scholarly journals Mortality risk and life years lost in young patients with heart failure according ejection fraction. Data from the Swedish Heart failure, National Patient, Cause of Death and Population Registers

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
C Basic ◽  
A.R Rosengren A ◽  
U.D Dahlstrom ◽  
M.E Edner ◽  
T.Z.S Zverkova Sandstrom ◽  
...  
Keyword(s):  
Heart Failure ◽  
General Population ◽  
Life Expectancy ◽  
Ejection Fraction ◽  
Cause Of Death ◽  
Mortality Risk ◽  
Young Patients ◽  
Life Years ◽  
National Patient ◽  
Life Years Lost

Abstract Background There is a lack of data evaluating excess mortality risk (over that of the general population) and life-years lost in young patients with different heart failure (HF) phenotypes. Purpose To study excess risk for all-cause mortality in patients <55 years by their ejection fraction (EF) categories and estimate lost “life years” compared to the general population in Sweden. Methods All patients ≥18 years registered in the national quality register SwedeHF from 2003 to 2014 were included. Patients were divided into ≥55 years and <55 years. For each patient two controls without a HF diagnosis, matched for age, sex and county, were identified from the Swedish Population Register. The use of personal identification number enabled linkage to other registers. All somatic hospital discharge diagnoses are recorded in the National Patient Register (NPR). Time of death and causes of death were obtained from the Cause of Death Register. International Classification of Disease ICD 9 and ICD 10-codes for all co-morbidities were identified in NPR and for underlying causes of death during the observation period from the 1st January 2003 to 31st December 2015. Life expectancy tables from Statistics Sweden were used as reference to the conditional life expectancy for controls calculated at the age 20, 25, 30, 35 and 40 years. Life-years lost were calculated as the difference between conditional life expectancy and conditional survival for patients with HF <55 years presented as median. Results In total 60,962 patients, out of whom 3752 <55 years and 7425 controls <55 years were identified. Total observation time was 12 years; median 4.89 years. There were 2549 (67.9%) patients with ejection fraction (EF) <40% and 357 (9.5%) with EF >50%. Patients with HF<40% were more likely to be men (78.2% vs. 56.3%), to have ischemic heart disease (16.9% vs. 2.3%) and dilated cardiomyopathy (38.1% vs. 29.7%) whereas patients with EF >50% more often had hypertension (40.6% vs. 29.8%), hypertrophic cardiomyopathy (11.5% vs. 0.7%) and congenital heart disease (7.6% vs. 2.7%), all p>0.001. Cardiovascular death was the most common cause of death in all EF categories (about 55%). In a Cox proportional hazard model, patients with EF >50% had hazard ratio (HR) (95% CI) 10.6 (5.71–19.8), those with EF 40–49% 6.83 (4.43–10.5) and patients with EF<40% 7.97 (6.45–9.85) for all-cause mortality (NS). According to the conditional survival analysis patients aged 20, 25, 30, 35 and 40 years with EF<40% lost a median of 28.5, 26.6, 24.7, 22.2 and 20.1 “life years” whereas patients with EF>50% lost 32.3, 28.7, 26.1, 26.3 and 21.6 “life years” as presented in figure 1. Conclusion HF patients <55 years with EF>50% had different coexisting conditions and higher mortality risk, although not significant when compared to patients with EF <40%. Moreover, compared to the general population patients with EF>50% lost more life years than patients with EF<40%. Figure 1 Funding Acknowledgement Type of funding source: None

2372Causes of death and effect of co-morbidities on mortality in young patients with heart failure. Data from the Swedish Heart Failure, Cause of Death and National Patient Registers

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
C Basic ◽  
A Rosengren ◽  
U Dahlstrom ◽  
M Edner ◽  
T Zverkova Sandstrom ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cause Of Death ◽  
Causes Of Death ◽  
Young Patients ◽  
Mortality Data ◽  
Quality Register ◽  
Co Morbidity ◽  
National Patient ◽  
Age And Sex ◽  
Observation Period

