Colon tumour cell death causes mTOR dependence by paracrine P2X4 stimulation.

Solid cancers exhibit a dynamic balance between cell death and proliferation ensuring continuous tumour maintenance and growth1,2. Increasing evidence links enhanced cancer cell apoptosis to paracrine activation of cells in the tumour microenvironment initiating tissue repair programs that support tumour growth3,4, yet the direct effects of dying cancer cells on neighbouring tumour epithelia and how this paracrine effect potentially contributes to therapy resistance are unclear. Here we demonstrate that chemotherapy-induced tumour cell death in patient-derived colorectal tumour organoids causes ATP release triggering P2X4 (also known as P2RX4) to mediate an mTOR-dependent pro-survival program in neighbouring cancer cells, which renders surviving tumour epithelia sensitive to mTOR inhibition. The induced mTOR addiction in persisting epithelial cells is due to elevated production of reactive oxygen species and subsequent increased DNA damage in response to the death of neighbouring cells. Accordingly, inhibition of the P2X4 receptor or direct mTOR blockade prevents induction of S6 phosphorylation and synergizes with chemotherapy to cause massive cell death induced by reactive oxygen species and marked tumour regression that is not seen when individually applied. Conversely, scavenging of reactive oxygen species prevents cancer cells from becoming reliant on mTOR activation. Collectively, our findings show that dying cancer cells establish a new dependency on anti-apoptotic programs in their surviving neighbours, thereby creating an opportunity for combination therapy in P2X4-expressing epithelial tumours.

Mailed fecal immunochemical test outreach for colorectal cancer screening: Summary of a Centers for Disease Control and Prevention-sponsored Summit.

Uptake of colorectal cancer screening remains suboptimal. Mailed fecal immunochemical testing (FIT) offers promise for increasing screening rates, but optimal strategies for implementation have not been well synthesized. In June 2019, the Centers for Disease Control and Prevention convened a meeting of subject matter experts and stakeholders to answer key questions regarding mailed FIT implementation in the United States. Points of agreement included: 1) primers, such as texts, telephone calls, and printed mailings before mailed FIT, appear to contribute to effectiveness; 2) invitation letters should be brief and easy to read, and the signatory should be tailored based on setting; 3) instructions for FIT completion should be simple and address challenges that may lead to failed laboratory processing, such as notation of collection date; 4) reminders delivered to initial noncompleters should be used to increase the FIT return rate; 5) data infrastructure should identify eligible patients and track each step in the outreach process, from primer delivery through abnormal FIT follow-up; 6) protocols and procedures such as navigation should be in place to promote colonoscopy after abnormal FIT; 7) a high-quality, 1-sample FIT should be used; 8) sustainability requires a program champion and organizational support for the work, including sufficient funding and external policies (such as quality reporting requirements) to drive commitment to program investment; and 9) the cost effectiveness of mailed FIT has been established. Participants concluded that mailed FIT is an effective and efficient strategy with great potential for increasing colorectal cancer screening in diverse health care settings if more widely implemented.

Excess natural-cause mortality in US counties and its association with reported COVID-19 deaths.

In the United States, estimates of excess deaths attributable to the COVID-19 pandemic have consistently surpassed reported COVID-19 death counts. Excess deaths reported to non-COVID-19 natural causes may represent unrecognized COVID-19 deaths, deaths caused by pandemic health care interruptions, and/or deaths from the pandemic's socioeconomic impacts. The geographic and temporal distribution of these deaths may help to evaluate which explanation is most plausible. We developed a Bayesian hierarchical model to produce monthly estimates of excess natural-cause mortality for US counties over the first 30 mo of the pandemic. From March 2020 through August 2022, 1,194,610 excess natural-cause deaths occurred nationally [90% PI (Posterior Interval): 1,046,000 to 1,340,204]. A total of 162,886 of these excess natural-cause deaths (90% PI: 14,276 to 308,480) were not reported to COVID-19. Overall, 15.8 excess deaths were reported to non-COVID-19 natural causes for every 100 reported COVID-19 deaths. This number was greater in nonmetropolitan counties (36.0 deaths), the West (Rocky Mountain states: 31.6 deaths; Pacific states: 25.5 deaths), and the South (East South Central states: 26.0 deaths; South Atlantic states: 25.0 deaths; West South Central states: 24.2 deaths). In contrast, reported COVID-19 death counts surpassed estimates of excess natural-cause deaths in metropolitan counties in the New England and Middle Atlantic states. Increases in reported COVID-19 deaths correlated temporally with increases in excess deaths reported to non-COVID-19 natural causes in the same and/or prior month. This suggests that many excess deaths reported to non-COVID-19 natural causes during the first 30 mo of the pandemic in the United States were unrecognized COVID-19 deaths.

