Cost-Effectiveness of Treatment Strategies with Biologics in Accordance with Treatment Guidelines for Ankylosing Spondylitis: A Patient-Level Model.

BACKGROUND: Ankylosing spondylitis (AS) is a form of rheumatic disease caused by chronic inflammation of the axial skeleton. Patients with AS experience significant functional limitations and reduced quality of life. Consequently, AS imposes a substantial economic burden on society due to productivity loss and work disability. Biologics, including tumor necrosis factor (TNF) inhibitors and human anti-interleukin-17A monoclonal antibody (IL-17A) agents, are effective treatment strategies in relieving symptoms and slowing down disease progression. Currently, 5 TNF inhibitors and 2 IL-17A antibody agents are approved by the FDA for the management of AS. Of these agents, there is no clear preferred agent in initial biologic therapy, although an IL-17A antibody agent or alternative TNF inhibitor agent is recommended after failure of the initial TNF inhibitor therapy. OBJECTIVE: To assess cost-effectiveness of treatment strategies with biologics, TNF inhibitor or IL-17A, in accordance with the treatment guidelines for patients with AS. METHODS: An economic patient-level simulation combining decision-tree and Markov models was constructed from the U.S. health care payer's perspective over a 10-year time horizon. The current model examined 5 treatment strategies: (1) conventional care treatment with nonsteroidal anti-inflammatory drugs, (2) 1 TNF inhibitor, (3) an IL-17A antibody agent, (4) sequential therapy with 2 TNF inhibitors, and (5) sequential therapy with a TNF inhibitor followed by an IL-17A antibody agent. Initially, treatment responses were determined after 12-week treatments. Patients who responded to treatment entered a "responders" Markov model. Patients entered a "nonresponders" Markov model if they inadequately responded to treatment. In sequential treatment strategies, patients who inadequately responded to treatment with the first TNF inhibitor received a second TNF inhibitor or an IL-17A antibody agent. Health utility was estimated based on the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Functional Index (BASFI) scores. The models accounted for real-world adherence to TNF inhibitor treatment. Scenario and probabilistic sensitivity analyses were performed to test the robustness and uncertainty of the model results. RESULTS: Over a 10-year time horizon and 100,000 simulated patients for each treatment strategy, base-case results produced average total discounted per-patient costs of $19,765, $130,302, $159,934, $190,553, and $179,118 and quality-adjusted life-years (QALYs) of 4.675, 5.410, 5.499, 5.919, and 5.893 for conventional care, treatment strategies with 1 TNF inhibitor, an IL-17A, 2 TNF inhibitors, and a TNF inhibitor followed by an IL-17A, respectively. The optimal treatments at willingness-to-pay (WTP) thresholds ≤ $130,813 per QALY, between $130,813 per QALY and $442,728 per QALY, and > $442,728 per QALY were conventional care and sequential treatment strategies with 1 TNF inhibitor, followed by an IL-17A agent and 2 TNF inhibitors, respectively. CONCLUSIONS: Study findings suggested that all treatment strategies with biologics, TNF inhibitors or IL-17A antibody agents, in the treatment guidelines for AS were not cost-effective at the common WTP of $100,000 per QALY. However, the sequential treatment with 1 TNF inhibitor followed by an IL-17A antibody agent was considered cost-effective at a higher WTP of $150,000 per QALY. DISCLOSURES: No outside funding supported this study. The authors have nothing to disclose. Primary findings of this study were presented in part at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) in Baltimore, MD, May 2018.

The Authors Respond.

DISCLOSURES: Funding for the original study referred to in this letter was received through the PhRMA Foundation Value Assessment Challenge Award. The authors have no conflicts of interest to declare.

Patient-Level Modeling Approach Using Discrete-Event Simulation: A Cost-Effectiveness Study of Current Treatment Guidelines for Women with Postmenopausal Osteoporosis.

