Estimated Life Expectancy Research Articles

The burden of disease due to COVID-19 in Sweden: a disability-adjusted life years (DALY) study

Abstract Background Many countries have been severely affected by the COVID-19 pandemic, including Sweden, which has been in the spotlight regarding its policies and their impact on mortality and morbidity. Therefore, it is of high interest to measure the disease burden of COVID-19 in terms of disability-adjusted life years (DALYs). DALYs have two main components: the years of life lost through premature death (YLL) and the number of years lived with disability (YLD). This study aims to measure DALYs due to COVID-19 in Sweden. Methods This study used data from the nationwide multi-register observational study SCIFI-PEARL (Swedish COVID-19 Investigation for Future Insights - a Population Epidemiology Approach using Register Linkage) covering the entire Swedish population. The methodology used in the modelling and calculation of DALYs was based on the Global Burden of Disease guidelines, using Sweden-specific life tables for estimated life expectancies. Results In Sweden, 152877 DALYs were lost to COVID-19 between March 2020 and October 2021, corresponding to 1447/ 100 000, 99,3% of which was attributed to YLL. DALYs loss occurred mainly among elderly groups with 66,78 % of DALYs being attributed to individuals above 70 years old. 57,6% of the lost DALYs occurred among men that lost more DALYs compared to females in all age groups. Conclusions Similar to other countries, the burden of COVID-19 in Sweden is concentrated mainly among the elderly, which contributed to the highest DALY loss due to mortality. Yet, DALY loss remains lower for COVID-19 compared to other major non-communicable diseases such as cardiovascular diseases and neoplasms. The contribution of YLD was minimal. However, YLD due to post-Covid is not well understood and long-term disability is likely still underestimated. Key messages • The burden of COVID-19 was mainly due to premature mortality in the older age groups. • More research is needed especially on post-COVID disability to derive better estimates of YLD.

Life Expectancy Prediction through Analysis of Immunization and HDI Factors using Machine Learning Regression Algorithms

One of the most crucial elements in end-of-life judgment is life expectancy. For example, good forecasting aids in determining the course of therapy and planning for the acquisition of wellness services and infrastructure. Physicians, on the other hand, tend to overestimate life expectancy, missing the window of opportunity to begin a plan of care. This study examines the feasibility of estimating life expectancy from a WHO dataset collected from Kaggle using machine learning techniques. Even though much research has been conducted in the past on factors influencing life expectancy, including demographic factors, economic distribution, and death rates. It was observed that the impact of immunizations on the standard of living was not previously considered. In this paper, we analyzed life expectancy based on various features, including immunization features (Polio, Hepatitis B, Diphtheria, etc..), HDI factors (schooling, GDP, etc.) of various countries for 15 years period. We also proposed machine learning algorithms for the prediction of life expectancy. We applied regression algorithms logistic regression, SVM, Decision Tree, and random forest regression and achieved a good r-squared value with the random forest algorithm.

Prediction of long-term mortality for patients with severe asymptomatic de novo carotid stenosis undergoing carotid endarterectomy (PREMY2SE-CEA): Derivation and validation of a novel risk score

ObjectiveThe aim of the present study was to develop and validate a risk prediction model for the prediction of long-term mortality for patients with severe asymptomatic de novo carotid stenosis undergoing carotid endarterectomy (PREMY2SE-CEA). MethodsData were collected retrospectively from a dedicated database of consecutive patients who had undergone elective CEA for severe (>70% using the NASCET [North American Symptomatic Carotid Endarterectomy Trial] criteria) asymptomatic carotid stenosis at two Italian University Hospitals from 2008 through 2016. Internal validation of the score was performed after random sampling in a 3:1 fashion. The primary end point of the PREMY2SE-CEA risk score was the 5-year mortality. ResultsOf the 1214 patients, 901 were included in the derivation cohort and 313 in the validation cohort. Using multivariable logistic regression with backward elimination, a parsimonious model was derived. A risk score incorporating eight risk factors was generated and found to be highly predictive of long-term mortality in the derivation (odds ratio [OR], 1.38; 95% confidence interval [CI], 1.28-1.41; P < .001) and validation (OR, 1.29; 95% CI, 1.21-1.37; P <.001) cohorts. The discrimination power in the receiver operating characteristic curve analysis was C = 0.775 (95% CI, 0.74-.80), and the optimism-corrected area under the curve in the bootstrapped samples was 0.761 (P < .001). A strong correlation was found between the predicted and actual mortality rates in the validation cohort (r = 0.71; P < .001). ConclusionsIn the present study, we have described the development, evaluation, and validation of a risk prediction model (PREMY2SE-CEA) for long-term mortality after CEA in asymptomatic patients. Physicians could use the PREMY2SE-CEA risk scoring tool to complement their estimates of life expectancy and prompt selective consideration of prophylactic CEA to improve the long-term benefits of interventions.