Infant Mortality in the United States, 2022: Data From the Period Linked Birth/Infant Death File.

Objectives: This report presents final 2022 infant mortality statistics by age at death, maternal race and Hispanic origin, maternal age, gestational age, leading causes of death, and maternal state of residence. Trends in infant mortality are also examined. Methods: Descriptive tabulations of data are presented and interpreted for infant deaths and infant mortality rates using the 2022 period linked birth/infant death file. The linked birth/infant death file is based on birth and death certificates registered in all 50 states and the District of Columbia. Results: A total of 20,577 infant deaths were reported in the United States in 2022, up 3% from 2021. The U.S. infant mortality rate was 5.61 infant deaths per 1,000 live births, a 3% increase from the rate of 5.44 in 2021. The neonatal mortality rate increased 3% from 3.49 in 2021 to 3.59 in 2022, and the postneonatal mortality rate increased 4% from 1.95 to 2.02. The overall infant mortality rate increased for infants of American Indian and Alaska Native non-Hispanic, White non-Hispanic, and Dominican women in 2022 compared with 2021; changes in rates for the other race and Hispanic-origin groups were not significant. Infants of Black non-Hispanic women had the highest mortality rate (10.90) in 2022, followed by infants of American Indian and Alaska Native non-Hispanic and Native Hawaiian or Other Pacific Islander non-Hispanic (9.06 and 8.50, respectively), Hispanic (4.89), White non-Hispanic (4.52), and Asian non-Hispanic (3.51) women. Mortality rates increased from 2021 to 2022 among preterm (less than 37 weeks of gestation) infants (33.59 to 34.78) and for infants born term (37 to 41 weeks of gestation) (2.08 to 2.18). The five leading causes of infant death in 2022 were the same as in 2021. Infant mortality rates by state for 2022 ranged from a low of 3.32 in Massachusetts to a high of 9.11 in Mississippi.

Fetal Mortality: United States, 2022.

Objectives: This report presents 2022 fetal mortality data by maternal race and Hispanic origin, age, tobacco use during pregnancy, and state of residence, as well as by plurality, sex, gestational age, birthweight, and selected causes of death. Trends in fetal mortality are also examined. Methods: Descriptive tabulations of data are presented and interpreted for all fetal deaths reported for the United States for 2022 with a stated or presumed period of gestation of 20 weeks or more. Cause-of-fetal-death data only are restricted to residents of the 43 states and District of Columbia where cause of death was based on the 2003 fetal death report revision and less than 50% of deaths were attributed to Fetal death of unspecified cause (P95). Results: A total of 20,202 fetal deaths at 20 weeks of gestation or more were reported in the United States in 2022. The 2022 U.S. fetal mortality rate was 5.48 fetal deaths at 20 weeks of gestation or more per 1,000 live births and fetal deaths, 4% lower than in 2021 (5.73) and a new historic low for the United States. The fetal mortality rate in 2022 for deaths occurring at 20-27 weeks of gestation was 2.79, a 5% decline from 2021 (2.95). For deaths occurring at 28 weeks of gestation or more, the rate in 2022 was 2.71, a 3% decline from 2021 (2.80). In 2022, the fetal mortality rate was highest for Native Hawaiian or Other Pacific Islander non-Hispanic (10.36) and Black non-Hispanic (10.05) females and lowest for Asian non-Hispanic females (3.70). Fetal mortality rates were highest for women ages 40 and older, for women who smoked during pregnancy, and for women with multiple gestation pregnancies. Five selected causes accounted for 90.0% of fetal deaths in the 43-state and District of Columbia reporting area.

