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.

Electronic supplementary material

The online version of this article (10.1186/s12875-018-0714-9) contains supplementary material, which is available to authorized users.

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.

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.

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.

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.

Cost-effectiveness analysis of new generation coronary CT scanners for difficult-to-image patients

AIMS

New generation dual-source coronary CT (NGCCT) scanners with more than 64 slices were evaluated for patients with (known) or suspected of coronary artery disease (CAD) who are difficult to image: obese, coronary calcium score > 400, arrhythmias, previous revascularization, heart rate > 65 beats per minute, and intolerance of betablocker. A cost-effectiveness analysis of NGCCT compared with invasive coronary angiography (ICA) was performed for these difficult-to-image patients for England and Wales.

METHODS AND RESULTS

Five models (diagnostic decision model, four Markov models for CAD progression, stroke, radiation and general population) were integrated to estimate the cost-effectiveness of NGCCT for both suspected and known CAD populations. The lifetime costs and effects from the National Health Service perspective were estimated for three strategies: (1) patients diagnosed using ICA, (2) using NGCCT, and (3) patients diagnosed using a combination of NGCCT and, if positive, followed by ICA. In the suspected population, the strategy where patients only undergo a NGCCT is a cost-effective option at accepted cost-effectiveness thresholds. The strategy of using NGCCT in combination with ICA is the most favourable strategy for patients with known CAD. The most influential factors behind these results are the percentage of patients being misclassified (a function of both diagnostic accuracy and the prior likelihood), the complication rates of the procedures, and the cost price of a NGCCT scan.

CONCLUSION

The use of NGCCT might be considered cost-effective in both populations since it is cost-saving compared to ICA and generates similar effects.

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.

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.

AdViSHE: A Validation-Assessment Tool of Health-Economic Models for Decision Makers and Model Users

BACKGROUND

A trade-off exists between building confidence in health-economic (HE) decision models and the use of scarce resources. We aimed to create a practical tool providing model users with a structured view into the validation status of HE decision models, to address this trade-off.

METHODS

A Delphi panel was organized, and was completed by a workshop during an international conference. The proposed tool was constructed iteratively based on comments from, and the discussion amongst, panellists. During the Delphi process, comments were solicited on the importance and feasibility of possible validation techniques for modellers, their relevance for decision makers, and the overall structure and formulation in the tool.

RESULTS

The panel consisted of 47 experts in HE modelling and HE decision making from various professional and international backgrounds. In addition, 50 discussants actively engaged in the discussion at the conference workshop and returned 19 questionnaires with additional comments. The final version consists of 13 items covering all relevant aspects of HE decision models: the conceptual model, the input data, the implemented software program, and the model outcomes.

CONCLUSIONS

Assessment of the Validation Status of Health-Economic decision models (AdViSHE) is a validation-assessment tool in which model developers report in a systematic way both on validation efforts performed and on their outcomes. Subsequently, model users can establish whether confidence in the model is justified or whether additional validation efforts should be undertaken. In this way, AdViSHE enhances transparency of the validation status of HE models and supports efficient model validation.

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.

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.

Continuous versus Intermittent Data Collection of Health Care Utilization

Background: In economic evaluations, participants have to report their health care utilization continuously during follow-up. To unburden participants, researchers often collect data intermittently (i.e., in at least 3 months a year). However, comparability of intermittent v. continuous data collection is unknown. Therefore, this study aimed to compare costs estimated with intermittent data collection of health care utilization with those based on continuous data collection. Methods: We used continuous health care utilization data from a trial with 12 months of follow-up and simulated several intermittent data collection patterns. Then 3 imputation techniques—individual mean (IM), last observation carried forward (LOCF) and next observation carried backward (NOCB)—were used to estimate total annual costs. Estimated annual costs were compared with observed annual costs from continuous data collection both in the original sample and in 1000 bootstrap samples. Results: Analyses showed that intermittent data collection using cost diaries may offer good estimates of the actual total annual health expenditures. However, estimations of groups of costs differ between data collection patterns and imputation methods. The best estimations of annual total costs and groups of costs were obtained by random cohort data collection, using 3 random cohorts, ensuring that at least a third of the participants were measuring costs each month, combined with IM imputation. Intermittent data collection of health expenditures carries a small risk of missing infrequent expensive events. Conclusions: Continuous cost data collection remains the first choice. However, if intermittent measurement is chosen, we recommend calculating annual costs from intermittent data collection in random cohorts, combined with IM imputation.

