More accurate cancer-related excess mortality through correcting background mortality for extra variables

2019 ◽  
Vol 29 (1) ◽  
pp. 122-136 ◽  
Author(s):  
C Touraine ◽  
N Grafféo ◽  
R Giorgi ◽  
Keyword(s):  
Colon Cancer ◽  
General Population ◽  
Excess Mortality ◽  
Relative Survival ◽  
Type Model ◽  
Extended Model ◽  
Piecewise Constant ◽  
Cancer Registry Data ◽  
Background Mortality ◽  
Expected Mortality

Relative survival methods used to estimate the excess mortality of cancer patients rely on the background (or expected) mortality derived from general population life tables. These methods are based on splitting the observed mortality into the excess mortality and the background mortality. By assuming a regression model for the excess mortality, usually a Cox-type model, one may investigate the effects of certain covariates on the excess mortality. Some covariates are cancer-specific whereas others are variables that may influence the background mortality as well. The latter should be taken into account in the background mortality to avoid biases in estimating their effects on the excess mortality. Unfortunately, the available life table might not include such variables and, consequently, might provide inaccurate values of the background mortality. We propose a model that uses multiplicative parameters to correct potentially inaccurate background mortality. The model can be seen as an extension of the frequently used Estève model because we assume a Cox-type model for the excess mortality with a piecewise constant baseline function and introduce additional parameters that multiply the background mortality. The original and the extended model are compared, first in a simulation study, then in an application to colon cancer registry data.

scholarly journals Incidence, Characteristics, and Outcome of COVID-19 in Adults on Kidney Replacement Therapy: A Regionwide Registry Study

2020 ◽  
pp. ASN.2020060875
Author(s):  
Johan De Meester ◽  
Dirk De Bacquer ◽  
Maarten Naesens ◽  
Bjorn Meijers ◽  
Marie M. Couttenye ◽  
...  
Keyword(s):  
General Population ◽  
Excess Mortality ◽  
Mortality Rates ◽  
Incidence Rates ◽  
Registry Study ◽  
Additional Risk ◽  
Mortality Burden ◽  
Kidney Replacement Therapy ◽  
Expected Mortality ◽  
Chronic Comorbidities

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection disproportionally affects frail, elderly patients and those with multiple chronic comorbidities. Whether patients on RRT have an additional risk because of their specific exposure and complex immune dysregulation is controversial.MethodsTo describe the incidence, characteristics, and outcomes of SARS-CoV-2 infection, we conducted a prospective, multicenter, region-wide registry study in adult patients on RRT versus the general population from March 2 to May 25, 2020. This study comprised all patients undergoing RRT in the Flanders region of Belgium, a country that has been severely affected by coronavirus disease 2019 (COVID-19).Results At the end of the epidemic wave, crude and age-standardized cumulative incidence rates of SARS-CoV-2 infection were 5.3% versus 2.5%, respectively, among 4297 patients on hemodialysis, and 1.4% versus 1.6%, respectively, among 3293 patients with kidney transplants (compared with 0.6% in the general population). Crude and age-standardized cumulative mortality rates were 29.6% versus 19.9%, respectively, among patients on hemodialysis, and 14.0% versus 23.0%, respectively, among patients with transplants (compared with 15.3% in the general population). We found no excess mortality in the hemodialysis population when compared with mean mortality rates during the same 12-week period in 2015–2019 because COVID-19 mortality was balanced by lower than expected mortality among uninfected patients. Only 0.18% of the kidney transplant population died of SARS-CoV-2 infection.ConclusionsMortality associated with SARS-CoV-2 infection is high in patients on RRT. Nevertheless, the epidemic’s overall effect on the RRT population remained remarkably limited in Flanders. Calculation of excess mortality and age standardization provide a more reliable picture of the mortality burden of COVID-19 among patients on RRT.

scholarly journals Patterns of Survival Among Patients With Myeloproliferative Neoplasms Diagnosed in Sweden From 1973 to 2008: A Population-Based Study