Abstract Background The last two decades incidence and prevalence of heart failure (HF) among young patients have increased in Sweden. Up to the beginning of the 21st century mortality in patients with HF has decreased but causes of death and the effects of co-morbidity on mortality in young patients with HF are not well studied. Purpose To address causes of death and the effect of co-morbidity at baseline on mortality during the last decade in young patients with HF. Methods The Swedish Heart Failure Register (SwedeHF,) a nationwide quality register, was introduced in Sweden in 2003. All hospital discharge diagnoses are recorded in the National Patient Register (NPR) and deaths are registered in the Cause of Death Register. All patients ≥18 and <55 years with a HF diagnosis in SwedeHF were included and linked to the Cause of Death Register and NPR with the personal identification number. ICD 10-codes for all comorbidities and principal cause of death were identified during the observation period from 2003 to 2016. Besides, comorbidity and mortality data were compared with age and sex matched controls from the general population, database from Statistics Sweden (SCB). Results We identified 3752 (6.2%) patients <55 years from the total SwedeHF population (n=60,962) and added 7573 age and sex matched controls. There were 971 (25.9%) women and 2781 (74.1%) men mean age 44.9 (8.4) and 46.4 (7.3) years respectively. Among the young 604 (16.1%) patients died vs. 162 (2.2%) among matched controls (p<0.001) during the observation period. Principal cause of death was HF in 2.7% of the young patients (in men 3% vs. 1.4% in women (p=0.221)), other cardiovascular diseases 48.7% (27.7% in men vs. 20% in women (p=0.05)), congenital heart disease 4% (3% in men vs. 6.9% in women (p=0.077)), cancer 12.9% (9.6% in men vs. 23.6% in women (p=0.003)), neurologic disease 4.5% (5.4% in men vs. 1.4% in women (p=0.028)) suicide 0.8% (0.7% in men vs 1.4% in women (p=0.47)) and other causes 15.1% (15.9% in men vs 12.5% in women (p=0.179)) vs. 0, 26.5%, 1.2%, 32.7%, 1.2%, 9.9% and 18.5% in matched controls (all p<0.0001). The effect of co-morbidity at baseline on mortality in young patients with HF is presented in Figure 1. Effect of co-morbidity on mortality Conclusion Compared to matched controls young patients with HF had worse survival. Almost one quarter of women with HF had cancer as a principal cause of death. Men with AF, obesity and depression at baseline had higher risk to die than women. Women with HF and hypertension, PAH or kidney disease at baseline had higher risk to die than men with HF and the same co-morbidities. Acknowledgement/Funding Swedish state under the agreement concerning research and education of doctors, The Swedish Heart and Lung Foundation, Västra Götaland Region grants

Temporal Trends in Chronic Myeloid Leukemia Outcome Using the Loss in Expectation of Life: A Swedish Population-Based Study

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2779-2779 ◽  
Author(s):  
Magnus Bjorkholm ◽  
Hannah Bower ◽  
Paul W Dickman ◽  
Paul C Lambert ◽  
Martin Höglund ◽  
...  
Keyword(s):  
Chronic Myeloid Leukemia ◽  
General Population ◽  
Life Expectancy ◽  
Myeloid Leukemia ◽  
Population Based ◽  
Population Based Study ◽  
Younger Age ◽  
Life Years ◽  
Life Years Lost ◽  
The Impact

