Calculate Life Expectancy Research Articles

Geospatial Data Aggregation Methods for Novel Geographies: Validating Congressional District Life Expectancy Estimates.

Place is a critical determinant of health. Recent novel analyses have explored health outcome estimation for small geographies, such as census tracts, as well as health outcome aggregation to geopolitical geographies with accountable political representatives, such as congressional districts. In one such application, combining these approaches, researchers aggregated census tract estimates of life expectancy to the congressional district level to derive local estimates, but such an approach has not been validated. Here, we compared two sources and approaches to calculating life expectancy data for Pennsylvania congressional districts. We used 2010-2015 census tract life expectancy estimates from the US Small-area Life Expectancy Estimates Project (LEEP) and dasymetric methods to compute population-weighted life expectancy aggregated to the congressional district level. Using georeferenced Vital Statistics data, we aggregated age-specific census tract death and population counts to congressional districts and used abridged life tables to estimate life expectancy. To validate the dasymetric aggregated estimates we compared absolute differences, assessed the correlation, and created Bland-Altman plots to visualize the agreement between the two measures. We found strong agreement between congressional district estimates of life expectancy at birth derived using the dasymetric LEEP model-based approach and Vital Statistics direct estimates approach, though life expectancy at older ages (75 and older) showed weak correlations. This validation contributes to our understanding of geospatial aggregation methods for novel geographies including congressional districts. Health outcome data aggregated to the congressional district geography can support congressional policy making aimed at improving population health outcomes.

Table of life for beneficiaries of the Institute of Security and Social Services of State Workers (ISSSTE), Mexico 2021.

Determine the life expectancy in the covered population of the Institute of Security and Social Services of State Workers in México for 2021. We used the abrogated method from Reed-Merrel, for calculate the life expectancy in age groups. By 2021, life expectancy general was 79.51 years; 81.40 years and 78.91 years for woman and men, respectively. The calculated life expectancy not show a reduction in the population of federal and State employees in Mexico.

Quantifying work-related social inequalities in life expectancy: a methodological proof-of-concept.

Employment and working conditions are strong social determinants of health, yet many epidemiological studies fail to account for their impact on life expectancy calculations. Integration of working conditions into health estimates requires both valid methodology and data sources. Using the French National Health and Career Path survey and French life tables, we quantified the impact of four major work-related factors (lack of job control, job insecurity, unemployment, and occupational physical activity) in explaining socio-occupational inequalities in life expectancy. Using a formula-based approach, we computed work-related loss in life expectancy by socio-occupational group separately by sex. Based on life expectancy at age 35, we estimated a range from 1.3 to 3.3 years of life lost for men, and from 0.5 to 1.8 years for women are attributed to a combination of these four key factors. Although subject to sources of under- and over-estimation, the differential life expectancy at age 35 between senior executives and manual workers would substantially decrease, had these exposures been set at the theoretical minimum level. This proof-of-concept analysis demonstrates the utility of accounting for occupational factors and the potential to quantify the improvements in life expectancy by modifying working and employment conditions.

Years of Healthy Life among Older Adults in Brazil: An Analysis Based on the Global Activity Limitation Indicator, 1998 and 2008

The aim of the study was to calculate life expectancy and Healthy Life Expectancy (HLY) through a Global Activity Limitation Indicator (GALI) proxy among Brazilian older adults according to sex for the years 1998 and 2008. The study was carried out using data from the Brazilian National Household Sample Survey (PNAD) and from Abbreviated Life Tables in 2000 and 2010 from Brazilian Institute of Demographic Geography and Statistics (IBGE) by sex. The activity limitation-free life expectancy was estimate based on the GALI for both sexes using the Sullivan method. The results showed an increase in life expectancy in the period for both sexes. The time of life without activity limitations in 2008 has decreased for men. For women, a reduction in percentage of the time lived without activity limitation has been shown. A small advantage in favor of men compare to women’s health was found. Comparing the two periods, the proportion of years expected to be lived without activity limitation was higher in 1998 than in 2008 and for both sexes. There are still many uncertainties about how the country is actually ageing. Given this context, an effort to maintain constant health monitoring through different indicators such as GALI is essential. At the same time, strengthening local and regional policies, aiming to build solid paths and mechanisms to promote an active and healthy ageing of its population must be a target.

