A novel comorbidity index in Italy based on diseases detected by the surveillance system PASSI and the Global Burden of Diseases disability weights

BACKGROUND

Understanding comorbidity and its burden characteristics is essential for policymakers and healthcare providers to allocate resources accordingly. However, several definitions of comorbidity burden can be found in the literature. The main reason for these differences lies in the available information about the analyzed diseases (i.e., the target population studied), how to define the burden of diseases, and how to aggregate the occurrence of the detected health conditions.

METHODS

In this manuscript, we focus on data from the Italian surveillance system PASSI, proposing an index of comorbidity burden based on the disability weights from the Global Burden of Disease (GBD) project. We then analyzed the co-presence of ten non-communicable diseases, weighting their burden thanks to the GBD disability weights extracted by a multi-step procedure. The first step selects a set of GBD weights for each disease detected in PASSI using text mining. The second step utilizes an additional variable from PASSI (i.e., the perceived health variable) to associate a single disability weight for each disease detected in PASSI. Finally, the disability weights are combined to form the comorbidity burden index using three approaches common in the literature.

RESULTS

The comorbidity index (i.e., combined disability weights) proposed allows an exploration of the magnitude of the comorbidity burden in several Italian sub-populations characterized by different socioeconomic characteristics. Thanks to that, we noted that the level of comorbidity burden is greater in the sub-population characterized by low educational qualifications and economic difficulties than in the rich sub-population characterized by a high level of education. In addition, we found no substantial differences in terms of predictive values of comorbidity burden adopting different approaches in combining the disability weights (i.e., additive, maximum, and multiplicative approaches), making the Italian comorbidity index proposed quite robust and general.

Catalogues of EQ-5D-3L Health-Related Quality of Life Scores for 199 Chronic Conditions and Health Risks for Use in the UK and the USA

BACKGROUND

Health-related quality of life (HRQoL) measures are essential in economic evaluation, but sometimes primary sources are unavailable, and information from secondary sources is required. Existing HRQoL UK/US catalogues are based on earlier diagnosis classification systems, amongst other issues. A recently published Danish catalogue merged EQ-5D-3L data from national health surveys with national registers containing patient information on ICD-10 diagnoses, healthcare activities and socio-demographics.

AIMS

To provide (1) UK/US EQ-5D-3L-based HRQoL utility population catalogues for 199 chronic conditions on the basis of ICD-10 codes and health risks and (2) regression models controlling for age, sex, comorbidities and health risks to enable predictions in other populations.

METHODS

UK and US EQ-5D-3L value sets were applied to the EQ-5D-3L responses of the Danish dataset and modelled using adjusted limited dependent variable mixture models (ALDVMMs).

RESULTS

Unadjusted mean utilities, percentiles and adjusted disutilities based on two ALDVMMs with different control variables were provided for both countries. Diseases from groups M, G, and F consistently had the smallest utilities and the largest negative disutilities: fibromyalgia (M797), sclerosis (G35), rheumatism (M790), dorsalgia (M54), cerebral palsy (G80-G83), post-traumatic stress disorder (F431), dementia (F00-2), and depression (F32, etc.). Risk factors, including stress, loneliness, and BMI30+, were also associated with lower HRQoL.

CONCLUSIONS

This study provides comprehensive catalogues of UK/US EQ-5D-3L HRQoL utilities. Results are relevant in cost-effectiveness analysis, for NICE submissions, and for comparing and identifying facets of disease burden.

Estimating Joint Health State Utility Algorithms Under Partial Information

OBJECTIVES

We explored the performance of existing joint health state utility estimators when data are not available on utilities that isolate single-condition health states excluding any co-occurring condition.

METHODS

Using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III, we defined 2 information sets: (1) a full-information set that includes the narrowly defined health state utilities used in most studies that test the performance of joint health state utility estimators, and (2) a limited information set that includes only the more broadly defined health state utilities more commonly available to researchers. We used an example of alcohol use disorder co-occurring with cirrhosis of the liver, depressive disorder, or nicotine use disorder to illustrate our analysis.

RESULTS

We found that the performance of joint health state utility estimators is appreciably different under limited information than under full information. Full-information estimators typically overestimate the joint state utility, whereas limited-information estimators underestimate the joint state utility, except for the minimum estimator, which is overestimated in all cases.

CONCLUSIONS

Researchers using joint health state utility estimators should understand the information set available to them and use methodological guidance appropriate for that information set. We recommend the minimum estimator under limited information based on its ease of use, consistency (and therefore a predictable direction of bias), and lower root mean squared error.

Catalog of EQ-5D-3L Health-Related Quality-of-Life Scores for 199 Chronic Conditions and Health Risks in Denmark

Background. Assessments of health-related quality of life (HRQoL) are essential in estimating quality-adjusted life-years. It is sometimes not feasible to collect primary HRQoL data, and reliable secondary sources are necessary. Current "off-the-shelf" HRQoL catalogs are based on older diagnosis classifications and include a limited number of diseases. This article aims to provide 1) a Danish EQ-5D-3L-based HRQoL catalog for 199 nationally representative chronic conditions based on ICD-10 codes and 2) a complementary model-based catalog controlling for age, sex, comorbidities, lifestyle, and health risks. Design. A total of 55,616 respondents from 3 national health survey samples were pooled and combined with 7 national registers containing patient-level information on diagnoses, health care activity, and sociodemographics. EQ-5D-3L data were converted to utility scores using the Danish EQ-5D-3L value set to estimate the mean utility for each chronic disease population. Adjusted limited dependent variable mixture models were estimated and used to provide a regression-based catalog of utilities/disutilities. Results. Diseases with the lowest mean EQ-5D score in the Danish population were systemic sclerosis (M34; score = 0.432), fibromyalgia (M797; score = 0.490), rheumatism (M790; score = 0.515), dementia (F00, G30; score = 0.546), posttraumatic stress syndrome (F431; score = 0.557), and systemic atrophies (G10-G14; score = 0.583. Based on the estimated models, the largest estimated disutilities were cystic fibrosis, cerebral palsy, depression, dorsalgia, sclerosis, and fibromyalgia. Lifestyle factors, including perceived stress, loneliness, and body mass index, were also significantly associated with low HRQoL. Conclusions. This study provides a comprehensive nationally representative catalog and a model-based catalog of EQ-5D-3L-based HRQoL scores for Denmark that can be used to describe aspects of disease burden and allocate resources within health care. Additional Stata programs are also provided to facilitate predictions in other populations.

