Cause-specific Excess Mortality Research Articles

Cause-specific excess mortality in Denmark, Finland, Norway, and Sweden during the COVID-19 pandemic 2020–2022: a study using nationwide population data

While there is substantial evidence on excess mortality in the first two years of the COVID-19 pandemic, no study has conducted a cause-specific analysis of excess mortality for the whole period 2020–2022 across multiple countries. We examined cause-specific excess mortality during 2020–2022 in Denmark, Finland, Norway, and Sweden—four countries with similar demographics and welfare provisions, which implemented different pandemic response policies. To this end, we utilized nationwide register-based information on annual cause-specific deaths stratified by age and sex, and applied linear regression models to predict mortality in 2020–2022 based on the reference period 2010–2019. Excess deaths were obtained by contrasting actual and expected deaths. Additional analyses employed standardization to a common population, as well as population adjustments to account for previous deaths. Our results showed that, besides deaths due to COVID-19 (a total of 32,491 during 2020–2022), all countries experienced excess deaths due to cardiovascular diseases (in total 11,610 excess deaths), and under-mortality due to respiratory diseases other than COVID-19 (in total 9878) and dementia (in total 8721). The excess mortality due to cardiovascular diseases was particularly pronounced in Finland and Norway in 2022, and the under-mortality due to dementia was particularly pronounced in Sweden in 2021–2022. In conclusion, while COVID-19 deaths emerge as the most apparent consequence of the pandemic, our findings suggest that mortality has also been influenced by substitutions between different causes of death and over time, as well as indirect consequences of COVID-19 infection and pandemic responses—albeit to different extents in the different countries.

Cause-Specific Excess Mortality During the COVID-19 Pandemic (2020–2021) in 12 Countries of the C-MOR Consortium

BackgroundThis study investigated cause-specific mortality rates in 12 countries during the COVID-19 pandemic in 2020 and 2021.MethodsWe collected weekly cause-specific mortality data from respiratory disease, pneumonia, cardiovascular disease (CVD) and cancer from national vital statistic databases. We calculated excess mortality for respiratory disease (excluding COVID-19 codes), pneumonia, and CVD in 2020 and 2021 by comparing observed weekly against expected mortality based on historical data (2015–2019), accounting for seasonal trends. We used multilevel regression models to investigate the association between country-level pandemic-related variables and cause-specific mortality.ResultsSignificant reductions in cumulative mortality from respiratory disease and pneumonia were observed in 2020 and/or 2021, except for Georgia, Northern Ireland, Kazakhstan, and Ukraine, which exhibited excess mortality for one or both causes. Australia, Austria, Cyprus, Georgia, and Northern Ireland experienced excess cumulative CVD mortality in 2020 and/or 2021. Australia, Austria, Brazil, Cyprus, Georgia, Northern Ireland, Scotland and Slovenia, experienced increased crude cumulative cancer mortality during 2020 and/or 2021 compared to previous years. Among pandemic-related variables, reported COVID-19 incidence was negatively associated with increased cancer mortality, excess respiratory, (2020) and pneumonia (2021) mortality, and positively associated with respiratory and CVD mortality (2021). Stringency of control measures were negatively associated with excess respiratory disease, CVD, and increased cancer mortality (2021).ConclusionsThis study provides evidence of substantial excess mortality from CVD, and notable reductions in respiratory disease and pneumonia in both years across most countries investigated. Our study also highlights the beneficial impact of stringent control measures in mitigating excess mortality from most causes in 2021.

Age and sex differences in cause-specific excess mortality and years of life lost associated with COVID-19 infection in the Swedish population.

