Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.
Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.
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作者：
治疗耐药仍然是急性髓系白血病（AML）的主要问题。我们使用受试者工作特征曲线下面积 (AUC) 来量化我们预测个体患者治疗耐药的能力，其中 AUC=1.0 表示完美预测，AUC=0.5 表示硬币翻转，使用来自 MRC/NCRI、HOVON、SWOG 和 MD 安德森癌症中心研究中接受 3+7 或更强烈标准方案诱导治疗的 4,601 名新诊断 AML 患者的数据。年龄、体能状态、白细胞计数、继发性疾病、细胞遗传学风险和 FLT3-ITD/NPM1 突变状态均与尽管没有早期死亡但未能实现完全缓解（“原发性难治性”）独立相关。然而，预测这一结果的引导校正多变量模型的 AUC 仅 0.78，表明预测能力还算不错。删除 FLT3-ITD 和 NPM1 信息仅略微降低了 AUC (0.76)。耐药性（定义为原发性难治性或短无复发生存期（RFS））的预测甚至更加困难。我们能够根据常规可用的治疗前协变量预测耐药性，这为标准疗法和新疗法之间的持续随机化提供了理论依据，并支持进一步检查遗传和治疗后数据，以优化 AML 的耐药性预测。
Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver operator characteristic curves (AUC) to quantify our ability to predict therapeutic resistance in individual patients where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4,601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in MRC/NCRI, HOVON, SWOG, and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk, and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death (“primary refractoriness”). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival (RFS), was even more difficult. Our ability to forecast resistance based on routinely available pre-treatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and post-treatment data to optimize resistance prediction in AML.
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影响因子：
20.3
作者：
Kayser, Sabine;Zucknick, Manuela;Schlenk, Richard F.
通讯作者：
Schlenk, Richard F.
影响因子：
20.3
作者：
Elliott, Michelle A.;Litzow, Mark R.;Tallman, Martin S.
通讯作者：
Tallman, Martin S.
影响因子：
45.3
作者：
Paschka, Peter;Schlenk, Richard F.;Doehner, Konstanze
通讯作者：
Doehner, Konstanze
影响因子：
7.7
作者：
Ishihara, Ryu;Yamada, Takuya;Ishiguro, Shingo
通讯作者：
Ishiguro, Shingo
DOI：
10.1056/nejmoa1005143
发表时间：
2010-12-16
期刊：
The New England journal of medicine
影响因子：
--
作者：
Ley TJ;Ding L;Walter MJ;McLellan MD;Lamprecht T;Larson DE;Kandoth C;Payton JE;Baty J;Welch J;Harris CC;Lichti CF;Townsend RR;Fulton RS;Dooling DJ;Koboldt DC;Schmidt H;Zhang Q;Osborne JR;Lin L;O'Laughlin M;McMichael JF;Delehaunty KD;McGrath SD;Fulton LA;Magrini VJ;Vickery TL;Hundal J;Cook LL;Conyers JJ;Swift GW;Reed JP;Alldredge PA;Wylie T;Walker J;Kalicki J;Watson MA;Heath S;Shannon WD;Varghese N;Nagarajan R;Westervelt P;Tomasson MH;Link DC;Graubert TA;DiPersio JF;Mardis ER;Wilson RK
通讯作者：
Wilson RK