Myelodysplastic Syndromes ARTICLE Optimized EBMT transplant-specific risk score Ferrata Storti Foundation in myelodysplastic syndromes after allogeneic stem-cell transplantation Nico Gagelmann,1 Diderik-Jan Eikema,2 Matthias Stelljes,3 Dietrich Beelen,4 Liesbeth de Wreede,2 Ghulam Mufti5, Nina Simone Knelange,6 Dietger Niederwieser,7 Lone S. Friis,8 Gerhard Ehninger,9 Arnon Nagler,10 Ibrahim Yakoub-Agha,11 Ellen Meijer,12 Per Ljungman,13 Johan Maertens,14 Lothar Kanz,15 Lucia Lopez-Corral,16 Arne Brecht,17 Charles Craddock,18 Jürgen Finke,19 Jan J. Cornelissen,20 Paolo Bernasconi,21 Patrice Chevallier,22 Jorge Sierra,23 Marie Robin24 and Nicolaus Kröger1 Haematologica 2019 Volume 104(5):929-936 1 University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 2EBMT Statistics, Leiden, the Netherlands; 3University of Münster, Germany; 4Department of Bone Marrow Transplantation, West German Cancer Center, University Hospital of Essen, Germany; 5 GKT School of Medicine, London, UK; 6EBMT Data Office, Leiden, the Netherlands; 7 University Hospital Leipzig, Germany; 8Rigshospitalet, Copenhagen, Denmark; 9 Universitätsklinikum Dresden, Germany; 10Chaim Sheba Medical Center, Tel-Hashomer, Israel; 11CHU de Lille, LIRIC, INSERM U995, Université Lille2, France; 12VU University Medical Center, Amsterdam, the Netherlands; 13Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden; 14University Hospital Gasthuisberg, Leuven, Belgium; 15Universität Tübingen, Germany; 16Hospital Clínico, Salamanca, Spain; 17 Deutsche Klinik für Diagnostik, Wiesbaden, Germany; 18Centre for Clinical Haematology, Birmingham, UK; 19University of Freiburg, Germany; 20Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, the Netherlands; 21Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; 22CHU Nantes, France; 23Hospital Santa Creu i Sant Pau, Jose Carreras Leukemia Research Institute, Barcelona, Spain and 24Hopital St. Louis, Paris, France Correspondence: ABSTRACT NICOLAUS KRÖGER nkroeger@uke.uni-hamburg.de T he aim of this study was to develop and validate a clinical and trans- plant-specific prognostic score using data from a large cohort of patients with myelodysplastic syndromes reported to the European Received: July 2, 2018. Society for Blood and Marrow Transplantation registry. A Cox model was Accepted: January 9, 2019. fitted to detect clinical and transplant-related variables prognostic of out- Pre-published: January 17, 2019. come. Then, cross-validation was performed to evaluate the validity and consistency of the model. Seven independent risk factors for survival were identified: age ≥50 years, matched unrelated donor, Karnofsky Performance doi:10.3324/haematol.2018.200808 Status <90%, very poor cytogenetics or monosomal karyotype, positive cytomegalovirus status of the recipient, blood blasts >1%, and platelet Check the online version for the most updated count ≤50 x 109/L prior to transplantation. Incorporating these factors into information on this article, online supplements, and information on authorship & disclosures: a four-level risk score yielded hazard ratios for death, with low-risk (score www.haematologica.org/content/104/5/929 of 0-1) as reference, of 2.02 (95% CI: 1.41-2.90) for the intermediate-risk group (score of 2-3), 3.49 (95% CI: 2.45-4.97) for the high-risk group (score of 4-5), and 5.90 (95% CI: 4.01-8.67) for the very high-risk group (score of ©2019 Ferrata Storti Foundation >5). The score was predictive of survival, relapse-free survival, relapse, and Material published in Haematologica is covered by copyright. non-relapse mortality (P<0.001, respectively). Cross-validation yielded sig- All rights are reserved to the Ferrata Storti Foundation. Use of published material is allowed under the following terms and nificant and reproducible improvement in prognostic ability with C-statis- conditions: tics being 0.609 (95% CI: 0.588-0.629) versus 0.555 for the Gruppo Italiano https://creativecommons.org/licenses/by-nc/4.0/legalcode. Trapianto di Midollo Osseo registry and 0.579 for the Center for Blood and Copies of published material are allowed for personal or inter- nal use. Sharing published material for non-commercial pur- Marrow Transplant Research registry. Prediction was even further aug- poses is subject to the following conditions: mented after applying a