File size: 14,791 Bytes
76eb942 bf53ff6 0b7b4ed bf53ff6 cac43bb 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 cac43bb 0b7b4ed bf53ff6 0b7b4ed bf53ff6 cac43bb 0b7b4ed bf53ff6 cac43bb bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 0b7b4ed bf53ff6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
Age (years),Gender,Ethnicity,Type of Leukemia,ECOG,Risk Assesment,"WBCs on Admission
( x10^9/L)",Hb on Admission (g/L),LDH on Admission (IU/L),MDx Leukemia Screen 1,Pre-Induction bone marrow biopsy blasts %,Date of 1st Bone Marrow biopsy (Date of Diagnosis),Post-Induction MRD,Date of 1st CR,First_Induction,death_date,last_followup_date,Thrombocytopenia,Bleeding,B Symptoms,Lymphadenopathy,CNS Involvement,Extramedullary Involvement,fish_inv16/cbfb_myh11,fish_t8;21/runx1_runx1t1,fish_t15;17/PML-RARA,fish_KMT2A-MLL/11q23,fish_BCR-ABL1/t9;22,fish_ETV6-RUNX1/t12;21,fish_TCF3_PBX1/t1;19,fish_IGH/14q32rearr,fish_CRLF2 rearr,fish_NUP214/9q34,fish_Other,fish_del7q/monosomy7,fish_TP53/del17p,fish_del13q,fish_del11q,Number of FISH alteration,ngs_FLT3,ngs_NPM1,ngs_CEBPA,ngs_DNMT3A,ngs_IDH1,ngs_IDH2,ngs_TET2,ngs_TP53,ngs_RUNX1,ngs_Other,ngs_spliceosome,No. of ngs_mutation
39,Female,Palestine,AML,0.0,Adverse,129.0,84,2869.0,Normal,65.0,,Negative,,3+7+MIDOSTARUIN,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,2
51,Male,Egypt,AML,0.0,Intermediate,174.9,110,711.0,Negative,91.0,,Positive,,3 + 7 ,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,2
37,Female ,India ,AML,0.0,Adverse,5.72,86,292.0,Negative,70.0,,Positive,,3 + 7 ,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
22,Female,United Arab Emirates,AML,4.0,adverse,54.7,98,570.0,Negative,87.0,,,,3 + 7 ,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,2
72,Male,Palestine,Secondary AML,3.0, Adverse,48.0,68,350.0,Negative,90.0,,,,HMA,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,3
74,Male,Sudan,APL,0.0,Adverse,23.82,111,427.0,t(15;17),88.0,,,,ATO+ATRA,,,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,1
47,Male,India,Secondary AML,0.0, adverse,3.12,63,523.0,Negative,56.0,,,,3 + 7 ,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,4
35,Female,Syria,AML,0.0, adverse,1.2,65,300.0,Negative,85.0,,Negative,,3+7+TKI,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,3
48,Female,Philippine,T-ALL,0.0,Favourable,4.2,113,170.0,,0.0,,,,HCVAD,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
34,Male,Nepal,B-ALL,0.0,Adverse,1.24,100,286.0,Negative,80.0,,,,HCVAD,,,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
44,Male,India,APL,0.0,Favourable,2.54,59,350.0,t(15;17),61.0,,,,ATO+ATRA,,,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,1,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0
82,Male,United Arab Emirates ,AML,3.0, adverse,2.4,80,750.0,Negative,64.0,,,,Not fit ,,,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,3
22,Male,United Arab Emirates ,Mixed phenotype ,0.0,Adverse,31.83,141,418.0,Negative,92.0,,Negative,,HCVAD+TKI,,,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,2
37,Male,Egypt ,B-ALL,0.0,Adverse,35.4,46,265.0,t(9;12),96.0,,Negative,,HCVAD,,,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
50,Male,Pakistan ,APL,0.0,Intermediate,2.12,83,218.0,t(15;17),90.0,,,,ATO+ATRA,,,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
51,Female,United Arab Emirates ,AML,2.0,Adverse,22.4,86,338.0,Negative,,,,,Unknown,,,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,2,0,0,0,0,0,0,0,1,0,0,0,1
35,Female,Ethiopia,B-ALL,0.0,Adverse,6.6,83,707.0,t(9;22),90.0,,Positive,,Dexa+TKI,,,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
