Appropriate Categorization of Inequality to Inform Policy Decisions: Estimating Distribution of Lifetime Health Using Alternative Approaches to Socioeconomic Stratification.

OBJECTIVES: Estimation of gradients in lifetime health, notably quality-adjusted life expectancy (QALE), has largely focused on index of multiple deprivation to categorize the population by socioeconomic position. In this article, we estimate QALE using alternate, individual- rather than area-level, indicators of socioeconomic position. METHODS: Building on previous research methods, the distribution of QALE is estimated across education and income groups based on data from the Health Survey for England and the Office for National Statistics. QALE is estimated for each group by combining multivariate mortality rates and health-related quality of life (HRQL) weights using life tables. HRQL weights were estimated using ordinary least squares and missing data were handled using multiple imputation. RESULTS: The estimated lifetime HRQL weights decreased with increased age, lower educational attainment, and lower income. For example, the QALE at birth for males in the lowest educational attainment group was 61.69 quality-adjusted life-years (QALYs), 1.54 QALYs lower than females in the same group. This is in contrast to 76.58 and 75.89 QALYs for males and females in the highest educational attainment group, respectively. A similar trend was observed across income quintiles albeit the gap was less pronounced. CONCLUSIONS: The use of index of multiple deprivation to assess health inequalities may be masking important information about individual-level variation. Decisions makers should consider this alongside the merits of using area-level approaches to categorizing the population if individual-level approaches are preferable.

EQ-5D-5L Population Norms and Quality-Adjusted Life Expectancy by Sociodemographic Characteristics and Modifiable Risk Factors for Adults in Queensland, Australia.

OBJECTIVES: Over half of Australia's disease burden is due to morbidity, predominantly chronic conditions. Health-related quality of life instruments provide measures of morbidity and health status across different dimensions with EQ-5D being one of the most widely used. This study reports EQ-5D-5L general population norms for Queensland, Australia using the recently published Australian value set. METHODS: Population survey results from cross-sectional computer-assisted telephone interviews for Queensland adults in 2022 and 2023 were analyzed. EQ-5D-5L, as well as modifiable risk factors and sociodemographic data were collected. Using the recently published final Australian EQ-5D-5L value set, mean utility scores were calculated for Queensland, as well as by sociodemographic characteristics, including remoteness and socioeconomic area-based measures, and modifiable risk factors, such as smoking and body mass index. Results were combined with life tables to estimate quality-adjusted life expectancy (QALE) for subgroups with different lifestyles. RESULTS: The EQ-5D utility score for the Queensland adult population was 0.916. Smoking daily, being obese or older in age, or living in the most disadvantaged socioeconomic area were associated with lower mean scores. QALE was 6.1 and 7.9 years shorter than the life expectancy for Queensland males and females, respectively, but generally, those who reported having healthier lifestyles had higher mean utility scores and thus longer QALE. CONCLUSIONS: In addition to reporting Queensland EQ-5D-5L general population norms, these results demonstrate potential QALE gains in people following healthier lifestyles. The results support investment in prevention and may motivate further studies in this important area.

An Intersectional Approach to Quantifying the Impact of Geographic Remoteness and Health Disparities on Quality-Adjusted Life Expectancy: Application to Australia.

OBJECTIVES: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) is a novel method for exploring the interaction between sociodemographic characteristics that affect health outcomes. This study explores the interaction between geographic remoteness and socioeconomic status on health outcomes in Australia from an intersectional perspective. METHODS: Data from a cross-sectional survey were matched with data from the Australian Bureau of Statistics and the Australian Institute of Health and Welfare. To explore the effect of health-related quality of life on life expectancy, quality-adjusted life expectancy (QALE) was estimated through applying utility values derived from the EQ-5D-5L to life table data from the Australian Bureau of Statistics. The effect of geographic remoteness on QALE was quantified using multivariable linear regression. An intersectional MAIHDA was performed to explore differences in mean QALE across strata formed by intersections of age, sex, and Socioeconomic Indexes for Areas score. RESULTS: Based on multivariable linear modeling, QALE declined significantly with increasing remoteness (inner regional, -1.0 years [undiscounted]; remote/very remote, -3.3 years [undiscounted]) (P < .001). In contrast, life expectancy was only significantly different between participants in remote/very remote areas and major cities (ß-coefficient, -2.4; 95% CI -4.4 to -0.4; P = .016). No intersectional interaction effects between strata on QALE were found in the MAIHDA. CONCLUSIONS: QALE has considerable value as a metric for exploring disparities in health outcomes. Given that no intersectional interactions were identified, our findings support broad interventions that target the underlying social determinants of health appropriately reduce disparities versus interventions targeting intersectional interactions.