Estimating excess mortality and years of life lost (YLL) attributed to coronavirus disease 19 (COVID-19) infection provides a comprehensive picture of the mortality burden on society. We aimed to estimate the impact of the COVID-19 pandemic on age- and sex-specific excess mortality and YLL in Sweden during the first 17 months of the pandemic. In this population-based observational study, we calculated age- and sex-specific excess all-cause mortality and excess YLL during 2020 and the first 5 months of 2021 and cause-specific death [deaths from cardiovascular disease (CVD), cancer, other causes and deaths excluding COVID-19] in 2020 compared with an average baseline for 2017-19 in the whole Swedish population. COVID-19 deaths contributed 9.9% of total deaths (98 441 deaths, 960 305 YLL) in 2020, accounting for 75 151 YLL (7.7 YLL/death). There were 2672 (5.7%) and 1408 (3.0%) excess deaths, and 19 141 (3.8%) and 3596 (0.8%) excess YLL in men and women, respectively. Men aged 65-110 years and women aged 75-110 years were the greatest contributors. Fewer deaths and YLL from CVD, cancer and other causes were observed in 2020 compared with the baseline adjusted to the population size in 2020. Compared with the baseline, excess mortality and YLL from all causes were experienced in Sweden during 2020, with a higher excess observed in men than in women, indicating that more men died at a younger age while more women died at older ages than expected. A notable reduction in deaths and YLL due to CVD suggests a displacement effect from CVD to COVID-19.

Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared.

During the COVID-19 pandemic, excess mortality has been reported worldwide, but its magnitude has varied depending on methodological differences that hinder between-study comparability. Our aim was to estimate variability attributable to different methods, focusing on specific causes of death with different pre-pandemic trends. Monthly mortality figures observed in 2020 in the Veneto Region (Italy) were compared with those forecasted using: (1) 2018-2019 monthly average number of deaths; (2) 2015-2019 monthly average age-standardized mortality rates; (3) Seasonal Autoregressive Integrated Moving Average (SARIMA) models; (4) Generalized Estimating Equations (GEE) models. We analyzed deaths due to all-causes, circulatory diseases, cancer, and neurologic/mental disorders. Excess all-cause mortality estimates in 2020 across the four approaches were: +17.2% (2018-2019 average number of deaths), +9.5% (five-year average age-standardized rates), +15.2% (SARIMA), and +15.7% (GEE). For circulatory diseases (strong pre-pandemic decreasing trend), estimates were +7.1%, -4.4%, +8.4%, and +7.2%, respectively. Cancer mortality showed no relevant variations (ranging from -1.6% to -0.1%), except for the simple comparison of age-standardized mortality rates (-5.5%). The neurologic/mental disorders (with a pre-pandemic growing trend) estimated excess corresponded to +4.0%/+5.1% based on the first two approaches, while no major change could be detected based on the SARIMA and GEE models (-1.3%/+0.3%). The magnitude of excess mortality varied largely based on the methods applied to forecast mortality figures. The comparison with average age-standardized mortality rates in the previous five years diverged from the other approaches due to the lack of control over pre-existing trends. Differences across other methods were more limited, with GEE models probably representing the most versatile option.

Cause-specific excess mortality after first diagnosis of bipolar disorder: population-based cohort study

BackgroundBipolar disorder (BD) is associated with increased mortality, but evidence on cause-specific mortality is limited.ObjectiveTo investigate cause-specific premature excess mortality in BD.MethodsFinnish nationwide cohort study of individuals with and without...

Changes in all-cause and cause-specific excess mortality before and after the Omicron outbreak of COVID-19 in Hong Kong.

