Remaining Life Expectancy Research Articles

Inferring the Prevalence and Age Dependence of Infection Fatality Rate from Excess Mortalities for COVID-19 in Germany

Background and Aims: The reported case and death numbers of the coronavirus disease (COVID-19) are often used to estimate the prevalence and infection fatality rate (IFR). We use the excess mortality instead in order to have an alternative and independent measure. In calculating age dependent IFR, we distinguish between healthy and weak individuals, where the latter are statistically defined as individuals with a remaining life expectancy of 20 weeks. Methods: We estimate the cumulated prevalence of SARS-COV-2 from the excess mortality curve of the 90+ age population, since this part of the population is most likely to die from the infection. We then assume this estimated cumulated prevalence to be the actual cumulated prevalence of SARS-COV-2 across all age bands in Germany during the first COVID-19 wave. From there we calculate the age dependent infection fatality rates. We distinguish between the individuals with life expectancy below 20 weeks and those above 20 weeks.Results: For the first COVID-19 wave, we find a cumulated prevalence of about 3% for Germany across all age bands.The steep age gradient of the IFR is significantly smaller by a factor of around 10 when considering healthy individuals only, as compared to the IFR calculated for all individuals in the respective age bands. For the 90+ age band we find an overall IFR of 7.0% while for healthy 90+ individuals, the IFR reduces to 0.50%. For the 80-90 age band the IFRs are 2.2% and 0.74% respectively, for the 60-80 age band 0.40% and 0.025%, for the 40-60 age band 0.071% and 0.023%, and finally for the 0-40 age band 0.0014% and The results for overall IFR are in agreement with previous seroprevalence studies, supporting the here presented approach. Conclusion: We conclude that around 2.5 million individuals in Germany were infected during the first COVID-19 wave, whereas less than 10% of infected individuals were detected via tests. In addition to the known fact that the infection fatality rate depends significantly on the age of the infected individual, we furthermore show that a second major factor is the life expectancy of the individual under mild (COVID-19-free) conditions. This second factor has not been paid much quantitative attention to so far. We find that a large fraction of deaths due to COVID-19 actually stem from such weak individuals, i.e. people who pre-died in the first COVID-19 wave and would have died without COVID-19 only a few weeks later (harvesting effect, well-known for COVID-19 from other studies).

Dødsfall i sykehjem etter covid-19-vaksine

In the period 27 December 2020 to 15 February 2021, about 29400 of Norway's roughly 35000 nursing home patients were vaccinated with the mRNA vaccine BNT162b2. During the same period, the Norwegian Medicines Agency received 100 reports of suspected fatal adverse reactions to the vaccine. An expert group has examined the reports and assessed the extent of a causal link between vaccination and death. The expert group worked in two pairs, each of which examined 50 anonymised reports. Each member first examined the reports alone and classified the causality as unlikely, possible, probable, certain or unclassifiable. Each pair then discussed their results until they reached a consensus. All four experts assessed a random sample of 20 reports. The degree of agreement was assessed using weighted kappa and McNemar's test of symmetry. The mean age of the patients was 87.7 years (range 61-103 years). Among 100 reported deaths, a causal link to the vaccine was considered probable in 10 cases, possible in 26 and unlikely in 59. Five were unclassifiable. Weighted kappa was 0.40 and 0.38 in the two expert pairs, respectively. Most nursing home patients have a short remaining life expectancy, but vaccination may, in a few cases, have accelerated a process of dying that had already begun. Nursing home patients should still be given priority for vaccination, but the benefits versus risk must be carefully weighed up for the frailest patients.

Survival Probability of Patients with Bladder Cancer Without Recurrence Following Radical Cystectomy Compared to Remaining Life Expectancy of the Average Danish Citizen

Survival Probability of Patients with Bladder Cancer Without Recurrence Following Radical Cystectomy Compared to Remaining Life Expectancy of the Average Danish Citizen

Change of the Way of Thinking and Institutional Reform about Equal Suffrage - Reverse Income-based Suffrage -

Change of the Way of Thinking and Institutional Reform about Equal Suffrage - Reverse Income-based Suffrage -

Time to Deprescribe: A Time-Centric Model for Deprescribing at End of Life.