Quality-Adjusted Life Expectancy Norms for the English Population.

OBJECTIVES: The National Institute for Health and Care Excellence in England has implemented severity-of-disease modifiers that give greater weight to health benefits accruing to patients who experience a larger shortfall in quality-adjusted life-years (QALYs) under current standard of care than healthy individuals. This requires an estimate of quality-adjusted life expectancy (QALE) of the general population based on age and sex. Previous QALE population norms are based on nearly 30-year-old assessments of health-related quality of life in the general population. This study provides updated QALE estimates for the English population based on age and sex. METHODS: 5-level version of EQ-5D data for 14 412 participants from the Health Survey for England (waves 2017 and 2018) were pooled, and health-related quality of life population norms were calculated. These norms were combined with official life tables from the Office for National Statistics for 2017 to 2019 using the Sullivan method to derive QALE estimates based on age and sex. Values were discounted using 0%, 1.5%, and 3.5% discount rates. RESULTS: QALE at birth is 68.24 QALYs for men and 68.21 QALYs for women. These values are significantly lower than previously published QALE population norms based on the older 3-level version of EQ-5D data. CONCLUSION: This study provides new QALE population norms for England that serve to establish absolute and relative QALY shortfalls for the purpose of health technology assessments.

Inequality in quality-adjusted life expectancy by educational attainment in Norway: an observational study.

BACKGROUND: Health inequalities are often assessed in terms of life expectancy or health-related quality of life (HRQoL). Few studies combine both aspects into quality-adjusted life expectancy (QALE) to derive comprehensive estimates of lifetime health inequality. Furthermore, little is known about the sensitivity of estimated inequalities in QALE to different sources of HRQoL information. This study assesses inequalities in QALE by educational attainment in Norway using two different measures of HRQoL. METHODS: We combine full population life tables from Statistics Norway with survey data from the Tromsø study, a representative sample of the Norwegian population aged ≥ 40. HRQoL is measured using the EQ-5D-5L and EQ-VAS instruments. Life expectancy and QALE at 40 years of age are calculated using the Sullivan-Chiang method and are stratified by educational attainment. Inequality is measured as the absolute and relative gap between individuals with lowest (i.e. primary school) and highest (university degree 4 + years) educational attainment. RESULTS: People with the highest educational attainment can expect to live longer lives (men: + 17.9% (95%CI: 16.4 to 19.5%), women: + 13.0% (95%CI: 10.6 to 15.5%)) and have higher QALE (men: + 22.4% (95%CI: 20.4 to 24.4%), women: + 18.3% (95%CI: 15.2 to 21.6%); measured using EQ-5D-5L) than individuals with primary school education. Relative inequality is larger when HRQoL is measured using EQ-VAS. CONCLUSION: Health inequalities by educational attainment become wider when measured in QALE rather than LE, and the degree of this widening is larger when measuring HRQoL by EQ-VAS than by EQ-5D-5L. We find a sizable educational gradient in lifetime health in Norway, one of the most developed and egalitarian societies in the world. Our estimates provide a benchmark against which other countries can be compared.

Combined quality of life and survival for estimation of long-term health outcome of patients with stroke.