Life expectancy changes since COVID-19

The COVID-19 pandemic triggered an unprecedented rise in mortality that translated into life expectancy losses around the world, with only a few exceptions. We estimate life expectancy changes in 29 countries since 2020 (including most of Europe, the United States and Chile), attribute them to mortality changes by age group and compare them with historic life expectancy shocks. Our results show divergence in mortality impacts of the pandemic in 2021. While countries in western Europe experienced bounce backs from life expectancy losses of 2020, eastern Europe and the United States witnessed sustained and substantial life expectancy deficits. Life expectancy deficits during fall/winter 2021 among people ages 60+ and <60 were negatively correlated with measures of vaccination uptake across countries (r60+ = −0.86; two-tailed P < 0.001; 95% confidence interval, −0.94 to −0.69; r<60 = −0.74; two-tailed P < 0.001; 95% confidence interval, −0.88 to −0.46). In contrast to 2020, the age profile of excess mortality in 2021 was younger, with those in under-80 age groups contributing more to life expectancy losses. However, even in 2021, registered COVID-19 deaths continued to account for most life expectancy losses.

Association of Neighborhood Conditions and Resources for Children With Life Expectancy at Birth in the US

To address inequities in life expectancy, we must understand the associations of modifiable socioeconomic and structural factors with life expectancy. However, the association of limited neighborhood resources and deleterious physical conditions with life expectancy is not well understood. To evaluate the association of community social and economic conditions and resources for children with life expectancy at birth. This cross-sectional study examined neighborhood child opportunity and life expectancy using data from residents of 65 662 US Census tracts in 2015. The analysis was conducted from July 6 to October 1, 2021. Neighborhood conditions and resources for children in 2015. The primary outcome was life expectancy at birth at the Census tract level based on data from the US Small-Area Life Expectancy Estimates Project (January 1, 2010, to December 31, 2015). Neighborhood conditions and resources for children were quantified by Census tract Child Opportunity Index (COI) 2.0 scores for 2015. This index captures community conditions associated with children's health and long-term outcomes categorized into 5 levels, from very low to very high opportunity. It includes 29 indicators in 3 domains: education, health and environment, and social and economic factors. Mixed-effects and simple linear regression models were used to estimate the associations between standardized COI scores (composite and domain-specific) and life expectancy. The study included residents from 65 662 of 73 057 US Census tracts (89.9%). Life expectancy at birth across Census tracts ranged from 56.3 years to 93.6 years (mean [SD], 78.2 [4.0] years). Life expectancy in Census tracts with very low COI scores was lower than life expectancy in Census tracts with very high COI scores (-7.06 years [95% CI, -7.13 to -6.99 years]). Stepwise associations were observed between COI scores and life expectancy. For each domain, life expectancy was shortest in Census tracts with very low compared with very high COI scores (education: β = -2.02 years [95% CI, -2.12 to -1.92 years]); health and environment: β = -2.30 years [95% CI, -2.41 to -2.20 years]; social and economic: β = -4.16 years [95% CI, -4.26 to -4.06 years]). The models accounted for 41% to 54% of variability in life expectancy at birth (R2 = 0.41-0.54). In this study, neighborhood conditions and resources for children were significantly associated with life expectancy at birth, accounting for substantial variability in life expectancy at the Census tract level. These findings suggest that community resources and conditions are important targets for antipoverty interventions and policies to improve life expectancy and address health inequities.

Heterogeneity in Disparities in Life Expectancy Across US Metropolitan Areas.