75,Female,Sudan,Secondary AML,2.0,adverse,5.19,134,297.0,Negative,41.0,,,,Aza+Ven,,,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,2,0,0,0,0,0,0,0,1,0,1,0,2
83,Male,United Arab Emirates ,AML,3.0,Intermediate,48.0,47,435.0,Negative,25.0,,,,HMA,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1
38,Male,Philippine,AML,0.0,Adverse,51.11,62,829.0,Negative,35.0,,,,Unknown,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1
74,Female,United Arab Emirates ,Secondary AML,2.0,Adverse,19.6,107,266.0,Negative,60.0,,Positive,,Aza+Ven,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1
43,Male,Pakistan ,B-ALL,0.0,Adverse,0.73,83,145.0,Negative,54.0,,Positive,,HCVAD,,,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0
58,Female,India ,Secondary AML,0.0,Adverse,123.99,78,492.0,Negative,49.0,,,,Aza+Ven,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,2
59,Female,India ,AML,0.0,Adverse,181.75,82,1197.0,Negative,80.0,,Negative,,3 + 7 ,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,4
18,Female,United Arab Emirates ,B-ALL,0.0,Favorable,14.99,108,5844.0,t(1;19),88.0,,Negative,,Pediatric protocol,,,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
58,Female,United Arab Emirates ,Secondary AML,1.0, adverse,1.3,85,330.0,Negative,10.0,, positive,,Aza+Ven,,,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,1,4,0,0,0,0,0,0,0,1,0,0,0,1
55,Male,United Arab Emirates ,AML,0.0,Favourable,16.89,81,623.0,RUNX1-RUNX1T1 ,69.0,,,,Unknown,,,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,3,0,0,0,0,0,0,0,0,0,0,0,0
43,Male,Egypt,B-ALL,1.0,Intermediate,1.0,130,351.0,Negative,86.0,,,,HCVAD,,,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0
50,Female,Syria,APL,0.0,Intermediate,4.68,66,236.0,t(15;17),90.0,,Negative,,ATO+ATRA,,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
22,Male,United Arab Emirates ,AML,0.0,Adverse,69.7,87,2408.0,"t(10;11)
",82.0,,Positive,,3 + 7 ,,,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,3,0,0,0,0,0,0,0,0,0,0,0,0
20,Male,Yemen,B-ALL,0.0,adverse,0.62,62,530.0,,80.0,, negative,, CALGB,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
40,Female,Philippine,AML,0.0,Intermediate,2.08,67,1222.0,Negative,,,,,Unknown,,,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1
42,Female,India ,B-ALL,0.0,Adverse,2.01,73,2172.0,Negative,72.0,,,,Unknown,,,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,1,0,1,9,0,0,0,0,0,0,0,0,0,0,0,0
72,Female,Yemen,AML,3.0, adverse,97.0,68,600.0,Negative,,,,,Not fit ,,,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,2,0,0,0,0,0,0,1,0,0,0,1,2
49,Male,Bangladesh,B-ALL,0.0,adverse,6.89,89,1306.0,Negative,94.0,,,,HCVAD+TKI,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0
36,Male,India ,AML,0.0,Favourable,6.72,64,318.0,inv(16),20.0,,Negative ,,3+7+GO,,,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
63,Female,United Arab Emirates ,AML,0.0,adverse,18.9,104,374.0,Negative,77.0,,Positive,,Aza+Ven,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0,0,3
41,Male,United Arab Emirates ,AML,2.0,adverse,2.03,79,563.0,Negative,65.0,,,,3 + 7 ,,,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,1,0,0,0,1
27,Male,America,B-ALL,0.0,Adverse,15.0,123,456.0,t(9;22),90.0,,,,HCVAD,,,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0
48,Male ,Bangladesh,B-ALL,0.0,Favourable,0.98,108,438.0,Normal,49.0,,,,Hyper-CVAD,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
67,Male,Bangladesh,AML,2.0,adverse,7.23,101,250.0,Negative,56.0,,,,HMA,,,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,3,0,1,0,0,0,0,0,0,0,0,0,1