In end-of-life care, deprescribing practices may vary considerably from one practitioner to the next, although most published frameworks for evaluating medication appropriateness in advanced illness consider three key principles (1) patient and caregiver goals, (2) remaining life expectancy (LE), and (3) medication time to benefit (TTB). The objective of this article is to provide clinicians with a structured, consistent approach for deprescribing that does not replace clinical judgment or the preferences of patients and their families but enhances it through clinical data. The emphasis will be on the time component of published models, including how to estimate remaining LE and medication TTB. Through case examples of two new hospice admissions, LE and TTB will be estimated and applied to deprescribing decisions. This time-centric approach may satisfy the palliative and hospice clinicians' desire for clear clinical justification for medication discontinuation while at the same time providing a strategy for communicating deprescribing rationale to patients and families.

Quantifying Longevity Gaps Using Micro-Level Lifetime Data

Abstract Using flexible Poisson regressions, we analyse a huge micro-level lifetime dataset from a Dutch pension fund, including categorical, continuous and spatial risk factors collected on participants in the fund. The availability of granular lifetime data allows us to quantify the longevity gap between the national population and the fund on the one hand, and between participants within the fund on the other hand. We identify the most important risk factors using statistical criteria that measure the in- and out-of-sample performance of the regression models. We evaluate the financial performance of the models by introducing a novel type of backtest, which selects the risk factors that contribute most to an accurate prediction of future pension liabilities. For this portfolio, the most relevant risk factors (next to age and gender) are the salary, the time spent in disability and working at irregular hours. The resulting personalized mortality risk profiles show substantial differences between the remaining life expectancies for the most-favourable and least-favourable risk profiles. Our method to estimate these longevity gaps will help policymakers to assess wanted and unwanted consequences of longevity risk sharing in pension schemes.

Overdiagnosis in lung cancer screening: Estimates from the German Lung Cancer Screening Intervention Trial.

Overdiagnosis is a major potential harm of lung cancer screening; knowing its potential magnitude helps to optimize screening eligibility criteria. The German Lung Screening Intervention Trial ("LUSI") is a randomized trial among 4052 long-term smokers (2622 men), 50.3 to 71.9 years of age from the general population around Heidelberg, Germany, comparing five annual rounds of low-dose computed tomography (n = 2029) with a control arm without intervention (n = 2023). After a median follow-up of 9.77 years postrandomization and 5.73 years since last screening, 74 participants were diagnosed with lung cancer in the control arm and 90 in the screening arm: 69 during the active screening period; of which 63 screen-detected and 6 interval cancers. The excess cumulative incidence in the screening arm (N = 16) represented 25.4% (95% confidence interval: -11.3, 64.3] of screen-detected cancer cases (N = 63). Analyzed by histologic subtype, excess incidence in the screening arm appeared largely driven by adenocarcinomas. Statistical modeling yielded an estimated mean preclinical sojourn time (MPST) of 5.38 (4.76, 5.88) years and a screen-test sensitivity of 81.6 (74.4%, 88.8%) for lung cancer overall, all histologic subtypes combined. Based on modeling, we further estimated that about 48% (47.5% [43.2%, 50.7%]) of screen-detected tumors have a lead time ≥4 years, whereas about 33% (32.8% [28.4%, 36.1%]) have a lead time ≥6 years, 23% (22.6% [18.6%, 25.7%]) ≥8 years, 16% (15.6% [12.2%, 18.3%]) ≥10 years and 11% (10.7% [8.0%, 13.0%]) ≥12 years. The high proportions of tumors with relatively long lead times suggest a major risk of overdiagnosis for individuals with comparatively short remaining life expectancies.

Demographic and Socioeconomic Disparities in Life Expectancy With Hearing Impairment in the United States.