Cost-effectiveness acceptability curves revisited

Since the introduction of the cost-effectiveness acceptability curve (CEAC) in 1994, its use as a method to describe uncertainty around incremental cost-effectiveness ratios (ICERs) has steadily increased. In this paper, first the construction and interpretation of the CEAC is explained, both in the context of modelling studies and in the context of cost-effectiveness (CE) studies alongside clinical trials. Additionally, this paper reviews the advantages and limitations of the CEAC. Many of the perceived limitations can be attributed to the practice of interpreting the CEAC as a decision rule while it was not developed as such. It is argued that the CEAC is still a useful tool in describing and quantifying uncertainty around the ICER, especially in combination with other tools such as plots on the CE plane and value-of-information analysis.

The role of value-of-information analysis in a health care research priority setting: a theoretical case study

BACKGROUND

The Dutch reimbursement procedure for expensive drugs requires the submission of a baseline cost-effectiveness (CE) analysis and a research plan for the period of temporary reimbursement to estimate the real-life cost-effectiveness after 4 years. The Dutch guidelines recommend a value-of-information analysis to identify the critical parameters to be studied in such an outcome study.

OBJECTIVES

Identify situations where sensitivity analyses are sufficient to establish the need for additional data collection and priority setting.

METHODS

We used a hypothetical Markov model with 3 groups of parameters. We performed deterministic and probabilistic sensitivity analyses (PSA) and analyzed the expected value of partial perfect information (EVPPI), for different configurations of input parameters and a range of threshold incremental cost-effectiveness ratios (λ). We introduced a multivariate (deterministic) sensitivity analysis and a partial PSA.

RESULTS

Deterministic, partial PSA, and EVPPI analyses came to the same ranking of priorities for future research in most cases, irrespective of the place of the results on the CE plane. Rankings differed only when the statistical metrics that we calculated for each method were close together.

CONCLUSIONS

When a clear ranking can be established, all methods lead to the same priority setting. If there is no clear ranking, we regard the parameters as equally important. Priority setting for future research depends on λ and the location of results on the CE plane. The EVPPI is needed to estimate the value of doing additional research, but to prioritize parameters for further research, extensive (partial probabilistic) sensitivity analyses and expected value of perfect information are often sufficient.

Cost-effectiveness of tiotropium versus salmeterol: the POET-COPD trial

The aim of this study was to perform a 1-yr trial-based cost-effectiveness analysis (CEA) of tiotropium versus salmeterol followed by a 5-yr model-based CEA. The within-trial CEA, including 7,250 patients with moderate to very severe chronic obstructive pulmonary disease (COPD), was performed alongside the 1-yr international randomised controlled Prevention of Exacerbations with Tiotropium (POET)-COPD trial comparing tiotropium with salmeterol regarding the effect on exacerbations. Main end-points of the trial-based analysis were costs, number of exacerbations and exacerbation days. The model-based analysis was conducted to extrapolate results to 5 yrs and to calculate quality-adjusted life years (QALYs). 1-yr costs per patient from the German statutory health insurance (SHI) perspective and the societal perspective were €126 (95% uncertainty interval (UI) €55-195) and €170 (95% UI €77-260) higher for tiotropium, respectively. The annual number of exacerbations was 0.064 (95% UI 0.010-0.118) lower for tiotropium, leading to a reduction in exacerbation-related costs of €87 (95% UI €19-157). The incremental cost-effectiveness ratio was €1,961 per exacerbation avoided from the SHI perspective and €2,647 from the societal perspective. In the model-based analyses, the 5-yr costs per QALY were €3,488 from the SHI perspective and €8,141 from the societal perspective. Tiotropium reduced exacerbations and exacerbation-related costs, but increased total costs. Tiotropium can be considered cost-effective as the resulting cost-effectiveness ratios were below commonly accepted willingness-to-pay thresholds.