Life expectancy in the United States has declined since 2014 but characterization of disparities within and across metropolitan areas of the country is lacking. Using census tract-level life expectancy from the 2010 to 2015 US Small-area Life Expectancy Estimates Project, we calculate 10 measures of total and income-based disparities in life expectancy at birth, age 25, and age 65 within and across 377 metropolitan statistical areas (MSAs) of the United States. We found wide heterogeneity in disparities in life expectancy at birth across MSAs and regions: MSAs in the West show the narrowest disparities (absolute disparity: 8.7 years, relative disparity: 1.1), while MSAs in the South (absolute disparity: 9.1 years, relative disparity: 1.1) and Midwest (absolute disparity: 9.8 years, relative disparity: 1.1) have the widest life expectancy disparities. We also observed greater variability in life expectancy across MSAs for lower income census tracts (coefficient of variation [CoV] 3.7 for first vs. tenth decile of income) than for higher income census tracts (CoV 2.3). Finally, we found that a series of MSA-level variables, including larger MSAs and greater proportion college graduates, predicted wider life expectancy disparities for all age groups. Sociodemographic and policy factors likely help explain variation in life expectancy disparities within and across metro areas.

Long-term survival and ourtomes a large cohort of patients underwent with Transcatheter Aortic Valve Replacement: an 10-year single center TAVR experience

Abstract The use of transcatheter aortic valve replacement (TAVR) has expanded as an alternative to surgical aortic valve replacement and has become a widely accepted treatment option for patients with severe aortic stenosis who are considered intermediate- and high-risk surgical candidates. The information concerning the long-term durability of TAV devices is currently limited. The interplay between estimated life expectancy and prosthetic heart valve durability is a key consideration in these discussions. The aim of this study was to determine the clinical outcomes, survival and the factors predicting mortality after TAVR Methods From April 2008 to December 2020, the auto-expandible and baloom-expandable prostheses were implanted in 991 patients with symptomatic severe aortic stenosis with intermediate, high and deemed risk. Results The mean age was 79.43±6.7 years. The logistic EuroSCORE II and STS score were 5.92±5% and 5.22±3.7%, respectively. The implantation success rate was 98.7%. In-hospital mortality was 3.3%, and the combined endpoint of death, vascular complications, myocardial infarction or stroke had a rate of 17.2%. The late mortality (beyond 30 days) was 43.2%. Survival at 1, 3, 5, 7, 9 and ten years were 88.2%, 68.2%, 50,1%, 38.1%, 26.3% and 16.4% respectively, after a mean follow-up of 44.8±31 months. The NYHA functional class improved from 3.3±0.7 to 1.76±0.5 in the follow-up. At 7 years, 9 patients had severe prosthetic valve dysfunction (severe stenosis and moderate transvalvular regurgitationI. In 7 patients were treated again with TAVR. The predictors of cumulative mortality were: Charlson index [HR 1.167 (95% CI 1.078–1.264), p=0.001], Readmision Heart Failure [HR 2.793 (95% CI 1.948–4.005), p=0.001], stroke post-TAVR [HR 2.919 (95% CI 1.965–4.336), p=0.001], Left ventricular ejection fraction [HR −1.012 (95% CI 1.002–1.022) p=0.021] and Karnosfky index [HR −0.984 (95% CI 0.975–0.993), p=0,001] but the requirement of pacemaker or residual aortic regurgitation after TAVR were not predictors [HR 0,979 (CI 95% 0.678–1.415), p 0.911] and [HR 1.087 (CI 95% 0.913–1.294), p=0.349]. Conclusions TAVR is associated with excellent clinical results at follow-up. Long-term survival depends particularly on comorbidities and the left ventricular ejection fraction Funding Acknowledgement Type of funding sources: None.

Cohort profile: the Scottish Diabetes Research Network national diabetes cohort – a population-based cohort of people with diabetes in Scotland

PurposeThe Scottish Diabetes Research Network (SDRN)-diabetes research platform was established to combine disparate electronic health record data into research-ready linked datasets for diabetes research in Scotland. The resultant cohort, ‘The...