Abstract Background Chronic Myeloid Leukemia (CML) is a myeloproliferative neoplasm with an incidence of 1-1.5 cases per 100,000 adults, accounting for ∼ 15-20 % of newly diagnosed patients with myeloid leukemia in adults. Treatment for CML has changed dramatically with the introduction of imatinib mesylate (IM), the first tyrosine kinase inhibitor (TKI) targeting the BCR-ABL1 oncoprotein. Previous population-based research (Björkholm et al. JCO, 2011) showed a major improvement in outcome of patients with CML up to 79 years of age diagnosed from 2001 to 2008. The elderly still had poorer outcome, partly because of a limited use of IM. However, increasing recognition of IM resistance and intolerance has led to the development of additional (second and third-generation) TKIs, which have demonstrated effectiveness as salvage therapies or alternative first-line treatments. Here we quantify how the life years lost due to a diagnosis of CML has changed between 1973 and 2013 using a measure called the loss in expectation of life (LEL). Methods This population-based study included3,684CML patients diagnosed in Sweden between 1973 and 2013; diagnoses were obtained from the Swedish Cancer Registry. The LEL was estimated using flexible parametric models. The LEL is the difference between the life expectancy in the diseased population and that in a matched subset of the general population. This measure has a simple interpretation as the number of life years lost, or the reduction in the life expectancy, due to a diagnosis of cancer. Results The life expectancy increased dramatically between 1990 and 2013 for CML patients of all ages; see figure. Patients in 2013, on average, lose less than 3 life years due to their diagnosis of CML. The largest increase in the life expectancy and thus the largest decrease in LEL over time was seen in younger patients; a diagnosis of CML in 1990 for a male 55-year old, on average, reduced his life expectancy by approximately 20.6 (95% CI: 20.3-21.1) years whereas a diagnosis in 2010 in the same male would on average reduce his life expectancy by only 2.6 (95% CI: 1.4-3.8) years. Although the greatest improvements were seen in those diagnosed at a younger age, those diagnosed at 85 years still benefitted in better survival over year of diagnosis; a diagnosis of CML in 1990 for a 85-year old, on average, reduced his life expectancy by approximately 3.6 (95% CI: 3.5-3.8) years whereas a diagnosis in 2010 in the same male would on average reduce his life expectancy by only 1.6 (95% CI: 1.0-2.2) years. Conclusions The reduction in life expectancy, or the number of life years lost due to a diagnosis of CML has greatly reduced over the years Patients who are diagnosed at a younger age lose dramatically fewer years in the most recent calendar years compared to previous years due to their CML diagnosis. Improvements in survival in the late 1990s were at least as great as those from 2001 in the youngest patients. Increased number of allogeneic stem cell transplantations, the introduction of interferon-alpha, improved supportive care and second line treatment with IM have all contributed. Less improvement was seen in the older patients which is probably explained by the relatively slow implementation of IM in this patient group. The impact of second generation TKIs on long-term survival remains to be determined. Figure 1. Life expectancy of the general population and CML patients aged 55, 65, 75 and 85 years over year of diagnosis, by sex. Figure 1. Life expectancy of the general population and CML patients aged 55, 65, 75 and 85 years over year of diagnosis, by sex. Disclosures No relevant conflicts of interest to declare.

Abstract 19228: Cost-effectiveness of the CardioMems Implantable Pulmonary Artery Pressure Monitoring System in Patients With Chronic Heart Failure

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Alexander T Sandhu ◽  
Jeremy D Goldhaber-Fiebert ◽  
Mintu P Turakhia ◽  
Daniel W Kaiser ◽  
Paul A Heidenreich
Keyword(s):  
Heart Failure ◽  
Cost Effectiveness ◽  
Ejection Fraction ◽  
Nyha Class ◽  
Case Analysis ◽  
Preserved Ejection Fraction ◽  
Heart Failure Hospitalization ◽  
Reduced Ejection Fraction ◽  
Life Years ◽  
The Cost

Background: For management of heart failure, the value of the CardioMems device remains uncertain. We assessed the cost-effectiveness of the CardioMems device. Methods: We developed a Markov model to determine quality-adjusted life-years (QALYs), cost, and cost-effectiveness of patients with heart failure receiving CardioMems implantation compared to those with routine care. In the main case analysis, we modeled the intervention in the CHAMPION trial cohort, which included patients with NYHA Class III heart failure with a heart failure hospitalization within the past twelve months. We also performed subgroup analyses of patients with preserved ejection fraction or reduced ejection fraction, and a scenario analysis of a second cohort of patients from the CHARM trials with a previous heart failure hospitalization. We obtained event rates and utilities from published trial data; we used costs from literature estimates and Medicare payment data. The main case analysis was calibrated to the hospitalization and survival rates of the CHAMPION trial. Results: In the CHAMPION trial main case analysis, CardioMems reduced lifetime hospitalizations (2.37 versus 3.27), increased months of survival (67 versus 62), increased QALYs (2.66 versus 2.38) and increased costs ($171,132 versus $154,084), yielding a cost of $59,520 per QALY gained or $40,301 per life-year gained. The cost per QALY gained was $71,964 in patients with reduced ejection fraction compared to $34,899 in those with preserved ejection fraction. In less ill patients from the CHARM trials, which included patients with NYHA Class II heart failure, the device cost increased to $110,565 per QALY gained. If the device cost decreased from $17,500 in the main case analysis to $15,000, the intervention would cost less than $50,000 per QALY gained. The duration of effectiveness was initially assumed to be lifelong; if less than 29 months, CardioMems would cost more than $150,000 per QALY gained. Conclusion: The CardioMems device is cost-effective in populations similar to the CHAMPION trial, with a cost of less than $100,000 per QALY gained, if durability of device effectiveness is sustained. Post-marketing surveillance data on the device’s durability will further clarify its value.