Mortality variability and differentials by age and causes of death in rural South Africa, 1994–2018

IntroductionUnderstanding mortality variability by age and cause is critical to identifying intervention and prevention actions to support disadvantaged populations. We assessed mortality changes in two rural South African populations over...

Abstract P351: The Associations of Short-Term, Chronic Localized and Chronic Widespread Pain With Life Expectancy Free of Major Chronic Diseases

Introduction: Pain is among the top underlying causes of years lived with disability. Hypothesis: Pain with higher chronicity and widespreadness is associated with shorter life expectancy free of major chronic diseases (cardiovascular disease, cancer, type 2 diabetes, and dementia), and longer lifespan lived with chronic diseases. Methods: The study included a total of 427,464 women and men from the UK Biobank study, free of major chronic diseases at baseline and with available information of pain (categorized as short-term pain, chronic localized pain, and chronic widespread pain), followed up until May 31, 2021. Population-based multistate life tables were used to calculate life expectancy with and without major chronic diseases. Results: Chronic localized pain was associated with significant but modest loss in healthy life expectancy and gain in lifespan lived with chronic diseases. Chronic widespread pain was associated with the largest loss in healthy life expectancy. Men and women with chronic widespread pain at age 50 years had 3.17 (95% confidence interval, 3.07 - 3.30) and 2.74 (2.66 - 2.83) shorter life expectancy free of major chronic diseases, 1.86 (1.73 - 1.97) and 1.84 (1.75 - 1.92) longer life expectancy with major chronic diseases as compared to individuals without pain ( Figure ). Chronic widespread pain was associated with ~15% and ~10% shorter life expectancy free of major chronic diseases in men and women at age 50 years, respectively, which increased to ~40% and ~30% after age 80 years. In terms of life expectancy in the presence of major chronic diseases, chronic widespread pain was constantly associated with ~25% and >30% longer life expectancy as compared to those without pain in men and women, respectively. Conclusions: Chronic pain, especially chronic widespread pain, was associated with larger loss in healthy life expectancy and more lifespan lived with chronic diseases. Our study suggests chronic pain as a potential intervention target to improve quality of life.

Effects of lifestyle-related risk factors on life expectancy: A comprehensive model for use in early prevention of premature mortality from noncommunicable diseases.

Morbidity and premature mortality from noncommunicable diseases can be largely prevented by adopting a healthy lifestyle at the earliest possible age. However, tools designed for the early identification of those at risk among young adults are lacking. We developed and validated a multivariable model for the prediction of life expectancy, allowing the early identification of apparently healthy adults at risk of lifestyle-related diseases. We used a cross-sectional approach to calculate life expectancy using data from 38,481 participants of the National Health and Nutrition Examination Survey (1999-2014), aged ≥20 years. A multivariable logistic model was used to quantify the impact of risk factors on mortality. The model included the following lifestyle-related mortality risk factors as predictors: smoking, diet, physical activity, and body mass index. The presence of the following chronic diseases was considered: diabetes, arrhythmia, coronary artery disease, myocardial infarction, stroke, and malignant neoplasms. The model showed a good predictive ability; the area under the receiver operating characteristic curve measure was 0.846 (95% uncertainty interval 0.838-0.859). Life expectancy was determined using the life table method and the period life tables for the US population as the baseline. The results of this model underscore the importance of lifestyle-related risk factors in life expectancy. The difference between life expectancy for 30-year-old individuals with lifestyle characteristics ranked in 90% and 10% of their gender and age groups was 23 years for males and 18 years for females, whereas in 75% and 25%, it was 14 years for males and 10 years for females. In addition to early risk identification, the model estimates the deferred effect of lifestyle and the impact of lifestyle changes on life expectancy. Thus, it can be used in early prevention to demonstrate the potential risks and benefits of complex lifestyle modifications for educational purposes or to motivate behavioral changes.

The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark

BackgroundDenmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014–2019).MethodsWe used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category.ResultsWe observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups.ConclusionsCOVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries.