Highlights

A Danish national representative catalog of health-related quality-of-life scores for 199 chronic conditions is presented, which provides population estimates for chronic conditions subgroups that can be used for health economic evaluation.Two separate regression models of EQ-5D-3L utility scores with different sets of control variables are estimated to allow researchers to adjust for differences in the composition of the subgroups and provide a tool that can be used in other settings.Results indicate that health-related quality of life varies across disease groups but is lowest for renal disease, mental and behavioral disorders, benign neoplasms and diseases of the blood, digestive systems, and nervous systems.Health risks and lifestyle factors such as perceived stress, loneliness, and a large body mass index are highly correlated with health-related quality of life, and, in many cases, the correlation is higher than with individual diseases.

Catalog of EQ-5D-3L Health-Related Quality-of-Life Scores for 199 Chronic Conditions and Health Risks in Denmark

Background. Assessments of health-related quality of life (HRQoL) are essential in estimating quality-adjusted life-years. It is sometimes not feasible to collect primary HRQoL data, and reliable secondary sources are necessary. Current "off-the-shelf" HRQoL catalogs are based on older diagnosis classifications and include a limited number of diseases. This article aims to provide 1) a Danish EQ-5D-3L-based HRQoL catalog for 199 nationally representative chronic conditions based on ICD-10 codes and 2) a complementary model-based catalog controlling for age, sex, comorbidities, lifestyle, and health risks. Design. A total of 55,616 respondents from 3 national health survey samples were pooled and combined with 7 national registers containing patient-level information on diagnoses, health care activity, and sociodemographics. EQ-5D-3L data were converted to utility scores using the Danish EQ-5D-3L value set to estimate the mean utility for each chronic disease population. Adjusted limited dependent variable mixture models were estimated and used to provide a regression-based catalog of utilities/disutilities. Results. Diseases with the lowest mean EQ-5D score in the Danish population were systemic sclerosis (M34; score = 0.432), fibromyalgia (M797; score = 0.490), rheumatism (M790; score = 0.515), dementia (F00, G30; score = 0.546), posttraumatic stress syndrome (F431; score = 0.557), and systemic atrophies (G10-G14; score = 0.583. Based on the estimated models, the largest estimated disutilities were cystic fibrosis, cerebral palsy, depression, dorsalgia, sclerosis, and fibromyalgia. Lifestyle factors, including perceived stress, loneliness, and body mass index, were also significantly associated with low HRQoL. Conclusions. This study provides a comprehensive nationally representative catalog and a model-based catalog of EQ-5D-3L-based HRQoL scores for Denmark that can be used to describe aspects of disease burden and allocate resources within health care. Additional Stata programs are also provided to facilitate predictions in other populations.

HIGHLIGHTS

A Danish national representative catalog of health-related quality-of-life scores for 199 chronic conditions is presented, which provides population estimates for chronic conditions subgroups that can be used for health economic evaluation.Two separate regression models of EQ-5D-3L utility scores with different sets of control variables are estimated to allow researchers to adjust for differences in the composition of the subgroups and provide a tool that can be used in other settings.Results indicate that health-related quality of life varies across disease groups but is lowest for renal disease, mental and behavioral disorders, benign neoplasms and diseases of the blood, digestive systems, and nervous systems.Health risks and lifestyle factors such as perceived stress, loneliness, and a large body mass index are highly correlated with health-related quality of life, and, in many cases, the correlation is higher than with individual diseases.

Cost-effectiveness of apixaban and rivaroxaban in thromboprophylaxis of cancer patients treated with chemotherapy in Spain

BACKGROUND

Apixaban and rivaroxaban are two direct-acting oral anticoagulants (DOACs) recommended for thromboprophylaxis in cancer patients treated with chemotherapy in an ambulatory setting. We aimed to assess the cost-utility of thromboprophylaxis with apixaban and rivaroxaban vs no thromboprophylaxis in ambulatory cancer patients starting chemotherapy with an intermediate-to-high risk of venous thromboembolism (VTE), Khorana score ≥ 2 points.

METHODS

A cost-effectiveness analysis was performed from the perspective of Spain's National Health System (NHS) using an analytical decision model in the short-term (180 days) and a Markov model in the long-term (5 years). Transition probabilities were obtained from randomized, double-blind, placebo-controlled clinical trials of apixaban and rivaroxaban in adult ambulatory patients with cancer at risk for VTE, treated with chemotherapy (AVERT and CASSINI trials). The costs (€2,021) were taken from Spanish sources. The utilities of the model were obtained through the EQ-5D questionnaire. Deterministic (base case) and probabilistic (second-order Monte Carlo simulation) analyses were conducted.

RESULTS

In the probabilistic sensitivity analysis, apixaban generated a cost per patient of €1,082 ± 187, with a 95% confidence interval (CI) of €713-1,442, while no prophylaxis produced a cost per patient of €1,146 ± 218, with a 95% CI of €700-1,491, with a saving of €64 per patient and a gain of 0.008 QALYs. Likewise, rivaroxaban provided a cost per patient of €993 ± 133, with a 95% CI of €748-1,310, while no prophylaxis produced a cost per patient of €872 ± 152, with a 95% CI of €602-1,250, with an additional expense of €121 per patient and a gain of 0.008 QALYs.

CONCLUSIONS

In thromboprophylaxis of cancer patients, the use of apixaban and rivaroxaban generated similar costs compared to non-prophylaxis, without the difference found being statistically significant, with a clinically insignificant QALY gain.

A National Catalog of Mapped Short-Form Six-Dimension Utility Scores for Chronic Conditions in the United States From 2010 to 2015

OBJECTIVES

This study examined health preference utility weights and utility decrements associated with different types of chronic conditions in the United States.

METHODS

We used the 2010-2015 Medical Expenditure Panel Survey data for persons aged ≥ 18 years with 12-Item Short-Form Survey Physical and Mental Component Summary scores. 12-Item Short-Form Survey scores were converted to Short-Form Six-Dimension (SF-6D) preference scores to measure utilities of different chronic diseases. We used the Clinical Classification Code to identify 30 chronic diseases from 12 categories, such as cardiovascular diseases, cerebrovascular diseases, hypertension, hyperlipidemia, obesity, cancers, musculoskeletal diseases, endocrine or metabolic diseases, oral diseases, respiratory diseases, and mental disorders. A generalized linear model was used to quantify the utility decrements for 30 chronic diseases, controlling for demographic characteristics.