While coronavirus 2019 (COVID-19) deaths were generally underestimated in many countries, Hong Kong may show a different trend of excess mortality due to stringent measures, especially for deaths related to respiratory diseases. Nevertheless, the Omicron outbreak in Hong Kong evolved into a territory-wide transmission, similar to other settings such as Singapore, South Korea, and recently, mainland China. We hypothesized that the excess mortality would differ substantially before and after the Omicron outbreak. We conducted a time-series analysis of daily deaths stratified by age, reported causes, and epidemic wave. We determined the excess mortality from the difference between observed and expected mortality from 23 January 2020 to 1 June 2022 by fitting mortality data from 2013 to 2019. During the early phase of the pandemic, the estimated excess mortality was -19.92 (95% confidence interval (CI) = -29.09, -10.75) and -115.57 (95% CI = -161.34, -69.79) per 100 000 population overall and for the elderly, respectively. However, the overall excess mortality rate was 234.08 (95% CI = 224.66, 243.50) per 100 000 population overall and as high as 928.09 (95% CI = 885.14, 971.04) per 100 000 population for the elderly during the Omicron epidemic. We generally observed negative excess mortality rates of non-COVID-19 respiratory diseases before and after the Omicron outbreak. In contrast, increases in excess mortality were generally reported in non-respiratory diseases after the Omicron outbreak. Our results highlighted the averted mortality before 2022 among the elderly and patients with non-COVID-19 respiratory diseases, due to indirect benefits from stringent non-pharmaceutical interventions. The high excess mortality during the Omicron epidemic demonstrated a significant impact from the surge of COVID-19 infections in a SARS-CoV-2 infection-naive population, particularly evident in the elderly group.

The Effect of COVID-19 Pandemic on Overall and Cause-Specific Mortality in Pavia, Northern Italy: Updated Estimates for the Year 2021

Excess mortality estimates are considered relevant indicators of direct and indirect pandemic effects on the population. Scant data have been published on cause-specific excess mortality. Using individual-level administrative data covering the Pavia province of Italian northern Lombardy region, we provided all-cause and cause-specific raw (RMR) and age-standardized (ASMR) mortality rates in 2021 and 2015-2019, the rate ratio, and 95% confidence intervals, overall and by sex. We obtained the excess deaths in 2021 as the difference between the number of observed and expected deaths from all causes and the two leading causes of death (all neoplasms and circulatory system diseases) by fitting over-dispersed quasi-Poisson regression models, accounting for temporal, seasonal and demographic changes. The total ASMR in 2021 was 972.4/100,000 (6836 certified deaths), with the highest ASMRs for circulatory system diseases (272.6/100,000) and all neoplasms (270.3/100,000), followed by COVID-19 (94.8/100,000 and 662 deaths). Compared to the expected, we estimated a total of 6.2% excess deaths in 2021 (7.2% in males and 5.4% in females), with no excess deaths from all neoplasms and a 6.2% reduction from circulatory system diseases. COVID-19 continued to affect total mortality in 2021, albeit to a lesser extent than in 2020, consistently with national patterns.

Cause-specific excess mortality after hip fracture: the Norwegian Epidemiologic Osteoporosis Studies (NOREPOS)

BackgroundInformation on cause of death may help appraise the degree to which the high excess mortality after hip fracture reflects pre-existing comorbidities or the injury itself. We aimed to describe causes of death and cause-specific excess mortality through the first year after hip fracture.MethodsFor studying the distribution of causes of death by time after hip fracture, we calculated age-adjusted cause-specific mortality at 1, 3, 6 and 12 months in patients hospitalized with hip fracture in Norway 1999–2016. Underlying causes of death were obtained from the Norwegian Cause of Death Registry and grouped by the European Shortlist for Causes of Death. For estimating excess mortality, we performed flexible parametric survival analyses comparing mortality hazard in patients with hip fracture (2002–2017) with that of age- and sex matched controls drawn from the Population and Housing Census 2001.ResultsOf 146,132 Norwegians with a first hip fracture, a total of 35,498 (24.3%) died within one year. By 30 days post-fracture, external causes (mainly the fall causing the fracture) were the underlying cause for 53.8% of deaths, followed by circulatory diseases (19.8%), neoplasms (9.4%), respiratory diseases (5.7%), mental and behavioural disorders (2.0%) and diseases of the nervous system (1.3%). By one-year post-fracture, external causes and circulatory diseases together accounted for approximately half of deaths (26.1% and 27.0%, respectively). In the period 2002–2017, cause-specific one-year relative mortality hazard in hip fracture patients vs. population controls ranged from 1.5 for circulatory diseases to 2.5 for diseases of the nervous system in women, and correspondingly, from 2.4 to 5.3 in men.ConclusionsHip fractures entail high excess mortality from all major causes of death. However, the traumatic injury of a hip fracture is the most frequently reported underlying cause of death among older patients who survive less than one year after their fracture.