2012 ◽  
Vol 30 (24) ◽  
pp. 2995-3001 ◽  
Author(s):  
Malin Hultcrantz ◽  
Sigurdur Yngvi Kristinsson ◽  
Therese M.-L. Andersson ◽  
Ola Landgren ◽  
Sandra Eloranta ◽  
...  
Keyword(s):  
General Population ◽  
Life Expectancy ◽  
Excess Mortality ◽  
Myeloproliferative Neoplasms ◽  
Treatment Options ◽  
Large Population ◽  
Relative Survival ◽  
Population Based ◽  
Population Based Study ◽  
Over Time

PurposeReported survival in patients with myeloproliferative neoplasms (MPNs) shows great variation. Patients with primary myelofibrosis (PMF) have substantially reduced life expectancy, whereas patients with polycythemia vera (PV) and essential thrombocythemia (ET) have moderately reduced survival in most, but not all, studies. We conducted a large population-based study to establish patterns of survival in more than 9,000 patients with MPNs.Patients and MethodsWe identified 9,384 patients with MPNs (from the Swedish Cancer Register) diagnosed from 1973 to 2008 (divided into four calendar periods) with follow-up to 2009. Relative survival ratios (RSRs) and excess mortality rate ratios were computed as measures of survival.ResultsPatient survival was considerably lower in all MPN subtypes compared with expected survival in the general population, reflected in 10-year RSRs of 0.64 (95% CI, 0.62 to 0.67) in patients with PV, 0.68 (95% CI, 0.64 to 0.71) in those with ET, and 0.21 (95% CI, 0.18 to 0.25) in those with PMF. Excess mortality was observed in patients with any MPN subtype during all four calendar periods (P < .001). Survival improved significantly over time (P < .001); however, the improvement was less pronounced after the year 2000 and was confined to patients with PV and ET.ConclusionWe found patients with any MPN subtype to have significantly reduced life expectancy compared with the general population. The improvement over time is most likely explained by better overall clinical management of patients with MPN. The decreased life expectancy even in the most recent calendar period emphasizes the need for new treatment options for these patients.

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.

scholarly journals Correcting inaccurate background mortality in excess hazard models through breakpoints

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Robert Darlin Mba ◽  
◽  
Juste Aristide Goungounga ◽  
Nathalie Grafféo ◽  
Roch Giorgi
Keyword(s):  
Excess Mortality ◽  
Cancer Survival ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Relative Survival ◽  
Population Based ◽  
Deprivation Level ◽  
Parameter Estimates ◽  
Background Mortality ◽  
Proposed Model

Abstract Background Methods for estimating relative survival are widely used in population-based cancer survival studies. These methods are based on splitting the observed (the overall) mortality into excess mortality (due to cancer) and background mortality (due to other causes, as expected in the general population). The latter is derived from life tables usually stratified by age, sex, and calendar year but not by other covariates (such as the deprivation level or the socioeconomic status) which may lack though they would influence background mortality. The absence of these covariates leads to inaccurate background mortality, thus to biases in estimating the excess mortality. These biases may be avoided by adjusting the background mortality for these covariates whenever available. Methods In this work, we propose a regression model of excess mortality that corrects for potentially inaccurate background mortality by introducing age-dependent multiplicative parameters through breakpoints, which gives some flexibility. The performance of this model was first assessed with a single and two breakpoints in an intensive simulation study, then the method was applied to French population-based data on colorectal cancer. Results The proposed model proved to be interesting in the simulations and the applications to real data; it limited the bias in parameter estimates of the excess mortality in several scenarios and improved the results and the generalizability of Touraine’s proportional hazards model. Conclusion Finally, the proposed model is a good approach to correct reliably inaccurate background mortality by introducing multiplicative parameters that depend on age and on an additional variable through breakpoints.

scholarly journals Sex Differences in Mortality Among People with End-Stage Kidney Disease: Bi-National Data-Linkage Cohort Study

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Nicole L De La Mata ◽  
Grace Macleod ◽  
Patrick J Kelly ◽  
Brenda Rosales ◽  
Philip Masson ◽  
...  
Keyword(s):  
Sex Differences ◽  
General Population ◽  
Excess Mortality ◽  
Data Linkage ◽  
Relative Survival ◽  
Average Life ◽  
End Stage Kidney Disease ◽  
Life Years ◽  
Life Years Lost ◽  
End Stage