RESULTS

We identified 132 737 adults (mean age 47.2 years, 52.2% female, 80% white); 73% had at least one identified chronic disease, and the mean SF-6D was 0.786. Among 30 chronic diseases, the unadjusted mean SF-6D scores of patients with cognitive disorder (0.607) were the lowest, followed by congestive heart failure (0.629), rheumatoid arthritis (0.654), and lung cancer (0.662). After controlling for demographic variables (ie, age, sex) and comorbidities, cognitive disorders (-0.116), mood disorders (-0.099), rheumatoid arthritis (-0.090), liver cancer (-0.078), and stroke (-0.063) showed the highest decrements in the SF-6D scores (P < .05).

CONCLUSIONS

This study provides a nationally representative catalog of utility weights for major chronic diseases in the US general population. The utility decrements will enable researchers to calculate the health utilities of patients with multiple comorbid diseases.

Cost-utility of ticagrelor plus aspirin in diabetic patients with stable coronary artery disease

AIMS

Ticagrelor plus aspirin could reduce the risks of major adverse cardiac events in diabetic patients with stable coronary artery disease (SCD), and yet it also increases bleeding risk. This study would compare the cost and effectiveness of aspirin and ticagrelor plus aspirin therapies in diabetic patients with SCD from a US healthcare sector perspective.

METHODS AND RESULTS

A state-transition Markov model was developed to project probabilities of myocardial infarction, ischaemic stroke, bleeding, and death with and without ticagrelor among all diabetic patients with SCD as the overall population, and those with a history of previous percutaneous coronary intervention (PCI) as a sub-population. Model inputs were extracted from published sources. Lifetime costs and quality-adjusted life-years (QALYs) were measured. The clinical benefits and bleeding risk of ticagrelor added to aspirin were translated into additional 0.08 QALYs at incremental costs of $19 580 in the overall population, yielding an incremental cost-utility ratio (ICUR) of $260 032/QALY. In the sub-population with an additional 0.43 QALYs at an incremental cost of $20 189, the ICUR was $46 426/QALY. Two-way sensitivity showed the clinical benefits of ticagrelor plus aspirin was counterbalanced by its risk of major bleeding. One-way sensitivity and probabilistic sensitivity analysis demonstrated that the results were generally robust except the all-cause death reduction.

CONCLUSION

The results indicated that ticagrelor plus aspirin is likely to be a cost-effective option in the diabetic patients with a history of PCI. Diabetes management can be improved by carefully prescribing ticagrelor to individuals with low risk of bleeding and high risk of ischaemic events.

Review and estimation of disutility for joint health states of severe and nonsevere hypoglycemic events in diabetes

Aim: Many economic evaluations used linear or log-transformed additive methods to estimate the disutility of hypoglycemic events in diabetes, both nonsevere (NSHEs) and severe (SHEs). Methods: We conducted a literature search for studies of disutility for hypoglycemia. We used additive, minimum and multiplicative methods, and the adjusted decrement estimator to estimate the disutilities of joint health states with both NSHEs and SHEs in six scenarios. Results: Twenty-four studies reported disutilities for hypoglycemia in diabetes. Based on construct validity, the adjusted decrement estimator method likely provides less biased estimates, predicting that when SHEs occur, the additional impact from NSHEs is marginal. Conclusion: Our proposed new method provides a different perspective on the estimation of quality-adjusted life-years in economic evaluations of hypoglycemic treatments.

Cost burden and net monetary benefit loss of neonatal hypoglycaemia

BACKGROUND

Neonatal hypoglycaemia is a common but treatable metabolic disorder that affects newborn infants and which, if not identified and treated adequately, may result in neurological sequelae that persist for the lifetime of the patient. The long-term financial and quality-of-life burden of neonatal hypoglycaemia has not been previously examined.

METHODS

We assessed the postnatal hospital and long-term costs associated with neonatal hypoglycaemia over 80 year and 18 year time horizons, using a health-system perspective and assessing impact on quality of life using quality-adjusted life year (QALYs). A decision analytic model was used to represent key outcomes in the presence and absence of neonatal hypoglycaemia.

RESULTS

The chance of developing one of the outcomes of neonatal hypoglycaemia in our model (cerebral palsy, learning disabilities, seizures, vision disorders) was 24.03% in subjects who experienced neonatal hypoglycaemia and 3.56% in those who do did not. Over an 80 year time horizon a subject who experienced neonatal hypoglycaemia had a combined hospital and post-discharge cost of NZ$72,000 due to the outcomes modelled, which is NZ$66,000 greater than a subject without neonatal hypoglycaemia. The net monetary benefit lost due to neonatal hypoglycaemia, using a value per QALY of NZ$43,000, is NZ$180,000 over an 80 year time horizon.

CONCLUSIONS

Even under the most conservative of estimates, neonatal hypoglycaemia contributes a significant financial burden to the health system both during childhood and over a lifetime. The combination of direct costs and loss of quality of life due to neonatal hypoglycaemia means that this condition warrants further research to focus on prevention and effective treatment.

Cost-effectiveness Analysis of Preoperative Screening Strategies for Obstructive Sleep Apnea among Patients Undergoing Elective Inpatient Surgery

Background

Obstructive sleep apnea is underdiagnosed in surgical patients. The cost-effectiveness of obstructive sleep apnea screening is unknown. This study’s objective was to evaluate the cost-effectiveness of preoperative obstructive sleep apnea screening (1) perioperatively and (2) including patients’ remaining lifespans.

Methods

An individual-level Markov model was constructed to simulate the perioperative period and lifespan of patients undergoing inpatient elective surgery. Costs (2016 Canadian dollars) were calculated from the hospital perspective in a single-payer health system. Remaining model parameters were derived from a structured literature search. Candidate strategies included: (1) no screening; (2) STOP-Bang questionnaire alone; (3) STOP-Bang followed by polysomnography (STOP-Bang + polysomnography); and (4) STOP-Bang followed by portable monitor (STOP-Bang + portable monitor). Screen-positive patients (based on STOP-Bang cutoff of at least 3) received postoperative treatment modifications and expedited definitive testing. Effectiveness was expressed as quality-adjusted life month in the perioperative analyses and quality-adjusted life years in the lifetime analyses. The primary outcome was the incremental cost-effectiveness ratio.