nomogram using age and platelets as continuous https://creativecommons.org/licenses/by-nc/4.0/legalcode, variables showing C-statistics of 0.628 (95% CI: 0.616-0.637). In conclu- sect. 3. Reproducing and sharing published material for com- mercial purposes is not allowed without permission in writing sion, compared to existing prognostic systems, this proposed transplant- from the publisher. specific risk score offers improved performance with respect to post-trans- plant risk stratification in myelodysplastic syndromes. haematologica | 2019; 104(5) 929 N. Gagelmann et al. Introduction regulations that were applicable at the time of transplantation. All transplantation centers were required to obtain written Myelodysplastic syndromes (MDS) are a heteroge- informed consent before data registration with the EBMT in neous group of clonal hematopoietic disorders that are accordance with the 1975 Helsinki Declaration. characterized by abnormal cellular maturation resulting in cytopenia and a variable risk of progression to acute Patients leukemia.1 Allogeneic stem-cell transplantation is still the Adult patients (≥18 years) with MDS who underwent trans- only curative treatment option.2-4 In order to recommend plantation from an HLA-identical sibling or matched unrelated MDS patients for transplantation besides considering donor between 2000 to 2014 were included. Patients were eligi- only disease-specific factors, such as those proposed by ble if there was full information on their: diagnosis, donor data, the International Prognostic Scoring System (IPSS) and its cytogenetic risk, platelet count and blood blasts at transplanta- revision (IPSS-R),5,6 a valid and readily reproducible trans- tion. Cytogenetic risk was stratified based on previously estab- plant-specific scoring system is needed.7,8 lished systems.6,11 The prognostic subgroups were the following: Recently, two groups have developed prognostic sys- del(11q) and -Y (very good); del(5q), del(12p), del(20q), and nor- tems incorporating patient-specific as well as transplant- mal karyotype (good); del(7q), +8, i(17q), +19, and other inde- specific factors. The Gruppo Italiano Trapianto di Midollo pendent clones (intermediate); complex karyotype (three abnor- Osseo (GITMO) registry developed a transplantation risk malities), inv(3), del(3q), and translocations involving 3q (poor), index consisting of the following factors: age (<50 or ≥50 and very complex karyotype with more than three abnormali- years), IPSS-R score (low, intermediate, high, or very ties (very poor). Monosomal karyotype was defined as mono- high), monosomal karyotype (yes or no), refractoriness to somy of two or more chromosomes or one single autosomal chemotherapy (yes or no), and Hematopoietic Cell monosomy in the presence of other structural abnormalities.12 Transplantatiom Comorbidity Index score (HCT-CI).9 The IPSS-R was calculated prior to transplantation. In total, 1059 The resulting risk index could clearly distinguish four dif- patients met the criteria and were included in the EBMT cohort. ferent groups (low, intermediate, high, and very high) To evaluate possible selection bias, outcomes were compared with corresponding overall survival rates at 5 years of between the final cohort and remaining patients not included in 76%, 48%, 18%, and 5%. The other prognostic score, by the analysis due to missing data in the registry (n=5122). Within the Center for Blood and Marrow Transplant Research the EBMT cohort, 519 and 876 patients had full data on all fac- (CIBMTR) registry, included the following criteria: age tors included in either the GITMO or CIBMTR score. (18-29, 30-49, or ≥50 years), Karnofsky status (90-100 or <90%), cytogenetics (very good to intermediate, poor, Score development very poor or monosomal karyotype), blood blasts before The development of the transplant-specific risk score consist- transplantation (>3 or ≤3%) and platelet count before ed of two steps. First, a Cox proportional hazards model using transplantation (>50 or ≤50 x 109/L). This system also dis- backward and forward selection was used to identify significant criminated four risk groups (low, intermediate, high, and covariates for overall survival.13 Then, the hazard ratios (HR) very high) and showed corresponding overall survival obtained were classified as large (HR >1.59), intermediate (1.25< rates at 3 years of 71%, 49%, 41%, and 25%.10 Both sys- HR <1.60) and small (HR <1.25). Subsequently, a scoring rule tems resulted in relevant re-classification of patients in was defined in which large effects were assigned two points, comparison with the IPSS-R while providing only modest intermediate effects were assigned one point and small effects improvement in predictability. While neither score has were assigned zero points. Scores were grouped based on asso- been externally validated nor investigated regarding prog- ciated hazard ratios into low-, intermediate-, high-, and very nostic power in large and independent cohorts, we high–risk groups, providing group-based risk predictions for hypothesized that both scores not only vary in design MDS. A second score was developed, based on the β coefficients and follow-up but would also vary in prognostic ability derived from the model defined above, to provide individual- when applied to the same cohort.7,8 ized/patient-specific risk predictions. Second, both developed We, therefore, aimed to develop and validate a clinical scores were validated and then compared to existing systems by and transplant-specific prognostic score using data from a assessing each score’s prognostic performance. large cohort of MDS patients reported to the European Society for Blood and Marrow Transplantation (EBMT) Statistical analysis registry and to validate and compare currently existing Overall survival and relapse-free survival were estimated using systems with respect to the resulting EBMT transplant- the Kaplan-Meier method and compared with the log-rank test in specific risk score. univariable analysis. Non-relapse mortality and relapse were ana- lyzed in a competing risks framework by using the cumulative incidence estimator and the Gray test for univariable analysis.14 Methods Cox proportional hazards regression of complete data was used to develop the two new scores. Maximum likelihood from the Data source Cox model was used to establish cutoffs for continuous variables. The EBMT is a voluntary organization that comprises more Score performance was analyzed using the concordance index than 500 transplant centers, mainly from Europe. Membership (C): the probability that a patient who experienced an event had requires submission of the minimal essential data form A for all a higher risk score than a patient who did not (C >0.5 suggesting consecutive patients to a central registry from which patients predictive ability).15,16 Each system was validated using 5-fold can be identified by diagnosis of underlying disease and type of cross-validation with 100 repetitions. P values <0.05 were consid- transplantation. The information in the minimal essential data ered statistically significant. Analyses were performed using SPSS form A data is updated annually. Informed consent to transplan- for Windows version 24 (SPSS, Chicago, IL, USA) and R package tation was obtained and data were collected locally according to version 3.4.3 (The R Foundation, Vienna, Austria). 930 haematologica | 2019; 104(5) EBMT transplant-specific risk score for MDS Results blasts >1%, and platelet count ≤50 x 109/L prior to trans- plantation were assigned a score of one. Patients The overall score ranged from zero to nine, with increas- The characteristics of the patients and transplants of the ing scores indicating higher risk of death. Based on the total EBMT cohort (n=1059) are listed in Table 1. The score, four risk groups were delineated: low (0-1), interme- median follow-up was 69 months (95% CI: 62-76) and the diate (2-3), high (4-5), and very high (>5). The hazard ratio 5-year overall survival was 38.6% (95% CI: 35.4-41.7) for death (with the low-risk group as the reference) was while the relapse-free survival was 33.5% (95% CI: 30.4- 2.02 (95% CI: 1.41-2.90) for the intermediate-risk group, 36.6). 