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.

scholarly journals Sex differences in mortality among binational cohort of people with chronic kidney disease: population based data linkage study

BMJ ◽  
2021 ◽  
pp. e068247
Author(s):  
Nicole L De La Mata ◽  
Brenda Rosales ◽  
Grace MacLeod ◽  
Patrick J Kelly ◽  
Philip Masson ◽  
...  
Keyword(s):  
General Population ◽  
Confidence Interval ◽  
Kidney Failure ◽  
Excess Mortality ◽  
Data Linkage ◽  
Relative Survival ◽  
Population Based ◽  
Years Of Life Lost ◽  
Female Patients ◽  
Male Patients

Abstract Objective To evaluate sex differences in mortality among people with kidney failure compared with the general population. Design Population based cohort study using data linkage. Setting The Australian and New Zealand Dialysis and Transplant Registry (ANZDATA), which includes all patients receiving kidney replacement therapy in Australia (1980-2019) and New Zealand (1988-2019). Data were linked to national death registers to determine deaths and their causes, with additional details obtained from ANZDATA. Participants Of 82 844 people with kidney failure, 33 329 were female (40%) and 49 555 were male (60%); 49 376 deaths (20 099 in female patients; 29 277 in male patients) were recorded over a total of 536 602 person years of follow-up. Main outcome measures Relative measures of survival, including standardised mortality ratios, relative survival, and years of life lost, using general population data to account for background mortality (adjusting for country, age, sex, and year). Estimates were stratified by dialysis modality (haemodialysis or peritoneal dialysis) and for the subpopulation of kidney transplant recipients. Results Few differences in outcomes were found between male and female patients with kidney failure. However, compared with the general population, female patients with kidney failure had greater excess all cause deaths than male patients (female patients: standardised mortality ratio 11.3, 95% confidence interval 11.2 to 11.5, expected deaths 1781, observed deaths 20 099; male patients: 6.9, 6.8 to 6.9, expected deaths 4272, observed deaths 29 277). The greatest difference was observed among younger patients and those who died from cardiovascular disease. Relative survival was also consistently lower in female patients, with adjusted excess mortality 11% higher (95% confidence interval 8% to 13%). Average years of life lost was 3.6 years (95% confidence interval 3.6 to 3.7) greater in female patients with kidney failure compared with male patients across all ages. No major differences were found in mortality by sex for haemodialysis or peritoneal dialysis. Kidney transplantation reduced but did not entirely remove the sex difference in excess mortality, with similar relative survival (P=0.83) and years of life lost difference reduced to 2.3 years (95% confidence interval 2.2 to 2.3) between female and male patients. Conclusions Compared with the general population, female patients had greater excess deaths, worse relative survival, and more years of life lost than male patients, however kidney transplantation reduced these differences. Future research should investigate whether systematic differences exist in access to care and possible strategies to mitigate excess mortality among female patients.

scholarly journals Correcting inaccurate background mortality in excess hazard models through breakpoints

2020 ◽  
Author(s):  
Robert Darlin Mba ◽  
Juste Aristide Goungounga ◽  
Nathalie Grafféo ◽  
Roch Giorgi
Keyword(s):  
Excess Mortality ◽  
Cancer Survival ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Relative Survival ◽  
Population Based ◽  
Deprivation Level ◽  
Parameter Estimates ◽  
Background Mortality ◽  
Proposed Model

Abstract Background : Methods for estimating relative survival are widely used in population-based cancer survival studies. These methods are based on splitting the observed (the overall) mortality into excess mortality (due to cancer) and background mortality (due to other causes, as expected in the general population). The latter is derived from life tables usually stratified by age, sex, and calendar year but not by other covariates (such as the deprivation level or the socioeconomic status) which may lack though they would influence background mortality. The absence of these covariates leads to inaccurate background mortality, thus to biases in estimating the excess mortality. These biases may be avoided by adjusting the background mortality for these covariates whenever available. Methods : In this work, we propose a regression model of excess mortality that corrects for potentially inaccurate background mortality by introducing age-dependent multiplicative parameters through breakpoints, which gives some flexibility. The performance of this model was first assessed with a single and two breakpoints in an intensive simulation study, then the method was applied to French population-based data on colorectal cancer. Results: The proposed model proved to be interesting in the simulations and the applications to real data; it limited the bias in parameter estimates of the excess mortality in several scenarios and improved the results and the generalizability of Touraine’s proportional hazards model. Conclusion: Finally, the proposed model is a good approach to correct reliably inaccurate background mortality by introducing multiplicative parameters that depend on age and on an additional variable through breakpoints.