Decision tree and Markov models have been the most commonly used modeling methods in health economic evaluations. Both methods are known for their limitations. Discrete-event simulation (DES), an event-driven model in continuous time at the patient level, is a relatively new method in health economic evaluations that addresses some limitations of the common modeling techniques. Specifically, with the advent of personalized medicine, conventional methods for value assessment that are based on population-level measures might not be appropriate. The best treatment would depend on patient characteristics and clinical profiles. Value assessment of health interventions can vary substantially and may lead to different health decision making due to patient heterogeneity. As such, modeling at the patient level is an appropriate approach for value assessment of health interventions. The DES model has several advantages, such as flexibility, ability to reflect patient heterogeneity, increased precision, and better characterization of modeling uncertainty, that may be preferred to decision tree and Markov models. In addition, with increasing health care spending and drug prices, it is important to quantify value of available treatment options for women with postmenopausal osteoporosis (PMO). The purpose of this Viewpoints article was to describe and demonstrate an application of a DES model to evaluate the cost-effectiveness of the current treatment guidelines for women with PMO. In particular, the DES model indicated that the optimal treatment at the common willingness-to-pay thresholds between $100,000 per quality-adjusted life-year (QALY) and $150,000 per QALY was denosumab. Analysis of patient heterogeneity in terms of low, medium, high, and very high risk of fractures resulted in a similar conclusion. DISCLOSURES: Funding for this study was received through the PhRMA Foundation Value Assessment Challenge Award. The author has no conflicts of interest to declare.

Cost-effectiveness Analysis of Sequential Treatment of Abaloparatide Followed by Alendronate Versus Teriparatide Followed by Alendronate in Postmenopausal Women With Osteoporosis in the United States.

BACKGROUND: The US Food and Drug Administration has recently approved abaloparatide (ABL) for treatment of women with postmenopausal osteoporosis (PMO) at high risk of fracture. With increasing health care spending and drug prices, it is important to quantify the value of newly available treatment options for PMO. OBJECTIVE: To determine cost-effectiveness of ABL compared with teriparatide (TPTD) for treatment of women with PMO in the United States. METHODS: A discrete-event simulation (DES) model was developed to assess cost-effectiveness of ABL from the US health care perspective. The model included three 18-month treatment strategies with either placebo (PBO), TPTD, or ABL, all followed by additional 5-year treatment with alendronate (ALN). High-risk patients were defined as women with PMO ⩾65 years old with a prior vertebral fracture. Baseline clinical event rates, risk reductions, and patient characteristics were based on the Abaloparatide Comparator Trial in Vertebral Endpoints (ACTIVE) trial. RESULTS: Over a 10-year period, the DES model yielded average total discounted per-patient costs of $10 212, $46 783, and $26 837 and quality-adjusted life-years (QALYs) of 6.742, 6.781, and 6.792 for PBO/ALN, TPTD/ALN, and ABL/ALN, respectively. Compared with TPTD/ALN, ABL/ALN accrued higher QALYs at lower cost and produced an incremental cost-effectiveness ratio (ICER) of $333 266/QALY relative to PBO/ALN. In high-risk women, ABL/ALN also had more QALYs and less cost over TPTD/ALN and yielded an ICER of $188 891/QALY relative to PBO/ALN. Conclusion and Relevance: ABL is a dominant treatment strategy over TPTD. In women with PMO at high risk of fracture, ABL is an alternative cost-effective treatment.

Association between different types of comorbidity and disease burden in patients with diabetes.

BACKGROUND: This study examined the association between different types of comorbidities and the quality of diabetes care, health-related quality of life (HRQoL), and total health care expenditure. METHODS: Adult patients with diabetes were identified from the 2011 to 2013 Medical Expenditure Panel Survey, a nationally representative survey of the civilian non-institutionalized US population. Twenty different chronic conditions were captured and categorized as: (i) diabetes only; (ii) diabetes plus concordant (diabetes-related) comorbidity only; and (iii) diabetes plus one or more discordant (non-diabetes-related) comorbidities. Disease burden outcomes included the process of diabetes care (eye and foot examinations, HbA1c and cholesterol tests, influenza vaccination), HRQoL, and total health care expenditure. Multivariable models were used to examine associations between the type of comorbidity and outcomes. RESULTS: A sample of 8292 patients with diabetes was identified, of which 11.4% had diabetes only, 40.5% had concordant comorbidity only, and 48.1% reported one or more discordant comorbidities. Patients with diabetes and either type of comorbidity received better quality of diabetes care than those without a comorbidity. However, patients with discordant comorbidity showed significantly lower HRQoL measures and higher health care expenditure than those with concordant comorbidity. Adjusted total mean annual expenditure was US$4891, $6326, and $9210 for those with diabetes only and those with diabetes with one concordant or one discordant comorbidity, respectively. CONCLUSIONS: Higher disease burden in patients with diabetes was associated with discordant rather than concordant comorbidity. Future interventional studies evaluating patient-centered care models addressing different types of comorbidity are necessary to better manage these complex patients.

A Systematic Review of Health Economic Evaluation Studies Using the Patient's Perspective.