3.49 (95% CI: 2.45-4.97) for the high-risk group, and 5.90 (95% CI: 4.01-8.67) for the very high–risk group. Transplant-specific risk score Corresponding survival rates were 68.7% for the low-risk Table 2 summarizes the seven variables identified as group, 43.2% for the intermediate-risk group, 26.6% for independent predictors of overall survival in the multivari- the high-risk group, and 9.5% for the very high-risk group. able analysis: age ≥50 years, matched unrelated donor, Overall, the EBMT transplant-specific risk score was predic- Karnofsky Performance Status <90%, very poor cytogenet- tive of overall survival (P<0.001) (Figure 1). ics or monosomal karyotype, positive cytomegalovirus (CMV) status of the recipient, blood blasts >1%, and Secondary endpoints platelet count ≤50 x 109/L at the time of transplantation. A The EBMT cohort was also used to apply the developed weighted score of two was assigned to older age (≥50 years) score to all secondary objectives. The developed score and very poor cytogenetics or monosomal karyotype, (overall and in all risk groups) was associated with all sec- whereas matched unrelated donor, Karnofsky Performance ondary endpoints (P=0.001) (Table 3 and Figure 1B-D). Status <90%, positive CMV status of the recipient, blood The 5-year relapse-free survival rate was 68.4% (95% CI: Table 1. Patient and transplantation characteristics of 1059 patients continued from the previous coloum with myelodysplastic syndromes in the total EBMT cohort. Characteristics Total cohort, n (%) Platelets at transplant, x 109/L ≤ 50 382 (38) Number of patients 1059 > 50 677 (62) Age at transplant, years Revised IPSS category median (range) 56 (18 to 73) very low 32 (3) Patient’s sex low 259 (24) female 446 (42) intermediate 317 (32) male 613 (58) high 205 (20) Secondary disorder very high 86 (8) no 776 (74) unknown 150 (13) yes 201 (19) Conditioning intensity unknown 92 (7) myeloablative 336 (32) Karnofsky index, % reduced 620 (58) 90 to 100 630 (60) non-myeloablative 103 (10) < 90 252 (23) Pretreatment unknown 177(17) chemotherapy 235 (22) Comorbidity index, % hypomethylating agents 214 (20) 0 to 2 462 (44) both 42 (4) ≥3 190 (18) none 568 (54) unknown 407 (38) Graft source Cytogenetic risk bone marrow 147 (14) very good 26 (3) peripheral blood 912 (86) good 132 (13) Time to transplant, months intermediate 357 (34) median (range) 7 (0.2 to 328) poor 299 (28) Donor type very poor 45 (4) HLA-identical sibling 622 (59) monosomal karyotype 200 (19) matched unrelated 437 (41) Marrow blasts at transplant, % ≤2 Cytomegalovirus serostatus of recipient 333 (31) negative 416 (39) 2 to 5 258 (24) positive 614 (58) 5 to 10 170 (16) unknown 29 (3) > 10 114 (12) unknown 210 (17) Anti-thymocyte globulin 491 (46) Blood blasts at transplant, % Ex vivo T-cell depletion 43 (4) ≤1 929 (88) n: number; IPSS: International Prognosis Scoring System. >1 130 (12) continued in the next coloum haematologica | 2019; 104(5) 931 N. Gagelmann et al. 58.4-78.4) for the low-risk group, 43.3% (95% CI: 37.2- tinuous variables as indicated by the C-statistics of 0.628 49.4) for the intermediate-risk group, 26.0% (95% CI: (95% CI: 0.616-0.637). 20.7-31.3) for the high-risk group, and 11.5% (95% CI: 5.4-17.6) for the very high-risk group (P<0.001) (Figure 2B). The cumulative incidence of relapse and non-relapse Discussion mortality at 5 years according to risk group were, respec- tively: 16.9% and 12.8% (low-risk group), 28.2% and The major findings of this analysis can be summarized 27.7% (intermediate-risk group), 36.0% and 36.9% (high- as follows. First, seven independent risk factors (age, cyto- risk group), and 46.0% and 44.3% (very high-risk group) genetics, thrombocytopenia and increasing blood blasts at (Figure 2C,D). transplantation, Karnofsky Performance Status, donor relation, and CMV status of the recipient) could be suc- Nomogram cessfully incorporated into a transplant-specific risk score. We aimed to refine the transplant-specific risk score fur- Second, this EBMT transplant-specific risk score enabled ther by using age and platelet count at transplantation as significantly improved prediction of outcome in compari- continuous variables while the other variables remained in son with currently existing systems. their categorical structure. We provide a discrete/continu- The EBMT transplant-specific risk score presented here ous nomogram to interpolate the final score and assess an considered conventional clinically derived risk factors at individual patient’s risk in an easy manner (Figure 2). For transplantation and can thus be readily calculated. The pri- each of the seven prognostic factors, individual points are mary objective in developing this score was to improve assigned, which are subsequently