Frequency, predictors, and prognosis of ejection fraction improvement in heart failure: an echocardiogram-based registry study

2019 ◽  
Vol 40 (26) ◽  
pp. 2110-2117 ◽  
Author(s):  
Anukul Ghimire ◽  
Nowell Fine ◽  
Justin A Ezekowitz ◽  
Jonathan Howlett ◽  
Erik Youngson ◽  
...  
Keyword(s):  
Heart Failure ◽  
Atrial Fibrillation ◽  
Ejection Fraction ◽  
Mortality Risk ◽  
Left Ventricular ◽  
Lower Mortality ◽  
Ventricular Assist ◽  
Reduced Ejection Fraction ◽  
Multivariable Adjustment ◽  
Lower Mortality Risk

Abstract Aims To identify variables predicting ejection fraction (EF) recovery and characterize prognosis of heart failure (HF) patients with EF recovery (HFrecEF). Methods and results Retrospective study of adults referred for ≥2 echocardiograms separated by ≥6 months between 2008 and 2016 at the two largest echocardiography centres in Alberta who also had physician-assigned diagnosis of HF. Of 10 641 patients, 3124 had heart failure reduced ejection fraction (HFrEF) (EF ≤ 40%) at baseline: while mean EF declined from 30.2% on initial echocardiogram to 28.6% on the second echocardiogram in those patients with persistent HFrEF (defined by <10% improvement in EF), it improved from 26.1% to 46.4% in the 1174 patients (37.6%) with HFrecEF (defined by EF absolute improvement ≥10%). On multivariate analysis, female sex [adjusted odds ratio (aOR) 1.66, 95% confidence interval (CI) 1.40–1.96], younger age (aOR per decade 1.16, 95% CI 1.09–1.23), atrial fibrillation (aOR 2.00, 95% CI 1.68–2.38), cancer (aOR 1.52, 95% CI 1.03–2.26), hypertension (aOR 1.38, 95% CI 1.18–1.62), lower baseline ejection fraction (aOR per 1% decrease 1.07 (1.06–1.08), and using hydralazine (aOR 1.69, 95% CI 1.19–2.40) were associated with EF improvements ≥10%. HFrecEF patients demonstrated lower rates per 1000 patient years of mortality (106 vs. 164, adjusted hazard ratio, aHR 0.70 [0.62–0.79]), all-cause hospitalizations (300 vs. 428, aHR 0.87 [0.79–0.95]), all-cause emergency room (ER) visits (569 vs. 799, aHR 0.88 [0.81–0.95]), and cardiac transplantation or left ventricular assist device implantation (2 vs. 10, aHR 0.21 [0.10–0.45]) compared to patients with persistent HFrEF. Females with HFrEF exhibited lower mortality risk (aHR 0.94 [0.88–0.99]) than males after adjusting for age, time between echocardiograms, clinical comorbidities, medications, and whether their EF improved or not during follow-up. Conclusion HFrecEF patients tended to be younger, female, and were more likely to have hypertension, atrial fibrillation, or cancer. HFrecEF patients have a substantially better prognosis compared to those with persistent HFrEF, even after multivariable adjustment, and female patients exhibit lower mortality risk than men within each subgroup (HFrecEF and persistent HFrEF) even after multivariable adjustment.

scholarly journals Direct modeling of the crude probability of cancer death and the number of life years lost due to cancer without the need of cause of death: a pseudo-observation approach in the relative survival setting

Biostatistics ◽  
2020 ◽  
Author(s):  
Dimitra-Kleio Kipourou ◽  
Maja Pohar Perme ◽  
Bernard Rachet ◽  
Aurelien Belot
Keyword(s):  
Cause Of Death ◽  
Relative Survival ◽  
Population Based ◽  
Subdistribution Hazard ◽  
Cancer Data ◽  
Regression Parameters ◽  
Life Years ◽  
Direct Modeling ◽  
Life Years Lost ◽  
Probability Of Cancer

