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Eutos long-term survival score discriminates different Sokal score categories in chronic myeloid leukemia patients, showing better survival prediction. Analysis of the GIMEMA CML observational study
After reading the study by Pfirrmann et al. [1], the aim of our present analysis was to support the ELN evidence, by comparing the ELTS score with the Sokal score in a large dataset of patients drawn from the GIMEMA observational study; among these only 70 patients were previously enrolled in the EUTOS project. The retrospective/prospective GIMEMA observational study started enrollment in January 2012 and at the time of this study, data were available until May 2020. In the prospective cohort, definitive information about firstline treatment was available in 1206 patients: of these, 608 received imatinib and 598 dasatinib or nilotinib (2gen TKIs). Overall, median age of the whole cohort was 60 years (range 48–77, 51.9% over 60), with a prevalence of males (60.3%). The 3-year OS of the whole cohort was 93%. Only 21 CML-related deaths were recorded and 51 for other causes: the present analysis is focused on the prediction of OS and not on the probability of CML-related death. According to the Sokal score, 35% were stratified as low, 44.9% intermediate and 17.4% as high risk. Median follow-up of the whole cohort was 24.7 months (range 13.3–39.3). A difference in OS was observed in the 2gen TKIs cohort (93.8%) compared to imatinib-treated cohort (75.8%). A comparison between the Sokal and the ELTS score was made according to firstline TKIs. Both the scores were able to identifies differences in OS prediction in imatinib cohort (high versus low Sokal, p = 0.0017 and high versus low ELTS p < 0.0001) and in 2gen TKIs cohort (high versus low Sokal, p = 0.0382 and high versus low ELTS p = 0.0013). In the imatinib cohort, 164 patients were identified as low Sokal risk: the ELTS score identifies 152/164 patients as low risk, 11 as intermediate and 1 patient as high, thus yielding a 92.6% percentage of concordance. The Sokal score included 340 intermediate patients: the ELTS concordance is only for 170 patients (50%), whereas 129 were identified as low risk, and 41 patients as high score. The high Sokal risk classification comprised 89 patients: 37 (41.5%) were reclassified as high ELTS risk, 22 patients as low and 30 patients as intermediate ELTS risk. In a similar manner, we stratified newly diagnosed patients treated with 2gen TKIs. Of 261 patients identified as low Sokal risk, 238 patients remained low risk according to the ELTS score, 16 as intermediate, and 6 patients as high risk, showing a 91% level of concordance (Table 1). The Intermediate Sokal risk classification included 201 patients: only 76 patients were confirmed as intermediate by ELTS, whereas 117 patients were low risk and 8 high risk, thus yielding a concordance level of only 37.8%. Finally, 121 patients were classified as at high Sokal risk at presentation: of them 51 were reclassified with a high ELTS score (42% concordance), whereas 34 were low and 36 patients were intermediate ELTS risk. Therefore, in the low Sokal risk overall population, the ELTS stratification confirmed a concordance of low risk in 92% of patients, whereas the concordance between intermediate Sokal and ELTS was 45.4% and between high Sokal and ELTS was 42%. We calculated the corresponding OS within the groups redefined after ELTS stratification for imatinib treatment: in the low Sokal/low ELTS population 3-year OS was 93.1% (95% CI 83.5–97.2), whereas in the intermediate Sokal/Low ELTS the 3-year OS was 93.8% (95% CI 85.2–97.5) and in the high Sokal/low ELTS 83.9% (95% CI 49.4–95.7). A similar stratification of patients treated with second-generation TKIs showed a 3-year OS of 99% (95% CI 96.1–99.8), 97% (95% CI 97.4–99.3) and 100%, respectively, showing that second-generation TKIs can overcome the adverse prognostic role of a high-risk Sokal classification. In the intermediate ELTS subset treated with imatinib, for low Sokal risk patients the 3-year OS was 100%, for intermediate Sokal 83.4% (95%CI 27.3–97.5) and for high Sokal risk patients 83.3% (95% CI 27.3–97.5%). In the second-generation TKIs-treated patients the 3-year OS was 91.7% (95% CI 53.9–98.8), 95.8% (95% CI 84.3–98.9) and 92.3% (95% CI 72.6–98), respectively. Indeed, in the high ELTS risk subset, none of the patients were initially stratified as low Sokal risk in the imatinib-treated group, whereas the 3-year OS of high ELTS/intermediate Sokal was 67.8% (95% CI 42.7–83.8) and for high ELTS/high Sokal 75.4% (95% CI 54.3–87.8). In the second-generation TKIs cohort the risk was 100%, 80% (95% CI 20.4–90.6) and 87.4% (95% CI 72.1–94.6), respectively.