Developing and applying a stochastic dynamic population model for chronic obstructive pulmonary disease

OBJECTIVES

To develop a stochastic population model of disease progression in chronic obstructive pulmonary disease (COPD) that includes the effects of COPD exacerbations on health-related quality of life, costs, disease progression, and mortality and can be used to assess the effects of a wide range of interventions.

METHODS

The model is a multistate Markov model with time varying transition rates specified by age, sex, smoking status, COPD disease severity, and/or exacerbation type. The model simulates annual changes in COPD prevalence due to COPD incidence, exacerbations, disease progression (annual decline in the forced expiratory volume in 1 second as percentage of the predicted value), and mortality. The main outcome variables are quality-adjusted life years, total exacerbations, and COPD-related health care costs. Exacerbation-related input parameters were based on quantitative meta-analysis. All important model parameters are entered into the model as probability distributions. To illustrate the potential use of the model, costs and effects were calculated for 3-year implementation of three different COPD interventions, one pharmacologic, one on smoking cessation, and one on pulmonary rehabilitation using a time horizon of 10 years for reporting outcomes.

RESULTS

Compared with minimal treatment the cost/quality-adjusted life year was €8,300 for the pharmacologic intervention, €10,800 for the smoking cessation therapy, €8,700 for the combination of the pharmacologic intervention and the smoking cessation therapy, and €17,200 for the pulmonary rehabilitation program. The probability of the interventions to be cost-effective at a ceiling ratio of €20,000 varied from 58% to 100%.

CONCLUSIONS

The COPD model provides policy makers with information about the long-term costs and effects of interventions over the entire chain of care, from primary prevention to care for very severe COPD and includes uncertainty around the outcomes.

Inverse probability weighting to control for censoring in a post hoc analysis of quality-adjusted survival data from a clinical trial of temsirolimus for renal cell carcinoma

OBJECTIVE

This post hoc analysis evaluated treatment-associated quality-adjusted survival (QAS) in patients randomly assigned to temsirolimus or interferon alfa (IFN-alfa), corrected for censoring using inverse probability weighting (IPW), in the Advanced Renal Cell Carcinoma (ARCC) trial.

METHODS

Follow-up was divided into 11 time intervals; Kaplan-Meier estimates for not being censored were estimated for each interval. The QAS for each interval was weighted by the inverse probability of not being censored in that interval. Overall treatment-associated QAS was calculated as the sum of the weighted QAS across all follow-up intervals. Differences in mean QAS between temsirolimus and IFN-alfa were evaluated with t-statistics at a two-sided α = 0.05.

RESULTS

In total, 416 patients were randomly assigned to temsirolimus (n = 209) or IFN-alfa (n = 207); 400 patients were included in this analysis. Overall weighted mean (standard deviation) QAS during progression-free survival was 111.9 (5.3) days with temsirolimus (n = 204) and 75.7 (6.3) days with IFN-alfa (n = 196). The mean weighted QAS difference of 36.2 days in favor of temsirolimus was significant (p < 0.05).

LIMITATIONS

One potential limitation is that the weights developed by the Kaplan-Meier estimates did not allow for covariates to be adjusted among treatment arms. Another possible limitation is that the ARCC trial included patients with advanced renal cell carcinoma, and thus it cannot be conclusively determined how our findings would apply to patients with less advanced disease.

CONCLUSIONS

Patients with poor-prognosis advanced renal cell carcinoma treated with temsirolimus had an incremental gain of 48% (36.2 days) in QAS compared with patients treated with IFN-alfa.