BACKGROUND: Advanced medical technologies can prolong life of stroke survivors. Dynamic change of health outcomes provides essential information to manage stroke. Mathematical models, to extrapolate health status over a lifetime from cross-sectional data, can be used to investigate long term health outcomes among stroke survivors. This study aimed to estimate the health outcomes of ischemic stroke (IS) and intracerebral hemorrhage (ICH) at each survival time point. METHODS: The cohort of 5391 patients with IS and ICH stroke, registered at Ramathibodi Hospital from 2005 to 2013, were followed up regarding survival status until 2016 with the National Mortality Registry. Survival functions were extrapolated over 50 years to age- and sex-matched referents simulated from the national data of the Thailand National Health Statistic Office. From July to December 2016, the EuroQoL 5-dimension questionnaire was used to measure quality of life (QoL) among 400 consecutive, cross-sectional subsamples. The survival functions were then adjusted by the utility values of QoL for the stroke cohort to estimate quality adjusted life expectancy (QALE). RESULTS: The average health utility values were lower in the initial months, then slowly increased to stable levels. However, male stroke survivors presented higher health utility than females. Throughout lifetime estimation, patients with IS stroke exhibit better health outcomes than those with ICH [10.2 vs. 7.5 quality-adjusted life years (QALYs)]. Patients with ICH presented a significantly decreased QoL than patients with IS (16.3 and 8.5 QALYs). CONCLUSION: Preventing stroke can save people from reduced years and QoL, which can be quantified by loss-of-QALE in QALY units to compare health benefits from prevention, clinical diagnosis and direct treatment.

Treatment selection for life-critical shared decision making under ranges of health-state utility scenarios.

BACKGROUND: Selecting the best treatment for life-critical conditions via a shared decision making approach is a uniquely important challenge. Besides data from the healthcare physicians, other data that need to be considered are the personal values and perceptions of the patient. Usually, these data come in the form of health-state utility values. They are subjective and often times are elicited from the patient under emotional and stressful conditions. This paper examines an approach for selecting the best treatment under a life-critical shared decision making (SDM) framework. METHODS: Health-state utility values are used in practice to quantify what is known as quality-adjusted life years (QALYs) and quality-adjusted life expectancy (QALE). The QALEs from different treatments are used to select the best treatment. This paper describes methods for determining QALEs under a range of scenarios defined by the way some key assumptions on the health-state utility values are satisfied. Approaches for comparing different treatments are described along with some counter-intuitive results. These approaches are based on some optimization formulations. The proposed approaches are demonstrated in terms of a real example taken from the literature. RESULTS: Having results that are robust under a spectrum of different scenarios can provide more confidence that the most suitable treatment has been selected in a given case. On the other hand, having non-robust results can be useful information too as they may provide evidence that a more thorough assessment of the benefits and harms of the treatments may be needed to select a treatment with higher confidence. Finally, this study demonstrates that under certain mathematical conditions among the data it is possible to decide which treatment is better among two treatments without having to use health-state utility values. CONCLUSION: The significance of this study is that it provides valuable and actionable insights for the important question of how health-state utilities can be used in treatment selection.

Estimation of losses of quality-adjusted life expectancy attributed to the combination of cognitive impairment and multimorbidity among Chinese adults aged 45 years and older.

OBJECTIVES: This study aims to estimate the losses of quality-adjusted life expectancy (QALE) due to the joint effects of cognitive impairment and multimorbidity, and to further confirm additional losses attributable to this interaction among middle-aged and elderly Chinese people. METHODS: The National Cause of Death Monitoring Data were linked with the China Health and Retirement Longitudinal Study (CHARLS). A mapping and assignment method was used to estimate health utility values, which were further used to calculate QALE. Losses of QALE were measured by comparing the differences between subgroups. All the losses of QALE were displayed at two levels: the individual and population levels. RESULTS: At age 45, the individual-level and population-level losses of QALE attributed to the combination of cognitive impairment and multimorbidity were 7.61 (95% CI: 5.68, 9.57) years and 4.30 (95% CI: 3.43, 5.20) years, respectively. The losses for cognitive impairment alone were 3.10 (95% CI: 2.29, 3.95) years and 1.71 (95% CI: 1.32, 2.13) years at the two levels. Similarly, the losses for multimorbidity alone were 3.53 (95% CI: 2.53, 4.56) years and 1.91 (95% CI: 1.24, 2.63) years at the two levels. Additional losses due to the interaction of cognitive impairment and multimorbidity were indicated by the 0.98 years of the individual-level gap and 0.67 years of the population-level gap. CONCLUSION: Among middle-aged and elderly Chinese people, cognitive impairment and multimorbidity resulted in substantial losses of QALE, and additional QALE losses were seen due to their interaction at both individual and population levels.

QALYs and medical costs saved from prevention of a cancer: Analysis of nation-wide real-world data of Taiwan with lifetime horizon.