Results

In perioperative and lifetime analyses, no screening was least costly and least effective. STOP-Bang + polysomnography was the most effective strategy and was more cost-effective than both STOP-Bang + portable monitor and STOP-Bang alone in both analyses. In perioperative analyses, STOP-Bang + polysomnography was not cost-effective compared to no screening at the $4,167/quality-adjusted life month threshold (incremental cost-effectiveness ratio $52,888/quality-adjusted life month). No screening was favored in more than 90% of iterations in probabilistic sensitivity analyses. In contrast, in lifetime analyses, STOP-Bang + polysomnography was favored compared to no screening at the $50,000/quality-adjusted life year threshold (incremental cost-effectiveness ratio $2,044/quality-adjusted life year). STOP-Bang + polysomnography was favored in most iterations at thresholds above $2,000/quality-adjusted life year in probabilistic sensitivity analyses.

Conclusions

The cost-effectiveness of preoperative obstructive sleep apnea screening differs depending on time horizon. Preoperative screening with STOP-Bang followed by immediate confirmatory testing with polysomnography is cost-effective on the lifetime horizon but not the perioperative horizon. The integration of preoperative screening based on STOP-Bang and polysomnography is a cost-effective means of mitigating the long-term disease burden of obstructive sleep apnea.

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New Oral Anticoagulants for Thromboprophylaxis in Patients with Cancer Receiving Chemotherapy: An Economic Evaluation in a Chinese Setting

BACKGROUND AND OBJECTIVE

Recent trials showed that thromboprophylaxis with new oral anticoagulants (NOACs) is effective and safe in patients with cancer initiating chemotherapy. However, the cost effectiveness of NOACs is unknown. The objective of this study was to compare the cost effectiveness of preventing venous thromboembolism with NOACs with no thromboprophylaxis for patients with cancer initiating systemic chemotherapy from the perspective of the Chinese healthcare system.

METHODS

A decision analytical model consisting of both acute and chronic venous thromboembolism complications was used to assess the cost effectiveness of thromboprophylaxis with NOACs vs no thromboprophylaxis. The key clinical data were derived from the CASSINI and AVERT trials. Costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) were calculated for the two strategies. Scenario and sensitivity analyses were performed.

RESULTS

Compared with no thromboprophylaxis, NOACs gained 0.072 QALY at an incremental cost of $US930, leading to an ICER of 12,919/QALY in patients with Khorana scores ≥ 2 by pooling the data from the CASSINI and AVERT trials. Among patients confirmed with no deep-vein thrombosis before thromboprophylaxis (the CASSINI trial) and patients without deep-vein thrombosis screening before thromboprophylaxis (the AVERT trial), the ICERs were $70,897/QALY and $87,204/QALY, respectively. The probability of NOACs being cost effective was 42% at a willingness to pay of $10,276/QALY. The ICER was sensitive to the relative risks of death and asymptomatic venous thromboembolism between NOACs and no thromboprophylaxis and the cost of NOACs.

CONCLUSIONS

Thromboprophylaxis with NOACs is not likely to be cost effective in patients initiating chemotherapy in the Chinese context. The decision about thromboprophylaxis should be tailored based on the survival of patients with cancer, the risks of venous thromboembolism, and major bleeding.

Estimating Joint Health Condition Utility Values

OBJECTIVES

To predict health state utility values (HSUVs) for individuals with up to 4 conditions simultaneously.

METHODS

Person-level data were taken from the General Practice Patient Survey, a national survey of adult patients registered with general practices in England. Individuals reported whether they had any 1 of 16 chronic conditions and completed the 3-level EuroQol 5-dimensional questionnaire. Four nonparametric methods (additive, multiplicative, minimum, and the adjusted decrement estimator) and 1 parametric estimator (the linear index) were used to predict HSUVs for individuals with a joint health condition (JHC). Predicted and actual utility scores were compared for precision using root mean square error and mean absolute error. Bias was assessed using mean error.

RESULTS

The analysis included 929,565 individuals, of which 30.5% had at least 2 conditions. Of the nonparametric estimators, the multiplicative approach produced estimates with the lowest bias and most precision for 2 JHCs. For populations with a long-term mental health condition within the JHC, the multiplicative approach overestimated utility scores. All nonparametric methods produced biased results when estimating HSUVs for 3 or 4 JHCs. The linear index generally produced unbiased results with the highest precision.

CONCLUSIONS

The multiplicative approach was the best nonparametric estimator when estimating HSUVs for 2 JHCs. None of the nonparametric approaches for estimating HSUVs can be recommended with more than 2 JHCs. The linear index was found to have good predictive properties but needs external validation before being recommended for routine use.

Economic Evaluation of Letrozole for Early Breast Cancer in a Health Resource-Limited Setting

Objective

Long-term aromatase inhibitor (AI) therapy is expected to improve the health outcomes with high health resource consumption in early breast cancer. The aim of the study was to assess the cost-effectiveness of letrozole for postmenopausal women with estrogen receptor positive early breast cancer in a health resource-limited setting.

Methods

A Markov model was developed to project the lifetime outcomes based on the clinical course of early breast cancer. The clinical and utility data were derived from reported results. Costs were estimated from the perspective of Chinese health care. The quality-adjusted life-year (QALY) and incremental cost-effective ratio (ICER) were measured. Probabilistic sensitivity and one-way analyses were conducted.

Results

Compared to 5 years of tamoxifen therapy, 5 years of AI treatment with letrozole improved the QALYs (10.44 versus 10.84) and increased the lifetime costs (CNY ¥13,613 versus CNY ¥28,797), resulting in an ICER of CNY ¥38,092 /QALY. The ICER of 5 years of letrozole versus 2-3 years of tamoxifen and then letrozole was CNY ¥68,233 /QALY. Sensitivity analyses showed that the age of initiating adjuvant endocrine therapy was the most influential parameter.

Conclusions

In health resource-limited settings, adjuvant endocrine therapy with letrozole is a cost-effective strategy compared to tamoxifen in women with early breast cancer.