The impact of the SARS-CoV-2 pandemic on cause-specific- mortality: a systematic literature review

Abstract Background Although investigating the patterns of COVID-19 excess mortality (EM) is relevant, understanding the effects of the pandemic on cause-specific mortality is even crucial and should also be assessed, as this metric allows for a more detailed analysis of the true impact of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon. Methods We searched MEDLINE to identify studies that reported cause-specific mortality during the COVID-19 pandemic. We adopted several inclusion criteria: original article; assessed at least one cause-specific mortality during the pandemic; assessed causes of deaths using the ICD-10 classification; reporting of at least one of the following outcomes: cause-specific mortality estimates or cause-specific EM; full-length articles. Several relevant data were extracted (e.g. publication year, data stratification, territory, country income level, all-cause EM, and cause-specific mortality, etc.). Results The search identified 548 articles. After title, abstract and full-text screening, we extracted relevant data from the final set of 14 articles. Cause-specific mortality was reported using different units of measurement. Only 9 studies reported the statistical significance and/or confidence intervals. The most frequently analyzed causes of death were cardiovascular diseases (n = 11), cancer (n = 7), diabetes (n = 6), and suicide (n = 5). We found very heterogeneous patterns of cause-specific mortality, for all the specific causes of deaths, except for suicide and road accident. Conclusions The impact of the pandemic on cause-specific deaths has been very heterogeneous and the analyses conducted so far are not exhaustive. We advocate for the urgent need to find a consensus to define uniform methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality. Key messages • We reviewed the body of literature to estimate the impact of the COVID-19 pandemic on different causes of death, and to provide a quantitative and qualitative analysis of the phenomenon. • We did not identify unique patterns of cause-specific mortality due to too varied approaches in terms of disease classification and coding, and methodologies used for estimating mortality.

Leading causes of excess mortality in Mexico during the COVID-19 pandemic 2020–2021: A death certificates study in a middle-income country

SummaryBackgroundThe death toll after SARS-CoV-2 emergence includes deaths directly or indirectly associated with COVID-19. Mexico reported 325,415 excess deaths, 34.4% of them not directly related to COVID-19 in 2020. In this work, we aimed to analyse temporal changes in the distribution of the leading causes of mortality produced by COVID-19 pandemic in Mexico to understand excess mortality not directly related to the virus infection.MethodsWe did a longitudinal retrospective study of the leading causes of mortality and their variation with respect to cause-specific expected deaths in Mexico from January 2020 through December 2021 using death certificate information. We fitted a Poisson regression model to predict cause-specific mortality during the pandemic period, based on the 2015–2019 registered mortality. We estimated excess deaths as a weekly difference between expected and observed deaths and added up for the entire period. We expressed all-cause and cause-specific excess mortality as a percentage change with respect to predicted deaths by our model.FindingsCOVID-19 was the leading cause of death in 2020–2021 (439,582 deaths). All-cause total excess mortality was 600,590 deaths (38⋅2% [95% CI: 36·0 to 40·4] over expected). The largest increases in cause-specific mortality, occurred in diabetes (36·8% over expected), respiratory infections (33·3%), ischaemic heart diseases (32·5%) and hypertensive diseases (25·0%). The cause-groups that experienced significant decreases with respect to the expected pre-pandemic mortality were infectious and parasitic diseases (-20·8%), skin diseases (-17·5%), non-traffic related accidents (-16·7%) and malignant neoplasm (-5·3%).InterpretationMortality from COVID-19 became the first cause of death in 2020–2021, the increase in other causes of death may be explained by changes in the health service utilization patterns caused by hospital conversion or fear of the population using them. Cause-misclassification cannot be ruled out.FundingThis study was funded by Conacyt.

The US Midlife Mortality Crisis Continues: Excess Cause-Specific Mortality During 2020.