BACKGROUND/PURPOSE: To quantify savings of loss-of-QALE (quality-adjusted life expectancy) and lifetime medical costs from prevention of different cancers. METHODS: We collected nation-wide data on 808,700 new cancer cases of 14 different organ systems and followed them from 1998 to 2014 in Taiwan. We also collected 13,005 cancer patients from a medical center and 47,320 repeated measurements of quality of life (QoL) of EQ-5D to obtain utility values and multiplied them with the corresponding survival rates to calculate QALE. With Kaplan-Meier estimation to survival function to the end of follow-up, we extrapolated to lifetime through a rolling over algorithm on the logit transform of the survival ratio between the index cohort and age-, sex, and calendar year matched referents simulated from vital statistics. Lifetime costs for each cancer were estimated by multiplying survival with average monthly costs after adjustment with annual discount rate. The loss-of-QALE was estimated by the difference in QALE between the index cancer cohort and corresponding referents. RESULTS: The dynamic changes and weighted averages of the QoL utility values of 14 different cancers ranged from 0.82 to 0.95. Successful prevention of liver, lung, esophagus, or nasopharynx cancer would save more than 10 quality-adjusted life years and more than 21,000 USD per case for both genders. Since the saving of loss-of-QALE was adjusted for different age, sex, and calendar-year distributions, it could be used in cost effectiveness evaluation. CONCLUSION: Savings of loss-of-QALE and lifetime costs could be used for comparison of prevention, diagnosis, treatment and rehabilitation from a lifetime horizon.

Early HIV diagnosis enhances quality-adjusted life expectancy of men who have sex with men living with HIV: A population-based cohort study in Taiwan.

BACKGROUND: Whether early HIV diagnosis is beneficial for HIV patients themselves remains uncertain, given the stigma and social discrimination associated with an HIV diagnosis. This study aimed to measure the impact of early HIV diagnosis on quality-adjusted life expectancy (QALE) in comparison with late HIV diagnosis, from real-world data in Taiwan under universal access to antiretroviral therapy (ART). METHODS: This population-based cohort study included 14,570 men who have sex with men (MSM) in the national HIV registry and a quasi-random sample (n = 127) of MSM patients to measure quality of life using the EQ-5D health utility instrument. We integrated quality of life data into the extrapolated cohort survival curve to estimate the QALE in patients with early versus late HIV diagnosis (≤30 days before AIDS diagnosis). Loss-of-QALE were estimated by comparing the cohort with age-, sex-, and calendar-year-matched referents simulated from vital statistics. Difference-in-differences was estimated to quantify the effect of early HIV diagnosis. RESULTS: Early HIV diagnosis is associated with a loss-of-life expectancy of 3.11 years, with an average health utility of 0.95, in contrast to those diagnosed late (loss-of-life expectancy 8.47 years, with an average health utility of 0.86). After integration of survival and life quality, early HIV diagnosis results in a reduction of loss-of-QALE by 8.28 quality-adjusted life years among MSM living with HIV. CONCLUSIONS: Under universal access to ART, early HIV diagnosis is highly beneficial for people living with HIV themselves, with a net gain of 8.28 healthy life years compared with those diagnosed late.

Survival-weighted quality of life profiles in patients treated for laryngeal and hypopharyngeal cancers.

Objectives: This study assessed functional outcomes and quality of life (QoL) in the long term in individuals treated for laryngohypopharyngeal cancer (LHC) by estimating their life expectancy (LE), survival-weighted psychometric scores (SWPSs), and quality-adjusted LE (QALE). Materials and methods: To estimate survival outcomes, we retrospectively reviewed the data of 1576 patients treated for primary LHC between January 2010 and December 2018 and followed them until death or December 2020. We also prospectively collected QoL and functional data between October 2013 and November 2022 from 232 patients by administering the Taiwanese Chinese versions of the QoL Questionnaire Core 30, Head and Neck 35, and EQ-5D-3L. To estimate LE, we employed linear extrapolation of a logit-transformed curve. We calculated QALE and SWPSs by combining the QoL data with the LE results. Results: We estimated the LE of the patients with LHC to be 7.8 years and their loss of LE to be 15.7 years. The estimated QALE was 7.0 QALYs, with a loss of QALE of 16.5 QALYs. Lifetime impairment durations were estimated for cognitive (4.9 years), physical (4.2 years), emotional (3.4 years), social (3.4 years), and role functions (2.7 years). We estimated the durations of problems related to swallowing, speech, and teeth to be 6.2, 5.6, and 4.8 years, respectively. The patients were expected to be dependent on feeding tubes for 1.2 years. Conclusions: Patients with LHC experience significant reductions in both LE and QALE. SWPSs may constitute a valuable tool for obtaining subjective information regarding how LHC affects multifaceted QoL outcomes.