The "double jeopardy" of midlife and old age mortality trends in the United States.

Since 2010, US life expectancy growth has stagnated. Much research on US mortality has focused on working-age adults given adverse trends in drug overdose deaths, other external causes of death, and cardiometabolic deaths in midlife. We show that the adverse mortality trend at retirement ages (65+ y) has in fact been more consequential to the US life expectancy stagnation since 2010, as well as excess deaths and years of life lost in 2019, than adverse mortality trends at working ages. These results reveal that the United States is experiencing a "double jeopardy" that is driven by both mid-life and older-age mortality trends, but more so by older-age mortality. Understanding and addressing the causes behind the worsening mortality trend in older ages will be essential to returning to the pace of life expectancy improvements that the United States had experienced for decades.

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021.

BACKGROUND: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING: Bill & Melinda Gates Foundation.

Rates and causes of death after release from incarceration among 1 471 526 people in eight high-income and middle-income countries: an individual participant data meta-analysis.

BACKGROUND: Formerly incarcerated people have exceptionally poor health profiles and are at increased risk of preventable mortality when compared with their general population peers. However, not enough is known about the epidemiology of mortality in this population-specifically the rates, causes, and timing of death in specific subgroups and regions-to inform the development of targeted, evidence-based responses. We aimed to document the incidence, timing, causes, and risk factors for mortality after release from incarceration. METHODS: We analysed linked administrative data from the multi-national Mortality After Release from Incarceration Consortium (MARIC) study. We examined mortality outcomes for 1 471 526 people released from incarceration in eight countries (Australia, Brazil, Canada, New Zealand, Norway, Scotland, Sweden, and the USA) from 1980 to 2018, across 10 534 441 person-years of follow-up (range 0-24 years per person). We combined data from 18 cohort studies using two-step individual participant data meta-analyses to estimate pooled all-cause and cause-specific crude mortality rates (CMRs) per 100 000 person-years, for specific time periods (first, daily from days 1-14; second, weekly from weeks 3-12; third, weeks 13-52 combined; fourth, weeks 53 and over combined; and fifth, total follow-up) after release, overall and stratified by age, sex, and region. FINDINGS: 75 427 deaths were recorded. The all-cause CMR during the first week following release (1612 [95% CI 1048-2287]) was higher than during all other time periods (incidence rate ratio [IRR] compared with week 2: 1·5 [95% CI 1·2-1·8], I2=26·0%, weeks 3-4: 2·0 [1·5-2·6], I2=53·0%, and weeks 9-12: 2·2 [1·6-3·0], I2=70·5%). The highest cause-specific mortality rates during the first week were due to alcohol and other drug poisoning (CMR 657 [95% CI 332-1076]), suicide (135 [36-277]), and cardiovascular disease (71 [16-153]). We observed considerable variation in cause-specific CMRs over time since release and across regions. Pooled all-cause CMRs were similar between males (731 [95% CI 630-839]) and females (660 [560-767]) and were higher in older age groups. INTERPRETATION: The markedly elevated rate of death in the first week post-release underscores an urgent need for investment in evidence-based, coordinated transitional healthcare, including treatment for mental illness and substance use disorders to prevent post-release deaths due to suicide and overdose. Temporal variations in rates and causes of death highlight the need for routine monitoring of post-release mortality. FUNDING: Australia's National Health and Medical Research Council.

Incidence and Prediction of Unrelated Mortality After Successful Endoscopic Eradication Therapy for Barrett's Neoplasia.