СРАВНИТЕЛЬНЫЙ АНАЛИЗ ПОДХОДОВ К ОЦЕНКЕ ОЖИДАЕМОЙ ПРОДОЛЖИТЕЛЬНОСТИ ЗДОРОВОЙ ЖИЗНИ

Significance. Healthy life expectancy is a group of indicators that allows to estimate how long a person will live with “good” health given the current level of mortality and health of the population. The relevance of the calculation and assessment of healthy life expectancy is conditioned, among other things, by the Decree of the President of the Russian Federation dated 07.05.2024 N 309 “On the national development goals of the Russian Federation for the period until 2030 and prospects until 2036” - by 2030, it is planned to achieve “outpacing growth of healthy life expectancy indicators”, i.e. to reduce the difference between healthy life expectancy and life expectancy. The purpose of the study is to review the methods of calculating healthy life expectancy, sources of data on healthy life expectancy in Russia and the world, and a brief analysis of the dynamics in healthy life expectancy in Russia. Material and Methods. Literature sources and databases were studied to analyze the calculation methods and existing estimates of healthy life expectancy. Literature sources were searched in PubMed and eLibrary databases, and data - on the websites of the World Health Organization, Global Burden of Disease, Eurostat, “Unified Interdepartmental Information and Statistical System”. Results. One of the two main methods is usually chosen to estimate healthy life expectancy: the widely used Sullivan formula (cross-sectional analysis) and the less frequently used multistatus table method (longitudinal analysis). There are also various methods of defining “good” health: self-rated health or presence or absence of limitations or diseases. From 1990 to 2019, healthy life expectancy increased globally and in Russia; in Russia, there was a decline in healthy life expectancy during the Covid-19 pandemic, followed by a steady recovery afterwards. Conclusion. Healthy life expectancy in research and in public administration has not been as widely used as life expectancy, which is probably a consequence of the peculiarities of the methodology for calculating the indicator and its sensitivity not only to the objective parameter of mortality. However, being an integral indicator, healthy life expectancy can provide information on the “quality” of life expectancy growth.

Direct and indirect impact of COVID-19 on life expectancy at birth in Chile in 2020

This article shows the direct and indirect impacts of COVID-19 on life expectancy in Chile in 2020, based on mortality statistics published in March 2023. To this end, a counterfactual mortality was estimated for 2020 without COVID-19; based on the pattern of mortality by cause of death from 1997 to 2019, mortality charts were created to calculate life expectancy from 2015 to 2020 and an estimation for 2020, and the difference between expected and observed life expectancy in 2020 was then separated by age group and cause of death. Life expectancy in 2020 interrupted the upward trend from 2015 to 2019, showing a decline of 1.32 years in men and 0.75 years in women compared to 2019. Compared to the estimated 2020, life expectancy was 1.51 years lower in men and 0.92 years lower in women, but the direct impact of COVID-19 on the decrease in life expectancy was greater (1.89 for men and 1.5 for women) in the 60-84 age group in men and the 60-89 age group in women. The direct negative impact of COVID-19 on life expectancy was partially mitigated by significant positive indirect impacts on two groups of causes of death: diseases of the respiratory system and infectious and parasitic diseases. This study shows the need to differentiate direct and indirect impacts of COVID-19, due to the implications for public health when the intensity of COVID-19 decreases and mobility restrictions are suspended.

The English health inequalities strategy: A time-trend study of mortality rate disparities at 65

Abstract Background Rapid population ageing is common in many Global North countries, with the UK being a prime example (with 18.6% aged 65 and over in 2021). Despite this, life expectancy in the UK began to stall around 2011, and the gap between the least and most deprived has been widening. To address these inequalities, a ‘levelling up’ programme was announced by the current Conservative government. Previously, a national health inequalities strategy was implemented (2000 to 2010) by the then Labour government, with many of the interventions targeting older age groups. To provide evidence on the effects of national health inequalities strategies on life expectancy later in life, we assessed the impact of the English health inequalities strategy on inequalities in mortality rate at age 65 by area deprivation. Methods Using ecological mortality and population data for Middle Super Output and Local Authority areas, we calculated life expectancy for individuals aged 65 and over in England from 1991 to 2016. We applied time-trend analyses methods with marginal spline terms to evaluate how mortality rate trends at age 65 changed before, during and after the strategy period. We also conducted a series of robustness analyses to considering varying cut points, deprivation levels and geographical scales. Results Prior to the programme (1991-1998), there was no change in the absolute difference in mortality rate between the 20% most deprived areas and the rest. During the programme, inequalities decreased at a rate of -0.0000936 (95% CI -0.0001281to -0.0000592) each year. However, after the strategy period (2011-2016) inequalities widened at an annual rate of 0.000078 (95% CI 0.0000166 to 0.0001395). Conclusions This study provides evidence of an association between the national health inequalities strategy and a narrowing of inequalities in mortality rate at age 65. Future strategies to address inequalities in ageing populations may benefit from adopting a similar approach. Key messages • The national health inequalities strategy (2000 to 2010) was associated with a narrowing of inequalities in mortality rate at age 65. • Future national strategies which aim to reduce inequalities in life expectancy in older age groups may benefit from adopting a similar approach.