BACKGROUND: Patient-centered care has become increasingly important and relevant for informed health care decision making. OBJECTIVE: Our study aimed to perform a systematic review of health economic evaluation studies from the patient's perspective. METHODS: PubMed, EMBASE, and Cochrane Central databases were searched through May 2014 for cost-effectiveness, cost-utility, and cost-benefit studies using the patient's perspective in their analysis. The reporting quality of the studies was evaluated on the basis of Consolidated Health Economic Evaluation Reporting Standards. RESULTS: We identified 30 health economic evaluations using the patient's perspective, of which 7 were conducted in the United States, 9 in Europe, and 14 in Asian or other countries. Seventeen of 23 health conditions evaluated were chronic in nature. Among 12 studies that justified the use of the patient's perspective, patient's financial burden associated with medical treatment was the most commonly cited rationale. A total of 29, 17, and 15 studies examined direct medical, direct nonmedical, and indirect costs, respectively. Seventeen studies also included societal, governmental or payer's, and/or provider's perspective(s) in their analyses. Based on Consolidated Health Economic Evaluation Reporting Standards, more than 20% of the reporting items in these studies were either partially satisfied or not satisfied. CONCLUSIONS: There is a paucity of health economic evaluations conducted from the patient's perspective in the literature. For those studies using the patient's perspective, the true patient costs were not fully explored and study reporting quality was not optimal. With the increasing focus on patient-centered outcomes in health policy research, more frequent use of the patient's perspective in economic studies should be advocated.

Cost-effectiveness analysis of trastuzumab emtansine (T-DM1) in human epidermal growth factor receptor 2 (HER2): positive advanced breast cancer.

PURPOSE: The EMILIA trial demonstrated that trastuzumab emtansine (T-DM1) significantly increased the median profession-free and overall survival relative to combination therapy with lapatinib plus capecitabine (LC) in patients with HER2-positive advanced breast cancer (ABC) previously treated with trastuzumab and a taxane. We performed an economic analysis of T-DM1 as a second-line therapy compared to LC and monotherapy with capecitabine (C) from both perspectives of the US payer and society. METHODS: We developed four possible Markov models for ABC to compare the projected life-time costs and outcomes of T-DM1, LC, and C. Model transition probabilities were estimated from the EMILIA and EGF100151 clinical trials. Direct costs of the therapies, major adverse events, laboratory tests, and disease progression, indirect costs (productivity losses due to morbidity and mortality), and health utilities were obtained from published sources. The models used 3 % discount rate and reported in 2015 US dollars. Probabilistic sensitivity analysis and model averaging were used to account for model parametric and structural uncertainty. RESULTS: When incorporating both model parametric and structural uncertainty, the resulting incremental cost-effectiveness ratios (ICER) comparing T-DM1 to LC and T-DM1 to C were $183,828 per quality-adjusted life year (QALY) and $126,001/QALY from the societal perspective, respectively. From the payer's perspective, the ICERs were $220,385/QALY (T-DM1 vs. LC) and $168,355/QALY (T-DM1 vs. C). CONCLUSIONS: From both perspectives of the US payer and society, T-DM1 is not cost-effective when comparing to the LC combination therapy at a willingness-to-pay threshold of $150,000/QALY. T-DM1 might have a better chance to be cost-effective compared to capecitabine monotherapy from the US societal perspective.

Structural Uncertainty of Markov Models for Advanced Breast Cancer: A Simulation Study of Lapatinib.

OBJECTIVE: To examine the impact of structural uncertainty of Markov models in modeling cost-effectiveness for the treatment of advanced breast cancer (ABC). METHODS: Four common Markov models for ABC were identified and examined. Markov models 1 and 2 have 4 health states (stable-disease, responding-to-therapy, disease-progressing, and death), and Markov models 3 and 4 only have 3 health states (stable-disease, disease-progressing, and death). In models 1 and 3, the possibility of death can occur in any health state, while in models 2 and 4, the chance of dying can only occur in the disease-progressing health state. A simulation was conducted to examine the impact of using different model structures on cost-effectiveness results in the context of a combination therapy of lapatinib and capecitabine for the treatment of HER2-positive ABC. Model averaging with an assumption of equal weights in all 4 models was used to account for structural uncertainty. RESULTS: Markov model 3 yielded the lowest incremental cost-effectiveness ratio (ICER) of $303,909 per quality-adjusted life year (QALY), while Markov model 1 produced the highest ICER ($495,800/QALY). At a willingness-to-pay threshold of $150,000/QALY, the probabilities that the combination therapy is considered to be cost-effective for Markov models 1, 2, 3, and 4 were 14.5%, 14.1%, 21.6%, and 17.0%, respectively. When using model averaging to synthesize different model structures, the resulting ICER was $389,270/QALY. CONCLUSIONS: Our study shows that modeling ABC with different Markov model structures yielded a wide range of cost-effectiveness results, suggesting the need to investigate structural uncertainty in health economic evaluation. When applied in the context of HER2-positive ABC treatment, the combination therapy with lapatinib is not cost-effective, regardless of which model was used and whether uncertainties were accounted for.