Whether monthly excess mortality in the United States during 2020 varied by age and cause of death is investigated in this analysis. Based on national-level death counts and population estimates for 1999-2020, sex-specific negative binomial regression models were used to estimate monthly cause-specific excess mortality by age group during 2020. Among men, 71% non-COVID excess deaths occurred at working ages (25-64 years), but those ages accounted for only 36% of non-COVID excess deaths among women. Many excess deaths resulted from external causes (particularly among men), heart disease, diabetes, Alzheimer disease (particularly among women), and cerebrovascular disease. For men, the largest share of non-COVID excess deaths resulted from external causes, nearly 80% of which occurred at working ages. Although incorrectly classified COVID-19 deaths may explain some excess non-COVID mortality, misclassification is unlikely to explain the increase in external causes of death. Auxiliary analyses suggested that drug-related deaths may be driving the increase in external mortality, but drug overdoses were already increasing for a full year before the pandemic. The oldest Americans bore the brunt of COVID-19 deaths, but working-age Americans, particularly men, suffered substantial numbers of excess non-COVID deaths, most commonly from external causes and heart disease.

Reduced mortality during the COVID-19 outbreak in Japan, 2020: a two-stage interrupted time-series design.

BackgroundCoronavirus disease 2019 (COVID-19) continues to be a major global health burden. This study aims to estimate the all-cause excess mortality occurring in the COVID-19 outbreak in Japan, 2020, by sex and age group.MethodsDaily time series of mortality for the period January 2015–December 2020 in all 47 prefectures of Japan were obtained from the Ministry of Health, Labour and Welfare, Japan. A two-stage interrupted time-series design was used to calculate excess mortality. In the first stage, we estimated excess mortality by prefecture using quasi-Poisson regression models in combination with distributed lag non-linear models, adjusting for seasonal and long-term variations, weather conditions and influenza activity. In the second stage, we used a random-effects multivariate meta-analysis to synthesize prefecture-specific estimates at the nationwide level.ResultsIn 2020, we estimated an all-cause excess mortality of −20 982 deaths [95% empirical confidence intervals (eCI): −38 367 to −5472] in Japan, which corresponded to a percentage excess of −1.7% (95% eCI: −3.1 to −0.5) relative to the expected value. Reduced deaths were observed for both sexes and in all age groups except those aged <60 and 70–79 years.ConclusionsAll-cause mortality during the COVID-19 outbreak in Japan in 2020 was decreased compared with a historical baseline. Further evaluation of cause-specific excess mortality is warranted.

Temporal dynamic in the impact of COVID\u2212\u200919 outbreak on cause-specific mortality in Guangzhou, China

BackgroundStudies related to the SARS-CoV-2 spikes in the past few months, while there are limited studies on the entire outbreak-suppressed cycle of COVID-19. We estimate the cause-specific excess mortality during the complete circle of COVID-19 outbreak in Guangzhou, China, stratified by sociodemographic status.MethodsGuangzhou Center for Disease Control Prevention provided the individual data of deaths in Guangzhou from 1 January 2018 through 30 June 2020. We applied Poisson regression models to daily cause-specific mortality between 1 January 2018 and 20 January 2020, accounting for effects of population size, calendar time, holiday, ambient temperature and PM2.5. Expected mortality was estimated for the period from 21 January through 30 June 2020 assuming that the effects of factors aforementioned remained the same as described in the models. Excess mortality was defined as the difference between the observed mortality and the expected mortality. Subgroup analyses were performed by place of death, age group, sex, marital status and occupation class.ResultsFrom 21 January (the date on which the first COVID-19 case occurred in Guangzhou) through 30 June 2020, there were three stages of COVID-19: first wave, second wave, and recovery stage, starting on 21 January, 11 March, and 17 May 2020, respectively. Mortality deficits were seen from late February through early April and in most of the time in the recovery stage. Excesses in hypertension deaths occurred immediately after the starting weeks of the two waves. Overall, we estimated a deficit of 1051 (95% eCI: 580, 1558) in all-cause deaths. Particularly, comparing with the expected mortality in the absence of COVID-19 outbreak, the observed deaths from pneumonia and influenza substantially decreased by 49.2%, while deaths due to hypertension and myocardial infarction increased by 14.5 and 8.6%, respectively. In-hospital all-cause deaths dropped by 10.2%. There were discrepancies by age, marital status and occupation class in the excess mortality during the COVID-19 outbreak.ConclusionsThe excess deaths during the COVID-19 outbreak varied by cause of death and changed temporally. Overall, there was a deficit in deaths during the study period. Our findings can inform preparedness measures in different stages of the outbreak.

