IMPACT OF RED BLOOD CELL TRANSFUSION RATE, ADJUSTED BY THERAPEUTIC INTERVENTIONS, ON PROGRESSION-FREE SURVIVAL IN LOWER RISK MDS PATIENTS WITHIN THE EUROPEAN LEUKEMIANET MDS REGISTRY
Author(s): ,
Louise de Swart
Affiliations:
Hematology,Radboudumc,Nijmegen,Netherlands
,
Marlijn Hoeks
Affiliations:
Centre for Clinical Transfusion Research,Sanquin Research,Leiden,Netherlands
,
Simon Crouch
Affiliations:
Epidemiology and Cancer Statistics Group, Department of Health Sciences,University of York,York,United Kingdom
,
Alexandra Smith
Affiliations:
Epidemiology and Cancer Statistics Group, Department of Health Sciences,University of York,York,United Kingdom
,
Saskia Langemeijer
Affiliations:
Hematology,Radboudumc,Nijmegen,Netherlands
,
Pierre Fenaux
Affiliations:
Service d'Hématologie,Hôpital Saint-Louis,Paris,France
,
Argiris Symeonidis
Affiliations:
Medicine, Div. Hematology,University of Patras Medical School,Patras,Greece
,
Jaroslav Čermák
Affiliations:
Clinical Hematology,Inst. of Hematology & Blood Transfusion,Praha,Czech Republic
,
Eva Hellström-Lindberg
Affiliations:
Medicine, Div. Hematology,Karolinska Institutet,Stockholm,Sweden
,
Reinhard Stauder
Affiliations:
Internal Medicine V (Haematology and Oncology),Innsbruck Medical University,Innsbruck,Austria
,
Guillermo Sanz
Affiliations:
Haematology,Hospital Universitario La Fe,Valencia,Spain
,
Moshe Mittelman
Affiliations:
Medicine A,Tel Aviv Sourasky (Ichilov) Medical Center,Tel Aviv,Israel
,
Mette Skov Holm
Affiliations:
Haematology,Aarhus University Hospital,Aarhus ,Denmark
,
Luca Malcovati
Affiliations:
Hematology Oncology, Fondazione IRCCS Policlinico San Matteo,University of Pavia,Pavia,Italy
,
Krzysztof Madry
Affiliations:
Haematology, Oncology and Internal Medicine,Warszawa Medical University,Warszawa,Poland
,
Ulrich Germing
Affiliations:
Haematology, Oncology and Clinical Immunology,Universitätsklinik Düsseldorf,Düsseldorf,Germany
,
Aleksandar Savic
Affiliations:
Clinic of Hematology - Clinical Center of Vojvodina,Faculty of Medicine,Novi Sad,Serbia
,
António Medina Almeida
Affiliations:
Hematology,Instituto Português de Oncologia de Lisboa,Lisboa,Portugal
,
Agnes Guerci-Bresler
Affiliations:
Service d'Hématologie,CHU Brabois Vandoeuvre,Nancy,France
,
Raphael Itzykson
Affiliations:
Service d'Hématologie,Hôpital Saint-Louis,Paris,France
,
Odile Beyne-Rauzy
Affiliations:
Service de Medecine Interne,CHU Toulouse,Toulouse,France
,
Dominic Culligan
Affiliations:
Haematology,Aberdeen Royal Infirmary,Aberdeen,United Kingdom
,
Corine van Marrewijk
Affiliations:
Hematology,Radboudumc,Nijmegen,Netherlands
,
Nicole Blijlevens
Affiliations:
Hematology,Radboudumc,Nijmegen,Netherlands
,
David Bowen
Affiliations:
St. James's Institute of Oncology,Leeds Teaching Hospitals,Leeds,United Kingdom
Theo de Witte
Affiliations:
Tumor Immunology,Radboudumc,Nijmegen,Netherlands
EHA Library. de Swart L. 06/16/18; 215537; PS1233
Louise de Swart
Louise de Swart
Contributions
Abstract

Abstract: PS1233

Type: Poster Presentation

Presentation during EHA23: On Saturday, June 16, 2018 from 17:30 - 19:00

Location: Poster area

Background
 Progression-free survival (PFS) of lower-risk (LR) MDS patients treated with red blood cell transfusions (transfusions) is usually reduced, but whether this effect is caused by the actual transfusion itself remains debatable. The EUMDS Registry contains data on 2,192 newly diagnosed LR-MDS patients from 16 European countries and Israel, collected at diagnosis and at 6 months intervals.

Aims
The aim of this analysis is to assess the effect of transfusion rate on PFS.

Methods
The cumulative dose received at the end of each interval was divided by the time since the start of the first RBCT to give an overall dose density in that period. Dose density rises over time when transfusion rate increases over time, but declines when a patient becomes RBCT independent after treatment. PFS was adjusted by relevant confounders, including age, gender, self-reported patient condition (proxied by EQ-5D index), and number of cytopenias at diagnosis, using Cox regression with time-varying covariates.