Hearing impairment is one of the most common disabilities among older people, and its prevalence will increase as the U.S. population ages. However, little is known about social disparities in onset or transitions into and out of hearing impairment, nor how these transitions impact years of life to be spent impaired. We investigate the number of years an "average" person can expect to live with and without hearing impairment after age 50; sex, race, educational, and regional differences in these expectancies; and the implication of hearing impairment for remaining life expectancy. Bayesian multistate life table methods are applied to 9 waves of data from the Health and Retirement Study (1998-2014) to investigate social disparities in life expectancy with hearing impairment (n = 20,200) for the general population, people hearing impaired at age 50, and people hearing unimpaired at age 50. Men, Hispanics, persons with less educational attainment, and those born in the south can expect to live a larger proportion of their remaining lives hearing impaired. Although transitions from hearing impaired to unimpaired occur, those with some hearing impairment at age 50 can expect to live more years with hearing impairment, and hearing impairment does not shorten remaining life expectancy. Significant sociodemographic disparities in hearing impaired life expectancy exist. In contrast to past research, we find that hearing impairment does not affect total life expectancy. Future research should consider the consequences of hearing impairment for years to be lived with other age-related and potentially downstream health outcomes.

Nature and prevalence of combinations of mental disorders and their association with excess mortality in a population-based cohortstudy.

The nature and prevalence of combinations of mental disorders and their associations with premature mortality have never been reported in a comprehensive way. We describe the most common combinations of mental disorders and estimate excess mortality associated with these combinations. We designed a population-based cohort study including all 7,505,576 persons living in Denmark at some point between January 1, 1995 and December 31, 2016. Information on mental disorders and mortality was obtained from national registers. A total of 546,090 individuals (10.5%) living in Denmark on January 1, 1995 were diagnosed with at least one mental disorder during the 22-year follow-up period. The overall crude rate of diagnosis of mental disorders was 9.28 (95% CI: 9.26-9.30) per 1,000 person-years. The rate of diagnosis of additional mental disorders was 70.01 (95% CI: 69.80-70.26) per 1,000 person-years for individuals with one disorder already diagnosed. At the end of follow-up, two out of five individuals with mental disorders were diagnosed with two or more disorder types. The most prevalent were neurotic/stress-related/somatoform disorders (ICD-10 F40-F48) and mood disorders (ICD-10 F30-F39), which - alone or in combination with other disorders - were present in 64.8% of individuals diagnosed with any mental disorder. Mortality rates were higher for people with mental disorders compared to those without mental disorders. The highest mortality rate ratio was 5.97 (95% CI: 5.52-6.45) for the combination of schizophrenia (ICD-10 F20-F29), neurotic/stress-related/somatoform disorders and substance use disorders (ICD-10 F10-F19). Any combination of mental disorders was associated with a shorter life expectancy compared to the general Danish population, with differences in remaining life expectancy ranging from 5.06 years (95% CI: 5.01-5.11) to 17.46 years (95% CI: 16.86-18.03). The largest excess mortality was observed for combinations that included substance use disorders. This study reports novel estimates related to the "force of comorbidity" and provides new insights into the contribution of substance use disorders to premature mortality in those with comorbid mental disorders.

Impact of area-level socioeconomic status and accessibility to treatment on life expectancy after a cancer diagnosis in Queensland, Australia

