Background: Sokal score prognosticates patients of chronic myeloid leukaemia at diagnosis. Its value has been tested in pre-imatinib era. We hypothesise that Sokal score is a useful prognostic tool to predict response to Nilotinib therapy.

Material and methods: CML patients were stratified into low, intermediate, and high Sokal score group at diagnosis. Nilotinib 300 mg twice a day was started and patients were followed up every 2 weeks for 4 weeks, then 4 monthly till 12 months, and then 4-8 weeks subsequently. Complete Haematological Response (CHR) and Major Molecular Response (MMR) were recorded at 3 months and 12 months respectively.

Results: Of 128 patients, there were 69 male (53.9%). Median age was 39 years (range, 06-68). Sokal score was low, intermediate and high in 9 (07%), 59 (46%), and 60 (47%) patients respectively. At 3 months, 89%, 88%, and 92% achieved CHR. At 12 months, 67%, 73%, and 43% achieved MMR (p-value 0.05). Fifty-seven percent patients above 40 years of age at diagnosis showed better response to Nilotinib (p-value 0.01).

Conclusion: Sokal score effectively prognosticates response to Nilotinib therapy. Most of our patients were in intermediate and high risk Sokal group. Age of patients and intermediate and high risk groups were found to be predictors of response to Nilotinib treatment.

Waheed S, Zaidi U, Maqsood S, Borhany M, Shamsi T (2017) Sokal Risk Score is a Useful Predictor of Response to Nilotinib Therapy. J Hematol Transfus 5(4): 1075.

Chronic Myeloid Leukemia (CML) is a clonal myeloproliferative neoplasm resulting from reciprocal translocation of ABL gene on chromosome 9 to BCR gene region on chromosome 22 (t [9:22]) [1,2]. This translocation leads to the formation of the BCR–ABL fusion gene which encodes an aberrant chimeric protein (BCR– ABL p210) with constitutively activated tyrosine kinase activity that promotes growth and replication through downstream pathways which influence leukemogenesis by creating a cytokine-independent cell cycle with aberrant apoptotic signals in response to cytokine withdrawal [3].

The introduction of Imatinib, first Tyrosine Kinase Inhibitor (TKIs), overturned the treatment paradigm for CML [4]. It inhibits the BCR/ABL tyrosine kinase activity by competing with ATP at the ATP binding site of BCR/ABL, leading to decreased phosphorylation of the tyrosine moieties [5,6]. However, despite the targeted treatment via Imatinib, need for TKIs with an even greated potency in comparison to Imatinib arose which led to the development of a whole new generation of drugs [7,8], eg. Nilotinib, Dasatinib, Bosutinib and Ponatinib. Nilotinib and Dasatinib have been approved as the first-line treatment of CMLCP (chronic phase) based on results of phase III trials which demonstrated better cytogenetic and molecular response as compared to Imatinib [9,10]. The advent of TKIs was found to dramatically alter the prognosis of the disease by improving the 10-year Overall Survival (OS) from 20% to astounding 80–90% [11,12].

Over the years different predictive and prognostic models have been used to risk stratify CML patients at baseline and thus far the most widely used scoring system is Sokal risk score which was developed in 1984. Later on, Hasford and Eutos scores were also introduced which were then validated as a prognostic model during treatment with Hydroxyurea, Interferon and Imatinib therapy [13]. However, the question remains that whether these scores can be applicable for the assessment of the prognosis and thus predict a response to second generation TKIs. However, National Comprehensive Cancer Network (NCCN) Guidelines recommend determination of Sokal or Hasford risk status as part of the initial diagnostic and prognostic workup of CML [14-16]. In this study, we aimed to elucidate the significance of Sokal score as a prognostic tool to predict the response to Nilotinib therapy.

It was a prospective descriptive study conducted over a period of four years. Patients of all age groups and both gender, who have been diagnosed with BCR-ABL positive CML-CP and were offered Nilotinib as frontline treatment at our center, were included in this study. Informed consent was taken from all patients. Patients in accelerated and blast phase of CM or those who had been treated with any other TKI previously were excluded from the study. The diagnosis of CML was established on the basis of characteristic peripheral smear or bone marrow biopsy findings along with the documentation of Philadelphia chromosome on conventional karyotyping and/or BCR-ABL rearrangement by Real Time-Polymerase Chain Reaction (RT-PCR). Chronic phase was defined as peripheral blood leucocytosis demonstrating bimodal peak of neutrophils and myelocytes, basophilia and less than 10% blasts in peripheral blood or bone marrow aspirate.