Results
We analysed a cohort of 1,273 patients with all relevant data available. Within this group 669 patients received transfusions after registration. Univariate analysis of the 669 transfused patients showed a strong association of age (p < 4 x 10-4) with PFS. The EQ-5D index, baseline MDS diagnosis, bone marrow percentage and number of cytopenias were all associated with PFS in univariate regression. The dose density was associated with PFS (p <1 x 10-4) with a significant non-linear component (p <1 x 10-4). The following variables were entered into multivariate regression analysis: transfusion dose density, diagnostic age, number of transfusions received before diagnosis, EQ-5D index, bone marrow blast percentage and cytogenetic category. All variables entered in the regression retained statistical significance. The functional form of the dose density effect (p = 0.009) is shown in Figure 1A. The dose density had an increasing effect until a dose density of about one unit/month. Thereafter, the effect leveled off. Treatment with ESAs, lenalidomide and iron chelators may improve erythropoiesis and reduce the need for RBCT, resulting in a gradual decrease of the subsequent RBCT dose densities in intervals during the response period. Patients, treated with ESA, lenalidomide, or iron chelators, showed a decrease of transfusion density in 22%, 53% and 40% of the patients, respectively. The observed patterns of dose density trajectories suggest that receipt of ESA, lenalidomide and iron chelation modulate the dose density and therefore, we included these variables as confounding variables in the regression model. This analysis showed that the impact of the dose density remained similar to the previous analyses, but in contrast the dose density effect continues to increase beyond 1 unit per month after correction for the three interventions (Figure 1B).

Conclusion
The multivariate regression models showed that administration of transfusions is associated with decreased PFS when compared to non-transfused patients. The negative effect of transfusions on PFS already occurs at low transfusion densities below 1 unit per month. This indicates that the transfusion dependency, even at relatively low rate, may be considered as an indicator of poor prognosis.

Session topic: 9. Myelodysplastic syndromes – Biology & Translational Research

Keyword(s): Myelodysplasia, Red blood cell, transfusion, Transplant-related mortality

Abstract: PS1233

Type: Poster Presentation

Presentation during EHA23: On Saturday, June 16, 2018 from 17:30 - 19:00

Location: Poster area

Background
 Progression-free survival (PFS) of lower-risk (LR) MDS patients treated with red blood cell transfusions (transfusions) is usually reduced, but whether this effect is caused by the actual transfusion itself remains debatable. The EUMDS Registry contains data on 2,192 newly diagnosed LR-MDS patients from 16 European countries and Israel, collected at diagnosis and at 6 months intervals.

Aims
The aim of this analysis is to assess the effect of transfusion rate on PFS.

Methods
The cumulative dose received at the end of each interval was divided by the time since the start of the first RBCT to give an overall dose density in that period. Dose density rises over time when transfusion rate increases over time, but declines when a patient becomes RBCT independent after treatment. PFS was adjusted by relevant confounders, including age, gender, self-reported patient condition (proxied by EQ-5D index), and number of cytopenias at diagnosis, using Cox regression with time-varying covariates.

Results
We analysed a cohort of 1,273 patients with all relevant data available. Within this group 669 patients received transfusions after registration. Univariate analysis of the 669 transfused patients showed a strong association of age (p < 4 x 10-4) with PFS. The EQ-5D index, baseline MDS diagnosis, bone marrow percentage and number of cytopenias were all associated with PFS in univariate regression. The dose density was associated with PFS (p <1 x 10-4) with a significant non-linear component (p <1 x 10-4). The following variables were entered into multivariate regression analysis: transfusion dose density, diagnostic age, number of transfusions received before diagnosis, EQ-5D index, bone marrow blast percentage and cytogenetic category. All variables entered in the regression retained statistical significance. The functional form of the dose density effect (p = 0.009) is shown in Figure 1A. The dose density had an increasing effect until a dose density of about one unit/month. Thereafter, the effect leveled off. Treatment with ESAs, lenalidomide and iron chelators may improve erythropoiesis and reduce the need for RBCT, resulting in a gradual decrease of the subsequent RBCT dose densities in intervals during the response period. Patients, treated with ESA, lenalidomide, or iron chelators, showed a decrease of transfusion density in 22%, 53% and 40% of the patients, respectively. The observed patterns of dose density trajectories suggest that receipt of ESA, lenalidomide and iron chelation modulate the dose density and therefore, we included these variables as confounding variables in the regression model. This analysis showed that the impact of the dose density remained similar to the previous analyses, but in contrast the dose density effect continues to increase beyond 1 unit per month after correction for the three interventions (Figure 1B).

Conclusion
The multivariate regression models showed that administration of transfusions is associated with decreased PFS when compared to non-transfused patients. The negative effect of transfusions on PFS already occurs at low transfusion densities below 1 unit per month. This indicates that the transfusion dependency, even at relatively low rate, may be considered as an indicator of poor prognosis.

Session topic: 9. Myelodysplastic syndromes – Biology & Translational Research

Keyword(s): Myelodysplasia, Red blood cell, transfusion, Transplant-related mortality

By clicking “Accept Terms & all Cookies” or by continuing to browse, you agree to the storing of third-party cookies on your device to enhance your user experience and agree to the user terms and conditions of this learning management system (LMS).

Cookie Settings
Accept Terms & all Cookies