AimsThis study quantifies geographic inequities in loss of life expectancy (LOLE) by area-level socioeconomic status (SES) and accessibility to treatment. MethodsAnalysis was conducted using a population-based cancer-registry cohort (n = 371,570) of Queensland (Australia) residents aged 50−89 years, diagnosed between 1997–2016. Flexible parametric survival models were used to estimate LOLE by area-level SES and accessibility for all invasive cancers and the five leading cancers. The gain in life years that could be achieved if all cancer patients experienced the same relative survival as those in the least disadvantaged-high accessibility category was estimated for the 2016 cohort. ResultsFor all invasive cancers, men living in the most disadvantaged areas lost 34 % of life expectancy due to their cancer diagnosis, while those from the least disadvantaged areas lost 25 %. The corresponding percentages for women were 33 % and 23 %. Accessibility had a lower impact on LOLE than SES, with patients from low accessibility areas losing 0–4 % more life expectancy than those from high accessibility areas. For cancer patients diagnosed in 2016 (n = 24,423), an estimated 101,387 life years will be lost. This would be reduced by 19 % if all patients experienced the same relative survival as those from the least disadvantaged-high accessibility areas. ConclusionThe impact of a cancer diagnosis on remaining life expectancy varies by geographical area. Establishing reasons why area disadvantage impacts on life expectancy is crucial to inform subsequent interventions that could increase the life expectancy of cancer patients from more disadvantaged areas.

What can lifespan variation tell us about trends in life expectancy in high income countries?

Abstract Building on the findings of presentations 1 and 2, we turn to two further measures of population health: life expectancy at birth and lifespan variation. Life expectancy at birth provides a single figure that captures the overall mortality experience of a nation, and, in the absence of data artefact, a wide-scale environmental event such as war or natural disaster, a disease epidemic or mass migration, life expectancy can be expected to continue to improve in HICs. Concurrently lifespan variation, which measures the average gap between the age at death of an individual and the remaining life expectancy at that age, should decrease as life expectancy increases. Recent analysis of life expectancy improvements in HICs by the Office for National Statistics, using Human Mortality Database data, found that while Japan continues to see improvements, the UK and the USA fell to the bottom of the rankings. Economically, both the UK and Japan have experienced 'lost decades' of poor economic growth, in 1990s and 2010s respectively. Yet, while Japan continued to see life expectancy improvements, in the UK life expectancy stalled, and both countries saw an increase in lifespan variation. In this presentation, we will present the analysis of lifespan variation of 5 HICs: the USA, where life expectancy has declined, the UK, where gains in life expectancy have trailed behind those in other industrialised countries, Japan, which has seen sustained progress, and France and Canada, neighbours of the UK and USA respectively, which lie in the middle. We will examine what can be determined from these measures over periods of poor economic growth, and the implications for achieving 'sustainable growth'.

Regional differences in the attributable burden for Germany: Exploring YLL for selected risk factors

Abstract Background Within the BURDEN 2020 project (Burden of disease in Germany at the national and sub-national level) we calculate burden of disease indicators on a small-scale level for Germany. In order to provide a comprehensive view over diseases and their impact on population health, Years of Life Lost due to premature death (YLL) and Years Lived with Disability (YLD) are summed up to the measure Disability Adjusted Live Years (DALY). YLL, YLD and DALY will be attributed to a set of risk factors. Methods Object of the analysis is the indicator YLL across spatial planning regions in Germany. It is calculated by multiplying the number of deaths with the remaining life expectancy at the age of deaths. A share of YLL can be attributed to specific risk factors. Smoking and ambient particulate matter pollution are used as examples. The distribution of risk factors is based on German health surveys and local air pollution measurements. The analysis follows the Comparative Risk Assessment approach, which quantifies the possible change in burden by assuming a different exposure level in the past. Results Based on the absolute YLL estimates, the overall leading causes of deaths are ischemic heart diseases, tracheal, bronchus, and lung cancer and stroke. In addition, for women breast cancer is a leading cause of death. Causes vary by age groups and by region. We expect the attributable fraction to vary across local areas as well. Conclusions When it comes to health care intervention, the method of attributing risk factors to burden of disease outcomes reveals necessary fields of action, especially across regions. In order to allocate financial resources within the health care, the CRA can provide additional arguments for political decision making. Key messages Causes of death and the related years of life lost are an integral part of health monitoring. Our analysis reveals how YLL and risk factor attributable burden vary across German regions.