Cost-effectiveness of prolonged exposure therapy versus pharmacotherapy and treatment choice in posttraumatic stress disorder (the Optimizing PTSD Treatment Trial): a doubly randomized preference trial.

OBJECTIVE: Cost-effectiveness of treatment for posttraumatic stress disorder (PTSD) may depend on type of treatment (eg, pharmacotherapy vs psychotherapy) and patient choice of treatment. We examined the cost-effectiveness of treatment with prolonged exposure therapy versus pharmacotherapy with sertraline, overall treatment preference, preference for choosing prolonged exposure therapy, and preference for choosing pharmacotherapy with sertraline from the US societal perspective. METHOD: Two hundred patients aged 18 to 65 years with PTSD diagnosis based on DSM-IV criteria enrolled in a doubly randomized preference trial. Patients were randomized to receive their treatment of choice (n = 97) or to be randomly assigned treatment (n = 103). In the choice arm, patients chose either prolonged exposure therapy (n = 61) or pharmacotherapy with sertraline (n = 36). In the no-choice arm, patients were randomized to either prolonged exposure therapy (n = 48) or pharmacotherapy with sertraline (n = 55). The total costs, including direct medical costs, direct nonmedical costs, and indirect costs, were estimated in 2012 US dollars; and total quality-adjusted life-year (QALY) was assessed using the EuroQoL Questionnaire-5 dimensions (EQ-5D) instrument in a 12-month period. This study was conducted from July 2004 to January 2009. RESULTS: Relative to pharmacotherapy with sertraline, prolonged exposure therapy was less costly (-$262; 95% CI, -$5,068 to $4,946) and produced more QALYs (0.056; 95% CI, 0.014 to 0.100) when treatment was assigned, with 93.2% probability of being cost-effective at $100,000/QALY. Independently, giving a choice of treatment also yielded lower cost (-$1,826; 95% CI, -$4,634 to $749) and more QALYs (0.010; 95% CI, -0.019 to 0.044) over no choice of treatment, with 87.0% probability of cost-effectiveness at $100,000/QALY. CONCLUSIONS: Giving PTSD patients a choice of treatment appears to be cost-effective. When choice is not possible, prolonged exposure therapy may provide a cost-effective option over pharmacotherapy with sertraline. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00127673.

Probabilistic mapping of the health status measure SF-12 onto the health utility measure EQ-5D using the US-population-based scoring models.

PURPOSE: Probabilistic mapping of the health status instrument SF-12 onto the health utility instrument EuroQol-5 dimensions (EQ-5D)-3L using the UK-population-based scoring model showed encouraging results as compared to other mapping methods, although its predictive performance using the US-population-based EQ-5D scoring models has not been investigated. In addition, a new and improved US-population-based EQ-5D scoring method has recently been developed and suggested for use in applications that required US societal health state values. In this study, we assessed predictive performance of the probabilistic mapping approach using the US-population-based scoring models on EQ-5D utility scores based on SF-12 responses and compared the results with those of other mapping methods. METHODS: Using a sample of 19,678 adults from the 2003 Medical Expenditure Panel Survey, we evaluated the predictive performance of probabilistic mapping using Bayesian networks, response mapping using multinomial logistic regression, ordinary least squares, and censored least absolute deviations models by implementing a fivefold cross-validation method. The EQ-5D utility scores were generated using two US-population-based models: D1 and MM-OC. RESULTS: Overall, the probabilistic mapping approach using Bayesian networks consistently outperformed other mapping methods with mean squared errors (MSE) of 0.007 and 0.007, mean absolute errors (MAE) of 0.057 and 0.039, and overall R (2) of 0.773 and 0.770 for the US-population-based EQ-5D scoring D1 and MM-OC models, respectively. CONCLUSION: The probabilistic mapping approach can be useful to estimate EQ-5D utility scores from SF-12 responses with better predictive measures in terms of MSE, MAE, and R (2) than other common mapping methods.

How to aggregate health? Separability and the effect of framing.