Cost-effectiveness analysis of simple hysterectomy compared to radical hysterectomy for early cervical cancer: analysis from the GCIG/CCTG CX.5/SHAPE trial.

OBJECTIVE: SHAPE (Simple Hysterectomy And PElvic node assessment) was an international phase III trial demonstrating that simple hysterectomy was non-inferior to radical hysterectomy for pelvic recurrence risk, but superior for quality of life and sexual health. The objective was to conduct a cost-effectiveness analysis comparing simple vs. radical hysterectomy for low-risk early-stage cervical cancer. METHODS: Markov model compared the costs and benefits of simple vs. radical hysterectomy for early cervical cancer over a 5-year time horizon. Quality-adjusted life years (QALYs) were estimated from health utilities derived from EQ-5D-3L surveys. Sensitivity analyses accounted for uncertainty around key parameters. Monte Carlo simulation estimated complication numbers according to surgical procedure. RESULTS: Simple hysterectomy was more effective and less costly than radical hysterectomy. Average overall costs were $11,022 and $12,533, and average gains were 3.56 and 3.54 QALYs for simple and radical hysterectomy, respectively. Baseline health utility scores were 0.81 and 0.83 for simple and radical hysterectomy, respectively. By year 3, these scores improved for simple hysterectomy (0.82) but not for radical hysterectomy (0.82). Assuming 800 early cervical cancer patients annually in Canada, the model estimated 3 vs. 82 patients with urinary retention, and 49 vs. 86 patients with urinary incontinence persisting 4 weeks after simple vs. radical hysterectomy, respectively. Results were most sensitive to variability in health utilities after surgery, but stable through wide ranges of costs and recurrence estimates. CONCLUSION: Simple hysterectomy is less costly and more effective in terms of quality-adjusted life expectancy compared to radical hysterectomy for early cervical cancer. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01658930.

The lifetime burden following stroke: Long term impact of stroke on survival and quality of life.

BACKGROUND: The absolute burden of stroke in Korea is ever growing. Many studies have explored the outcomes of mortality, quality of life (QOL), and/or economic burden with limited periods of observation. Relatively few have addressed the lifetime outcomes that are estimated beyond the limited observation period of study samples. AIMS: By combining QOL and the survival functions over a lifetime horizon, our aims were to estimate the quality-adjusted life expectancy (QALE) and loss-of-QALE of patients with ischemic and hemorrhagic stroke in South Korea, and to compare them between genders. METHODS: The survival function of stroke patients (n = 13,994) was estimated by the Kaplan-Meier's method from the National Health Insurance Service-National Sample Cohort of Korea (2002-2015), and then extrapolated to lifetime through a rolling-over algorithm. The QOL measurements, assessed by EuroQol 5-dimension (EQ-5D) questionnaire, of stroke patients (n = 474) were extracted from the Korea Health Panel (KHP, 2008-2018) to estimate the QALE. All stroke patients were categorized by sex and two types of stroke: ischemic and hemorrhagic. Age-, sex-, and calendar year-matched referents were simulated from the Korean life tables to be integrated with the general population's QOL from the KHP to estimate the QALE of the referents. We calculated the loss-of-QALE by comparing the above two sets of QALE. RESULTS: The QALE and loss-of-QALE for ischemic stroke were 10.8 and 6.1 QALYs (quality-adjusted life years), respectively, and 14.0 and 9.0 QALYs for hemorrhagic stroke. The loss-of-QALE in men was 3.0 QALYs larger than that of women with hemorrhagic stroke (p < 0.05), while the difference for ischemic stroke was much smaller and statistically insignificant at 0.6 QALYs. CONCLUSIONS: The lifetime impact of stroke in Korea is large, especially for males who survived hemorrhagic stroke. Future studies assessing the lifetime needs for long-term care of stroke patients are warranted to quantify the burden of stroke from the societal perspective.