Forecasting health prior to state pension age – projections for the Netherlands 2040

Abstract Objectives In many Western societies, the state pension age is being raised to stimulate prolonged working. In the Netherlands, the raise of the state pension age is linked to the remaining life expectancy at age 65 with a factor of 2/3rd, and is expected to be 68 years in 2040. It is not yet well understood whether health of the 60+ permits this increase. In this study, health of Dutch adults aged 60 to 68 is forecasted up to 2040. Methods Data are from the Dutch Health Interview Survey (HIS) 1990-2017 (N≈280.000) and the Dutch Public Health Monitor (PHM) 2016 (N≈460.000). Health is operationalized using binomial scores of 1) self-rated health and 2) limitations in hearing, seeing or mobility. Categories are: good health (healthy on both items), moderate health (healthy on one item) and poor health (unhealthy on both items). First, based on the HIS, health status in 5-year age categories was modelled up to 2040 using logistic regression analysis in R. Second, the growth factor from 2016 to 2040 was applied to the health level from the PHM 2016. Results In 2016, 63% of men aged 60-65 had good health, 25% had moderate health and 12% had poor health. Among women, this distribution was 64%, 22% and 14%, respectively. In 2040, the health distribution among men aged 60-68 is estimated to be 63-71% in good health, 17-28% in moderate health and 9-12% in poor health. Among women this is estimated to be 64-69%, 17-24% and 12-14%, respectively. Conclusions Health of Dutch cohorts nearing the state pension age in the future is estimated to remain the same or improve up to 2040. This development in health is not an obstacle to raising the state pension age. However, due to the increasing state pension age and the baby boom generation reaching age 60+ in the coming years, the absolute number of people aged 60+ in poor and moderate health that participates in labor will increase. Policy aiming at sustainable employability will therefore become increasingly important. Key messages Health of Dutch cohorts nearing the state pension age is estimated to remain the same or improve in the future. The development in health is not an obstacle to raising the state pension age. Although health is estimated to remain the same or improve, the absolute number of people aged 60+ in poor and moderate health that participate in labor will increase due to an aging population.

Interventions to suppress the coronavirus pandemic will increase unemployment and lead to many premature deaths.

Background and aims:Interventions to suppress the coronavirus pandemic have led to economic recession and higher unemployment, which will increase mortality and decrease quality of life. The aim of this article is to estimate the consequences on mortality and life expectancy of increased unemployment rates due to the coronavirus pandemic in Sweden and other countries.Methods:Based on recent increases and expected future unemployment rates due to the coronavirus pandemic, results from a systematic review and data from vital statistics in Sweden, the number of premature deaths due to unemployment in Sweden have been estimated.Results:Based on our assumptions, the calculations show that if the number of unemployed persons in Sweden increases by 100,000, one may expect some 1800 more premature deaths during the following 9 years. If the duration of the recession is limited to 4 years, excess deaths due to unemployment may be around 800. On average, the unemployed will lose 2 years of their remaining life expectancy. In many other countries unemployment rates have or are estimated to rise more than in Sweden, sometimes two- or threefold, suggesting hundreds of thousands of excess deaths due to unemployment.Conclusions: Interventions to suppress the coronavirus pandemic include the shut-down of economic activities and lead to increased all-cause mortality. These public health effects must be considered in the decision-making process and should be added to overall estimates of the effects of the pandemic on public health.

Oncologic outcomes of patients with Merkel Cell Carcinoma (MCC): A multi-institutional cohort study

BackgroundMerkel cell carcinoma (MCC) is a rare cutaneous neuroendocrine tumor that primarily affects elderly patients. Despite aggressive treatment, overall survival (OS) remains low. MethodsThis study is a multi-institutional, retrospective review of 102 patients with MCC. We evaluated OS, disease-specific survival (DSS), and risk factors for recurrence. ResultsMedian age of patients was 71.46% of patients recurred. Patients with stage I disease had median 5-year OS of 59.3%, compared to 68.1% DSS. For stage III, median 5-year OS was 46.0% vs 58.2% DSS. Disease stage and advanced age were risk factors for recurrence and decreased OS. Immunocompromised status and disease stage were the strongest predictors of DSS. ConclusionsDSS is significantly better than OS for patients with MCC. Many elderly patients with newly diagnosed MCC have low remaining life expectancy, regardless of their MCC diagnosis. Patient age and overall health status should be considered to personalize care plans for patients with MCC.