39,Male ,India ,APL,0.0,Intermediate,0.71,73,320.0,t(15;17),25.0,,,,ATRA (20/6/2021) and arsenic (22/6/2021) ,,,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
31,Male ,Pakistan ,T-ALL,2.0,Favourable,9.6,123,159.0,Negative,0.0,,,,HCVAD,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
32,Male,Nepal,AML,1.0,Intermediate,1.05,75,155.0,Negative,45.0,,Negative ,,3 + 7 ,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
79,Male,Palestine,Secondary AML,3.0,Intermediate ,27.27,89,354.0,,43.0,,,,Not fit ,,,0,0,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
24,Female,India,T-ALL,0.0,adverse,236.0,36,419.0,del(9),95.0,,,, CALGB,,,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0
32,Female,United Arab Emirates ,AML,0.0,Intermediate,14.0,95,1086.0,inv(16),45.0,,,,Unknown,,,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
50,Female,India,B-ALL,0.0,adverse,416.0,57,2217.0,KMT2A-AFF1,90.0,,,,HCVAD,,,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0
44,Male,Lebanon,B-ALL,0.0,Adverse,68.35,106,818.0,t(9;22),90.0,,Negative ,,HCVAD+TKI,,,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0
62,Male,Lebanon,Secondary AML,3.0,Adverse,8.64,64,317.0,RUNX1-RUNX1T1 ,18.0,,,,Dexa+TKI,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
26,Male,United Arab Emirates ,AML,1.0,Favourable,0.96,109,149.0,Negative,21.0,,Positive,,3 + 7 ,,,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
36,Male,Pakistan ,AML,0.0,,8.37,144,431.0,,,,,,Unknown,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
79,Male,United Arab Emirates ,Mixed phenotype ,1.0, adverse,25.0,100,550.0,t(9;22),82.0,,,,Dexa+TKI,,,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
26,Male,Cameroon,B-ALL,2.0,Favourable,1.0,60,218.0,Negative,86.0,,,,Unknown,,,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
43,Male ,Syria,AML ,1.0,Favourable,58.6,131,934.0,inv(16),58.0,,Negative,,3+7+GO,,,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
20,Male,Bangladesh,T-ALL,2.0,adverse,9.61,106,499.0,,20.0,,,,HCVAD,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
75,Female ,United Arab Emirates ,AML,1.0,Intermediate,19.24,107,370.0,,68.0,,,,HMA,,,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
27,Female,Jordan,AML,0.0,Adverse,2.17,91,476.0,RUNX1-RUNX1T1,54.0,,Negative,,3 + 7 ,,,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,3,0,0,0,0,1,0,0,0,0,1,0,2
30,Male ,Eritrea,T-ALL,1.0,adverse,32.54,91,877.0,,3.0,,Negative,,HCVAD,,,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1
46,Female,Philippine,AML,0.0,Adverse,7.95,72,918.0,Negative,83.0,,,,3 + 7 ,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,0,1,1,0,0,0,0,0,0,3
28,Male,Pakistan,APL,0.0,adverse,10.89,129,224.0,t(15;17),57.0,,,,ATO+ATRA,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
56,Male,Bangladesh,B-ALL,,Favourable,2.18,74,265.0,Negative,90.0,,,,HCVAD,,,0,0,0,0,0,1,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,1,0,1
52,Female,Philippine,AML,0.0,Adverse,1.4,85,195.0,Negative,15.0,,Positive,,3+7+GO,,,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,1,0,1,0,0,1,0,0,3
23,Female,Sudan,AML,0.0,Adverse,76.8,88,247.0,t(11;17) ,74.0,,Negative,,3 + 7 ,,,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0
23,Male,Cameroon,T-ALL,0.0,Adverse,159.27,67,401.0,Negative,88.0,,Negative ,,Pediatric protocol,,,0,0,1,1,0,1,0,0,0,1,0,0,0,0,0,1,1,0,0,0,1,4,0,0,0,0,0,0,0,0,0,0,0,0
31,Male,Malaysia,AML,0.0,Adverse,5.0,71,1800.0,Negative,25.0,,Negative,,3 + 7 ,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,2,0,0,0,0,0,0,0,1,0,1,0,2