Multidimensional evaluation of healthy life expectancy indicators based on mental health among the rural older population: A large-scale cross-sectional study.

BACKGROUND: This study aimed to estimate healthy life expectancy (HLE) regarding anxiety, depression and their comorbidity among rural older adults. METHODS: A total of 12,851 subjects (5790 men and 7061 women) enrolled from the Henan Rural Cohort Study were used to evaluate healthy status expectancy (HSE), and 10,096 (4475 men and 5621 women) of them were used to estimate health-adjusted life expectancy (HALE). The life expectancy was calculated using period life table, and HSE and HALE indicators were calculated via the Sullivan method. RESULTS: For participants aged 60, the depression-free life expectancy (DFLE), anxiety-free life expectancy (AFLE), and depression- and anxiety-free life expectancy (DAFLE) were 23.0993, 23.3314, and 22.7206 years, respectively. The quality-adjusted life expectancy (QALE) of those with neither anxiety nor depression, with anxiety, with depression, and with comorbidity was 22.0727, 20.8751, 18.1484, and 17.0823 years, respectively. The ratio of DFLE (AFLE) to LE increased with age among both genders, while the DAFLE/LE showed a decreasing trend. Regardless of HSE or HALE indicators, women tended to have higher HLE, while HLE/LE was lower than men. Furthermore, all HLE indicators associated with anxiety were the largest in both genders compared to indicators regarding depression. LIMITATIONS: The HLE may be overestimated ignoring institutional population in the study. CONCLUSION: Anxiety and depression played essential roles in the quality of life among rural older adults, especially depression. Comorbidity would intensify the adverse effect in rural areas, especially for older men. More attention should be paid to the psychological problems among rural older population.

Changes in quality-adjusted life expectancy in Belgium, 2013 and 2018.

INTRODUCTION: No information is available in Belgium on life expectancy adjusted for health-related quality of life (HRQoL). Quality-adjusted life expectancy (QALE) captures the multidimensionality of health by accounting for losses in mortality and HRQoL linked to physical, mental, and social impairments. The objective of this study is to estimate for Belgium QALE, the changes in QALE between 2013 and 2018 and the contribution of mortality, HRQoL and its dimensions to this trend. METHODS: The Belgian Health Interview Survey (BHIS), a representative sample of the general population, included the EQ-5D-5L instrument in 2013 and 2018. The tool assesses HRQoL comprising five dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) using a 5-level severity scoring to define a large variety of health states. The Sullivan method was used to compute at different ages QALE by gender using mortality data from the Belgian statistical office and average EQ-5D scores from the BHIS. QALE was calculated for 2013 and 2018, and changes in QALE over time were decomposed into mortality and ill-health effect. RESULTS: In 2018, QALE at age 15 years (QALE15) was 56.3 years for women and 55.8 years for men, a decrease from 2013 by 0.7 year for women and a stagnation for men. In men, the decrease in mortality counterbalanced the decline in HRQoL. The decline in QALE in women is driven by a decrease in mortality rates that is too small to compensate for the substantial decline in HRQoL before the age of 50 years. In women at older ages, improvements in HRQoL are observed. In women, QALE15 is decreasing due to an increase in pain/discomfort, anxiety/depression and problems in usual activities. In men at age 15, the pain/discomfort and anxiety/depression domains contributed to the stagnation. QALE65 increased somewhat, due to an improvement in self-care and mobility for both genders, and usual activities and anxiety/depression in men only. CONCLUSION: The strength of QALE as member of the family of composite indicators, the health expectancies, is the multidimensional structure of the underlying health component, including both ill-health with different health domains as levels of severity. The ability to decompose differences in the health expectancy not only into a mortality and health component but also into the different health dimensions allows to better inform on general population health trends. Next, compared to other health expectancy indicators, QALE is more sensitive to changes at younger ages.

A Review of the Types and Characteristics of Healthy Life Expectancy and Methodological Issues.

