Development of a Nomogram for Predicting the Cumulative Incidence of Disease Recurrence of AML After Allo-HSCT.
Development of a Nomogram for Predicting the Cumulative Incidence of Disease Recurrence of AML After Allo-HSCT.
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开发列线图来预测 Allo-HSCT 后 AML 疾病复发的累积发生率
DOI:
10.3389/fonc.2021.732088
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发表时间:
2021
影响因子:
4.7
通讯作者:
Xu Y
中科院分区:
文献类型:
--
作者:
Zhang T;Bao X;Qiu H;Tang X;Han Y;Fu C;Sun A;Ruan C;Wu D;Chen S;Xu Y
Using targeted exome sequencing, we studied correlations between mutations at diagnosis and transplant outcomes in 332 subjects with acute myeloid leukemia (AML) receiving allotransplantation. A total of 299 patients (299/332, 90.1%) had at least one oncogenic point mutation. In multivariable analyses, pretransplant disease status, minimal residual disease (MRD) before transplantation (pre-MRD), cytogenetic risk classification, and TP53 and FLT3-ITD high ratio mutations were independent risk factors for AML recurrence after allotransplantation (p < 0.05). A nomogram for the cumulative incidence of relapse (CIR) that integrated all the predictors in the multivariable model was then constructed, and the concordance index (C-index) values at 6, 12, 18, and 24 months for CIR prediction were 0.754, 0.730, 0.715, and 0.690, respectively. Moreover, calibration plots showed good agreements between the actual observation and the nomogram prediction for the 6, 12, 18, and 24 months posttransplantation CIR in the internal validation. The integrated calibration index (ICI) values were 0.008, 0.055, 0.094, and 0.136 at 6, 12, 18, and 24 months posttransplantation, respectively. With a median cutoff score of 9.73 from the nomogram, all patients could be divided into two groups, and the differences in 2-year CIR, disease-free survival (DFS), and overall survival (OS) between these two groups were significant (p < 0.05). Taken together, the results of our study indicate that gene mutations could help to predict the outcomes of patients with AML receiving allotransplantation.
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影响因子:
64.5
作者:
Welch JS;Ley TJ;Link DC;Miller CA;Larson DE;Koboldt DC;Wartman LD;Lamprecht TL;Liu F;Xia J;Kandoth C;Fulton RS;McLellan MD;Dooling DJ;Wallis JW;Chen K;Harris CC;Schmidt HK;Kalicki-Veizer JM;Lu C;Zhang Q;Lin L;O'Laughlin MD;McMichael JF;Delehaunty KD;Fulton LA;Magrini VJ;McGrath SD;Demeter RT;Vickery TL;Hundal J;Cook LL;Swift GW;Reed JP;Alldredge PA;Wylie TN;Walker JR;Watson MA;Heath SE;Shannon WD;Varghese N;Nagarajan R;Payton JE;Baty JD;Kulkarni S;Klco JM;Tomasson MH;Westervelt P;Walter MJ;Graubert TA;DiPersio JF;Ding L;Mardis ER;Wilson RK
通讯作者:
Wilson RK
影响因子:
20.3
作者:
Armand, Philippe;Kim, Haesook T.;Saber, Wael
通讯作者:
Saber, Wael
影响因子:
11.4
作者:
Versluis, J.;Labopin, M.;Mohty, M.
通讯作者:
Mohty, M.
影响因子:
20.3
作者:
Kim, TaeHyung;Moon, Joon Ho;Kim, Dennis Dong Hwan
通讯作者:
Kim, Dennis Dong Hwan
影响因子:
6.2
作者:
Gratwohl, Alois;Stern, Martin;Niederwieser, Dietger
通讯作者:
Niederwieser, Dietger