Prospective measures of aging for Central and South America.

By conventional measures, it is often remarked that Central and South America is one of the fastest aging geographic regions in the world. In recent years, however, scholars have sought to problematize the orthodox measures and concepts employed in the aging literature. By not taking dynamic changes in life expectancy into account, measures which hold chronological age constant (e.g. defining a boundary to old age at 60 or 65) represent a very narrow view of population aging. Furthermore, such constant measures may misrepresent differences between territories when performing a comparative analysis. Prospective measures based on the number of years until death present an alternative approach which can adapt to dynamic changes in life expectancy and differences over time and space. The objective of this paper, then, is to apply the new ‘prospective’ measures of aging to the territories of Central and South America. We calculate prospective median age; an alternative old-age threshold based on the age at which remaining life expectancy is 15 years, and calculate prospective old-age dependency ratio for 1950–2100 using estimated and projected life tables from the latest iteration of the UN’s World Population Prospects. These new measures present a very different view of aging in Central and South America. While there are significant differences across countries, the pace and scale of aging are considerably slower and diminished when compared to standard, orthodox measures based on fixed chronological ages. Applying these new measures can not only serve to present a more realistic view of aging which maps onto demographic reality but can also serve to reconceptualize and reframe the issue as something which is far more manageable (e.g. through institutional reform) than is often perceived to be.

Life expectancy of parkinsonism patients in the general population

IntroductionDetailed data on the life expectancy of patients with parkinsonism from the general population are largely lacking. This study aimed to determine the absolute life expectancy of patients newly-diagnosed with parkinsonism. MethodsThis study was part of the Rotterdam Study, an ongoing, population-based cohort study in the Netherlands. We included 12,789 participants of 50 years and older, free of parkinsonism. Patients diagnosed with parkinsonism were matched to controls on sex, birth year, dementia status, cancer status, and coronary heart disease status. We used Gompertz regression and lifetables to estimate the remaining life expectancy per year of age. ResultsThe mean age of our study population was 65.0 (SD 9.7) years and 57.6% were women. During an average follow-up of 12 years, 297 participants were diagnosed with parkinsonism. The mean age at parkinsonism diagnosis was 78.6 (SD 8.1) years. Once diagnosed with parkinsonism, the life expectancy was lower than matched controls across a wide age range. At 65 years, the life expectancy of patients with parkinsonism was reduced with 6.7 [95% CI: 2.4;10.7] years compared to controls. At 85, the difference in life expectancy was 1.2 [95% CI: -2.2;4.5] years compared to controls. ConclusionPatients diagnosed with parkinsonism have a reduced life expectancy compared to their peers in the general population. The absolute life expectancy is mainly reduced if parkinsonism is diagnosed before the age of 70.

Generalized mean residual life models for case-cohort and nested case-control studies.

Mean residual life (MRL) is the remaining life expectancy of a subject who has survived to a certain time point and can be used as an alternative to hazard function for characterizing the distribution of a time-to-event variable. Inference and application of MRL models have primarily focused on full-cohort studies. In practice, case-cohort and nested case-control designs have been commonly used within large cohorts that have long follow-up and study rare diseases, particularly when studying costly molecular biomarkers. They enable prospective inference as the full-cohort design with significant cost-saving benefits. In this paper, we study the modeling and inference of a family of generalized MRL models under case-cohort and nested case-control designs. Built upon the idea of inverse selection probability, the weighted estimating equations are constructed to estimate regression parameters and baseline MRL function. Asymptotic properties of the proposed estimators are established and finite-sample performance is evaluated by extensive numerical simulations. An application to the New York University Women's Health Study is presented to illustrate the proposed models and demonstrate a model diagnostic method to guide practical implementation.