scholarly journals Correcting inaccurate background mortality in excess hazard models through breakpoints

2020 ◽  
Author(s):  
Robert Darlin Mba ◽  
Juste Aristide Goungounga ◽  
Nathalie Grafféo ◽  
Roch Giorgi ◽  
CENSUR working survival group
Keyword(s):  
Excess Mortality ◽  
Cancer Survival ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Relative Survival ◽  
Population Based ◽  
Deprivation Level ◽  
Parameter Estimates ◽  
Background Mortality ◽  
Proposed Model

Abstract Background: Methods for estimating relative survival are widely used in population-based cancer survival studies. These methods are based on splitting the observed (the overall) mortality into excess mortality (due to cancer) and background mortality (due to other causes, as expected in the general population). The latter is derived from life tables usually stratified by age, sex, and calendar year but not by other covariates (such as the deprivation level or the socioeconomic status) which may lack though they would influence background mortality. The absence of these covariates leads to inaccurate background mortality, thus to biases in estimating the excess mortality. These biases may be avoided by adjusting the background mortality for these covariates whenever available.Methods: In this work, we propose a regression model of excess mortality that corrects for potentially inaccurate background mortality by introducing age-dependent multiplicative parameters through breakpoints, which gives some flexibility. The performance of this model was first assessed with a single and two breakpoints in an intensive simulation study, then the method was applied to French population-based data on colorectal cancer.Results: The proposed model proved to be interesting in the simulations and the applications to real data; it limited the bias in parameter estimates of the excess mortality in several scenarios and improved the results and the generalizability of Touraine’s proportional hazards model.Conclusion: Finally, the proposed model is a good approach to correct reliably inaccurate background mortality by introducing multiplicative parameters that depend on age and on an additional variable through breakpoints.

scholarly journals Postoperative cure in Iranian patients with gastric cancer: estimating the crude conditional probability in a relative survival setting in the presence of competing risks

2017 ◽  
Vol 11 (6) ◽  
pp. 461-467
Author(s):  
Fatemeh Paknazar ◽  
Mahmood Mahmoudi ◽  
Kazem Mohammad ◽  
Hojjat Zeraati ◽  
Mohammad Ali Mansournia ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
General Population ◽  
Competing Risks ◽  
Excess Mortality ◽  
Stage Iv ◽  
Relative Survival ◽  
Population Data ◽  
Old Men ◽  
Iranian Patients

AbstractBackgroundFollowing treatment, cancer patients may be clinically cured. However, they may die for reasons other than cancer, called competing risks.ObjectiveTo estimate postoperative cure while considering the competing risks in Iranian patients with gastric cancer.MethodData were obtained from the Cancer Institute of Imam Hospital in Tehran. The analysis was conducted within the framework of relative survival by fitting the data to a flexible parametric cure model, taking into account the competing risks using general population data by adjusting for age, sex, and year of diagnosis.ResultsOf the 326 patients (224 male and 102 female) whose data were included, 235 deaths (72.1%) occurred during the follow-up period. The probability of conditional cure in terms of crude ratios of dying from causes other than gastric cancer in the surviving patients increased with the passage of time, and the slope of excess mortality approached almost 0 after 7 years. The estimated cure ratios showed a variation from 69% for 50-year-old men with diagnosis at early stages (I and II) to 3% for 80-year-old women with diagnosis at stage IV.ConclusionThe ratio of patients in Iran who were estimated to die from cancer reduced significantly with the passage of time following the diagnosis, and the statistical cure point was estimated to be 7 years after diagnosis. However, aging was shown to be inversely associated. Although the same trend was observed in both sexes, we showed that men were statistically more likely to reach the cure point.