Comparative quality-adjusted survival analysis between radiation therapy alone and radiation with androgen deprivation therapy in patients with locally advanced prostate cancer: a secondary analysis of Radiation Therapy Oncology Group 85-31 with novel decision analysis methods

Background

Androgen deprivation therapy in addition to radiation therapy (RT + ADT) has shown benefits in local control and progression-free survival compared with RT alone for patients with locally advanced prostate cancer in Radiation Therapy Oncology Group 85-31. However, the survival gain may be diluted with increased toxicity of ADT. The aim of the study is to compare quality-adjusted life years (QALYs) values between two groups.

Methods

We developed “quality-adjusted survival analysis using duration” (QASAD) and “quality-adjusted survival analysis using probability” (QASAP) to estimate the quality-adjusted survival time. The QASAD uses the median duration in each health state to weight the utilities, whereas the QASAP uses the proportional probability of being in each state for weighting. The survival and complication rates were reconstructed based on published Kaplan–Meier survival curves, and the utility values for states were obtained from the previous literature.

Results

QALYs values for RT + ADT were generally higher than those for RT. The QASAD resulted in a QALY value of 4.93 [95% bootstrapped confidence interval (CI) = 4.12–5.71] for RT and of 5.60 (95% CI = 4.30–6.48) for RT + ADT. QASAP resulted in a QALY value of 4.85 (95% CI = 4.16–5.39) for RT and 4.96 (95% CI = 3.73–5.78) for RT + ADT.

Conclusions

We showed that RT + ADT provided slightly better quality-adjusted survival outcome than RT alone. The QASAD and QASAP methods may help the decision of optimal treatment balancing between survival gain and unfavorable quality of life.

Estimating Health State Utility Values for Comorbidities

A comorbidity is defined as the presence of at least one additional health condition co-occurring with a primary health condition. Decision analytic models in healthcare depict the typical clinical pathway of patients in general clinical practice and frequently include health states defined to represent comorbidities such as sequelae or adverse events. Health state utility values (HSUVs) are often not available for these and analysts generally estimate them. This article provides a summary of the methodological literature on estimating methods frequently used together with worked examples. The three main methods used (minimum, multiplicative and additive) can produce a wide range in the values estimated. In general, the minimum method overestimates observed HSUVs and the magnitude of error tends to increase as the observed values decrease. Conversely, the additive and multiplicative methods generally underestimate observed values and the magnitude of the errors is generally greater for the additive method. HSUVs estimated using the multiplicative method tend to decrease for lower HSUVs and the largest errors are in observed HSUVs >0.6. Differences in estimated values can produce substantial differences in the resulting incremental cost effectiveness ratio. Based on the current evidence, the multiplicative method is advocated but additional research is required to determine appropriate methods when estimating values for additional comorbidities.

Joint Utility Estimators in Substance Use Disorders

BACKGROUND

Although co-occurring conditions are common with substance use disorders (SUDs), estimation methods for joint health state utilities have not yet been tested in this context.

OBJECTIVES

To compare joint health state utility estimators in SUD to inform economic evaluation.

METHODS

We conducted two Internet-based surveys of US adults to collect community perspective standard gamble utilities for SUD and common co-occurring conditions. We evaluated six conditions as they occur individually and four combinations of these as they occur in tandem. We applied joint utility estimators using the six individual conditions' utilities to compare their performance relative to the observed combination states' utilities. We assessed performance with bias (estimated utility minus observed utility) and root mean square error (RMSE).

RESULTS

Using 3892 utilities from 1502 respondents, the minimum estimator was statistically unbiased (i.e., the 95% confidence interval included 0) for all combination states that we measured. The maximum estimator was unbiased for two states and the linear index and adjusted decrement estimators were unbiased for one state. The maximum estimator had the smallest RMSE for two combination states (back pain and prescription opioid misuse [0.0004] and injection crack and injection opioid use [0.0007]); the linear index and minimum estimators had the smallest RMSE for one combination state each. The additive and multiplicative estimators had the largest RMSE for all states.

CONCLUSIONS

Our results demonstrate the usefulness of the minimum estimator in this context, and confirm the inadequacy of the additive and multiplicative estimators. Further research is needed to extend these results to other SUD states.

Cost-Effectiveness of Different Strategies for the Prevention of Venous Thromboembolism After Total Hip Replacement in China

Introduction

The aim of this study was to evaluate the cost-effectiveness of rivaroxaban and apixaban versus enoxaparin for the universal prophylaxis of venous thromboembolism (VTE) and associated long-term complications in Chinese patients after total hip replacement (THR).

Methods

A decision model, which included both acute VTE (represented as a decision tree) and the long-term complications of VTE (represented as a Markov model), was developed to assess the economic outcomes of the three prophylactic strategies for Chinese patients after THR. Transition probabilities for acute VTE were derived from two randomized controlled studies, RECORD1 and ADVANCE3, of patients after THR. The transition probabilities of long-term complications after acute VTE, utilities, and costs were derived from the published literature and local healthcare settings. One-way and probabilistic sensitivity analyses (PSA) were performed to test the uncertainty concerning the model parameters. The quality-adjusted life years (QALYs) and direct medical costs were reported over a 5-year horizon, and incremental cost-effectiveness ratios (ICERs) were also calculated.

Results

Thromboprophylaxis with apixaban was estimated to have a higher cost (US $178.70) and more health benefits (0.0025 QALY) than thromboprophylaxis with enoxaparin over a 5-year time horizon, which resulted in an ICER of US $71,244 per QALY gained and was more than three times the GDP per capita of China in 2014 (US $22,140). Owing to the higher cost and lower generated QALYs, rivaroxaban was inferior to enoxaparin among post-THR patients. The sensitivity analyses confirmed these results.

Conclusions

The analysis found that apixaban was not cost-effective and that rivaroxaban was inferior to enoxaparin. This finding indicates that compared with enoxaparin, the use of apixaban for VTE prophylaxis after THR does not represent a good value for the cost at the acceptable threshold in China; in addition, the cost of rivaroxaban was higher with lower QALYs.

Accounting for multimorbidity can affect the estimation of the Burden of Disease: a comparison of approaches

Background

Various Burden of Disease (BoD) studies do not account for multimorbidity in their BoD estimates. Ignoring multimorbidity can lead to inaccuracies in BoD estimations, particularly in ageing populations that include large proportions of persons with two or more health conditions. The objective of this study is to improve BoD estimates for the Netherlands by accounting for multimorbidity. For this purpose, we analyzed different methods for 1) estimating the prevalence of multimorbidity and 2) deriving Disability Weights (DWs) for multimorbidity by using existing data on single health conditions.