Spleen size and biochemical parameters of all the patients were recorded at baseline. All patients received oral Nilotinib 300mg twice daily. Complete blood count was monitored fortnightly for the first month and then monthly till the patient achieved complete hematological response and every 2 months thereafter.

In accordance to the European Leukemia Net (ELN) recommendations 2013, haematological response was evaluated at 3 months after the commencement of therapy, whereas molecular response was assessed at 12 months of treatment [17]. Complete Haematological Response (CHR) was defined as platelet count of less than 450x109 /L, WBC count of less than 10 x 109 /L with the differential displaying basophils less than 5% and an absence of immature granulocytes and a non-palpable spleen. Major Molecular Response (MMR) was defined as BCR-ABL1 transcripts level less than 0.1% via Real Time-PCR. Treatment failure was defined as not achieving CHR after 3 months or MMR not achieved after 12 months of treatment.

TKI domain mutation analysis was done in 15 patients who resistant to therapy by Amplification-Refractory Mutation System (ARMS-PCR). Sokal score was calculated at the time of diagnosis for risk stratification by using four clinical variables (i.e. age, size of spleen, percentage of blast cells and platelet count). Calculation was done by entering data in the following equation.

11 Exp [0.116 (age- 43.4)] +0.0345 (spleen size-7.51) +0.188 [(platelets/700)2-0.563] +0.0887 (blast %-2.10) [18].

This classification divides patients into three risk groups: low risk group (Sokal score 1.2).

Statistical analysis

All data was computed with SPSS (Statistical Package for Social Sciences) statistical software version 23. Data was presented as mean, standard deviation, median values, ranges and percentages. Chi-square test was applied to compare differences between categorical variables. P value <0.05 was considered as significant. Overall response rate was calculated using Sokalscoring system. Age and duration of Nilotinib treatment were also analyzed as prognostic factors in all patients.

A total of one hundred and twenty eight patients were treated with Nilotinib over a period of four years. The demographic characteristics of patients are described in Table 1.

The median age at diagnosis was 39 years (range, 6-68 years) while male to female ratio was 1:1. Majority of patients presented with either a complaint of abdominal discomfort, fever or an incidental finding of leucocytosis in Complete Blood Count (CBC). At the time of presentation, 91 patients (65%) had splenomegaly. Mean haemoglobin level was 10.3 ± 8.2 g/dl, mean WBC count 201.2 ± 330.7 x 109 /L and mean platelet count 465 ± 308 x109 /L. The mean blast and basophil count was 4% and 5% respectively. All patients were followed for a median duration of 30 months. Of 128 patients, 9 (7%) were in low risk group, 59 (46%) were in intermediate risk group and 60 (47%) were in high risk group.

Out of 128 patients who completed 3 months of continuous treatment, 115 (90%) achieved complete haematological response while at 12 months Major Molecular Response (MMR) was observed in 80 patients (62.5%). Haematological and molecular responses are listed in Table 2.

Two patients achieved delayed hematological response after 5 months. Molecular response rate among patients with low versus intermediate/high Sokal risk group was found to be statistically significant (p-value <0.05) and is listed in Table 3. None of the patient with low risk Sokal score had treatment failure, whereas 11 and 21 patients, in intermediate and high Sokal risk groups respectively, failed to achieve optimal response after 12 months of treatment. Impact of other risk factors such as age and treatment duration on the achievement of MMR was also calculated and is highlighted in Table 3.

TKI domain mutation analysis was done in 15 patients who belonged to the intermediate and high risk Sokal group, out of which 9(67%) showed T315I mutation while 1 patient had E255K mutation. Two (2%) patients transformed into accelerated phase and 1(1%) transformed in to blast phase. Out of 128 patients, two patients expired.

Nilotinib treatment has been reported to have a favorable overall impact on survival and early molecular response [19]. Various studies have validated the importance of Sokal scoring system in response to interferon alpha and imatinib [20]. However, to the best of our knowledge, none of the previous data has computed the response to newer TKIs like Nilotinib. In this study, we evaluated the efficacy of Nilotinib as first-line treatment in CML-CP and assessed if Sokal score could be used as a predictor of response to this drug.