summed to a total point our ability to predict survival of MDS patients after trans- scale. The final score is then translated into predicted sur- plantation; furthermore, the score was predictive of vival rates at different time points for each patient. For relapse-free survival, relapse and non-relapse mortality. instance, 55-year old patients presenting with a platelet Moreover, sub-analyses of all MDS patients in the EBMT count of 150 x 109/L, blasts ≤1%, good cytogenetics, a registry (n=6181), of whom 5122 were not included in the Karnofsky Performance Status of 90% who are seroposi- present study because of missing data, revealed a better tive for CMV and for whom an identical sibling donor is overall survival rate at 5 years for excluded patients (48%) available show estimated survival rates at 3 and 5 years of compared with that of the patients used to develop the 57% (95% CI: 51-63) and 47% (95% CI: 41-54), respec- score (39%) while non-relapse mortality was 29%, respec- tively. tively. Most patients had to be excluded because of miss- ing information regarding cytogenetics. Multiple imputa- Validation of existing systems tion of these patients revealed no difference in score per- The overall score from the CIBMTR ranged from zero formance. Collectively, the prognostic ability could be to seven and was used to define four risk categories: low improved using the proposed EBMT transplant-specific risk (0-1, n=46), intermediate risk (2-3, n=434), high risk (4-5, n=365), and very high risk (>5, n=31). The 5-year overall survival rates were 55.8% (95% CI: 39.9-71.7) for Table 2. Multivariate analysis on overall survival showing seven inde- the low-risk group, 42.3% (95% CI: 37.2-47.4) for the pendent risk factors after stepwise selection using a Cox proportional intermediate-risk group, and 27.2% (95% CI: 21.9-32.5) hazards model. for the high-risk group. Rates were not estimable in the Factor HR (95% CI) P Score very high-risk group because the median follow-up was value 42.6 months in this group while median overall survival was 11.8 months (95% CI: 3.1-20.4) (Figure 3A). The Age at transplant, years <0.001 GITMO score values ranged from zero to eight. The actu- < 50 reference al score delineated four risk-groups: low (0-1, n=81), inter- ≥ 50 1.71 (1.39-2.09) 2 mediate (2-3, n=200), high (4, n=123), and very high (>4, Blood blasts at transplant, % 0.03 n=115). The overall survival rates at 5 years were 62.7% ≤1 reference (95% CI: 51.7-73.7) for the low-risk group, 41.4% (95% >1 1.39 (1.03-1.86) 1 CI: 34.0-48.8) for the intermediate-risk group, 24.1% Platelets at transplant, x109/L 0.001 (95% CI: 15.1-33.1) for the high-risk group, and 15.8% > 50 reference (95% CI: 8.2-23.4) for the very high-risk group (Figure 3B). ≤ 50 1.46 (1.17-1.82) 1 Overall, both scores could be validated (P<0.001). Donor type <0.001 HLA-identical sibling reference Comparison of prognostic systems matched unrelated 1.39 (1.13-1.71) 1 Both existing scores from GITMO and CIBMTR were Cytogenetic risk <0.001 then compared with the developed EBMT transplant-spe- very good to poor reference cific risk score with respect to their performance regard- very poor/monosomal karyotype 1.71 (1.43-2.06) 2 ing overall survival. The CIBMTR and GITMO scores Cytomegalovirus serostatus showed modest performance, with C-statistics after of recipient <0.001 cross-validation being 0.555 (95% CI: 0.524-0.586) and negative reference 0.579 (95% CI: 0.570-0.588), whereas the IPSS-R resulted positive 1.39 (1.16-1.65) 1 in C-statistics of 0.551 (95% CI: 0.530-0.566). The devel- Karnofsky index, % <0.001 oped categorized EBMT transplant-specific risk score 90 to 100 reference showed C-statistics of 0.609 (95% CI: 0.588-0.629) indi- < 90 1.44 (1.20-1.72) 1 cating an improvement in prognostic performance, which HR: hazard ratio; CI: confidence interval. was further improved using age and platelet count as con- 932 haematologica | 2019; 104(5) EBMT transplant-specific risk score for MDS risk score while C-statistics still showed moderate power; in a sufficient number of patients, which could therefore thus, prognostic systems in MDS may be validated and not be included in the final multivariable model for the updated offering improved risk stratification if more data development of the EBMT transplant-specific risk