Associations between ambient PM2.5 – components and age-specific mortality risk in the United States

Long-term exposure to fine particulate matter (PM 2.5 ) has been associated with premature mortality, but less work has examined associations with multiple PM 2.5 components. In this study we assess the relationship between specific PM 2.5 components (black carbon (BC), organic matter (OM), sulfate (SO 4 ), nitrate (NO 3 ), ammonium (NH 4 ), soil, and seasalt) and mean age-specific mortality risk (ASMR) between 2010 and 2015 at the census tract (CT) level from the US Small-Area Life Expectancy Estimates Project using multilevel models that control for a rich set of socioeconomic factors (SES) and weather conditions. We observed that ASMR and PM-components varied substantially across the US CTs. CTs accounted for the majority of the total variability in ASMR (∼75-95%). Much of the variation in ASMR observed at the state and county level were explained by SES (∼70-90%) and PM 2.5 -component concentrations (∼ 20-50%). Underprivileged CTs (CTs with a high proportion of Black residents, residents living in poverty, foreign-born residents, residents with no college education) had higher PM 2.5 and PM 2.5 -component concentrations. We observed significant associations between PM 2.5 -components, OM, SO 4 , soil and seasalt, in fully adjusted models with ASMR for most age groups > 25 years and older, with the highest associations observed for OM and ASMR across most age groups. The strongest associations between PM 2.5 -components and ASMR were observed for older residents (65-74 years of age). The associations detected were highest in underprivileged CTs. Our findings support that the impact of PM 2.5 on the risk of mortality, likely varies by particle composition.

Differences in healthy longevity by HIV status and viral load among older South African adults: an observational cohort modelling study

The population of people living with HIV in South Africa is rapidly ageing due to increased survivorship attributable to antiretroviral therapy (ART). We sought to understand how the combined effects of HIV and ART have led to differences in healthy longevity by HIV status and viral suppression in this context. In this observational cohort modelling study we use longitudinal data from the 2015 baseline interview (from Nov 13, 2014, to Nov 30, 2015) and the 2018 longitudinal follow-up interview (from Oct 12, 2018, to Nov 7, 2019) of the population-based study Health and Ageing in Africa: a Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) to estimate life expectancy and disability-free life expectancy (DFLE) of adults aged 40 years and older in rural South Africa. Respondents who consented to HIV testing, responded to survey questions on disability, and who were either interviewed in both surveys or who died between survey waves were included in the analysis. We estimate life expectancy and DFLE by HIV status and viral suppression (defined as <200 copies per mL) using Markov-based microsimulation. Among the 4322 eligible participants from the HAALSI study, we find a clear gradient in remaining life expectancy and DFLE based on HIV serostatus and viral suppression. At age 45 years, the life expectancy of a woman without HIV was 33·2 years (95% CI 32·0-35·0), compared with 31·6 years (29·2-34·1) a woman with virally suppressed HIV, and 26·4 years (23·1-29·1) for a woman with unsuppressed HIV; life expectancy for a 45 year old man without HIV was 27·2 years (25·8-29·1), compared with 24·1 years (20·9-27·2) for a man with virally suppressed HIV, and 17·4 years (15·0-20·3) for a man with unsuppressed HIV. Men and women with viral suppression could expect to live nearly as many years of DFLE as HIV-uninfected individuals at ages 45 years and 65 years. These results highlight the tremendous benefits of ART for population health in high-HIV-prevalence contexts and reinforce the need for continued work in making ART treatment accessible to ageing populations. National Institutes of Health.

Smoking and the widening inequality in life expectancy between metropolitan and nonmetropolitan areas of the United States.

BackgroundGeographic inequality in US mortality has increased rapidly over the last 25 years, particularly between metropolitan and nonmetropolitan areas. These gaps are sizeable and rival life expectancy differences between the US and other high-income countries. This study determines the contribution of smoking, a key contributor to premature mortality in the US, to geographic inequality in mortality over the past quarter century.MethodsWe used death certificate and census data covering the entire US population aged 50+ between Jan 1, 1990 and Dec 31, 2019. We categorized counties into 40 geographic areas cross-classified by region and metropolitan category. We estimated life expectancy at age 50 and the index of dissimilarity for mortality, a measure of inequality in mortality, with and without smoking for these areas in 1990–1992 and 2017–2019. We estimated the changes in life expectancy levels and percent change in inequality in mortality due to smoking between these periods.ResultsWe find that the gap in life expectany between metros and nonmetros increased by 2.17 years for men and 2.77 years for women. Changes in smoking-related deaths are responsible for 19% and 22% of those increases, respectively. Among the 40 geographic areas, increases in life expectancy driven by changes in smoking ranged from 0.91 to 2.34 years for men while, for women, smoking-related changes ranged from a 0.61-year decline to a 0.45-year improvement. The most favorable trends in years of life lost to smoking tended to be concentrated in large central metros in the South and Midwest, while the least favorable trends occurred in nonmetros in these same regions. Smoking contributed to increases in mortality inequality for men aged 70+, with the contribution ranging from 8 to 24%, and for women aged 50–84, ranging from 14 to 44%.ConclusionsMortality attributable to smoking is declining fastest in large cities and coastal areas and more slowly in nonmetropolitan areas of the US. Increasing geographic inequalities in mortality are partly due to these geographic divergences in smoking patterns over the past several decades. Policies addressing smoking in non-metropolitan areas may reduce geographic inequality in mortality and contribute to future gains in life expectancy.