Cost-consequence analysis of remifentanil-based analgo-sedation vs. conventional analgesia and sedation for patients on mechanical ventilation in the Netherlands

Introduction

Hospitals are increasingly forced to consider the economics of technology use. We estimated the incremental cost-consequences of remifentanil-based analgo-sedation (RS) vs. conventional analgesia and sedation (CS) in patients requiring mechanical ventilation (MV) in the intensive care unit (ICU), using a modelling approach.

Methods

A Markov model was developed to describe patient flow in the ICU. The hourly probabilities to move from one state to another were derived from UltiSAFE, a Dutch clinical study involving ICU patients with an expected MV-time of two to three days requiring analgesia and sedation. Study medication was either: CS (morphine or fentanyl combined with propofol, midazolam or lorazepam) or: RS (remifentanil, combined with propofol when required). Study drug costs were derived from the trial, whereas all other ICU costs were estimated separately in a Dutch micro-costing study. All costs were measured from the hospital perspective (price level of 2006). Patients were followed in the model for 28 days. We also studied the sub-population where weaning had started within 72 hours.

Results

The average total 28-day costs were €15,626 with RS versus €17,100 with CS, meaning a difference in costs of €1474 (95% CI -2163, 5110). The average length-of-stay (LOS) in the ICU was 7.6 days in the RS group versus 8.5 days in the CS group (difference 1.0, 95% CI -0.7, 2.6), while the average MV time was 5.0 days for RS versus 6.0 days for CS. Similar differences were found in the subgroup analysis.

Conclusions

Compared to CS, RS significantly decreases the overall costs in the ICU.

Trial Registration

Clinicaltrials.gov NCT00158873.

Expected value of perfect information: an empirical example of reducing decision uncertainty by conducting additional research

OBJECTIVE

Value of information (VOI) analysis informs decision-makers about the expected value of conducting more research to support a decision. This expected value of (partial) perfect information (EV(P)PI) can be estimated by simultaneously eliminating uncertainty on all (or some) parameters involved in model-based decision-making. This study aimed to calculate the EVPPI, before and after collecting additional information on the parameter of a probabilistic Markov model with the highest EVPPI.

METHODS

The model assessed the 5-year costs per quality-adjusted life year (QALY) of three bronchodilators in chronic obstructive pulmonary disease (COPD). It had identified tiotropium as the bronchodilator with the highest expected net benefit. Total EVPI was estimated plus the EVPPIs for four groups of parameters: 1) transition probabilities between COPD severity stages; 2) exacerbation probabilities; 3) utility weights; and 4) costs. Partial EVPI analyses were performed using one-level and two-level sampling algorithms.

RESULTS

Before additional research, the total EVPI was Euro 1985 per patient at a threshold value of Euro 20,000 per QALY. EVPPIs were Euro 1081 for utilities, Euro 724 for transition probabilities, and relatively small for exacerbation probabilities and costs. A large study was performed to obtain more precise EQ-5D utilities by COPD severity stages. After using posterior utilities, the EVPPI for utilities decreased to almost zero. The total EVPI for the updated model was reduced to Euro 1037. With an EVPPI of Euro 856, transition probabilities were now the single most important parameter contributing to the EVPI.

CONCLUSIONS

This VOI analysis clearly identified parameters for which additional research is most worthwhile. After conducting additional research on the most important parameter, i.e., the utilities, total EVPI was substantially reduced.

Costs and effects of various analgesic treatments for patients with rheumatoid arthritis and osteoarthritis in the Netherlands

OBJECTIVE

To assess the balance between costs and upper gastrointestinal (GI) side effects of treatment with celecoxib, nonsteroidal antiinflammatory drugs (NSAIDs) alone, NSAID plus misoprostol, NSAID plus histamine-2 receptor antagonist (H(2)RA), NSAID plus proton pump inhibitor (PPI), and Arthrotec in The Netherlands.

METHODS

A model was used to convene data from various sources on the probability of GI side effects and resource use. The probabilities of GI side effects for celecoxib and NSAIDs alone were derived from trial data. Calculations were based on 6 months of treatment, and were from a societal perspective. Distinction was made between low-, medium-, and high-risk patients. An extensive probabilistic sensitivity analysis was performed to address uncertainty.