Association of Specific Mental Disorders With Premature Mortality in the Danish Population Using Alternative Measurement Methods.

The association of mental disorders with premature mortality published in the Global Burden of Disease (GBD) studies has been underestimated because these analyses have recommended using only a small number of mental disorders as causes of death to estimate years of life lost (YLL). Alternative methods have been introduced, such as estimating life-years lost (LYL), to compare individuals with mental disorders with the general population. To generate register-based YLL and LYL estimates and to use these measurement methods to assess the association of specific mental disorders with premature mortality. This population-based cohort study included all persons with and without mental disorders aged 0 to 94 years who were living in Denmark between January 1, 2000, and December 31, 2015. Data were analyzed from January to December 2019. Danish health registers were used to identify mental disorder diagnoses, dates of death, and causes of death. The YLLs were estimated for the set of mental health-associated causes of death, and all-cause and cause-specific LYLs were estimated for 18 specific mental disorders and 3 broad categories of mental disorders that were recommended for use in the GBD studies. The association between the number of comorbid mental disorders (divided into categories of persons with ≥1 type of disorder, ≥2 types of disorders, ≥3 types of disorders, and ≥4 types of disorders) and LYL estimates was also examined. A total of 6 989 627 individuals (3 481 219 male persons [49.8%] and 3 508 408 female persons [50.2%]; mean [SD] age at study enrollment, 32.2 [24.4] years) were followed up for a total of 85 911 461 person-years. The YLL rates per 100 000 person-years were highest for alcohol use disorder (for male individuals, 568.7 [95% CI, 564.4-572.7]; for female individuals, 155.5 [95% CI, 153.5-157.9]) and suicide (for male individuals, 590.1 [95% CI, 583.8-596.5]; for female individuals, 202.3 [95% CI, 198.5-206.4]). Although only 3 of 18 mental and substance use disorders could be associated with YLL, all mental disorders were associated with shorter life expectancies when LYL was used for measurement. Male and female individuals diagnosed with any mental disorder had life expectancies that were shorter by 11.2 years (95% CI, 11.1-11.3 years) and 7.9 years (95% CI, 7.8-8.0 years), respectively, and remaining life expectancy decreased further among those with comorbid mental disorders. Drug use disorders were associated with the highest excess LYL estimates; however, common mental disorders, such as depressive and anxiety disorders, were also associated with substantial premature mortality. Mental disorders were observed to be associated with reductions in life expectancy. This finding provides a foundation for future intervention programs designed to reduce the differential mortality gap associated with mental disorders. Register-based studies allow the calculation of precise individual-level YLLs and LYLs, and both measurement methods are informative for health care planning. Compared with YLL, the novel LYL measurement approach may more precisely capture the association of mental disorders with premature mortality and facilitates the exploration of comorbidity and specific causes of death in individuals with mental disorders.

A cost-utility analysis of open A1 pulley release for the treatment of trigger finger.

The United Kingdom National Institute for Health and Care Excellence considers a procedure to be cost-effective if the cost per quality-adjusted life year gained falls below a threshold of £20,000-£30,000 (€22,600-33,900; US$24,600-$36,900). This study used cost per quality-adjusted life year methodology to determine the cost-utility ratio of A1 pulley release. Pre- and postoperative EuroQol 5 Dimensions 5 Likert scores were collected prospectively over 6years from 192 patients. The median pre- and postoperative indices derived from the EuroQol 5 Dimensions 5 Likert scores were significantly different at 0.77 and 0.80. The mean life expectancy was 21years. The mean number of quality-adjusted life years gained was 1 per patient. The mean cost-utility ratio per patient was £32,308 (€36,508; US$39,730) and £16,154 (€18,254; US$19,869) at 1 and 2years, respectively. Provided the benefit of surgery was maintained over the remaining life expectancy, the cost-utility ratio decreased to £1537 (€1737; US$1891) per patient. A1 pulley release is cost-effective provided the benefit is maintained for 2years. The procedure is also associated with a statistically significant improvement in quality of life.Level of evidence: III.