Methods

We included 25 health conditions from the Dutch Burden of Disease study that have a high rate of prevalence and that make a large contribution to the total number of Years Lived with a Disability (YLD). First, we analyzed four methods for estimating the prevalence of multimorbid conditions (i.e. independent, independent age- and sex-specific, dependent, and dependent sex- and age-specific). Secondly, we analyzed three methods for calculating the Combined Disability Weights (CDWs) associated with multimorbid conditions (i.e. additive, multiplicative and maximum limit). A combination of these two approaches was used to recalculate the number of YLDs, which is a component of the Disability-Adjusted Life Years (DALY).

Results

This study shows that the YLD estimates for 25 health conditions calculated using the multiplicative method for Combined Disability Weights are 5 % lower, and 14 % lower when using the maximum limit method, than when calculated using the additive method. Adjusting for sex- and age-specific dependent co-occurrence of health conditions reduces the number of YLDs by 10 % for the multiplicative method and by 26 % for the maximum limit method. The adjustment is higher for health conditions with a higher prevalence in old age, like heart failure (up to 43 %) and coronary heart diseases (up to 33 %). Health conditions with a high prevalence in middle age, such as anxiety disorders, have a moderate adjustment (up to 13 %).

Conclusions

We conclude that BoD calculations that do not account for multimorbidity can result in an overestimation of the actual BoD. This may affect public health policy strategies that focus on single health conditions if the underlying cost-effectiveness analysis overestimates the intended effects. The methodology used in this study could be further refined to provide greater insight into co-occurrence and the possible consequences of multimorbid conditions in terms of disability for particular combinations of health conditions.

Measuring benefits of opioid misuse treatment for economic evaluation: health-related quality of life of opioid-dependent individuals and their spouses as assessed by a sample of the US population

AIMS

To understand how the general public views the quality of life effects of opioid misuse and opioid use disorder on an individual and his/her spouse, measured in terms used in economic evaluations.

DESIGN

Cross-sectional internet survey of a US population-representative respondent panel conducted December 2013-January 2014.

SETTING

United States.

PARTICIPANTS

A total of 2054 randomly selected adults; 51.1% male (before weighting).

MEASUREMENTS

Mean (95% confidence interval) and median health 'utility' for six opioid misuse and treatment outcomes: active injection misuse; active prescription misuse; methadone maintenance therapy at initiation and when stabilized in treatment; and buprenorphine therapy at initiation and when stabilized. Utility is a numerical representation of health-related quality of life used in economic evaluations to 'adjust' estimated survival to include peoples' preferences for health states. Utilities are determined by surveying the general population to estimate the value they assign to particular health states on a scale where 0 = the value of being dead and 1.0 = the value of being in perfect health. Spouse spillover utility is assigned to a spouse of an individual who is in a particular health state.

FINDINGS

Mean individual utility ranged from 0.574 [95% confidence interval (CI) = 0.538, 0.611] for active injection opioid misuse to 0.766 for stabilized buprenorphine therapy (95% CI = 0.738, 0.795), with other states in between. Female respondents assigned higher utility to the active prescription misuse and buprenorphine therapy at initiation states than did males (P < 0.05); all other states did not differ by respondent gender. Mean spousal utilities were significantly lower than 1.0 but mostly higher than individual utility, and were similar between male and female respondents.

CONCLUSIONS

In the opinion of the US public, injection opioid misuse results in worse health-related quality of life than prescription misuse, and methadone therapy results in worse health-related quality of life than buprenorphine therapy. Spouses are negatively affected by their partner's opioid misuse and early treatment.

Valuation of depression co-occurring with a somatic condition: feasibility of the time trade-off task

BACKGROUND

Health state valuations obtained from the general population are used for cost-utility analyses of health-care interventions. Currently, most studies have focused on valuations of somatic conditions, to a much lesser extent of mental states, that is, depression and even less on valuations of depression co-occurring with somatic conditions.

OBJECTIVE

We tested the feasibility of the time trade-off (TTO) task to elicit valuations for depression solitary or co-occurring with a somatic condition. Moreover, we explored person- and state-related factors that may affect valuations.

DESIGN

During semi-structured interviews, 10 individuals (five women, mean age: 36 years) used a TTO task to value vignettes describing mild and severe depression; and mild depression co-occurring with moderate and severe states of cancer, diabetes or heart disease. During valuations, participants were thinking aloud. Feasibility criteria were successful completion and difficulty/concentration (1-10); logical consistency of values; and comprehension of the TTO, based on qualitative analysis of think aloud data. Factors influencing valuations were generated from think aloud data.

RESULTS

Participants reported satisfactory levels of difficulty (mean: 1.9) and concentration (mean: 8.3) and assigned consistent values. Qualitative analysis revealed difficulties with imagining: living with depression for lifetime (n = 4); reaching the age of 80 (n = 6); and living with a somatic condition and mentally healthy (n = 6). Person- and state-related factors, for example perceived susceptibility to depression (n = 4), appeared to affect valuations.

CONCLUSION

Quantitative findings supported feasibility of the valuation protocol, yet qualitative findings indicated that certain task aspects should be readdressed. Factors influencing valuations can be explored to better understand valuations.

Examining the relationship between health-related quality of life and increasing numbers of diagnoses

Purpose

Little is known about estimating utilities for comorbid (or ‘joint’) health states. Several joint health state prediction models have been suggested (for example, additive, multiplicative, best-of-pair, worst-of-pair, etc.), but no general consensus has been reached. The purpose of the study is to explore the relationship between health-related quality of life (HRQoL) and increasing numbers of diagnoses.

Methods

We analyzed a large dataset containing respondents’ ICD-9 diagnoses and preference-based HRQoL (EQ-5D and SF-6D). Data were stratified by the number of diagnoses, and mean HRQoL values were estimated. Several adjustments, accounting for the respondents’ age, sex, and the severity of the diagnoses, were carried out. Our analysis fitted additive and multiplicative models to the data and assessed model fit using multiple standard model selection methods.

Results

A total of 39,817 respondents were included in the analyses. Average HRQoL values were represented well by both linear and multiplicative models. Although results across all analyses were similar, adjusting for severity of diagnoses, age, and sex strengthened the linear model’s performance measures relative to the multiplicative model. Adjusted R² values were above 0.99 for all analyses (i.e., all adjusted analyses, for both HRQoL instruments), indicating a robust result.

