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

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.

2020 ◽  
Author(s):  
Sarwar Islam Mozumder ◽  
Paul Lambert ◽  
Mark Rutherford

Abstract We present various measures, specifically the expected life-years list due to a cause of death, that can be predicted for a specific covariate pattern. These can also be summarised at the population-level using standardisation to obtain marginal measures. The restricted mean survival time (RMST) measure can be obtained in the presence of competing risks using Royston-Parmar flexible parametric survival models (FPMs). Royston-Parmar FPMs can be fitted on either the cause-specific hazards or cumulative incidence scale in the presence of competing risks. An advantage of modelling within this framework for competing risks data is the ease at which other alternative predictions to the (cause-specific or subdistribution) hazard ratio can be obtained. The RMST estimate is one such measure. This has an attractive interpretation, especially when the proportionality assumption is violated. In addition to this, compared to similar measures, fewer assumptions are required and it does not require extrapolation. Furthermore, one can easily obtain the expected number of life-years lost, or gained, due to a particular cause of death, which is a further useful prognostic measure. We describe estimation of RMST after fitting a FPM on either the log-cumulative subdistribution, or cause-specific hazards scale. As an illustration of reporting such measures to facilitate interpretation of a competing risks analysis, models are fitted to English colorectal data.


2020 ◽  
Author(s):  
Sarwar Islam Mozumder ◽  
Mark Rutherford ◽  
Paul Lambert

Abstract We present various measures, specifically the expected life-years list due to a cause of death, that can be predicted for a specific covariate pattern to facilitate interpretation in observational studies. These can also be summarised at the population-level using standardisation to obtain marginal measures. The restricted mean survival time (RMST) measure can be obtained in the presence of competing risks using Royston-Parmar flexible parametric survival models (FPMs). Royston-Parmar FPMs can be fitted on either the cause-specific hazards or cumulative incidence scale in the presence of competing risks. An advantage of modelling within this framework for competing risks data is the ease at which other alternative predictions to the (cause-specific or subdistribution) hazard ratio can be obtained. The RMST estimate is one such measure. This has an attractive interpretation, especially when the proportionality assumption is violated. In addition to this, compared to similar measures, fewer assumptions are required and it does not require extrapolation. Furthermore, one can easily obtain the expected number of life-years lost, or gained, due to a particular cause of death, which is a further useful prognostic measure. We describe estimation of RMST after fitting a FPM on either the log-cumulative subdistribution, or cause-specific hazards scale. As an illustration of reporting such measures to facilitate interpretation of a competing risks analysis, models are fitted to English colorectal data.


Epidemiology ◽  
2019 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Aurélien Latouche ◽  
Per Kragh Andersen ◽  
Grégoire Rey ◽  
Margarita Moreno-Betancur

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Nicole De La Mata ◽  
Grace Macleod ◽  
Patrick Kelly ◽  
Brenda Rosales ◽  
Philip Masson ◽  
...  

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.


Author(s):  
Nicole L De La Mata ◽  
Grace Macleod ◽  
Patrick J Kelly ◽  
Brenda Rosales ◽  
Philip Masson ◽  
...  

IntroductionFemale 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 biological differences or healthcare inequities. Objectives and ApproachWe aimed to explore sex differences in mortality among people with end-stage kidney disease (ESKD). T he entire ESKD population in Australia, 1980-2013, and New Zealand,1988-2012, were included from the Australian and New Zealand Dialysis and Transplant Registry. Data linkage to national death registers was undertaken to ascertain deaths and their causes. We estimated relative measures of survival, including standardized mortality ratios (SMR), relative survival and expected life years lost, using general population data to account for background mortality, adjusting for country, age, sex and year. ResultsOf 60,823 ESKD patients, there were 25,042 females (41%) and 35,781 males (59%). Mortality sex differences within the ESKD population were minor, but once compared to the general population, female ESKD patients had more excess deaths, worse relative survival and greater life years lost compared to male ESKD patients. Females had 11.5 SMR (95%CI:11.3-11.7) and males had 6.7 SMR (95%CI:6.7-6.8), with greater disparity among younger ages and from certain causes. Relative survival was consistently lower in females, with adjusted excess mortality 9% higher (95%CI:7-12%) in ESKD females. Average life years lost was 4-5 years greater in ESKD females compared to males across all ages. Kidney transplantation reduced the sex differences in excess mortality, with similar relative survival (p=0.42) and average life years lost reduced to 3-4 years for females. Conclusion / ImplicationsThe 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.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2779-2779 ◽  
Author(s):  
Magnus Bjorkholm ◽  
Hannah Bower ◽  
Paul W Dickman ◽  
Paul C Lambert ◽  
Martin Höglund ◽  
...  