RESULTS

Assuming an average patient, the total costs per 6 months of therapy were: celecoxib 255 Euro, NSAIDs alone 166 Euro, NSAID plus misoprostol 285 Euro, NSAID plus H(2)RA 284 Euro, NSAID plus PPI 243 Euro, and Arthrotec 187 Euro. Treatment with celecoxib was associated with the lowest number of GI side effects and related deaths. Incremental costs per life-year saved for Arthrotec compared to NSAIDs alone were 5676 Euro for all patients and 526 Euro for medium-to-high-risk patients, whereas for high-risk patients, Arthrotec dominated NSAID alone. For celecoxib compared to Arthrotec, the incremental cost-effectiveness ratios (ICERs) were 56,667 Euro, 33,684 Euro, and 15,429 Euro, respectively.

CONCLUSION

Assuming a limit of 20,000 Euro per life-year gained, from an economic point of view, Arthrotec is the preferred treatment when all patients or medium-to-high-risk patients are considered. In high-risk patients, celecoxib is the preferred treatment strategy.

Review of A Large Clinical Series: A Microcosting Study of Intensive Care Unit Stay in the Netherlands

The primary objective of this study was to estimate the actual daily costs of intensive care unit stay using a microcosting methodology. As a secondary objective, the degree of association between daily intensive care unit costs and some patient characteristics was examined. This multicenter, retrospective cost analysis was conducted in the medical-surgical adult intensive care units of 1 university and 2 general hospitals in the Netherlands for 2006, from a hospital perspective. A total of 576 adult patients were included, consuming a total of 2868 nursing days. The mean total costs per intensive care unit day were 1911, with labour (33%) and indirect costs (33%) as the most important cost drivers. An ordinary least squares analysis including age, Nine Equivalent of Nursing Manpower Use score/Therapeutic Intervention Scoring System score, mechanical ventilation, blood products, and renal replacement therapy was able to predict 50% of the daily intensive care unit costs.

The analysis of incomplete cost data due to dropout

Incomplete data due to premature withdrawal (dropout) constitute a serious problem in prospective economic evaluations that has received only little attention to date. The aim of this simulation study was to investigate how standard methods for dealing with incomplete data perform when applied to cost data with various distributions and various types of dropout. Selected methods included the product-limit estimator of Lin et al. the expectation maximisation (EM-) algorithm, several types of multiple imputation (MI) and various simple methods like complete case analysis and mean imputation. Almost all methods were unbiased in the case of dropout completely at random (DCAR), but only the product-limit estimator, the EM-algorithm and the MI approaches provided adequate estimates of the standard error (SE). The best estimates of the mean and SE for dropout at random (DAR) were provided by the bootstrap EM-algorithm, MI regression and MI Monte Carlo Markov chain. These methods were able to deal with skewed cost data in combination with DAR and only became biased when costs also included the costs of expensive events. None of the methods were able to deal adequately with informative dropout. In conclusion, the EM-algorithm with bootstrap, MI regression and MI MCMC are robust to the multivariate normal assumption and are the preferred methods for the analysis of incomplete cost data when the assumption of DCAR is not justified.

Optimal allocation of resources over health care programmes: dealing with decreasing marginal utility and uncertainty

This paper addresses the problem of how to value health care programmes with different ratios of costs to effects, specifically when taking into account that these costs and effects are uncertain. First, the traditional framework of maximising health effects with a given health care budget is extended to a flexible budget using a value function over money and health effects. Second, uncertainty surrounding costs and effects is included in the model using expected utility. Other approaches to uncertainty that do not specify a utility function are discussed and it is argued that these also include implicit notions about risk attitude.

Decision makers’ views on health care objectives and budget constraints: results from a pilot study

Economic evaluations aim to inform policy makers about the costs and effects of medical interventions to support their decisions on the allocation of health care resources. Decision makers combine information on cost-effectiveness with their preferences and with possible constraints for the allocation of health care resources. That is, decision makers need to specify an optimality criterion and all possible (budget) constraints. Usually this is a more or less implicit process. The aim of our pilot study was to find out whether decision makers consider the objectives and budget constraints we selected for a theoretical model of resource allocation relevant, and to set priorities for these objectives.