Conclusions

Additive and multiplicative models perform equally well within our analyses. A practical implication of our findings, based on the presumption that a linear model is simpler than an additive model, is that an additive model should be preferred unless there is compelling evidence to the contrary.

Sourcing quality-of-life weights obtained from previous studies: theory and reality in Korea

BACKGROUND

The quality-of-life weights obtained in previous studies are frequently used in cost-utility analyses. The purpose of this study is to describe how the values obtained in previous studies are incorporated into the industry submissions requesting listing at the Korean National Health Insurance (NHI), focusing on the issues discussed in theoretical studies and national guidelines.

METHODS

The industry submissions requesting listing at the Korean NHI from January 2007 until December 2009 were evaluated by two independent researchers at the Health Insurance Review and Assessment Service (HIRA). Specifically, we observed the methods that were used to pool, predict joint health state utilities, and retain consistency within submissions in terms of the issues discussed in methodological research papers and recommendations from national guidelines.

RESULTS

More than half of the submissions used QALY as an outcome measure, and most of these submissions were sourced from prior studies. Heterogeneous methodologies were frequently used within a submission, with the inconsistent use of upper and lower anchors being prevalent. Assumptions behind measuring joint health state utilities or pooling multiple values for single health states were omitted in all submissions. Most national guidelines were rather vague regarding how to predict joint health states, how to select the best available value, how to maintain consistency within a submission, and how to generalize values obtained from prior studies.

CONCLUSIONS

Previously-generated values were commonly sourced, but this practice was frequently related to inconsistencies within and among submissions. Attention should be paid to the consistency and transparency of the value, especially if the value is sourced from prior studies.

Economic evaluation of apixaban for the prevention of stroke in non-valvular atrial fibrillation in the Netherlands

BACKGROUND

Stroke prevention is the main goal of treating patients with atrial fibrillation (AF). Vitamin-K antagonists (VKAs) present an effective treatment in stroke prevention, however, the risk of bleeding and the requirement for regular coagulation monitoring are limiting their use. Apixaban is a novel oral anticoagulant associated with significantly lower hazard rates for stroke, major bleedings and treatment discontinuations, compared to VKAs.

OBJECTIVE

To estimate the cost-effectiveness of apixaban compared to VKAs in non-valvular AF patients in the Netherlands.

METHODS

Previously published lifetime Markov model using efficacy data from the ARISTOTLE and the AVERROES trial was modified to reflect the use of oral anticoagulants in the Netherlands. Dutch specific costs, baseline population stroke risk and coagulation monitoring levels were incorporated. Univariate, probabilistic sensitivity and scenario analyses on the impact of different coagulation monitoring levels were performed on the incremental cost-effectiveness ratio (ICER).

RESULTS

Treatment with apixaban compared to VKAs resulted in an ICER of €10,576 per quality adjusted life year (QALY). Those findings correspond with lower number of strokes and bleedings associated with the use of apixaban compared to VKAs. Univariate sensitivity analyses revealed model sensitivity to the absolute stroke risk with apixaban and treatment discontinuations risks with apixaban and VKAs. The probability that apixaban is cost-effective at a willingness-to-pay threshold of €20,000/QALY was 68%. Results of the scenario analyses on the impact of different coagulation monitoring levels were quite robust.

CONCLUSIONS

In patients with non-valvular AF, apixaban is likely to be a cost-effective alternative to VKAs in the Netherlands.

Using health state utility values in models exploring the cost-effectiveness of health technologies

BACKGROUND

To improve comparability of economic data used in decision making, some agencies recommend that a particular instrument should be used to measure health state utility values (HSUVs) used in decision-analytic models. The methods used to incorporate HSUVs in models, however, are often methodologically poor and lack consistency. Inconsistencies in the methodologies used will produce discrepancies in results, undermining policy decisions informed by cost per quality-adjusted life-years.

OBJECTIVE

To provide an overview of the current evidence base relating to populating decision-analytic models with HSUVs.

FINDINGS

Research exploring suitable methods to accurately reflect the baseline or counterfactual HSUVs in decision-analytic models is limited, and while one study suggested that general population data may be appropriate, guidance in this area is poor. Literature describing the appropriateness of different methods used to estimate HSUVs for combined conditions is growing, but there is currently no consensus on the most appropriate methodology. While exploratory analyses suggest that a statistical regression model might improve accuracy in predicted values, the models require validation and testing in external data sets. Until additional research has been conducted in this area, the current evidence suggests that the multiplicative method is the most appropriate technique. Uncertainty in the HSUVs used in decision-analytic models is rarely fully characterized in decision-analytic models and is generally poorly reported.

CONCLUSIONS

A substantial volume of research is required before definitive detailed evidence-based practical advice can be provided. As the methodologies used can make a substantial difference to the results generated from decision-analytic models, the differences and lack of clarity and guidance will continue to lead to inconsistencies in policy decision making.

Estimating Health State Utility Values for Joint Health Conditions

Background. Analysts frequently estimate the health state utility values (HSUVs) for joint health conditions (JHCs) using data from cohorts with single health conditions. The methods can produce very different results, and there is currently no consensus on the most appropriate technique. Objective. To conduct a detailed critical review of existing empirical literature to gain an understanding of the reasons for differences in results and identify where uncertainty remains that may be addressed by further research. Results. Of the 11 studies identified, 10 assessed the additive method, 10 the multiplicative method, 7 the minimum method, and 3 the combination model. Two studies evaluated just 1 of the techniques, whereas the others compared results generated using 2 or more. The range of actual HSUVs can influence general findings, and methods are sometimes compared using descriptive statistics that may not be appropriate for assessing predictive ability. None of the methods gave consistently accurate results across the full range of possible HSUVs, and the values assigned to normal health influence the accuracy of the methods. Conclusions. Within the limitations of the current evidence base, we would advocate the multiplicative method, conditional on adjustment for baseline utility, as the preferred technique to estimate HSUVs for JHCs when using mean values obtained from cohorts with single conditions. We would recommend that a range of sensitivity analyses be performed to explore the effect on results when using the estimated HSUVs in economic models. Although the linear models appeared to give more accurate results in the studies we reviewed, these models require validating in external data before they can be recommended.

Comparing EQ-5D scores for comorbid health conditions estimated using 5 different methods

BACKGROUND

There is currently no consensus on the most appropriate method to estimate health state utility values (HSUVs) for comorbid health conditions.

