scope, with the exception of the choice of comparators for the combination therapy model. The most plausible ICER for ramucirumab monotherapy compared with BSC was £188,100 per QALY gained. The Committee considered that the ERG's exploratory analysis in which RAM + PAC was compared with PAC by using the direct head-to-head data (including utilities) from the RAINBOW trial, provided the most plausible ICER (i.e. £408,200 per QALY gained) for ramucirumab combination therapy. The Committee concluded that end-of-life considerations cannot be applied for either case, since neither failed to offer an extension to life of at least 3 months. The company did not submit a patient access scheme (PAS). After consideration of the evidence, the Committee concluded that ramucirumab alone or with paclitaxel could not be considered a cost-effective use of National Health Service resources for treating advanced GC/GOJ patients that were previously treated with chemotherapy, and therefore its use could not be recommended. We might wonder if a complete STA process is necessary for treatments without a PAS, which are, according to the company's submission, already associated with ICERs far above the currently accepted threshold in all (base-case, sensitivity and scenario) analyses.

Mix and match. A simulation study on the impact of mixed-treatment comparison methods on health-economic outcomes.

BACKGROUND: Decision-analytic cost-effectiveness (CE) models combine many parameters, often obtained after meta-analysis. AIM: We compared different methods of mixed-treatment comparison (MTC) to combine transition and event probabilities derived from several trials, especially with respect to health-economic (HE) outcomes like (quality adjusted) life years and costs. METHODS: Trials were drawn from a simulated reference population, comparing two of four fictitious interventions. The goal was to estimate the CE between two of these. The amount of heterogeneity between trials was varied in scenarios. Parameter estimates were combined using direct comparison, MTC methods proposed by Song and Puhan, and Bayesian generalized linear fixed effects (GLMFE) and random effects models (GLMRE). Parameters were entered into a Markov model. Parameters and HE outcomes were compared with the reference population using coverage, statistical power, bias and mean absolute deviation (MAD) as performance indicators. Each analytical step was repeated 1,000 times. RESULTS: The direct comparison was outperformed by the MTC methods on all indicators, Song's method yielded low bias and MAD, but uncertainty was overestimated. Puhan's method had low bias and MAD and did not overestimate uncertainty. GLMFE generally had the lowest bias and MAD, regardless of the amount of heterogeneity, but uncertainty was overestimated. GLMRE showed large bias and MAD and overestimated uncertainty. Song's and Puhan's methods lead to the least amount of uncertainty, reflected in the shape of the CE acceptability curve. GLMFE showed slightly more uncertainty. CONCLUSIONS: Combining direct and indirect evidence is superior to using only direct evidence. Puhan's method and GLMFE are preferred.

Cost Recommendation under Uncertainty in IQWiG's Efficiency Frontier Framework.

BACKGROUND: The National Institute for Quality and Efficiency in Health Care (IQWiG) employs an efficiency frontier (EF) framework to facilitate setting maximum reimbursable prices for new interventions. Probabilistic sensitivity analysis (PSA) is used when yes/no reimbursement decisions are sought based on a fixed threshold. In the IQWiG framework, an additional layer of complexity arises as the EF itself may vary its shape in each PSA iteration, and thus the willingness-to-pay, indicated by the EF segments, may vary. OBJECTIVES: To explore the practical problems arising when, within the EF approach, maximum reimbursable prices for new interventions are sought through PSA. METHODS: When the EF is varied in a PSA, cost recommendations for new interventions may be determined by the mean or the median of the distances between each intervention's point estimate and each EF. Implications of using these metrics were explored in a simulation study based on the model used by IQWiG to assess the cost-effectiveness of 4 antidepressants. RESULTS: Depending on the metric used, cost recommendations can be contradictory. Recommendations based on the mean can also be inconsistent. Results (median) suggested that costs of duloxetine, venlafaxine, mirtazapine, and bupropion should be decreased by €131, €29, €12, and €99, respectively. These recommendations were implemented and the analysis repeated. New results suggested keeping the costs as they were. The percentage of acceptable PSA outcomes increased 41% on average, and the uncertainty associated to the net health benefit was significantly reduced. CONCLUSIONS: The median of the distances between every intervention outcome and every EF is a good proxy for the cost recommendation that would be given should the EF be fixed. Adjusting costs according to the median increased the probability of acceptance and reduced the uncertainty around the net health benefit distribution, resulting in a reduced uncertainty for decision makers.