scholarly journals Excess Mortality in Low-Risk MDS Can be Explained By MDS and AML Related Causes of Death

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4385-4385
Author(s):  
Krzysztof Madry ◽  
Ge Yu ◽  
Karol Lis ◽  
Pierre Fenaux ◽  
David Bowen ◽  
...  
Keyword(s):  
Overall Survival ◽  
General Population ◽  
Board Of Directors ◽  
Research Funding ◽  
Causes Of Death ◽  
Excess Mortality ◽  
Laboratory Data ◽  
Relative Survival ◽  
Advisory Committees ◽  
The Impact

Abstract Background Data on causes of death (COD) in patients with lower-risk (LR-MDS) is limited and sometimes conflicting. In contrast to higher-risk MDS, many LR-MDS patients die from conditions associated with advanced age, not directly associated with the underlying disease. Infections and cardiovascular disorders (CVD) have been reported as frequent COD in LR-MDS, but whether the incidence is higher than in age-matched population, is not known. The EUMDS Registry has been collecting prospective observational data on LR-MDS since 2008. The comprehensive clinical and laboratory data provides a unique chance to assess the impact of LR-MDS on survival either by causes related to MDS or indirectly related to MDS by aggravation of co-morbidities. Objectives To assess the impact of MDS and associated co-morbidities on COD in patients with LR-MDS and to evaluate the COD in the whole group and across participating countries. Methods: We evaluated clinical and laboratory data of LR-MDS patients registered in EUMDS registry from 2008 to 2018. Data were obtained by 145 centers from 16 European countries and Israel. MDS related causes of death were defined as infection, bleeding, MDS progression and AML transformation. Overall survival(OS) and relative survival(RS) were estimated using the Stata program 'strel' with age, sex and country specific background obtained from national life tables for the CONCORD program. RS is a standard approach used to take into account competing causes of death by adjusting for the age and sex specific mortality in the general population, estimating the excess mortality in these patients compared to that seen in the general population of each country. Results Overall data on 2235 LR-MDS patients was available in the EUMDS registry. Of these, 822 (36,7%) patients had died at the time of analysis. Median age was 77 years and 65% of the patients were male. Nearly half of them (46.9%) were diagnosed as IPPS low risk. The MDS-Comorbidity Index was low, intermediate and high in 55.7%, 37.5% and 6.8% of patients respectively. The most common COD were those considered as related to MDS 41.7% (Table 1). Deaths due to cardiovascular and pulmonary diseases were reported in 10.1% and 4.9% respectively. Other reasons (e.g. liver, renal failure, second malignancy) were found in 18.2%. In 25% of patients, the precise reason of death remained unknown. The proportion of MDS related COD were different between participating countries with lower rates in Germany (30%), France (31.3%) and higher in Portugal (55%), Greece (55.2%) and Romania (63.1%). Median follow-up was 2.1 years (0.1-10 years). Five-year overall survival in the whole cohort was 47.1% (95% CI: 44.1%-49.9%) and 5-year relative survival (attributed to MDS/AML only) was 59.1% (95% CI:55.4%-62.5%)(Figure 1). One year overall and relative survival was 90.4% (95% CI:89.1%-91.6%) and 94.4% (95% CI:93%-95.5%) respectively. Conclusions: MDS- related complications are the most common causes of death in LR-MDS patients. Comparison of overall and relative survival supports that observation and indicates that excess mortality in LR-MDS patients can be mainly explained by MDS/AML related causes. Interestingly, the strongest influence of MDS/AML attributable deaths was observed during the first year from diagnosis. Disclosures Fenaux: Janssen: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Roche: Honoraria; Otsuka: Honoraria, Research Funding. Stauder:Teva: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Germing:Novartis: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria, Research Funding. de Witte:Novartis: Research Funding; Celgene: Honoraria, Research Funding; Amgen: Consultancy, Research Funding. Smith:Jazz Pharmaceuticals: Research Funding; Johnson & Johnson: Research Funding; Gilead Sciences: Consultancy; Novartis: Research Funding.

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