BACKGROUND & AIMS: Follow-up (FU) strategies after endoscopic eradication therapy (EET) for Barrett's neoplasia do not consider the risk of mortality from causes other than esophageal adenocarcinoma (EAC). We aimed to evaluate this risk during long-term FU, and to assess whether the Charlson Comorbidity Index (CCI) can predict mortality. METHODS: We included all patients with successful EET from the nationwide Barrett registry in the Netherlands. Data were merged with National Statistics for accurate mortality data. We evaluated annual mortality rates (AMRs, per 1000 person-years) and standardized mortality ratio for other-cause mortality. Performance of the CCI was evaluated by discrimination and calibration. RESULTS: We included 1154 patients with a mean age of 64 years (±9). During median 59 months (p25-p75 37-91; total 6375 person-years), 154 patients (13%) died from other causes than EAC (AMR, 24.1; 95% CI, 20.5-28.2), most commonly non-EAC cancers (n = 58), cardiovascular (n = 31), or pulmonary diseases (n = 26). Four patients died from recurrent EAC (AMR, 0.5; 95% CI, 0.1-1.4). Compared with the general Dutch population, mortality was significantly increased for patients in the lowest 3 age quartiles (ie, age <71 years). Validation of CCI in our population showed good discrimination (Concordance statistic, 0.78; 95% CI, 0.72-0.84) and fair calibration. CONCLUSION: The other-cause mortality risk after successful EET was more than 40 times higher (48; 95% CI, 15-99) than the risk of EAC-related mortality. Our findings reveal that younger post-EET patients exhibit a significantly reduced life expectancy when compared with the general population. Furthermore, they emphasize the strong predictive ability of CCI for long-term mortality after EET. This straightforward scoring system can inform decisions regarding personalized FU, including appropriate cessation timing. (NL7039).

Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy.

Determining causes of deaths (CODs) occurred outside of civil registration and vital statistics systems is challenging. A technique called verbal autopsy (VA) is widely adopted to gather information on deaths in practice. A VA consists of interviewing relatives of a deceased person about symptoms of the deceased in the period leading to the death, often resulting in multivariate binary responses. While statistical methods have been devised for estimating the cause-specific mortality fractions (CSMFs) for a study population, continued expansion of VA to new populations (or "domains") necessitates approaches that recognize between-domain differences while capitalizing on potential similarities. In this article, we propose such a domain-adaptive method that integrates external between-domain similarity information encoded by a prespecified rooted weighted tree. Given a cause, we use latent class models to characterize the conditional distributions of the responses that may vary by domain. We specify a logistic stick-breaking Gaussian diffusion process prior along the tree for class mixing weights with node-specific spike-and-slab priors to pool information between the domains in a data-driven way. The posterior inference is conducted via a scalable variational Bayes algorithm. Simulation studies show that the domain adaptation enabled by the proposed method improves CSMF estimation and individual COD assignment. We also illustrate and evaluate the method using a validation dataset. The article concludes with a discussion of limitations and future directions.

Autopsies in the United States in 2020.

Objectives-This report presents information on autopsy data by age, cause, place of death, and year.

Deaths: Leading Causes for 2020.

Objectives-This report presents final 2020 data on the 10 leading causes of death in the United States by age, race and Hispanic origin, and sex. Leading causes of infant, neonatal, and postneonatal death are also presented. This report supplements "Deaths: Final Data for 2020," the National Center for Health Statistics' annual report of final mortality statistics. Methods-Data in this report are based on information from all death certificates filed in the 50 states and the District of Columbia in 2020. Causes of death classified by the International Classification of Diseases, 10th Revision (ICD-10) are ranked according to the number of deaths. Cause-of-death statistics are based on the underlying cause of death. Race and Hispanicorigin data are based on the Office of Management and Budget's 1997 standards for reporting race and Hispanic origin. Results-In 2020, many of the 10 leading causes of death changed rank order due to the emergence of COVID-19 as a leading cause of death in the United States. The 10 leading causes of death in 2020 were, in rank order: Diseases of heart; Malignant neoplasms; COVID-19; Accidents (unintentional injuries); Cerebrovascular diseases; Chronic lower respiratory diseases; Alzheimer disease; Diabetes mellitus; Influenza and pneumonia; and Nephritis, nephrotic syndrome and nephrosis. They accounted for 74.1% of all deaths occurring in the United States. Differences in the rankings are evident by age, race and Hispanic origin, and sex. Leading causes of infant death for 2020 were, in rank order: Congenital malformations, deformations and chromosomal abnormalities; Disorders related to short gestation and low birth weight, not elsewhere classified; Sudden infant death syndrome; Accidents (unintentional injuries); Newborn affected by maternal complications of pregnancy; Newborn affected by complications of placenta, cord and membranes; Bacterial sepsis of newborn; Respiratory distress of newborn; Diseases of the circulatory system; and Neonatal hemorrhage.