Table 1 Redistribution according to the ELTS score.
The use of ELTS score was suggested by ELN recommendations and validated by several groups [2,3,4,5]. Recently, the EUTOS group reported a validation of the ELTS score in 2949 CML patients, 236 of whom died, 89 of CML-related causes [1]. The overall probability of CML-related death was 5%: with the ELTS score both the intermediate and high-risk groups had significantly higher probabilities of dying of the disease as compared to high-risk only patients according to the Sokal score. In accordance with these findings, we showed a significant prognostic refinement passing from the Sokal to the ELTS score: in the high-risk Sokal group, 3-year OS ranged from 94.8% to 82.4% for patients considered as “true” high risk. Similar findings of a refined prognosis were found for intermediate Sokal risk patients, in which high-risk patients were shown to have a 3-year OS of only 70.7% as compared to 95.4% for low risk and 87.9% for “true” intermediate risk patients.
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References
Pfirrmann M, Clark RE, Prejzner W, Lauseker M, Baccarani M, Saussele S, et al. The EUTOS long-term survival (ELTS) score is superior to the Sokal score for predicting survival in chronic myeloid leukemia. Leukemia. 2020;34:2138–49.
Pfirrmann M, Baccarani M, Saussele S, Guilhot F, Cervantes F, Ossenkoppele G, et al. Prognosis of long-term survival considering disease-specific death in patients with chronic myeloid leukemia. Leukemia. 2016;30:48–56.
Hochhaus A, Baccarani M, Silver RT, Schiffer C, Apperley JF, Cervantes F, et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia. 2020;34:966–84.
Molica M, Canichella M, Alunni Fegatelli D, Colafigli G, Massaro F, Latagliata R, et al. The Eutos long-term survival score accurately predicts the risk of death in chronic myeloid leukaemia patients treated outside of clinical trials. Am J Hematol. 2017;92:e661–e664.
Geelen IGP, Sandin F, Thielen N, Janssen JJWM, Hoogendoorn M, Visser O, et al. Validation of the EUTOS long-term survival score in a recent independent cohort of “real world” CML patients. Leukemia. 2018;32:2299–303.
Department of Translational and Precision Medicine, Az. Policlinico Umberto I-Sapienza University, Rome, Italy
Massimo Breccia
Hematology Unit, Az Ospedaliero Universitaria Città’ della Salute e della Scienza, Torino, Italy
Patrizia Pregno
Institute of Hematology “L. and A. Seràgnoli”, Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, “S. Orsola-Malpighi” Hospital, Bologna, Italy
Fausto Castagnetti
Department of Medicine, Section of Hematology, University of Verona, Verona, Italy
Massimiliano Bonifacio
Division of Hematology and BMT, Department of Medical Area, University of Udine, Udine, Italy
Mario Tiribelli
Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
MB received honoraria from Novartis, Incyte, Pfizer, BMS/Celgene, AbbVie; PP received honoraria from Novartis, Incyte, Pfizer; FC received honoraria from Novartis, BMS, Pfizer, Incyte; GS received honoraria from Novartis, Incyte, Pfizer; all the others declare no conflict of interest
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