Flexible parametric methods for calculating life expectancy in small populations

BackgroundLife expectancy is a simple measure of assessing health differences between two or more populations but current life expectancy calculations are not reliable for small populations. A potential solution to this is to borrow strength from larger populations from the same source, but this has not formally been investigated.MethodsUsing data on 451,222 individuals from the Clinical Practice Research Datalink on the presence/absence of intellectual disability and type 2 diabetes mellitus, we compared stratified and combined flexible parametric models, and Chiang’s methods, for calculating life expectancy. Confidence intervals were calculated using the Delta method, Chiang’s adjusted life table approach and bootstrapping.ResultsThe flexible parametric models allowed calculation of life expectancy by exact age and beyond traditional life expectancy age thresholds. The combined model that fit age interaction effects as a spline term provided less bias and greater statistical precision for small covariate subgroups by borrowing strength from the larger subgroups. However, careful consideration of the distribution of events in the smallest group was needed.ConclusionsLife expectancy is a simple measure to compare health differences between populations. The use of combined flexible parametric methods to calculate life expectancy in small samples has shown promising results by allowing life expectancy to be modelled by exact age, greater statistical precision, less bias and prediction of different covariate patterns without stratification. We recommend further investigation of their application for both policymakers and researchers.

Widening rural–urban gap in life expectancy in China since COVID-19

IntroductionDisparities in life expectancy between rural and urban populations are well established but how it varies with epidemics and pandemics remains poorly understood. We aimed to quantify the rural–urban differences...

Life-expectancy changes during the COVID-19 pandemic from 2019-2021: estimates from Japan, a country with low pandemic impact.

The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan. We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020-2021 into age-specific and cause of death-specific contributions. We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019-21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components. From 2019-2020, Japan's national level life expectancy across the entire population was extended by 0.24 years. From 2020-2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020-2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020-2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life expectancy, whereas respiratory diseases did not. The decades-long increasing trend in life expectancy was suspended by the COVID-19 pandemic. However, life expectancy changes from 2019-2020 and 2020-2021 were small in Japan. This may be attributable to the small epidemiological impact of COVID-19 during this time period, but nonetheless, the negative impact of COVID-19 on life expectancy was indicated in the present study. The chance of death accelerated in older people in 2021, but a smaller number of deaths than usual among infants and working age adults contributed to extended life expectancy, and the change in the cause of death structure under the COVID-19 pandemic also significantly contributed to shortening life expectancy.

The impact of the COVID-19 pandemic on life expectancy by the level of area deprivation in South Korea.

Comparative evidence suggests that the impact of COVID-19 on life expectancy has been relatively milder in South Korea. This study aims to examine whether the pandemic has universal or unequal impacts on life expectancy across 250 districts with varying levels of deprivation. Using mortality data from 2012 to 2021 obtained from the Microdata Integrated Service of Statistics Korea, we calculated life expectancy at birth and age 65 for both sexes, by deprivation quintiles, before and during the pandemic. We summarized life expectancy gaps using the slope of the inequality index (SII) and further decomposed the gaps by the contribution of age and cause of death using Arriaga's method. Both men and women experienced consistent improvements in life expectancy from 2012 to 2019, but the trend was disrupted during 2020 and 2021, primarily driven by older people. While men in more deprived areas were initially hit harder by the pandemic, the life expectancy gap across deprivation quintiles remained relatively constant and persistent across the study period [SII: -2.48 (CI: -2.70 from -2.27) for 2019 and - 2.84 (CI: -3.06 from -2.63) for 2020]. Middle-aged men from the most deprived areas were the most significant contributors to the life expectancy gap, with liver disease, liver cancer, transport accidents, and intentional injuries being the leading causes, both in the pre and during the pandemic. While these contributors remained largely similar before and during the pandemic, the contribution of transport accidents and liver cancer to the male life expectancy gap slightly decreased during the pandemic, while that of ischemic heart disease and pneumonia slightly increased. A similar increase was also observed for the female life expectancy gap. This study found no clear evidence of an increased life expectancy gap during the pandemic in South Korea, unlike in other countries, although access to emergency healthcare services may have been slightly more disturbed in deprived areas. This achievement can provide lessons for other countries. However, the persistent regional gaps in life expectancy observed over the past decade indicate the need for more targeted public health policies to address this issue.