Protocolo diagnóstico y terapéutico de la demencia avanzada en las personas mayores

Dementia is an acquired, chronic, progressive neurodegenerative disease with a terminal phase characterized by profound cognitive impairment with an inability to communicate verbally; functional dependence for basic activities of daily living; and the presence of other common medical problems, including eating problems, infections, and pain. A mean survival of ten years from its diagnosis is estimated. Establishing a prognosis in advanced stages is a challenge due to uncertainty regarding its progress and the onset of complications. Therefore, care and decision-making must be aimed at the patient's needs and care objectives more than the estimated life expectancy, taking into account the patient's and family members’ preferences.

Прогноз ожидаемой продолжительности жизни населения России на основе модели влияния комплекса социально-гигиенических детерминант на коэффициенты повозрастной смертности на примере болезней системы кровообращения

The article dwells on cause-effect relations between certain socio-hygienic factors and age-specific mortality rates due to cardiovascular diseases. New research trends in hygiene, a multidisciplinary approach to studies in the field and the current state policy make the present work topical. Our methodical approach to predicting probable age-specific mortality rates due to cardiovascular diseases relied on applying artificial neural networks. We analyzed a set of indicators that described the public healthcare system, sanitary-epidemiological welfare on a given territory, lifestyle, economic conditions, sociodemographic conditions, and primary incidence. Overall, we obtained 18 models (as per 5-year age-specific periods) of a relationship between socio-hygienic determinants and mortality rates due to cardiovascular diseases. The determination coefficients fell within 0.01–0.75 range and the greatest explanatory power occurred when the age period “30 years and older” was analyzed. We detected comparability of variational series obtained for mortality due to cardiovascular diseases among the whole population and the determination coefficients of the created models. We established predictive estimates of life expectancy at birth (LEB) in case there were changes in the analyzed socio-hygienic determinants by 2024 set within a certain scenario. Thus, changes in the whole set of determinants would result in 514 days added to LEB; lifestyle-related indicators, 205 days; indicators describing sanitary-epidemiological welfare, 126 days; economic indicators, 102 days; sociodemographic indicators, 101 days; primary incidence rates, 40 days; indicators describing the public healthcare system, 19 days. Several determinants were shown to be the most significant for reducing mortality due to cardiovascular diseases among working age population and older age groups. They are indicators describing people’s physical and motor activity, income levels, consumption of vegetables, education, and working conditions. Our research results are consistent with those obtained by other studies with their focus on establishing cause-effect relations between environmental factors and public health.

Life expectancy at birth for the rf population: prediction based on modeling influence exerted by a set of socio-hygienic determinants on age-specific mortality rates exemplified by diseases of the circulatory system

The article dwells on cause-effect relations between certain socio-hygienic factors and age-specific mortality rates due to cardiovascular diseases. New research trends in hygiene, a multidisciplinary approach to studies in the field and the current state policy make the present work topical. Our methodical approach to predicting probable age-specific mortality rates due to cardiovascular diseases relied on applying artificial neural networks. We analyzed a set of indicators that described the public healthcare system, sanitary-epidemiological welfare on a given territory, lifestyle, economic conditions, sociodemographic conditions, and primary incidence. Overall, we obtained 18 models (as per 5-year age-specific periods) of a relationship between socio-hygienic determinants and mortality rates due to cardiovascular diseases. The determination coefficients fell within 0.01–0.75 range and the greatest explanatory power occurred when the age period “30 years and older” was analyzed. We detected comparability of variational series obtained for mortality due to cardiovascular diseases among the whole population and the determination coefficients of the created models. We established predictive estimates of life expectancy at birth (LEB) in case there were changes in the analyzed socio-hygienic determinants by 2024 set within a certain scenario. Thus, changes in the whole set of determinants would result in 514 days added to LEB; lifestyle-related indicators, 205 days; indicators describing sanitary-epidemiological welfare, 126 days; economic indicators, 102 days; sociodemographic indicators, 101 days; primary incidence rates, 40 days; indicators describing the public healthcare system, 19 days. Several determinants were shown to be the most significant for reducing mortality due to cardiovascular diseases among working age population and older age groups. They are indicators describing people’s physical and motor activity, income levels, consumption of vegetables, education, and working conditions. Our research results are consistent with those obtained by other studies with their focus on establishing cause-effect relations between environmental factors and public health.