Deaths: Final Data for 2020.

Objective-This report presents final 2020 data on U.S. deaths, death rates, life expectancy, infant and maternal mortality, and trends by selected characteristics such as age, sex, Hispanic origin and race, state of residence, and cause of death. Methods-Information reported on death certificates is presented in descriptive tabulations. The original records are filed in state registration offices. Statistical information is compiled in a national database through the Vital Statistics Cooperative Program of the National Center for Health Statistics. Causes of death are processed according to the International Classification of Diseases, 10th Revision. Beginning in 2018, all states and the District of Columbia were using the 2003 revised certificate of death for the entire year, which includes the 1997 Office of Management and Budget revised standards for race. Data based on these revised standards are not completely comparable to previous years. Results-In 2020, a total of 3,383,729 deaths were reported in the United States. The age-adjusted death rate was 835.4 deaths per 100,000 U.S. standard population, an increase of 16.8% from the 2019 rate. Life expectancy at birth was 77.0 years, a decrease of 1.8 years from 2019. Age-specific death rates increased from 2019 to 2020 for age groups 15 years and over and decreased for age group under 1 year. Many of the 15 leading causes of death in 2020 changed from 2019. COVID-19, a new cause of death in 2020, became the third leading cause in 2020. The infant mortality rate decreased 2.9% to a historic low of 5.42 infant deaths per 1,000 live births in 2020. Conclusions-In 2020, the age-adjusted death rate increased and life expectancy at birth decreased for the total, male, and female populations, primarily due to the influence of deaths from COVID-19.

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.

This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.

Genetically Predicted Body Mass Index and Mortality in Chronic Obstructive Pulmonary Disease.

Rationale: Body mass index (BMI) is associated with chronic obstructive pulmonary disease (COPD) mortality, but the underlying mechanisms are unclear. The effect of genetic variants aggregated into a polygenic score may elucidate the causal mechanisms and predict risk. Objectives: To examine the associations of genetically predicted BMI with all-cause and cause-specific mortality in COPD. Methods: We developed a polygenic score (PGS) for BMI (PGSBMI) and tested for associations of the PGSBMI with all-cause, respiratory, and cardiovascular mortality in participants with COPD from the COPDGene (Genetic Epidemiology of COPD), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), and Framingham Heart studies. We calculated the difference between measured BMI and PGS-predicted BMI (BMIdiff) and categorized participants into groups of discordantly low (BMIdiff <20th percentile), concordant (BMIdiff between the 20th and 80th percentiles), and discordantly high (BMIdiff >80th percentile) BMI. We applied Cox models, examined potential nonlinear associations of the PGSBMI and BMIdiff with mortality, and summarized results with meta-analysis. Measurements and Main Results: We observed significant nonlinear associations of measured BMI and BMIdiff, but not PGSBMI, with all-cause mortality. In meta-analyses, a one-standard deviation increase in the PGSBMI was associated with an increased hazard for cardiovascular mortality (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.12-1.49), but not for respiratory or all-cause mortality. Compared with participants with concordant measured and genetically predicted BMI, those with discordantly low BMI had higher risks for all-cause mortality (HR, 1.57; 95% CI, 1.41-1.74) and respiratory death (HR, 2.01; 95% CI, 1.61-2.51). Conclusions: In people with COPD, a higher genetically predicted BMI is associated with higher cardiovascular mortality but not respiratory mortality. Individuals with a discordantly low BMI have higher all-cause and respiratory mortality rates than those with a concordant BMI.

In MI with preserved LVEF, long-term ß-blocker use vs. no use did not reduce all-cause death or MI at 3.5 y.