Summary In population-based cancer studies, net survival is a crucial measure for population comparison purposes. However, alternative measures, namely the crude probability of death (CPr) and the number of life years lost (LYL) due to death according to different causes, are useful as complementary measures for reflecting different dimensions in terms of prognosis, treatment choice, or development of a control strategy. When the cause of death (COD) information is available, both measures can be estimated in competing risks setting using either cause-specific or subdistribution hazard regression models or with the pseudo-observation approach through direct modeling. We extended the pseudo-observation approach in order to model the CPr and the LYL due to different causes when information on COD is unavailable or unreliable (i.e., in relative survival setting). In a simulation study, we assessed the performance of the proposed approach in estimating regression parameters and examined models with different link functions that can provide an easier interpretation of the parameters. We showed that the pseudo-observation approach performs well for both measures and we illustrated their use on cervical cancer data from the England population-based cancer registry. A tutorial showing how to implement the method in R software is also provided.

scholarly journals A Note on the Measurement of Socioeconomic Inequalities in Life Years Lost by Cause of Death

Epidemiology ◽  
2019 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Aurélien Latouche ◽  
Per Kragh Andersen ◽  
Grégoire Rey ◽  
Margarita Moreno-Betancur
Keyword(s):  
Cause Of Death ◽  
Socioeconomic Inequalities ◽  
Life Years ◽  
Life Years Lost

SO061SEX DIFFERENCES IN MORTALITY AMONG PEOPLE WITH END-STAGE KIDNEY DISEASE: DO WOMEN ALWAYS LIVE LONGER?

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Nicole De La Mata ◽  
Grace Macleod ◽  
Patrick Kelly ◽  
Brenda Rosales ◽  
Philip Masson ◽  
...  
Keyword(s):  
Sex Differences ◽  
Kidney Transplantation ◽  
General Population ◽  
Excess Mortality ◽  
Relative Survival ◽  
Average Life ◽  
End Stage Kidney Disease ◽  
Life Years ◽  
Life Years Lost ◽  
End Stage

Abstract Background and Aims Female life expectancies consistently exceed males in the general population. Yet, this survival advantage may not persist in the presence of a chronic disease due to sex-based differences or healthcare inequities. We aimed to explore sex differences in survival among people with end-stage kidney disease (ESKD) compared to the general population. Method We included the entire ESKD population in Australia, 1980-2013 and New Zealand, 1988-2012 from the Australian and New Zealand Dialysis and Transplant Registry. These were linked to national death registers to ascertain deaths and their causes. We estimated relative measures of survival, including standardized mortality ratios (SMR), cumulative relative survival and expected life years lost, using general population data (adjusting for country, age, sex and calendar year) to account for background mortality. Results Of the 60,823 ESKD patients, there were 25,042 females (41%) and 35,781 males (59%). Overall 34,417 deaths occurred over the 368,719 person-years of follow-up where a similar proportion of females (57%) and males (56%) died. While mortality sex differences within the ESKD population were minor, once compared to the general population female ESKD patients had greater excess deaths, worse relative survival and greater life years lost compared to male ESKD patients. Female ESKD patients had 12 times (SMR:11.5; 95%CI:11.3-11.7) and males had 7 times (SMR:6.7; 95%CI:6.7-6.8) the expected deaths, with the greatest sex disparity among younger ages and from cardiovascular disease. Relative survival was consistently lower in females (0.57, 95%CI:0.57-0.58 in males vs 0.54, 95%CI:0.54-0.55 in females at 5 years), where the excess mortality was 9% higher (95%CI:7-12%) in female ESKD patients (Fig 1A), adjusting for year and age. The average life years lost for female ESKD patients was 4-5 years greater than male ESKD patients (Average life years lost 25.9 years, 95%CI:25.1-26.7 in males and 31.4 years, 95%CI:30.5-32.1 in females aged 15 years at ESKD) (Fig 1B). Kidney transplantation reduced the sex differences in excess mortality, with similar relative survival (p=0.42; Fig 1C) and average life years lost reduced to 3-4 years for females (Fig 1D). Conclusion The impact of ESKD is more profound for women than men with greater excess mortality, however kidney transplantation attenuates these differences. Our findings show that chronic diseases and sex can compound to produce worse outcomes where women lose their survival advantage in the presence of ESKD.

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