Sex Differences in Causes of Death After Stroke: Evidence from a National, Prospective Registry

Background: We examined sex differences in cause of death and cause-specific excess mortality after stroke. Materials and Methods: First-ever strokes (2010–2013; 35 hospitals) participating in the Australian Stroke Clinical Registry were linked to national death registrations and other administrative datasets. One-year cause-specific mortality was categorized as stroke, ischemic heart disease, other cardiovascular disease (CVD; e.g., hypertension), cancer, and other. Specific hazard ratios (sHRs) of death for women compared to men were estimated using competing risk models, with adjustment for factors differing by sex (e.g., age and stroke severity). Age- and sex-specific mortality rates expected in the general population were derived from national data. Standardized mortality ratios (SMRs; observed/expected deaths) were estimated for cause-specific mortality by sex after age standardization. Results: Among 9,441 cases (46% women), women were 7 years older than men, had more severe strokes, and received similar patterns of suboptimal secondary prevention medications at discharge. Women had greater mortality associated with stroke (sHRunadjusted 1.65) and other CVD (sHRunadjusted 1.65), which was related to age and stroke severity rather than other factors. Compared to population norms, those surviving to 30 days had eight-fold increased mortality from stroke (primary/recurrent) events irrespective of sex (SMRage-standardised women 8.8; men 8.3). Excess mortality from other CVD was greater in women (SMRage-standardised 3.6 vs. men 2.8; p = 0.026). Conclusions: Cause-specific mortality after first-ever stroke differs by sex. The greater death rate attributed to stroke/other CVD in women was mostly explained by age and stroke severity. Greater implementation of secondary stroke prevention is relevant to both sexes.

Cause-specific life years lost in individuals with treatment-resistant depression: A Danish nationwide register-based cohort study

BackgroundDepression is associated with excess mortality, but it is not known how treatment-resistance influences life expectancy. We estimated cause-specific excess mortality and Life Years Lost (LYL) in patients with treatment-resistant depression (TRD). MethodsThe population included all individuals born and living in Denmark who redeemed their first prescription for an antidepressant at age 18–69 years between 2005 and 2012, identified in the Danish National Prescription Registry. TRD was defined as at least two additional and different antidepressant trials within two years. Mortality rate ratios (MRRs) were estimated with Cox regression adjusted for age at first prescription, calendar year and comorbidity. Differences in life expectancy were estimated by the Life Years Lost (LYL) method. ResultsThe cohort included 154,513 first-time pharmacologically treated patients with depression, of whom 8,294 (5.4%) were identified as having TRD. Patients were followed for 1,032,245 person-years during which 9,795 deaths occurred. Men and women with TRD had significantly higher mortality than non-TRD (aMRR: 1.34, 95% CI 1.18–1.52 and aMRR: 1.39, 95% CI 1.19–1.63, respectively). Life expectancy for men and women with TRD was 1.21 (95% CI 0.36–2.44) and 1.24 (95% CI 0.35–2.34) years shorter than in all patients with depression. Suicide accounted for the majority of excess LYL, with 1.10 (95% CI 0.46–1.61) years in men and 0.82 (95% CI 0.44–1.27) years in women with TRD. LimitationsUsing redeemed prescriptions to define TRD may increase the risk of misclassification. ConclusionsPatients not responding adequately to several treatment trials are at increased risk for premature death, particularly suicide.