A Risk-Adjusted Approach to Comparing the Return on Investment in Health Care Programs

The league table approach to rank ordering health care programs according to the incremental cost-effectiveness ratio is a common method to guide policy makers in setting priorities for resource allocation. In the presence of uncertainty, however, ranking programs is complicated by the degree of variability associated with each program. Confidence intervals for cost-effectiveness ratios may be overlapping. Moreover, confidence intervals may include negative ratios and the interpretation of negative cost-effectiveness ratios is ambiguous. We suggest to rank mutually exclusive health care programs according to their rate of return which is defined as the net monetary benefit over the costs of the program. However, how does a program with a higher expected return but higher uncertainty compare to a program with a lower expected return but lower risk? In the present paper we propose a risk-adjusted measure to compare the return on investment in health care programs. Financing a health care program is treated as an investment in a risky asset. The risky asset is combined with a risk-free asset in order to construct a combined portfolio. The weights attributed to the risk-free and risky assets are chosen in such a manner that all programs under consideration exhibit the same degree of uncertainty. We can then compare the performance of the individual programs by constructing a risk-adjusted league table of expected returns.

Portfolio theory and cost-effectiveness analysis: a further discussion

OBJECTIVES

Portfolio theory has been suggested as a means to improve the risk-return characteristics of investments in health-care programs through diversification when costs and effects are uncertain. This approach is based on the assumption that the investment proportions are not subject to uncertainty and that the budget can be invested in toto in health-care programs.

METHODS

In the present paper we develop an algorithm that accounts for the fact that investment proportions in health-care programs may be uncertain (due to the uncertainty associated with costs) and limited (due to the size of the programs). The initial budget allocation across programs may therefore be revised at the end of the investment period to cover the extra costs of some programs with the leftover budget of other programs in the portfolio.

RESULTS

Once the total budget is equivalent to or exceeds the expected costs of the programs in the portfolio, the initial budget allocation policy does not impact the risk-return characteristics of the combined portfolio, i.e., there is no benefit from diversification anymore.

CONCLUSION

The applicability of portfolio methods to improve the risk-return characteristics of investments in health care is limited to situations where the available budget is much smaller than the expected costs of the programs to be funded.

Portfolio theory and the alternative decision rule of cost-effectiveness analysis: theoretical and practical considerations

Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.

[Guideline 'NSAID use and the prevention of gastric damage']

Supported by the Dutch Institute for Health Care Improvement (CBO), a committee consisting of rheumatologists, general practitioners, gastroenterohepatologists, hospital pharmacists and a health-economist have developed a national evidence-based guideline for the prevention of gastric damage by non-steroidal anti-inflammatory drugs (NSAIDs). The goal of the guideline is to reduce the number of gastric ulcers with perforation or bleeding as a consequence of NSAID use. It is estimated that 165 patients died as a result of these complications in the year 2000. The guideline comprises chapters on the risk factors for ulceration during NSAID use, the effectiveness and relative toxicity of different NSAIDs for the stomach, the effectiveness of various treatments meant to reduce the risk of gastro-duodenal damage, and the management of dyspeptic symptoms during NSAID use. A strategy is recommended in which prescription of NSAIDs is always preceded by an assessment of the degree to which the risk of gastric damage is increased: the most important risk factors that need to be identified are previous peptic ulcer disease, age over 70 years, and an untreated Helicobacter pylori infection associated with peptic ulcer disease. Whenever an increased risk of gastro-duodenal damage is present, the prescribing physician can choose one of three preventive strategies: addition of misoprostol, addition of a proton-pump inhibitor, or the prescription of a COX-2-selective NSAID. Provided that adequate risk assessment has been carried out, the guideline leaves it to the patient and physician to choose which of these preventive measures, all of which result in roughly equal risk reduction and costs, is the most suitable for individual situations. The use of aspirin or a coumarin derivative increases the risk; several preventive strategies are possible; the guideline discusses the situation that arises when NSAIDs are added to the treatment.