Lenalidomide for the Treatment of Low- or Intermediate-1-Risk Myelodysplastic Syndromes Associated with Deletion 5q Cytogenetic Abnormality: An Evidence Review of the NICE Submission from Celgene.

The National Institute for Health and Care Excellence (NICE) invited the manufacturer of lenalidomide (Celgene) to submit evidence of the clinical and cost effectiveness of the drug for treating adults with myelodysplastic syndromes (MDS) associated with deletion 5q cytogenetic abnormality, as part of the Institute's single technology appraisal (STA) process. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company's submission, the ERG review, and the NICE's subsequent decisions. The ERG reviewed the evidence for clinical and cost effectiveness of the technology, as submitted by the manufacturer to the NICE. The ERG searched for relevant additional evidence and validated the manufacturer's decision analytic model to examine the robustness of the cost-effectiveness results. Clinical effectiveness was obtained from a three-arm, European, randomized, phase III trial among red blood cell (RBC) transfusion-dependent patients with low-/intermediate-1-risk del5q31 MDS. The primary endpoint was RBC independence for ≥26 weeks, and was reached by a higher proportion of patients in the lenalidomide 10 and 5 mg groups compared with placebo (56.1 and 42.6 vs 5.9 %, respectively; both p < 0.001). The option of dose adjustments after 16 weeks due to dose-limiting toxicities or lack of response made long-term effectiveness estimates unreliable, e.g. overall survival (OS). The de novo model of the manufacturer included a Markov state-transition cost-utility model implemented in Microsoft Excel. The base-case incremental cost-effectiveness ratio (ICER) of the manufacturer was £56,965. The ERG assessment indicated that the modeling structure represented the course of the disease; however, a few errors were identified and some of the input parameters were challenged. In response to the appraisal documentation, the company revised the economic model, which increased the ICER to £68,125 per quality-adjusted life-year. The NICE Appraisal Committee (AC) did not recommend lenalidomide as a cost-effective treatment. Subsequently, the manufacturer submitted a Patient Access Scheme (PAS) that provided lenalidomide free of charge for patients who remained on treatment after 26 cycles. This PAS improved the ICER to £25,300, although the AC considered the proportion of patients who received treatment beyond 26 cycles, and hence the ICER, to be uncertain. Nevertheless, the AC accepted a commitment from the manufacturer to publish, once available, data on the proportion of patients eligible for the PAS, and believed this provided reassurance that lenalidomide was a cost-effective treatment for low- or intermediate-1-risk MDS patients.

Effects of Achieving Target Measures in Rheumatoid Arthritis on Functional Status, Quality of Life, and Resource Utilization: Analysis of Clinical Practice Data.

OBJECTIVE: To evaluate associations between achieving guideline-recommended targets of disease activity, defined by the Disease Activity Score in 28 joints using C-reactive protein level (DAS28-CRP) <2.6, the Simplified Disease Activity Index (SDAI) ≤3.3, or the Clinical Disease Activity Index (CDAI) ≤2.8, and other health outcomes in a longitudinal observational study. METHODS: Other defined thresholds included low disease activity (LDA), moderate (MDA), or severe disease activity (SDA). To control for intraclass correlation and estimate effects of independent variables on outcomes of the modified Health Assessment Questionnaire (M-HAQ), the EuroQol 5-domain (EQ-5D; a quality-of-life measure), hospitalization, and durable medical equipment (DME) use, we employed mixed models for continuous outcomes and generalized estimating equations for binary outcomes. RESULTS: Among 1,297 subjects, achievement (versus nonachievement) of recommended disease targets was associated with enhanced physical functioning and lower health resource utilization. After controlling for baseline covariates, achievement of disease targets (versus LDA) was associated with significantly enhanced physical functioning based on SDAI ≤3.3 (ΔM-HAQ -0.047; P = 0.0100) and CDAI ≤2.8 (-0.073; P = 0.0003) but not DAS28-CRP <2.6 (-0.022; P = 0.1735). Target attainment was associated with significantly improved EQ-5D (0.022-0.096; P < 0.0030 versus LDA, MDA, or SDA). Patients achieving guideline-recommended disease targets were 36-45% less likely to be hospitalized (P < 0.0500) and 23-45% less likely to utilize DME (P < 0.0100). CONCLUSION: Attaining recommended target disease-activity measures was associated with enhanced physical functioning and health-related quality of life. Some health outcomes were similar in subjects attaining guideline targets versus LDA. Achieving LDA is a worthy clinical objective in some patients.