In our study, median age was 30 years while the reported median age from the West has been 55 years, [21]. A slightly increased male preponderance was also noted in another study [22]. Our study reported majority of patients in intermediate or high Sokal risk group which was comparable to a regional study [23]. This might be due to thrombocytosis, massive splenomegaly as well as delay in diagnosis in most of the patients. In our analysis, 90% of the patients had complete haematological response, which is comparable to most of the studies worldwide [24]. Complete haematological response was almost same in all three Sokal risk groups in our study which is in contrast to Imatinib data that showed significant difference in haematological response rates in the three risk groups [25]. This significant difference may be due to small sample size in this risk group. There is no data available for comparison of the effect of different Sokal risk groups score on molecular response while on Nilotinib therapy. We found a significant difference in low, intermediate and high risk Sokal group patients with respect to molecular response to Nilotinib (p-value 0.05).

Overall 62% of patients had a major molecular response out of which 67% belonged to the low risk Sokal group, 73% to the intermediate risk Sokal group and 52% to the high-risk Sokal group. There was no treatment failure in low risk Sokal arm; only 3 patients had suboptimal response at 12 months, however all 3 of them achieved MMR at 18 months. Patients who had suboptimal response in intermediate and high risk Sokal group later developed complete treatment failure. Most of the patients who transformed to accelerated or blast phase were from high risk Sokal group which signifies the importance of this traditional scoring tool. Our findings were comparable to study done in India comparing different scoring tools and assessing their correlation with molecular, haematological, and cytogenetic response. Interestingly, patients older than 40 years at diagnosis were associated with higher MMR rate (p-value 0.01) which was contrary to the published regional or international studies [25].

Patients, who received Nilotinib therapy for 2 years or more, had no major impact on the rate or depth of molecular response any further. This finding highlights the fact that with Nilotinib therapy, major and deep molecular responses are achieved earlier than Imatinib Mesylate; and continuation of treatment does not improve the response rates. In the ENESTnd trial, early and deep molecular response rate was reported with Nilotinib [26]. Three out of four variables of Sokal score (spleen size, blast count and platelet count) were found to have a negative effect on the prognosis of the disease while the fourth variable i.e. age did not have any.

To conclude, we found that most patients in our study had an intermediate and high Sokal score. We found it as a useful predictor of response to Nilotinib and can be utilized in clinical setting. Age of the patient independently predicts the response. This is the first large based local study from Pakistan compiling the response of Nilotinib in CML combined with assessment of factors which can help to predict the response.

Samra Waheed had contributed in collection of patient’s data, literature search and manuscript writing. Uzma Zaidi contributed in literature search and critical evaluation. Munira Borhany helped in editing the manuscript. Tahir Shamsi critically reviewed, edited and revised the manuscript. Sidra Maqsood contributed in statistical analysis.

1.Chandra HS, Heisterkamp NC, Hungerford A, Morrissette JJ, Nowell PC, Rowley JD, et al. Philadelphia Chromosome Symposium. Commemoration of the 50th anniversary of the discovery of the Ph chromosome. Cancer Genet. 2011; 204: 171–9.

2. Lee SJ. Chronic myelogenous leukaemia. Br J Haematol. 2000; 111: 993–1009.

3. Kumar L.Chronic myelogenous leukaemia (CML): an update. Natl Med J India. 2006; 19: 255–263.

4. Dasgupta AL, Kumar L. Chronic myeloid leukaemia: A paradigm shift in management. Natl Med J India. 2014; 27: 316-323.

5. Goldman JM. How I treat chronic myeloid leukemia in the imatinib era. Blood. 2007; 110: 2828–2837.

6. Leitner AA, Hehlmann R. Modern therapy of chronic myeloid leukemia: an example for paradigma shift in Hemato-oncology. Internist (Berl). 2011; 52: 209–217.

7. Baccarani M, Castagnetti F, Gugliotta G, Palandri F, Soverini S, European Leukemia Net. Response definitions and European Leukemia net Management recommendations. Best Pract Res Clin Haematol. 2009; 22: 331–341.

8. Javier Pinilla KSLZ. Biomarkers for determining the prognosis in chronic myelogenous leukemia. Journal of Hematology & Oncology. 2013; 6–54.

9. Larson RA, Hochhaus A, Hughes TP, Clarke RE, Etienne G, Kim DW, et al. Nilotinib vs imatinib in patients with newly diagnosed Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase: ENESTnd 3-year follow-up. Leukemia. 2012; 26: 2197-2203.