Age structure and growth features of the Tajikistan toadhead agama Phrynocephalus sogdianus (Reptilia, Agamidae)

The paper presents the results of age and growth studying of the Tajikistan toadhead agama Phrynocephalus sogdianus by skeletochronology. A total of 29 adult individuals (14 females and 15 males) from the vicinity of Uchkyzil (Termez district, Surkhandarya region, Uzbekistan) were studied. All animals, on the section of tubular bones had a birth (hatching) line appearing shortly after the lizards hatching. The majority of the sample consisted of one-year-old and two-year-old specimens (89.7%). The age of females and males varied between 1–3 years, averaging 1.53 and 1.71 years, respectively. The expected calculated life expectancy for females after one wintering was 2.25 years, for males 2.06 years. Females and males did not differ in body length. The length of the males’ body depended on their age. Males aged one and two years statistically significantly differed in size among themselves. The authors note that P. sogdianus has very high growth rates (growth coefficient k is 2.84 in females and 1.40 in males), exceeding that of other toadhead agamas.

Changes in contributions of age- and cause-specific mortality to the widening life expectancy gap between North and South Korea, 1990–2019: An analysis of the Global Burden of Disease Study 2019

BackgroundLife expectancy gaps between North and South Korea have increased but contributions to these gaps remain poorly understood. Using data from the Global Burden of Disease Study (GBD) 2019, we examined how much death from specific diseases contributed to these gaps in different age groups over three decades. MethodsData for death numbers and population by sex and 5-year age groups in both North and South Korea from 1990 to 2019 were extracted from the GBD 2019 to calculate life expectancy. Joinpoint regression analysis was conducted to investigate changes in life expectancy in North and South Korea. We used decomposition analysis to partition differences in life expectancy within and between the two Koreas into changes in age- and cause-specific death contributions. ResultsLife expectancy increased in two Koreas from 1990 to 2019, but North Korea experienced a marked decline in life expectancy during the mid-1990s. The life expectancy gaps between the two Koreas were greatest in 1999, with a difference of 13.3 years for males and 14.9 years for females. The main contributors to these gaps were higher under-5 mortality from nutritional deficiencies for males (4.62 years) and females (4.57 years) in North Korea, accounting for about 30% of the total gap in life expectancy. After 1999, the life expectancy gaps reduced but persisted with differences of about ten years by 2019. Notably, chronic diseases contributed to about 8 out of 10 years of life expectancy gap between the two Koreas in 2019. Differential cardiovascular disease mortality in the older groups was the main contributor to the life expectancy gap. ConclusionsThe contributors to this gap have shifted from nutritional deficiencies in children younger than five years to cardiovascular disease among elderly people. Efforts for strengthening social and healthcare systems are needed to curb this large gap.

A Geriatrician’s Perspective on an Aging Joe Biden

A Geriatrician’s Perspective on an Aging Joe Biden

Predicting All-Cause Mortality in Women With and Without Breast Cancer Using the Schonberg Index: A Women's Health Initiative Study.