score. become available in the registries in the future. The Karnofsky Performance Status was used instead. While another study by the EBMT assessed the prog- However, the actual performance status of a patient may nostic utility of the IPSS-R in patients following transplan- vary according to clinicians or at different times during the tation, finding modest applicability of this disease-specific transplantation evaluation. Other tools evaluating patient approach,17 we evaluated two systems that used trans- fitness, including the HCT-CI may be additionally used as plant- and patient-related approaches. The CIBMTR score they become available in larger populations. showed limited to modest performance (0.555) but result- To investigate to what extent a transplant-specific ed in an even better prognostic ability (with a concordance approach will be generally feasible, we evaluated the index up to 0.582 after cross-validation) in our cohort than prognostic power of the IPSS-R resulting in C-statistics of originally reported (0.575) while the GITMO score 0.551 (95% CI: 0.530-0.566), confirming that transplant- showed better performance (0.579). We acknowledge the specific risk stratification may enable optimized counsel- limitation of the lack of information regarding the HCT-CI ing of patients. However, although the proposed EBMT A B C D Figure 1. Kaplan-Meier analysis of survival following allogeneic stem cell transplantation in patients with myelodysplastic syndrome stratified according to each risk group of the EBMT transplant-specific risk score. (A) Overall survival. (B) Relapse-free survival. (C) Cumulative incidence of relapse. (D) Non-relapse mortality. haematologica | 2019; 104(5) 933 N. Gagelmann et al. transplant-specific risk score demonstrated improved been developed.19-21 A recent evidence synthesis of the prognostic capacity over the IPSS-R, the magnitude of this efficacy and safety of different prophylactic strategies for benefit was still moderate, suggesting that the combined CMV highlighted inconclusive results in terms of sur- use of prognostic systems may provide the most appropri- vival while CMV disease and infection could be signifi- ate prognostication, until systems with significantly better cantly reduced using antiviral agents.20 Furthermore, it is performance become available. unclear whether different prophylactic agents for graft- None of the existing scores investigated the possible versus-host disease increase the risk for CMV infection or impact of CMV on outcome. CMV is an important cause disease after transplantation. Aggregated evidence did of morbidity and mortality after allogeneic stem-cell not show an increased risk for CMV reactivation in ran- transplantation.18 During recent years, major advances domized trials on antithymocyte globulin, which was have been achieved regarding antiviral prophylactic given to 46% of our EBMT cohort, in comparison with strategies, and new sensitive diagnostic techniques have standard prophylaxis using cyclosporine and methotrex- Table 3. Transplant-specific MDS risk score prediction of relapse-free survival, non-relapse mortality and incidence of relapse. Relapse-free survival Non-relapse mortality Incidence of relapse Risk group HR (95% CI) P HR (95% CI) P HR (95% CI) P Score overall <0.001 <0.001 <0.001 low reference reference reference intermediate 2.03 (1.38-2.98) <0.001 2.08 (1.16-3.75) 0.01 1.80 (1.04-3.10) 0.03 high 3.47 (2.39-5.06) <0.001 2.99 (1.68-5.30) <0.001 2.68 (1.57-4.57) <0.001 very high 5.77 (3.85-8.66) <0.001 4.18 (2.25-7.76) <0.001 3.70 (2.09-6.55) <0.001 HR: hazard ratio; CI: confidence interval. Figure 2. Nomogram of the EBMT transplant-specific risk score: for each of the seven prognostic factors. Corresponding points are assigned, which are subsequently summed to make a total point scale. This final score is then translated into predicted survival rates at different time points for each patient. CMV: cytomegalovirus; Tx: transplantation; MK: monosomal karyotype; 12m: 12-month; 36m: 36-month; 60m: 60-month. 