Characteristics of patients with advanced cancer preferring not to know prognosis: a multicenter survey study

BackgroundFor some patients with advanced cancer not knowing prognosis is essential. Yet, in an era of informed decision-making, the potential protective function of unawareness is easily overlooked. We aimed to investigate 1) the proportion of advanced cancer patients preferring not to know prognosis; 2) the reasons underlying patients’ prognostic information preference; 3) the characteristics associated with patients’ prognostic information preference; and 4) the concordance between physicians’ perceived and patients’ actual prognostic information preference.MethodsThis is a cross-sectional study with structured surveys (PROSPECT). Medical and thoracic oncologists included patients (n = 524), from seven Dutch hospitals, with metastatic/inoperable cancer and an expected median overall survival of ≤ 12 months. For analysis, descriptive statistics and logistic regression models were used.ResultsTwenty-five to 31% of patients preferred not to know a general life expectancy estimate or the 5/2/1-year mortality risk. Compared to patients preferring to know prognosis, patients preferring unawareness more often reported optimism, avoidance and inability to comprehend information as reasons for wanting limited information; and less often reported expectations of others, anxiety, autonomy and a sense of control as reasons for wanting complete information. Females (p < .05), patients receiving a further line of systemic treatment (p < .01) and patients with strong fighting spirit (p < .001) were more likely to prefer not to know prognosis. Concordance between physicians’ perceived and patients’ actual prognostic information preference was poor (kappa = 0.07).ConclusionsWe encourage physicians to explore patients’ prognostic information preferences and the underlying reasons explicitly, enabling individually tailored communication. Future studies may investigate changes in patients’ prognostic information preferences over time and examine the impact of prognostic disclosure on patients who prefer unawareness.

Individualising Life Expectancy Is Necessary for Optimal Prescribing.

One possible cause of overprescribing (or insufficient deprescribing) is the failure to explicitly address the individual's life expectancy (LE). For example, if a LE estimate shows the person has six months to live, this should influence the prescribing of a medication that offers benefits only over a much longer LE. Predicting exactly the number of years a person will live is impossible, but probabilistic forecasting is possible and arguably essential, both for the selection of the optimal intervention and for meeting the 'reasonable patient' standard of information about the harms and benefits of alternative options. One side-effect of the COVID-19 pandemic has been to bring mortality into greater prominence, hopefully facilitating its discussion in the clinic as part of the 'new normal'. This paper outlines the case for introducing LE into prescribing decisions as a way of making more individualised decisions and potentially reducing overprescribing. It concentrates on how the clinical task of arriving at individualised estimates of LE might be tackled, especially in the case of the growing number of older patients with heterogeneous sociodemographic characteristics who are experiencing multiple long term conditions of varying severity and are frequently subject to 'polypharmacy'.

The Clinical Utility of Systemic Immune-Inflammation Index Supporting Charlson Comorbidity Index and CAPRA-S Score in Determining Survival after Radical Prostatectomy-A Single Centre Study.