SOURCE CITATION: Yndigegn T, Lindahl B, Mars K, et al; REDUCE-AMI Investigators. Beta-blockers after myocardial infarction and preserved ejection fraction. N Engl J Med. 2024;390:1372-1381. 38587241.

In adults with AMI who are at risk for HF, empagliflozin did not reduce a composite of first HF hospitalization or all-cause death at 18 mo.

SOURCE CITATION: Butler J, Jones WS, Udell JA, et al. Empagliflozin after acute myocardial infarction. N Engl J Med. 2024;390:1455-1466. 38587237.

Benefits and Risks Associated With Statin Therapy for Primary Prevention in Old and Very Old Adults : Real-World Evidence From a Target Trial Emulation Study.

BACKGROUND: There is little consensus on using statins for primary prevention of cardiovascular diseases (CVDs) and all-cause mortality in adults aged 75 years or older due to the underrepresentation of this population in randomized controlled trials. OBJECTIVE: To investigate the benefits and risks of using statins for primary prevention in old (aged 75 to 84 years) and very old (aged ≥85 years) adults. DESIGN: Sequential target trial emulation comparing matched cohorts initiating versus not initiating statin therapy. SETTING: Territory-wide public electronic medical records in Hong Kong. PARTICIPANTS: Persons aged 75 years or older who met indications for statin initiation from January 2008 to December 2015 were included. Participants with preexisting diagnosed CVDs at baseline, such as coronary heart disease (CHD), were excluded from the analysis. Among 69 981 eligible persons aged 75 to 84 years and 14 555 persons aged 85 years or older, 41 884 and 9457 had history of CHD equivalents (for example, diabetes) in the respective age groups. INTERVENTION: Initiation of statin therapy. MEASUREMENTS: Incidence of major CVDs (stroke, myocardial infarction, or heart failure), all-cause mortality, and major adverse events (myopathies and liver dysfunction). RESULTS: Of 42 680 matched person-trials aged 75 to 84 years and 5390 matched person-trials aged 85 years or older (average follow-up, 5.3 years), 9676 and 1600 of them developed CVDs in each age group, respectively. Risk reduction for overall CVD incidence was found for initiating statin therapy in adults aged 75 to 84 years (5-year standardized risk reduction, 1.20% [95% CI, 0.57% to 1.82%] in the intention-to-treat [ITT] analysis; 5.00% [CI, 1.11% to 8.89%] in the per protocol [PP] analysis) and in those aged 85 years or older (ITT: 4.44% [CI, 1.40% to 7.48%]; PP: 12.50% [CI, 4.33% to 20.66%]). No significantly increased risks for myopathies and liver dysfunction were found in both age groups. LIMITATION: Unmeasured confounders, such as lifestyle factors of diet and physical activity, may exist. CONCLUSION: Reduction for CVDs after statin therapy were seen in patients aged 75 years or older without increasing risks for severe adverse effects. Of note, the benefits and safety of statin therapy were consistently found in adults aged 85 years or older. PRIMARY FUNDING SOURCE: Health Bureau, the Government of Hong Kong Special Administrative Region, China, and National Natural Science Foundation of China.

Associations of Testosterone and Related Hormones With All-Cause and Cardiovascular Mortality and Incident Cardiovascular Disease in Men : Individual Participant Data Meta-analyses.