OBJECTIVE

The objective of the study was to assess the accuracy by applying 5 different methods to an EQ-5D dataset.

METHODS

EQ-5D data (n=41,174) from the Health Survey for England were used to compare HSUVs generated using the additive, multiplicative and minimum methods, the adjusted decrement estimator, and a linear regression.

RESULTS

The additive and multiplicative methods underestimated the majority of HSUVs and the magnitude of the errors increased as the actual HSUV increased. Conversely, the minimum and adjusted decrement estimator methods overestimated the majority of HSUVs and the magnitude of errors increased as the actual HSUV decreased. Although the simple linear model produced the most accurate results, there was a tendency to underpredict higher HSUVs and overpredict lower HSUVs. The magnitude and direction of mean errors could be driven by the actual scores being estimated in addition to the technique used and the HSUVs estimated using an adjusted baseline were generally more accurate.

CONCLUSIONS

The additive and minimum methods performed very poorly in our data. Although the simple linear model gave the most accurate results, the model requires validating in external data obtained from the EQ-5D and other preference-based measures. Based on the current evidence base, we would recommend the multiplicative method is used together with a range of univariate sensitivity analyses.

The impact of co-morbidity burden on preference-based health-related quality of life in the United States

BACKGROUND

Many statistical analyses, clinical trials and cost-utility analyses designed to measure the impact of a particular disease on utility scores often overlook the important influence of co-morbidity burden.

OBJECTIVES

This study aims to examine the impact of co-morbidity burden on EQ-5D index scores in a nationally representative sample of the US.

METHODS

The pooled 2001 and 2003 Medical Expenditure Panel Survey was used. The total number of chronic conditions for each individual was calculated based on Clinical Classification Categories codes. Spline regression was used to identify nonlinear age effects: individuals were separated into four quartiles based on age. Censored least absolute deviation was used to regress EQ-5D index scores on age and chronic co-morbidity, controlling for income, gender, race, ethnicity, education, physical activity and smoking status. Interactions between age and chronic conditions were also explored.

RESULTS

The coefficients for chronic co-morbidities were highly statistically significant with large magnitudes for those with two or more chronic conditions (coefficient two chronic conditions=-0.16; coefficient nine chronic conditions=-0.28). After controlling for chronic co-morbidities and other confounders, age was not statistically significant except for those aged>58 years and the magnitude of this coefficient was very small (coefficient aged>58 years=-0.0006). The interactions between age and chronic co-morbidity were significant, but the deleterious impact of their interaction was largely dominated by the existence and number of chronic conditions.

CONCLUSIONS

Chronic conditions have a significant deleterious impact on EQ-5D index scores that is much more pronounced than age and other sociodemographic and behavioural characteristics. Future analyses and cost-utility models should incorporate the impact of multiple morbidity.

Cost-effective screening for acute hepatitis C virus infection in HIV-infected men who have sex with men

BACKGROUND

We used a Monte Carlo computer simulation to estimate the effectiveness and cost-effectiveness of screening for acute hepatitis C virus (HCV) infection in human immunodeficiency virus (HIV)-infected men who have sex with men.

METHODS

One-time screening for prevalent HCV infection was performed at the time of enrollment in care, followed by either symptom-based screening, screening with liver function tests (LFTs), HCV antibody (Ab) screening, or HCV RNA screening in various combinations and intervals. We considered both treatment with pegylated interferon and ribavirin (PEG/RBV) alone and with an HCV protease inhibitor. Outcome measures were life expectancy, quality-adjusted life expectancy, direct medical costs, and cost-effectiveness, assuming a societal willingness to pay $100000 per quality-adjusted life-year (QALY) gained.

RESULTS

All strategies increased life expectancy (from 0.49 to 0.94 life-months), quality-adjusted life expectancy (from 0.47 to 1.00 quality-adjusted life-months), and costs (from $1900 to $7600), compared with symptom-based screening. The incremental cost-effectiveness ratio of screening with 6-month LFTs and a 12-month HCV Ab test, compared with symptom-based screening, was $43 700/QALY (for PEG/RBV alone) and $57 800/QALY (for PEG/RBV plus HCV protease inhibitor). The incremental cost-effectiveness ratio of screening with 3-month LFTs, compared with 6-month LFTs plus a 12-month HCV Ab test, was $129 700/QALY (for PEG/RBV alone) and $229 900/QALY (for PEG/RBV plus HCV protease inhibitor). With HCV protease inhibitor-based therapy, screening with 6-month LFTs and a 12-month HCV Ab test was the optimal strategy when the HCV infection incidence was ≤1.25 cases/100 person-years. The 3-month LFT strategy was optimal when the incidence was >1.25 cases/100 person-years.

CONCLUSIONS

Screening for acute HCV infection in HIV-infected MSM prolongs life expectancy and is cost-effective. Depending on incidence, regular screening with LFTs, with or without an HCV Ab test, is the optimal strategy.

Estimating health state utility values for comorbid health conditions using SF-6D data

INTRODUCTION

When health state utility values for comorbid health conditions are not available, data from cohorts with single conditions are used to estimate scores. The methods used can produce very different results and there is currently no consensus on which is the most appropriate approach.

OBJECTIVE

The objective of the current study was to compare the accuracy of five different methods within the same dataset.

METHOD

Data collected during five Welsh Health Surveys were subgrouped by health status. Mean short-form 6 dimension (SF-6D) scores for cohorts with a specific health condition were used to estimate mean SF-6D scores for cohorts with comorbid conditions using the additive, multiplicative, and minimum methods, the adjusted decrement estimator (ADE), and a linear regression model.

RESULTS

The mean SF-6D for subgroups with comorbid health conditions ranged from 0.4648 to 0.6068. The linear model produced the most accurate scores for the comorbid health conditions with 88% of values accurate to within the minimum important difference for the SF-6D. The additive and minimum methods underestimated or overestimated the actual SF-6D scores respectively. The multiplicative and ADE methods both underestimated the majority of scores. However, both methods performed better when estimating scores smaller than 0.50. Although the range in actual health state utility values (HSUVs) was relatively small, our data covered the lower end of the index and the majority of previous research has involved actual HSUVs at the upper end of possible ranges.

CONCLUSIONS

Although the linear model gave the most accurate results in our data, additional research is required to validate our findings.