Determining the impact of modeling additional sources of uncertainty in value-of-information analysis.

BACKGROUND: The conditional reimbursement policy for expensive medicines in The Netherlands requires data collection on actual use and cost-effectiveness after the initial decision to reimburse a drug. This introduces new sources of uncertainty (less important in a randomized controlled trial than in daily practice), which may affect priorities for further research. OBJECTIVES: This article focuses on determining the impact of including these uncertainties at the time a decision is made, and whether more complex models are always needed to address prioritization of additional research. METHODS: We constructed a typical decision model for chronic progressive diseases with four health states and parameters related to transition and exacerbation probabilities, costs, and utilities. Different scenarios are built on the basis of three additional uncertainties: persistence, compliance, and broadening of indication. Persistence refers to treatment duration. Compliance describes the fraction of treatment benefit obtained because of not taking the medication as prescribed. Broadening of indication reflects a shift in the severity distribution at treatment start. These uncertainties were parameterized in the model and included in the value-of-information analysis. RESULTS: The most important parameters were transition probabilities. Broadening of indication had little impact on the overall uncertainty. Compliance and persistence were important when establishing priorities for further research. Major differences with respect to the reference scenario were due to the parameterization of compliance in the decision model. CONCLUSIONS: The usual practice of modeling only randomized controlled trial data at the time the decision on conditional reimbursement is made can lead to wrong decisions. Additional uncertainties arising from outcomes studies should be anticipated at an early stage and included in the model because this can have a strong impact on the prioritization of further research.

A choice that matters? Smulation study on the impact of direct meta-analysis methods on health economic outcomes.

BACKGROUND: Decision-analytic cost-effectiveness (CE) models combine many different parameters like transition probabilities, event probabilities, utilities and costs, which are often obtained after meta-analysis. The method of meta-analysis may affect the CE estimate. AIM: Our aim was to perform a simulation study that compares the performance of different methods of meta-analysis, especially with respect to model-based health economic (HE) outcomes. METHODS: A reference patient population of 50,000 was simulated from which sets of samples were drawn. Each sample drawn represented a clinical trial comparing two fictitious interventions. In several scenarios, the heterogeneity between these trials was varied, by drawing one or more of the trials from predefined subpopulations. Parameter estimates from these trials were combined using frequentist fixed (FFE) and random effects (FRE), and Bayesian fixed (BFE) and random effects (BRE) meta-analysis. The pooled parameter estimates were entered into a probabilistic cost-effectiveness Markov model. The four methods of meta-analysis resulted in different parameter estimates and HE outcomes, which were compared with the true values in the reference population. Performance statistics were: (1) the percentage of repetitions that the confidence interval of the probabilistic sensitivity analysis covers the true value (coverage), (2) the difference between the estimated and true value (bias), (3) the mean absolute value of the bias (MAD) and (4) the percentage of repetitions that result in a statistically significant difference between the two interventions (statistical power). As the differences between methods could be due to chance, we repeated every step of the analysis 1,000 times to study whether differences were systematic. RESULTS: FFE, FRE and BFE lead to different parameter estimates, but, when entered into the model, they do not lead to large differences in the point estimates of the HE outcomes, even in scenarios where we built in heterogeneity. Random effects methods do not necessarily reduce bias when heterogeneity is added to the trials, and may even increase bias in certain situations. BRE tends to overestimate uncertainty reflected in the CE acceptability curve. CONCLUSION: FFE, FRE and BFE lead to comparable HE outcomes. BRE tends to overestimate uncertainty. Based on this study, we recommend FRE as the preferred method of meta-analysis.