BACKGROUND: Whether circulating sex hormones modulate mortality and cardiovascular disease (CVD) risk in aging men is controversial. PURPOSE: To clarify associations of sex hormones with these outcomes. DATA SOURCES: Systematic literature review to July 2019, with bridge searches to March 2024. STUDY SELECTION: Prospective cohort studies of community-dwelling men with sex steroids measured using mass spectrometry and at least 5 years of follow-up. DATA EXTRACTION: Independent variables were testosterone, sex hormone-binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone (DHT), and estradiol concentrations. Primary outcomes were all-cause mortality, CVD death, and incident CVD events. Covariates included age, body mass index, marital status, alcohol consumption, smoking, physical activity, hypertension, diabetes, creatinine concentration, ratio of total to high-density lipoprotein cholesterol, and lipid medication use. DATA SYNTHESIS: Nine studies provided individual participant data (IPD) (255 830 participant-years). Eleven studies provided summary estimates (n = 24 109). Two-stage random-effects IPD meta-analyses found that men with baseline testosterone concentrations below 7.4 nmol/L (<213 ng/dL), LH concentrations above 10 IU/L, or estradiol concentrations below 5.1 pmol/L had higher all-cause mortality, and those with testosterone concentrations below 5.3 nmol/L (<153 ng/dL) had higher CVD mortality risk. Lower SHBG concentration was associated with lower all-cause mortality (median for quintile 1 [Q1] vs. Q5, 20.6 vs. 68.3 nmol/L; adjusted hazard ratio [HR], 0.85 [95% CI, 0.77 to 0.95]) and lower CVD mortality (adjusted HR, 0.81 [CI, 0.65 to 1.00]). Men with lower baseline DHT concentrations had higher risk for all-cause mortality (median for Q1 vs. Q5, 0.69 vs. 2.45 nmol/L; adjusted HR, 1.19 [CI, 1.08 to 1.30]) and CVD mortality (adjusted HR, 1.29 [CI, 1.03 to 1.61]), and risk also increased with DHT concentrations above 2.45 nmol/L. Men with DHT concentrations below 0.59 nmol/L had increased risk for incident CVD events. LIMITATIONS: Observational study design, heterogeneity among studies, and imputation of missing data. CONCLUSION: Men with low testosterone, high LH, or very low estradiol concentrations had increased all-cause mortality. SHBG concentration was positively associated and DHT concentration was nonlinearly associated with all-cause and CVD mortality. PRIMARY FUNDING SOURCE: Medical Research Future Fund, Government of Western Australia, and Lawley Pharmaceuticals. (PROSPERO: CRD42019139668).

Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study.

BACKGROUND AND AIMS: Emerging evidence has raised an obesity paradox in observational studies of body mass index (BMI) and health among the oldest-old (aged ≥80 years), as an inverse relationship of BMI with mortality was reported. This study was to investigate the causal associations of BMI, waist circumference (WC), or both with mortality in the oldest-old people in China. METHODS: A total of 5306 community-based oldest-old (mean age 90.6 years) were enrolled in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) between 1998 and 2018. Genetic risk scores were constructed from 58 single-nucleotide polymorphisms (SNPs) associated with BMI and 49 SNPs associated with WC to subsequently derive causal estimates for Mendelian randomization (MR) models. One-sample linear MR along with non-linear MR analyses were performed to explore the associations of genetically predicted BMI, WC, and their joint effect with all-cause mortality, cardiovascular disease (CVD) mortality, and non-CVD mortality. RESULTS: During 24 337 person-years of follow-up, 3766 deaths were documented. In observational analyses, higher BMI and WC were both associated with decreased mortality risk [hazard ratio (HR) 0.963, 95% confidence interval (CI) 0.955-0.971 for a 1-kg/m2 increment of BMI and HR 0.971 (95% CI 0.950-0.993) for each 5 cm increase of WC]. Linear MR models indicated that each 1 kg/m2 increase in genetically predicted BMI was monotonically associated with a 4.5% decrease in all-cause mortality risk [HR 0.955 (95% CI 0.928-0.983)]. Non-linear curves showed the lowest mortality risk at the BMI of around 28.0 kg/m2, suggesting that optimal BMI for the oldest-old may be around overweight or mild obesity. Positive monotonic causal associations were observed between WC and all-cause mortality [HR 1.108 (95% CI 1.036-1.185) per 5 cm increase], CVD mortality [HR 1.193 (95% CI 1.064-1.337)], and non-CVD mortality [HR 1.110 (95% CI 1.016-1.212)]. The joint effect analyses indicated that the lowest risk was observed among those with higher BMI and lower WC. CONCLUSIONS: Among the oldest-old, opposite causal associations of BMI and WC with mortality were observed, and a body figure with higher BMI and lower WC could substantially decrease the mortality risk. Guidelines for the weight management should be cautiously designed and implemented among the oldest-old people, considering distinct roles of BMI and WC.