One-year cost-effectiveness of tiotropiumversusipratropium to treat chronic obstructive pulmonary disease

The aim of this paper is to assess the health economic consequences of substituting ipratropium with the new, once-daily bronchodilator tiotropium in patients with a diagnosis of chronic obstructive pulmonary disease (COPD). This prospective cost-effectiveness analysis was performed alongside two 1-yr randomised, double-blind clinical trials in the Netherlands and Belgium. Patients had a diagnosis of COPD and a forced expiratory volume in one second (FEV1) < or = 65% predicted normal. Patients were randomised to tiotropium (18 microg once daily) or ipratropium (2 puffs of 20 microg administered four times daily) in a ratio of 2:1. The mean number of exacerbations was reduced from 1.01 in the ipratropium group (n = 175) to 0.74 in the tiotropium group (n = 344). The percentages of patients with a relevant improvement on the St. George's Respiratory Questionnaire (SGRQ) were 34.6% and 51.2%, respectively. Compared to ipratropium, the number of hospital admissions, hospital days and unscheduled visits to healthcare providers was reduced by 46%, 42% and 36% respectively. Mean annual healthcare costs including the acquisition cost of the study drugs were 1721 Euro (SEM 160) in the tiotropium group and 1,541 Euro (SEM 163) in the ipratropium group (difference 180 Euro). Incremental cost-effectiveness ratios were 667 Euro per exacerbation avoided and 1084 Euro per patient with a relevant improvement on the SGRQ. Substituting tiotropium for ipratropium in chronic obstructive pulmonary disease patients offers improved health outcomes and is associated with increased costs of 180 Euro per patient per year.

Optimising the performance of an outpatient setting

BACKGROUND

An outpatient setting typically includes experienced and novice resident physicians who are supervised by senior staff physicians. The performance of this kind of outpatient setting, for a given mix of experienced and novice resident physicians, is determined by the number of senior staff physicians available for supervision. The optimum mix of human resources may be determined using discrete-event simulation.

METHODS

An outpatient setting represents a system where concurrency and resource sharing are important. These concepts can be modelled by means of timed Coloured Petri Nets (CPN), which is a discrete-event simulation formalism. We determined the optimum mix of resources (i.e. the number of senior staff physicians needed for a given number of experienced and novice resident physicians) to guarantee efficient overall system performance.

RESULTS

In an outpatient setting with 10 resident physicians, two staff physicians are required to guarantee a minimum level of system performance (42-52 patients are seen per 5-hour period). However, with 3 senior staff physicians system performance can be improved substantially (49-56 patients per 5-hour period). An additional fourth staff physician does not substantially enhance system performance (50-57 patients per 5-hour period).

CONCLUSION

Coloured Petri Nets provide a flexible environment in which to simulate an outpatient setting and assess the impact of any staffing changes on overall system performance, to promote informed resource allocation decisions.

Optimising the performance of an outpatient setting

BACKGROUND

An outpatient setting typically includes experienced and novice resident physicians who are supervised by senior staff physicians. The performance of this kind of outpatient setting, for a given mix of experienced and novice resident physicians, is determined by the number of senior staff physicians available for supervision. The optimum mix of human resources may be determined using discrete-event simulation.

METHODS

An outpatient setting represents a system where concurrency and resource sharing are important. These concepts can be modelled by means of timed Coloured Petri Nets (CPN), which is a discrete-event simulation formalism. We determined the optimum mix of resources (i.e. the number of senior staff physicians needed for a given number of experienced and novice resident physicians) to guarantee efficient overall system performance.

RESULTS

In an outpatient setting with 10 resident physicians, two staff physicians are required to guarantee a minimum level of system performance (42-52 patients are seen per 5-hour period). However, with 3 senior staff physicians system performance can be improved substantially (49-56 patients per 5-hour period). An additional fourth staff physician does not substantially enhance system performance (50-57 patients per 5-hour period).