28,Male ,India ,AML,0.0,Intermediate ,93.56,73,2770.0,Normal ,90.0,,Negative ,,(3+7) & Mylotarg,,,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,3,1,0,0,0,0,0,0,0,0,0,0,1
83,Male,United Arab Emirates ,Secondary AML,1.0,Adverse,2.38,87,548.0,Negative,24.0,,,,HMA,,,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,1,1,5
32,Male,Bangladesh,AML,0.0,adverse,495.0,60,1139.0,Negative,90.0,,Positive ,,3 + 7 ,,,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1
62,Female,United Arab Emirates ,B-ALL,0.0,Adverse,2.81,83,266.0,t(9;22),90.0,,,,HCVAD+TKI,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
28,Male,Egypt,B-ALL,0.0,Adverse,21.11,44,249.0,Negative,54.0,,,,Unknown,,,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
37,Female,Philippine,AML,0.0,Intermediate,35.89,65,851.0,Negative,67.0,,,,Unknown,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,2
40,Female,Philippine,APL,0.0,Intermediate,1.02,80,174.0,t(15;17),34.0,,Positive,,ATO+ATRA,,,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1
62,Male,United Arab Emirates ,B-ALL,0.0,Adverse,3.64,99,947.0,t(9;22),62.0,,,,Dexa+TKI,,,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
35,Male,Pakistan,AML,0.0,adverse,41.05,102,391.0,Negative,57.0,,positive,,3 + 7 ,,,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,2
69,Male ,United Arab Emirates ,AML,1.0,Adverse,74.56,82,897.0,Negative,27.0,,,,Aza+Ven,,,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1
41,Female,United Arab Emirates ,Mixed phenotype ,0.0,adverse,1.4,92,255.0,Negative,49.0,,,,HCVAD,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
32,Male,Philippine,B-ALL,2.0,adverse,3.29,80,306.0,t(9;22),25.0,,Positive,, CALGB,,,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0
47,Male,Bangladesh,AML,1.0,Adverse,113.62,72,676.0,Negative,65.0,,,,Unknown,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,2
27,Male,Nepal,AML,0.0,Favourable,5.6,125,476.0,Negative,68.0,,,,Unknown,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1
51,Female,Philippine,AML,1.0,Favourable,23.3,99,177.0,Negative,79.0,,Negative,,3 + 7 ,,,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,1
42,Male,Bangladesh,AML,2.0,adverse,26.5,96,439.0,Negative,77.0,,,,Aza+Ven,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
25,Female,Somalia,AML,0.0,Favourable,42.92,81,220.0,Negative,94.0,,Negative,,3 + 7 ,,,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1
77,Male,Palestine,AML,1.0,Adverse,9.12,75,554.0,Negative,72.0,,,,Aza+Ven,,,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,3
34,Female,Indonesia,AML,0.0,Intermediate,63.96,83,557.0,Negative,82.0,,,,3 + 7 ,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
54,Female ,Philippine,B-ALL,0.0,Adverse,5.87,98,364.0,t(9;22),90.0,,,,HCVAD+TKI,,,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
17,Male,United Arab Emirates ,B-ALL,0.0,Favorable,7.68,77,350.0,Negative,59.0,,Negative,,Pediatric protocol,,,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
22,Female,Uganda,APL,4.0,Adverse,132.32,19,10000.0,t(15;17),82.0,,,,ATO+ATRA,,,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
28,Male ,United Arab Emirates ,B-ALL ,0.0,Adverse,8.7,109,535.0,t(9;22),80.0,,,,Unknown,,,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
35,Male,Bangladesh,B-ALL,0.0,Adverse,33.78,99,5000.0,t(9;22),71.0,,Negative,,HCVAD+TKI,,,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0
26,Male,Palestine,B-ALL,0.0,Adverse,17.96,119,456.0,t(9;22),90.0,,Positive,,HCVAD+TKI,,,0,0,1,0,1,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0
|