934 haematologica | 2019; 104(5) EBMT transplant-specific risk score for MDS A B Figure 3. Kaplan-Meier analysis of survival following allogeneic stem-cell transplantation in patients with myelodysplastic syndrome stratified according to their risk group. (A) Center for International Blood and Marrow Transplant Research (CIBMTR) registry. (B) Gruppo Italiano Trapianto di Midollo Osseo (GITMO) registry. ate or tacrolimus.22 Further analyses, however, showed Regarding conditioning regimens, the introduction of no significant impact of T-cell depletion or the presence reduced-intensity conditioning has resulted in a significant of acute graft-versus-host disease at baseline on outcome reduction of transplant-related toxicity and mortality.27 Our of antiviral prophylaxis in terms of CMV infection, sur- analysis, in line with the CIBMTR study, found at least vival or safety.20 Hence, the CMV serological status of the similar effects of reduced-intensity and myeloablative reg- transplant recipient still has a strong influence on out- imens. As with any retrospective analysis, these results are come.23 In our analysis, a positive CMV serostatus of the prone to bias. Patients perceived as being at greater risk recipient was associated with a 39% increased risk of might have been favorably treated using myeloablative death, as well as higher rates of non-relapse mortality. conditioning. In our study, patients receiving reduced- The significant impact of CMV on outcome in a multi- intensity conditioning were even older and showed a variable model in this large cohort of MDS patients sup- worse performance status than patients given myeloabla- ports further evaluation of antiviral agents, such as leter- tive conditioning. This observation is supported by a movir, affecting not only CMV infection and disease but recent prospective study by the EBMT,28 in which it was also mortality.20,21 found that the administration of reduced-intensity condi- The role of molecular genetics after transplantation has tioning before transplantation in MDS patients resulted in been investigated recently. Most studies24-26 found a nega- at least an equivalent survival trend for a better overall sur- tive impact on outcome in patients with p53 mutations vival at 2 years, whereas non-relapse mortality appeared to while one study26 suggested that p53 as well as RAS-path- be higher after using myeloablative conditioning. way mutations were mainly seen in patients carrying In conclusion, this EBMT transplant-specific risk score complex karyotypes. Although molecular genetics have could improve prediction of outcome for MDS patients not been included in any existing system and were not undergoing allogeneic stem-cell transplantation. This available in a suitable number of patients in this analysis, readily available score enables optimized clinical decision- incorporation of genomic aberrations may refine systems making with respect to allogeneic stem-cell transplanta- in the future. tion in patients with MDS. III study. Lancet Oncol. 2009;10(3): 223-232. International scoring system for evaluating References 3. Passweg JR, Baldomero H, Bader P, et al. prognosis in myelodysplastic syndromes. Hematopoietic stem cell transplantation in Blood. 1997;89(6):2079-2088. 1. Adès L, Itzykson R, Fenaux P. Europe 2014: more than 40,000 transplants 6. Greenberg PL, Tuechler H, Schanz J, et al. Myelodysplastic syndromes. Lancet. annually. Bone Marrow Transplant. Revised international prognostic scoring sys- 2014;383(9936):2239-2252. 2016;51(6):786-792. tem for myelodysplastic syndromes. Blood. 2. Fenaux P, Mufti GJ, Hellstrom-Lindberg E, et 4. Kröger N. Allogeneic stem cell transplanta- 2012;120(12):2454-2465. al. Efficacy of azacitidine compared with tion for elderly patients with myelodysplas- 7. Kröger N. Maximizing the benefit of allo- that of conventional care regimens in the tic syndrome. Blood. 2012;119(24):5632- geneic stem cell transplantation in myelodys- treatment of higher-risk myelodysplastic 5639. plastic syndromes. Semin Hematol. 2017;54 syndromes: a randomised, open-label, phase 5. Greenberg P, Cox C, LeBeau MM, et al. (3):154-158. haematologica | 2019; 104(5) 935 N. Gagelmann et al. 8. Malcovati L, Hellström-Lindberg E, Bowen Dehing-Oberije C, Lambin P. On ranking in N. Comparison of different rabbit anti-thy- D, et al. Diagnosis and treatment of primary survival analysis: bounds on the concor- mocyte globulin formulations in allogeneic myelodysplastic syndromes in adults: rec- dance index. Presented at the 21 Annual stem cell transplantation: systematic litera- ommendations from the European Conference on Neural Information ture review and network meta-analysis. Biol LeukemiaNet. Blood. 