10. Kantarjian HM, Hochhaus A, Saglio G, De Souza C, Flinn IW, Stenke L, et al. Nilotinib versus imatinib for the treatment of patients with newly diagnosed chronic phase, Philadelphia chromosome-positive, chronic myeloid leukaemia: 24-month minimum follow-up of the phase 3 randomised ENESTnd trial. Lancet Oncol. 2011; 12: 841–851.

11. Kantarjian H, Flinn IW, Goldberg S, Bunworasate U, Zanichelli MA, Nakamae H, et al. Nilotinib versus imatinib in patients (pts) with newly diagnosed chronic myeloid leukemia in chronic phase (CML-CP): ENESTnd 3-year (yr) follow-up. J Clin Oncol (ASCO Annual Meeting Abstracts). 2012; 30: 6509.

12. Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. 2010; 60: 277–300.

13. Bonifazi F, De Vivo A, Rosti G, Tiribelli M, Russo D, Trabacchi E, et al. Testing Sokal's and the new prognostic score for chronic myeloid leukaemia treated with alpha-interferon. Italian Cooperative Study Group on Chronic Myeloid Leukaemia. Br J Haematol. 2000; 111: 587-595.

14.Vardiman JW, Pierre R, Thiele J, Harris NL, Stein H, Campo E, et al .Chronic myelogenous leukemia World health organization classification of tumors. Pathology and genetics tumors of haemopoietic and lymphoid tissues. IARC Press. 2001: 20-26.

15. Rosti G, Palandri F, Castagnetti F, Breccia M, Levato L,Guqliotta G, et al. Nilotinib for the frontline treatment of Ph(+) chronic myeloid leukemia. Blood. 2009; 114: 4933-4938.

16. Sokal JE, Cox EB, Baccarani M, Tura S, Gomez GA, Robertson JE, et al. Prognostic discrimination in good-risk chronic granulocytic leukemia. Blood. 1984; 63: 789-799.

17. Baccarani M, Deninger MW, Rosti G, Hochaccus A, Soverini S, Apperley JF, et al. European LeukemiaNet recommendations for the management of chronic myeloid leukemia: 2013. Blood. 2013; 122: 872-884.

18. Hasford J, Ansari H, Pfirrmann M, Hehlmann R. Analysis and validation of prognostic factors for CML. German CML Study Group. Bone Marrow Transplant. 1996; 17: S49–S54.

19. Cortes J. Natural history and staging of chronic myeloid leukemia. Hematol Oncol Clin N Am. 2004; 18: 569-584.

20. Crossman LC, OÊ Brien. Imatinib therapy in chronic myeloid leukemia. Hematol Oncol Clin N Am. 2004; 18: 605-617.

21. Usman M, Syed NN, Kakepoto GN, Adil SN, Khurshid M. Chronic Phase Chronic Myeloid Leukemia: Response of Imatinib Mesylate and Significance of Sokal Score, Age and Disease Duration in Predicting the Hematological and Cytogenetic Response. JAPI. 2007; 55: 103-107.

22. Saglio G, Kim DW, Issaragrisil S, le Coutre P, Etiepagenne G, Lobo C, et al. ENESTnd Investigators. Nilotinib versus imatinib for newly diagnosed chronic myeloid leukemia. N Engl J Med. 2010; 362: 2251–2259.

23. Oyekunle AA, Osho PO, Aneke JC, Salawu L, Durosinmi MA. The predictive value of the Sokal and Hasford scoring systems in chronic myeloid leukaemia in the imatinib era. J Hemat Malignancies. 2012; 2: 25–32.

24. Kuntegowdanahalli LC, Kanakasetty GB, Thanky AH, Dasappa L, Jacob LA, Mallekavu SB, et al. Prognostic and predictive implications of Sokal, Euro and EutoS scores in chronic myeloid leukaemia in the imatinib era—experience from a tertiary oncology centre in Southern India. Ecancerm                edicalscience. 2016; 10: 679.

25. Cervantes F, Hernandez-Boluda JC, Steegmann JL, Conde E, Alvarez-Larran A, Lopez Jimenez J, et al. Imatinib mesylate therapy of chronic phase chronic myeloid leukemia resistant or intolerant to interferon: results and prognostic factors for response and progression-free survival in 150 patients. Haematologica. 2003; 88: 1117-1122.

26. Gugliotta G, Castagnetti F, Breccia M, Levato L, D’Adda M, Stagno F, et al. Long-term outcome of a phase 2 trial with nilotinib 400 mg twice daily in first-line treatment of chronic myeloid leukemia. Haematologica. 2015; 100: 1146-1150.