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.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
C Basic ◽  
A.R Rosengren A ◽  
U.D Dahlstrom ◽  
M.E Edner ◽  
T.Z.S Zverkova Sandstrom ◽  
...  

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


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sarwar I. Mozumder ◽  
Mark J. Rutherford ◽  
Paul C. Lambert

Abstract Background Royston-Parmar flexible parametric survival models (FPMs) can be fitted on either the cause-specific hazards or cumulative incidence scale in the presence of competing risks. An advantage of modelling within this framework for competing risks data is the ease at which alternative predictions to the (cause-specific or subdistribution) hazard ratio can be obtained. Restricted mean survival time (RMST), or restricted mean failure time (RMFT) on the mortality scale, is one such measure. This has an attractive interpretation, especially when the proportionality assumption is violated. Compared to similar measures, fewer assumptions are required and it does not require extrapolation. Furthermore, one can easily obtain the expected number of life-years lost, or gained, due to a particular cause of death, which is a further useful prognostic measure as introduced by Andersen. Methods In the presence of competing risks, prediction of RMFT and the expected life-years lost due to a cause of death are presented using Royston-Parmar FPMs. These can be predicted for a specific covariate pattern to facilitate interpretation in observational studies at the individual level, or at the population-level using standardisation to obtain marginal measures. Predictions are illustrated using English colorectal data and are obtained using the Stata post-estimation command, standsurv. Results Reporting such measures facilitate interpretation of a competing risks analysis, particularly when the proportional hazards assumption is not appropriate. Standardisation provides a useful way to obtain marginal estimates to make absolute comparisons between two covariate groups. Predictions can be made at various time-points and presented visually for each cause of death to better understand the overall impact of different covariate groups. Conclusions We describe estimation of RMFT, and expected life-years lost partitioned by each competing cause of death after fitting a single FPM on either the log-cumulative subdistribution, or cause-specific hazards scale. These can be used to facilitate interpretation of a competing risks analysis when the proportionality assumption is in doubt.


2021 ◽  
Vol 30 ◽  
Author(s):  
J. K. N. Chan ◽  
C. S. M. Wong ◽  
N. C. L. Yung ◽  
E. Y. H. Chen ◽  
W. C. Chang

Abstract Aims Bipolar disorder is associated with premature mortality, but evidence is mostly derived from Western countries. There has been no research evaluating shortened lifespan in bipolar disorder using life-years lost (LYLs), which is a recently developed mortality metric taking into account illness onset for life expectancy estimation. The current study aimed to examine the extent of premature mortality in bipolar disorder patients relative to the general population in Hong Kong (HK) in terms of standardised mortality ratio (SMR) and excess LYLs, and changes of mortality rate over time. Methods This population-based cohort study investigated excess mortality in 12 556 bipolar disorder patients between 2008 and 2018, by estimating all-cause and cause-specific SMRs, and LYLs. Trends in annual SMRs over the 11-year study period were assessed. Study data were retrieved from a territory-wide medical-record database of HK public healthcare services. Results Patients had higher all-cause [SMR: 2.60 (95% CI: 2.45–2.76)], natural-cause [SMR: 1.90 (95% CI: 1.76–2.05)] and unnatural-cause [SMR: 8.63 (95% CI: 7.34–10.03)] mortality rates than the general population. Respiratory diseases, cardiovascular diseases and cancers accounted for the majority of deaths. Men and women with bipolar disorder had 6.78 (95% CI: 6.00–7.84) years and 7.35 (95% CI: 6.75–8.06) years of excess LYLs, respectively. The overall mortality gap remained similar over time, albeit slightly improved in men with bipolar disorder. Conclusions Bipolar disorder is associated with increased premature mortality and substantially reduced lifespan in a predominantly Chinese population, with excess deaths mainly attributed to natural causes. Persistent mortality gap underscores an urgent need for targeted interventions to improve physical health of patients with bipolar disorder.


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