An index that evaluates the health level of a population group considering both death and loss of function due to disease is called a summary measure of population health (SMPH). SMPHs are broadly divided into life year indices and life expectancy indices, the latter of which comprise healthy life expectancy (HLE). HLE is included as a policy target in various national and regional level healthcare plans, and the term "HLE" is commonly used in academia and by the public. However, the overall level of understanding of HLE-such as the precise definition of HLE and methods of calculating HLE-still seems to be low. As discussed in this study, the types of HLE are classified into disability-free life expectancy, disease-free life expectancy, quality-adjusted life expectancy, self-rated HLE, and disability-adjusted life expectancy. Their characteristics are examined to facilitate a correct understanding and appropriate utilization of HLE. In addition, the Sullivan method, as a representative method for calculating HLE, is presented in detail, and major issues in the process of calculating HLE, such as selection of the population group and age group, estimation of death probability, calculation of life years, and incorporation of health weights, are reviewed. This study will help researchers to select an appropriate HLE type and evaluate the validity of HLE research results, and it is expected to contribute to the vitalization of HLE research.

Survival-Weighted Health Profiles in Nasopharyngeal Cancer Patients.

INTRODUCTION: In treating nasopharyngeal cancer (NPC) patients, excellent tumor control and patient survival rates can be achieved in the era of intensity-modulated radiotherapy (IMRT). However, treatment-related toxicities affect the quality of life (QoL) of NPC survivors. This study was devised to estimate the life expectancy (LE), quality-adjusted life expectancy (QALE) and survival-weighted psychometric scores (SWPS) in NPC patients. METHODS: A sample of 875 non-metastatic NPC patients diagnosed between January 1, 2009 and June 30, 2013 was collected for estimation of lifetime survival function. All patients were followed up until death or censored on December 31, 2015. To obtain the utility and psychometric score for estimation of LE, QALE, and SWPS, 99 patients were measured with the Taiwanese version of the EuroQol instrument (EQ-5D) and the Taiwan Chinese versions of the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ)-C30 and QLQ-H&N35 between October 1, 2013 and December 31, 2017. By utilizing linear extrapolation of a logit-transformed curve, the LE of NPC patients can be estimated. The QALE and SWPS can be obtained by combining the LE and the corresponding QOL function. RESULTS: The mean age of the 875 non-metastatic NPC patients was 50.3 years. The estimated average LE and QALE for NPC patients and for the reference population were 15.5 years and 14.3 quality-adjusted life years (QALYs) and 29.5 years and 29.5 QALYs, respectively. On average, the estimated lifelong duration of pain and painkiller use were 6.0 years and 2.2 years. The estimated lifelong duration of impairment of swallowing, speech, smell and taste were 14.0, 9.8, 8.7, and 7.5 years, respectively. The estimated lifelong duration of problems with dry mouth, teeth, emotion, fatigue, sleep, and social contact were 13.4, 10.1, 9.1, 12.3, 6.7, and 4.5 years, respectively. The estimated lifelong duration of tube-feeding was 1.3 months. CONCLUSIONS: The estimated LE and QALE for NPC patients were 15.5 years and 14.3 QALYs. Furthermore, SWPS could help people understand more about the impact of radiotherapy on NPC patients. These data could also be useful for policy makers to allocate limited resources in health care.

Survival-Weighted Health Profiles in Patients Treated for Advanced Oral Cavity Squamous Cell Carcinoma.

OBJECTIVES: For patients with oral cavity squamous cell carcinoma (OSCC), particularly for those with advanced disease, quality of life (QoL) is a key outcome measure. Therefore, we estimated survival-weighted psychometric scores (SWPS), life expectancy (LE), and quality-adjusted LE (QALE) in patients with advanced OSCC. METHODS AND MATERIALS: For estimation of survival function, we enrolled 2313 patients with advanced OSCC diagnosed between January 1, 2007, and December 31, 2013. The patients were followed until death or December 31, 2014. To acquire the QoL data, data from 194 patients were collected by employing the Taiwan Chinese versions of the Quality of Life Questionnaire Core 30 and Quality of Life Questionnaire Head and Neck 35 developed by the European Organisation for Research and Treatment of Cancer and the EQ-5D-3L between October 1, 2013, and December 31, 2017. The LE of the patients with OSCC were estimated through linear extrapolation of a logit-transformed curve. SWPS and QALE were determined by integrating the LE and corresponding QoL outcomes. RESULTS: For the patients with advanced OSCC, the estimated LE and QALE were 8.7 years and 7.7 quality-adjusted life years (QALYs), respectively. The loss of LE and QALE was 19.0 years and 20.0 QALYs, respectively. The estimated lifetime impairments of swallowing, speech, cognitive functioning, physical functioning, social functioning, and emotional functioning were 8.3, 6.5, 6.5, 6.1, 5.7, and 5.4 years, respectively. The estimated lifetime problems regarding mouth opening, teeth, social eating, and social contact were 6.6, 6.1, 7.5, and 6.1 years, respectively. The duration of feeding tube dependency was estimated to be 1.6 years. CONCLUSIONS: Patients with advanced OSCC had an estimated LE of 8.7 years and QALE of 7.7 QALYs. SWPS provided useful information regarding how advanced OSCC affects the subjective assessment of QoL. Our study results may serve as a reference for the allocation of cancer treatment resources.