Data from the ERA-EDTA Registry were examined for trends in excess mortality in European adults on kidney replacement therapy

The objective of this study was to investigate whether the improvement in survival seen in patients on kidney replacement therapy reflects the enhanced survival of the general population. Patient and general population statistics were obtained from the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry and the World Health Organization databases, respectively. Relative survival models were composed to examine trends over time in all-cause and cause-specific excess mortality, stratified by age and modality of kidney replacement therapy, and adjusted for sex, primary kidney disease and country. In total, 280,075 adult patients started kidney replacement therapy between 2002 and 2015. The excess mortality risk in these patients decreased by 16% per five years (relative excess mortality risk (RER) 0.84; 95% confidence interval 0.83-0.84). This reflected a 14% risk reduction in dialysis patients (RER 0.86; 0.85-0.86), and a 16% increase in kidney transplant recipients (RER 1.16; 1.07-1.26). Patients on dialysis showed a decrease in excess mortality risk of 28% per five years for atheromatous cardiovascular disease as the cause of death (RER 0.72; 0.70-0.74), 10% for non-atheromatous cardiovascular disease (RER 0.90; 0.88-0.92) and 10% for infections (RER 0.90; 0.87-0.92). Kidney transplant recipients showed stable excess mortality risks for most causes of death, although it did worsen in some subgroups. Thus, the increase in survival in patients on kidney replacement therapy is not only due to enhanced survival in the general population, but also due to improved survival in the patient population, primarily in dialysis patients.

Platinum exposure and cause-specific mortality among patients with testicular cancer.

BackgroundAlthough testicular cancer (TC) treatment has been associated with severe late morbidities, including second malignant neoplasms (SMNs) and ischemic heart disease (IHD), cause‐specific excess mortality has been rarely studied among patients treated in the platinum era.MethodsIn a large, multicenter cohort including 6042 patients with TC treated between 1976 and 2006, cause‐specific mortality was compared with general population mortality rates. Associations with treatment were assessed with proportional hazards analysis.ResultsWith a median follow‐up of 17.6 years, 800 patients died; 40.3% of these patients died because of TC. The cumulative mortality was 9.6% (95% confidence interval [CI], 8.5%‐10.7%) 25 years after TC treatment. In comparison with general population mortality rates, patients with nonseminoma experienced 2.0 to 11.6 times elevated mortality from lung, stomach, pancreatic, rectal, and kidney cancers, soft‐tissue sarcomas, and leukemia; 1.9‐fold increased mortality (95% CI, 1.3‐2.8) from IHD; and 3.9‐fold increased mortality (95% CI, 1.5‐8.4) from pneumonia. Seminoma patients experienced 2.5 to 4.6 times increased mortality from stomach, pancreatic, bladder cancer and leukemia. Radiotherapy and chemotherapy were associated with 2.1 (95% CI, 1.8‐2.5) and 2.5 times higher SMN mortality (95% CI, 2.0‐3.1), respectively, in comparison with the general population. In a multivariable analysis, patients treated with platinum‐containing chemotherapy had a 2.5‐fold increased hazard ratio (HR; 95% CI, 1.8‐3.5) for SMN mortality in comparison with patients without platinum‐containing chemotherapy. The HR for SMN mortality increased 0.29 (95% CI, 0.19‐0.39) per 100 mg/m2 platinum dose administered (P trend < .001). IHD mortality was increased 2.1‐fold (95% CI, 1.5‐4.2) after platinum‐containing chemotherapy in comparison with patients without platinum exposure.ConclusionsPlatinum‐containing chemotherapy is associated with a dose‐dependent increase in the risk of SMN mortality.