Simple SummaryRadical treatment of prostate cancer (PCa) provides excellent oncological outcomes. However, curative treatment of primary PCa, as well as salvage treatment of biochemical recurrence after radical treatment, requires at least a 10-year life expectancy to be beneficial. To provide an accurate selection for active treatment, several tools evaluating individual life expectancy have been developed. Our retrospective study aimed to determine the utility of the systemic immune-inflammation index (SII) in predicting early survival when used as an adjunct to CAPRA-S and Charlson comorbidity index (CCI) scores in non-metastatic PCa. We confirmed the SII as an independent predictor of survival. We have also validated the SII as a supplement to scoring systems when stratifying the risk of early mortality. In the setting of patients that might require salvage treatment, supplementing comorbidity status with the SII provided accurate discrimination of survival. The SII seems then to be useful when estimating life expectancy in patients with non-metastatic PCa.The selection of candidates for the curative treatment of PCa requires a careful assessment of life expectancy. Recently, blood-count inflammatory markers have been introduced as prognosticators of oncological and non-oncological outcomes in different settings. This retrospective, monocentric study included 421 patients treated with radical prostatectomy (RP) for nonmetastatic PCa and aimed at determining the utility of a preoperative SII (neutrophil count × platelet count/lymphocyte count) in predicting survival after RP. Patients with high SIIs (≥900) presented significantly shorter survival (p = 0.02) and high SIIs constituted an independent predictor of overall survival [HR 2.54 (95%CI 1.24–5.21); p = 0.01] when adjusted for high (≥6) age-adjusted CCI (ACCI) [HR 2.75 (95%CI 1.27–5.95); p = 0.01] and high (≥6) CAPRA-S [HR 2.65 (95%CI 1.32–5.31); p = 0.006]. Patients with high scores (ACCI and/or CAPRA-S) and high SIIs were at the highest risk of death (p < 0.0001) with approximately a one-year survival loss during the first seven years after surgery. In subgroup of high CAPRA-S (≥6), patients with high ACCIs and high SIIs were at the highest risk of death (p <0.0001). Our study introduces the SII as a straightforward marker of mortality after RP that can be helpful in pre- and postoperative decision-making.

Nomograms and scoring system for forecasting overall and cancer-specific survival of patients with prostate cancer.

Estimated life expectancy is one of the most important factors in determining treatment options for prostate cancer (PCa) patients. However, clinicians have few effective prognostic tools to individually assess survival in patients with PCa. We screened 283,252 patients diagnosed with PCa from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and randomly divided them into the training and validation groups. We used univariate and multivariate Cox analyses to identify independent prognostic factors and further established nomograms to predict 1-, 3-, 5-, and 10-year overall survival (OS) and cancer-specific survival (CSS) for PCa patients. The prediction performance of nomograms was tested and externally validated by Concordance index (C-index) and receiver operating characteristic (ROC) curve. Calibration curve and decision curve analysis (DCA) were used for internal validation. We further developed PCa prognostic scoring system based on the impact of available variables on survival. The variables age, race, marital status, TNM stage, surgery method, radiotherapy, chemotherapy, PSA value, and Gleason score identified as independent prognostic factors were included in the survival nomograms. The results of training (C-index: OS=0.776, CSS=0.889; AUC value: OS=0.772-0.802, CSS=0.892-0.936) and external validation (C-index: OS=0.759, CSS=0.875) indicated our nomograms had good performance in predicting 1-, 3-, 5-, and 10-year OS and CSS prediction. Internal validation using the calibration curves and DCA curves demonstrated the effectiveness of the prediction models. The prognostic scoring system was more effective than the AJCC staging system in predicting the survival of PCa patients, especially for OS. The prognostic nomograms and prognostic scoring system have favorable performance in predicting OS and CSS of PCa patients. These individualized survival prediction tools may contribute to clinical decisions.

Years of life gained when meeting sleep duration recommendations in Canada

ObjectiveTo estimate the years of life gained when meeting the sleep duration recommendations across the adult lifespan. MethodsThree pieces of information were used to estimate and compare life expectancy at each age of adult life among Canadian adults who did and did not meet sleep duration recommendations: (i) the prevalence of self-reported short sleep duration, recommended sleep duration, and long sleep duration; (ii) the relative risks of all-cause mortality associated with sleep duration obtained from recent meta-analyses; and (iii) the probability of death during each year of life obtained from life tables. ResultsAdults who meet the sleep duration recommendations have an estimated life expectancy at age 20 years that is 1.2 years longer than short sleepers and 2.6 years longer than long sleepers. Differences between men and women were minimal. ConclusionMeeting sleep duration recommendations is associated with increases in longevity in Canada.

Quality-Adjusted Life Expectancy Norms for the English Population

ObjectivesThe 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. Methods5-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. ResultsQALE 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. ConclusionThis study provides new QALE population norms for England that serve to establish absolute and relative QALY shortfalls for the purpose of health technology assessments.