When treating older women with breast cancer, life expectancy is an important consideration. ASCO recommends calculating 10-year mortality probabilities to inform treatment decisions. One useful tool is the Schonberg index, which predicts risk-based all-cause 10-year mortality. We investigated the use of this index in women aged ≥65 years with breast cancer in the Women's Health Initiative (WHI). We calculated 10-year mortality risk scores for 2,549 WHI participants with breast cancer ("cases") and 2,549 age-matched breast cancer-free participants ("controls") using Schonberg index risk scoring. Risk scores were grouped into quintiles for comparisons. Risk-stratified observed mortality rates and 95% confidence intervals were compared across cases and controls. Observed 10-year mortality rates in cases and controls were also compared with Schonberg index-based predicted 10-year mortality rates. Compared with controls, cases were more often white (P=.005), had higher income and education levels (P<.001 for both), more often lived with their husband/partner (P<.001), scored higher on subjective health/happiness (P<.001), and needed less assistance in activities of daily living (P<.001). Participants with breast cancer had similar risk-stratified 10-year mortality rates compared with controls (34% vs 33%, respectively). Stratified results showed that cases had slightly higher mortality rates than controls in the lowest risk quintile and lower mortality rates in the 2 highest risk quintiles. Observed mortality rates in cases and controls were similar to Schonberg index-predicted mortality, with model c-indexes of 0.71 and 0.76, respectively. Among women aged ≥65 years with incident breast cancer, the Schonberg index-based risk-stratified 10-year mortality rates were similar to those in women without breast cancer, demonstrating a similar performance of the index among both populations. Along with other health measures, prognostic indexes can help predict survival among older women with breast cancer and support geriatric oncology guidelines that promote using life expectancy calculation tools for shared decision-making.

MP59-18 THE INCIDENCE OF CLINICALLY SIGNIFICANT PROSTATE CANCER AFTER HoLEP

You have accessJournal of UrologyCME1 Apr 2023MP59-18 THE INCIDENCE OF CLINICALLY SIGNIFICANT PROSTATE CANCER AFTER HoLEP Ali S Antar, Tudor Borza, Ethan Richmond, Glenn O Allen, Jordan R Krieger, Margaret A Knoedler, Christopher M Manakas, Wei Huang, Dan R Gralnek, and Matthew D Grimes Ali S AntarAli S Antar More articles by this author , Tudor BorzaTudor Borza More articles by this author , Ethan RichmondEthan Richmond More articles by this author , Glenn O AllenGlenn O Allen More articles by this author , Jordan R KriegerJordan R Krieger More articles by this author , Margaret A KnoedlerMargaret A Knoedler More articles by this author , Christopher M ManakasChristopher M Manakas More articles by this author , Wei HuangWei Huang More articles by this author , Dan R GralnekDan R Gralnek More articles by this author , and Matthew D GrimesMatthew D Grimes More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003312.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Rates of incidental prostate cancer (iPCa) after Holmium Laser Enucleation of the Prostate (HoLEP) are higher than in other bladder outlet surgeries. Management presents a challenge considering the effects of HoLEP on anatomy and other causes of mortality in the older population. We examined cancer characteristics and initial management of patients with iPCa after HoLEP to understand the significance of these incidentally discovered cancers. METHODS: Patients with iPCa were identified over a 4 year period from a prospectively maintained institutional database. Clinical data collected included preoperative PSA levels, cancer stage, grade, initial management, post operative PSA, staging imaging or biopsy. We defined clinically significant cancers as those where treatment other than watchful waiting was recommended by NCCN guidelines based on predicted life expectancy, which was estimated using the Social Security Life Expectancy Calculator. RESULTS: 183/913 (20%) patients were diagnosed iPCa after HoLEP. 133 patients (73%) had clinically significant and 50 patients (27%) had clinically insignificant iPCa. Of clinically significant cancers, 7 patients with high risk PCa were managed with upfront local treatment and the rest underwent PSA surveillance (Figure 1). 11 experienced a PSA increase and underwent local treatment after confirmatory biopsy: 3 underwent RALP, 7 underwent XRT and one underwent ADT, all with appropriate PSA response to treatment. The clinically insignificant population underwent PSA observation. 9 were lost to follow up and 5 experienced a PSA increase triggering intervention: 4 underwent XRT and 1 underwent ADT with appropriate PSA response. At a mean follow-up of 16.3 months (IQR 7.9–13.4 months), there were 6 deaths, all from non-cancer related causes. CONCLUSIONS: Despite the low risk nature of many post-HoLEP iPCA, the majority were classified as clinically significant cancers based on NCCN guidelines. Data driven guidelines for pre-operative screening evaluation and post-operative management of iPCa after HoLEP are critical given the frequency and clinical implications these cancer diagnoses. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e815 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ali S Antar More articles by this author Tudor Borza More articles by this author Ethan Richmond More articles by this author Glenn O Allen More articles by this author Jordan R Krieger More articles by this author Margaret A Knoedler More articles by this author Christopher M Manakas More articles by this author Wei Huang More articles by this author Dan R Gralnek More articles by this author Matthew D Grimes More articles by this author Expand All Advertisement PDF downloadLoading ...