2013;122(17):2943- Processing Systems, Vancouver, British Blood Marrow Transplant. 2017;23(12): 2964. Columbia, Canada, December 3-6, 2007. 2184-2219. 9. Della Porta MG, Alessandrino EP, 17. Koenecke C, Göhring G, de Wreede LC, et 23. Ljungman P, Brand R, Hoek J, et al. Donor Bacigalupo A, et al. Predictive factors for the al. Impact of the revised International cytomegalovirus status influences the out- outcome of allogeneic transplantation in Prognostic Scoring System, cytogenetics and come of allogeneic stem cell transplant: a patients with MDS stratified according to monosomal karyotype on outcome after study by the European Group for Blood and the revised IPSS-R. Blood. 2014;123(15): allogeneic stem cell transplantation for Marrow Transplantation. Clin Infect Dis. 2333-2342. myelodysplastic syndromes and secondary 2014;59(4):473-481. 10. Shaffer BC, Ahn KW, Hu ZH, et al. Scoring acute myeloid leukemia evolving from 24. Della Porta MG, Gallì A, Bacigalupo A, et al. system prognostic of outcome in patients myelodysplastic syndromes: a retrospective Clinical effects of driver somatic mutations undergoing allogeneic hematopoietic cell multi-center study of the European Society on the outcomes of patients with myelodys- transplantation for myelodysplastic syn- of Blood and Marrow Transplantation. plastic syndromes treated with allogeneic drome. J Clin Oncol. 2016;34(16):1864-1871. Haematologica. 2015;100(3):400-408. hematopoietic stem-cell transplantation. J 11. Schanz J, Tüchler H, Solé F, et al. New com- 18. Teira P, Battiwalla M, Ramanathan M, et al. Clin Oncol. 2016;34(30):3627-3637. prehensive cytogenetic scoring system for Early cytomegalovirus reactivation remains 25. Lindsley RC, Saber W, Mar BG, et al. primary myelodysplastic syndromes (MDS) associated with increased transplant-related Prognostic mutations in myelodysplastic and oligoblastic acute myeloid leukemia mortality in the current era: a CIBMTR syndrome after stem-cell transplantation. N after MDS derived from an international analysis. Blood. 2016;127(20):2427-2438. Engl J Med. 2017;376(6):536-547. database merge. J Clin Oncol. 2012;30(17): 19. Goodrich J, Bowden R, Fisher L, Keller C, 26. Yoshizato T, Nannya Y, Atsuta Y, et al. 820-829. Schoch G, Meyers J. Ganciclovir prophylaxis Genetic abnormalities in myelodysplasia 12. Breems DA, Van Putten WL, De Greef GE, to prevent cytomegalovirus disease after and secondary acute myeloid leukemia: et al. Monosomal karyotype in acute allogeneic marrow transplant. Ann Intern impact on outcome after stem cell transplan- myeloid leukemia: a better indicator of poor Med. 1993;118(3):173-178. tation. Blood. 2017;129(17):2347-2358. prognosis than a complex karyotype. J Clin 20. Gagelmann N, Ljungman P, Styczynski J, 27. Sorror ML, Sandmaier BM, Storer BE, et al. Oncol. 2008;26(29):4791-4797. Kröger N. Comparative efficacy and safety Long-term outcomes among older patients 13. Cox DR. Regression models and life tables. J of different antiviral agents for following nonmyeloablative conditioning R Stat Soc B. 1972;34:187-220. cytomegalovirus prophylaxis in allogeneic and allogeneic hematopoietic cell transplan- 14. Fine JP, Gray RJ. A proportional hazards hematopoietic cell transplantation: a sys- tation for advanced hematologic malignan- model for the subdistribution of a compet- tematic review and meta-analysis. Biol cies. JAMA. 2011;306(17):1874-1883. ing risk. J Am Stat Assoc. 1999;94(9):496- Blood Marrow Transplant. 2018;24(10): 28. Kröger N, Iacobelli S, Franke GN, et al. 509. 2101-2109. Dose-reduced versus standard conditioning 15. Gónen M, Heller G. Concordance probabili- 21. Marty FM, Ljungman P, Chemaly RF, et al. followed by allogeneic stem-cell transplan- ty and discriminatory power in proportional Letermovir prophylaxis for cytomegalovirus tation for patients with myelodysplastic hazards regression. Biometrika. 2005;92(4): in hematopoietic-cell transplantation. N syndrome: a prospective randomized phase 965-970. Engl J Med. 2017;377(25):2433-2444. III study of the EBMT (RICMAC trial). J Clin 16. Raykar VC, Steck H, Krishnapuram B, 22. Gagelmann N, Ayuk F, Wolschke C, Kröger Oncol. 2017;35(19):2157-2164. 936 haematologica | 2019; 104(5)