CONCLUSION

Coloured Petri Nets provide a flexible environment in which to simulate an outpatient setting and assess the impact of any staffing changes on overall system performance, to promote informed resource allocation decisions.

Optimizing a portfolio of health care programs in the presence of uncertainty and constrained resources

Much research has been devoted to handling uncertainty in cost-effectiveness analysis. The current literature suggests summarizing uncertainty in cost-effectiveness analysis using acceptability curves or net health benefits. These approaches, however, focus only on uncertainty associated with costs and effects of the programs under consideration. In the real world, most decision-makers have to fund a portfolio of health care programs. Therefore, a more comprehensive approach would include in the analysis the uncertainty of costs and effects of all programs supported by the fixed budget. This paper extends the decision rule described by Birch and Gafni (J. Health Econ. 11(3) (1992) 279) within the context of a portfolio of programs when costs and effects are uncertain and resources constrained.

Revisiting the decision rule of cost-effectiveness analysis under certainty and uncertainty

The classical decision rule of cost-effectiveness analysis uses a threshold cost-effectiveness ratio as a cut-off point for resources allocation. One assumption of this decision rule is complete divisibility of health care programs. In this article, we argue that health care programs cannot be completely divisible since individuals are not divisible. Consequently, instead of a linear programming approach, an integer programming approach to budget allocation is suggested. The integer programming framework can be extended to include uncertainty in the analysis. An objective function (expected aggregate effects) is maximised subject to the constraint that the probability of exceeding the budget is limited to an arbitrary level (e.g., 0.05). In case the budget is exceeded, the objective function is penalised in order to account for the opportunity costs of the additional resource requirements.

Methods to analyse cost data of patients who withdraw in a clinical trial setting

BACKGROUND

Missing data resulting from premature study withdrawal are a common problem in the analysis of longitudinal data in clinical trials. To date, this subject has received little attention in the context of economic evaluations and with regard to the analysis of cost data.

OBJECTIVES

To (i) demonstrate the impact of patients who drop out during the study on the outcomes of an economic evaluation, and (ii) to compare the mean and variation in costs after applying five different methods to deal with incomplete data: multiple imputation, complete cases analysis, linear extrapolation, predicted mean and hot decking.

STUDY DESIGN

The study was performed using cost data collected in two randomised clinical trials comparing patients with chronic obstructive pulmonary disease receiving either tiotropium bromide or ipratropium bromide. The overall dropout rate was 17%, with the daily costs of the dropouts approximately 4 times higher than the costs of the completers.

METHODS

Multiple imputation is a principled method that deals with missing observations by replacing each missing observation with a set of multiple plausible values. The variance between the resulting multiple datasets is combined with the variance between the datasets to take account of the extra uncertainty that results from missing data. The outcomes after multiple imputation were compared with the results of four naive methods to deal with missing observations: complete cases analysis, linear extrapolation, predicted mean and hot decking. All costs were expressed in 2001 euros.

RESULTS

In the tiotropium bromide group, mean (standard error) costs varied from Euro 955 (137) after complete cases analysis to Euro 1298 (198) after linear extrapolation. The corresponding estimates in the ipratropium bromide group were Euro 970 (125) and Euro 1561 (244), respectively. The difference in costs between treatment groups varied from -Euro 15 (95% CI: -379 to 349) after complete cases analysis to -Euro 402 (95% CI: -883 to 79) after predicted mean, in favour of the tiotropium bromide group. The difference in costs according to the other methods varied from -Euro 263 (95% CI: -878 to 353) after linear extrapolation to -Euro 265 (95% CI: -709 to 180) after multiple imputation to -Euro 359 (95% CI: -771 to 54) after hot decking.

CONCLUSION

This study showed that the method of dealing with the data of the dropouts had a large impact on the outcomes of an economic evaluation. Information about the rate of patient withdrawal and the way data of dropouts are treated is of vital importance in assessing the results of economic evaluations and should always be reported. Multiple imputation is a principled method that can be used to deal with the data of these patients.