Cause-specific excess mortality in patients treated for cancer of the oral cavity and oropharynx: A population-based study

To assess cause-specific mortality in a large population-based cohort of 14,393 patients treated for squamous cell carcinoma of the oral cavity (OC) or oropharynx (OP) in The Netherlands between 1989 and 2006. Causes of death were obtained for 94.7% of 9620 patients who had died up to January 1, 2009. We assessed standardized mortality ratios (SMR) and absolute excess mortality (AEM), comparing observed cause-specific mortality with expected mortality for our cohort based on general population mortality rates. Median survival was 3.9 years. Overall, the study population experienced a 6-fold higher (95% Confidence Interval (95% CI) 5.9-6.1) mortality risk compared with the general population. After three years, 41% of OP and 29% of OC patients had died due to cancer of the oral cavity and pharynx. Additionally, OC and OP patients experienced high excess mortality from esophageal (SMR 10.6 and 17.9) and lung cancer (SMR 4.6 and 6.3). With regard to non-cancer deaths, the highest AEMs were due to diseases of the circulatory system, with OC patients experiencing an AEM of 11.3 per 10,000 person-years for ischemic heart disease. OP patients experienced excess mortality due to pneumonia (AEM 22.1 per 10,000 person-years). The risk of death due to diseases of the digestive system was for OP and OC patients where about equal (AEM 28.7 and 23.80, respectively). The SMR for death due to pneumonia was more than two times higher (4.4 vs. 1.7) for OP patients than for OC patients (P<0.001). From 15 years after diagnosis, second tumors located outside the head and neck region accounted for most of the excess mortality. Excess mortality in OC and OP patients appears to be dominated by effects of heavy tobacco and alcohol use with high AEM due to second tumors, respiratory, cardiovascular and gastrointestinal diseases. Patients with OP experienced more than two times higher risk of death due to pneumonia than OC patients. Therefore, awareness of this potential complication should be raised along with development of prevention strategies.

Cause-Specific Mortality of Psychiatric Inpatients and Outpatients in a General Hospital in Korea

This study aimed to examine the cause-specific excess mortality of psychiatric patients in a general hospital in Korea. Between January 1995 and December 2006, 29 986 patients presented to the outpatient clinic of a general hospital in Seoul, Korea, or were admitted to that hospital for psychiatric disorders. Their cause-specific mortality risk was compared with that of age-matched patients from the general Korean population. The mortality risk of psychiatric patients was 1.6 times higher than that of the general population. Inpatients, younger adults, and patients with alcohol use disorders or schizophrenia had the highest standardized mortality rates (SMRs). Alcohol use disorder was associated with extremely high SMRs of more than 20 for hematological disease and digestive system disease. Effective preventive measures are required to reduce the excess mortality of psychiatric patients, particularly alcohol-dependent patients and younger patients who have been admitted for general psychiatric care.

Survival after Hodgkin lymphoma

The objective of this study was to analyze cause-specific excess mortality in adult patients with Hodgkin lymphoma (HL) with respect to treatment modality. The study population consisted of 4401 Belgian, Dutch, and French patients aged 15 to 69, in all stages of disease, who were treated between 1964 and 2000. Excess mortality was expressed by using a standardized mortality ratio (SMR) and calculating the absolute excess risk (AER). Relative survival was calculated and analyzed using a previously described regression model. At a median follow-up of 7.8 years, 725 of 4401 patients (16.5%) had died, 51% of HL, 10% of treatment-related toxicity, 18% of second cancer, 5% of cardiovascular diseases, 2% of infections, 8% of other causes, and 6% of an unspecified cause. Overall, the SMR was 7.4 (95% confidence limits [CL], 6.9-8.0), and the AER was 182.8 (95% CL, 167.7-198.8). These indicators were 3.8 (95% CL, 3.2-4.5) and 27.9, respectively, for deaths from a second cancer and 4.0 (95% CL, 2.3-6.7) and 3.3, respectively for deaths from infection. After 15 years, the observed survival rate was 75%, and the relative survival rate was 80%. In patients with early-stage disease, the overall excess mortality was associated with age > or =40 years (P = .007), men (P < .001), unfavorable prognosis features (P < .001), and 2 treatments: combined nonstandard nonalkylating chemotherapy plus involved-field radiotherapy (P = .002) and mantle-field irradiation alone (P = .003). With follow-up censored at the first recurrence, no treatment modalities were associated with excess mortality. Progressive disease remained the primary cause of death in patients with HL in the first decades after treatment. Excess mortality in patients with early-stage disease was linked significantly to treatment modalities that were associated with poor treatment failure-free survival.