BACKGROUND: Unweighted summation or quality-adjusted life year (QALY) utilitarianism is the most common way to aggregate health benefits in a cost-effectiveness analysis. A key qualitative principle underlying QALY utilitarianism is separability: those individuals unaffected by a policy choice should not influence the policy choice. Separability also underlies several of the alternatives for QALY utilitarianism that have been proposed. OBJECTIVES: To test separability and to test whether the support for separability is affected by the framing of the choice questions. METHODS: In 2 experiments, 345 student subjects (162 in the first experiment, and 183 in the second experiment) were asked to select 1 of 2 possible treatments, with each treatment resulting in a different distribution of health across individuals. The only aspect that varied across choice questions was the state of the patients whose health was unaffected by the act of choosing a policy. In each experiment, we used 2 frames. In the implicit frame, it was implied but not plainly expressed what outcomes the treatments had in common. In the explicit frame, common outcomes of the 2 treatments were directly stated. The 2 experiments differed in the way the explicit frame was presented (verbal v. numerical). RESULTS: The support for separability was significantly greater in the explicit frame. The proportion of violations in the implicit frame was 44% in Experiment 1 and 31% in Experiment 2, while in the explicit frame, the proportion of violations was 28% in Experiment 1 and 8% in Experiment 2. CONCLUSIONS: Framing affected the support for separability, raising issues as to whether it is possible to achieve a canonical representation of social choices.

Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: an empirical analysis converting SF-12 into EQ-5D utility index in a national US sample.

BACKGROUND: As quality-adjusted life years have become the standard metric in health economic evaluations, mapping health-profile or disease-specific measures onto preference-based measures to obtain quality-adjusted life years has become a solution when health utilities are not directly available. However, current mapping methods are limited due to their predictive validity, reliability, and/or other methodological issues. OBJECTIVES: We employ probability theory together with a graphical model, called a Bayesian network, to convert health-profile measures into preference-based measures and to compare the results to those estimated with current mapping methods. METHODS: A sample of 19,678 adults who completed both the 12-item Short Form Health Survey (SF-12v2) and EuroQoL 5D (EQ-5D) questionnaires from the 2003 Medical Expenditure Panel Survey was split into training and validation sets. Bayesian networks were constructed to explore the probabilistic relationships between each EQ-5D domain and 12 items of the SF-12v2. The EQ-5D utility scores were estimated on the basis of the predicted probability of each response level of the 5 EQ-5D domains obtained from the Bayesian inference process using the following methods: Monte Carlo simulation, expected utility, and most-likely probability. Results were then compared with current mapping methods including multinomial logistic regression, ordinary least squares, and censored least absolute deviations. RESULTS: The Bayesian networks consistently outperformed other mapping models in the overall sample (mean absolute error=0.077, mean square error=0.013, and R overall=0.802), in different age groups, number of chronic conditions, and ranges of the EQ-5D index. CONCLUSION: Bayesian networks provide a new robust and natural approach to map health status responses into health utility measures for health economic evaluations.

Cost-effectiveness analysis of lapatinib in HER-2-positive advanced breast cancer.

BACKGROUND: A recent clinical trial demonstrated that the addition of lapatinib to capecitabine in the treatment of HER-2-positive advanced breast cancer (ABC) significantly increases median time to progression. The objective of the current analysis was to assess the cost-effectiveness of this therapy from the US societal perspective. METHODS: A Markov model comprising 4 health states (stable disease, respond-to-therapy, disease progression, and death) was developed to estimate the projected-lifetime clinical and economic implications of this therapy. The model used Monte Carlo simulation to imitate the clinical course of a typical patient with ABC and updated with response rates and major adverse effects. Transition probabilities were estimated based on the results from the EGF100151 and EGF20002 clinical trials of lapatinib. Health state utilities, direct and indirect costs of the therapy, major adverse events, laboratory tests, and costs of disease progression were obtained from published sources. The model used a 3% discount rate and reported in 2007 US dollars. RESULTS: Over a lifetime, the addition of lapatinib to capecitabine as combination therapy was estimated to cost an additional $19,630, with an expected gain of 0.12 quality-adjusted life years (QALY) or an incremental cost-effectiveness ratio (ICER) of $166,113 per QALY gained. The 95% confidence limits of the ICER ranged from $158,000 to $215,000/QALY. A cost-effectiveness acceptability curve indicated less than 1% probability that the ICER would be lower than $100,000/QALY. CONCLUSIONS: Compared with commonly accepted willingness-to-pay thresholds in oncology treatment, the addition of lapatinib to capecitabine is not clearly cost-effective; and most likely to result in an ICER somewhat higher than the societal willingness-to-pay threshold limits.