Impact of adverse childhood experiences on quality-adjusted life expectancy in the U.S. population.

BACKGROUND: Adverse childhood experiences (ACEs) adversely impact morbidity and mortality. OBJECTIVE: To quantify burden of disease associated with ACEs among U.S. adults by estimating quality-adjusted life expectancy (QALE) according to number of ACEs reported. PARTICIPANTS AND SETTING: Data from respondents' adverse experiences occurring before age 18 were collected in nine states through the 2011 and 2012 Behavioral Risk Factor Surveillance System (BRFSS). METHODS: We estimated health-related quality of life (HRQOL) scores from BRFSS data. We constructed life tables from the Compressed Mortality Files to calculate QALE, a generalization of life expectancy that weights expected years of life lived with the HRQOL score, according to number of ACEs. RESULTS: The QALE for an 18-year-old person reporting 0, 1-2, and 3+ ACEs was 55.1, 53.4, and 45.6 years, respectively. Reporting 3+ ACEs was associated with a 9.5-year decrease (17%) in QALE. The adverse impact of ACEs are present according to age, gender, and race/ethnicity subgroups. The impact of 3+ ACEs on QALE was nearly 3-fold greater for women than men (13.2 vs. 4.7-year decrease). By contrast, an 18-year-old reporting 1-2 ACEs experienced a small decrease in QALE (1.7 years). CONCLUSIONS: Reporting 3+ ACEs led to a significant burden of disease, as assessed by QALE loss, to a similar degree as many other well-established behavioral risk factors and chronic conditions. Providers and policymakers should focus on efforts to prevent ACEs, initiate early detection of and interventions to minimize the impact of an ACE, and reduce the likelihood of engaging in maladaptive risky behaviors.

Opioid agonist treatment reduces losses in quality of life and quality-adjusted life expectancy in heroin users: Evidence from real world data.

BACKGROUND: This study estimated the long-term changes of opioid agonist treatment (OAT) in quality of life (QOL) and quantified the quality-adjusted life years (QALY) from the loss of quality-adjusted life expectancy (QALE) in heroin users. METHODS: A total of 1283 heroin users stratified by OAT were linked to the National Mortality Registry for 8 years (2006-2014) to obtain survival functions, which were extrapolated to lifetime by applying a rolling extrapolation algorithm to survival ratio between the sub-cohorts and age- and sex-matched referents simulated from vital statistics of Taiwan. We performed cross-sectional measurement of EQ-5D on 349 participants, including those with a valid state of OAT or non-OAT plus newly recruited consecutive patients, during 2015-2017 for utility values, while the QOL of referents were abstracted from the 2009 National Health Interview Survey. The QALE was calculated by summing the products of the mean QOL and survival rate throughout life. The QALE difference between the cohort and corresponding referents was the loss-of-QALE. RESULTS: QOL of the OAT group was significantly better than that of the non-OAT group in every domain of the EQ-5D, which was quantified to be 0.23 for utility after controlling for other variables. After extrapolation to 70 years, the estimated QALE and loss-of-QALE were 17.8 and 18.2 QALY for OAT subjects, respectively, while those of the non-OAT group were 9.2 and 27.9 QALY. CONCLUSIONS: Receiving OAT could reduce QALE lost by 9.7 QALYs compared with non-OAT after accounting for QOL differences along time and different age and sex distributions.