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A precision medicine classification for treatment of acute myeloid leukemia in older patients
Journal of Hematology & Oncology ( IF 29.5 ) Pub Date : 2021-06-23 , DOI: 10.1186/s13045-021-01110-5
Alice S Mims 1 , Jessica Kohlschmidt 1, 2, 3 , Uma Borate 1 , James S Blachly 1 , Shelley Orwick 1 , Ann-Kathrin Eisfeld 1, 3 , Dimitrios Papaioannou 1 , Deedra Nicolet 1, 2, 3 , Krzysztof Mrόzek 1, 3 , Eytan Stein 4 , Bhavana Bhatnagar 1 , Richard M Stone 5 , Jonathan E Kolitz 6 , Eunice S Wang 7 , Bayard L Powell 8 , Amy Burd 9 , Ross L Levine 4 , Brian J Druker 10 , Clara D Bloomfield 1 , John C Byrd 1, 3, 11
Affiliation  

Older patients (≥ 60 years) with acute myeloid leukemia (AML) often have multiple, sequentially acquired, somatic mutations that drive leukemogenesis and are associated with poor outcome. Beat AML is a Leukemia and Lymphoma Society-sponsored, multicenter umbrella study that algorithmically segregates AML patients based upon cytogenetic and dominant molecular abnormalities (variant allele frequencies (VAF) ≥ 0.2) into different cohorts to select for targeted therapies. During the conception of the Beat AML design, a historical dataset was needed to help in the design of the genomic algorithm for patient assignment and serve as the basis for the statistical design of individual genomic treatment substudies for the Beat AML study. We classified 563 newly diagnosed older AML patients treated with standard intensive chemotherapy on trials conducted by Cancer and Leukemia Group B based on the same genomic algorithm and assessed clinical outcomes. Our classification identified core-binding factor and NPM1-mutated/FLT3-ITD-negative groups as having the best outcomes, with 30-day early death (ED) rates of 0 and 20%, respectively, and median overall survival (OS) of > 1 year and 3-year OS rates of ≥ 20%. All other genomic groups had ED rates of 17–42%, median OS ≤ 1 year and 3-year OS rates of ≤ 15%. By classifying patients through this genomic algorithm, outcomes were poor and not unexpected from a non-algorithmic, non-dominant VAF approach. The exception is 30-day ED rate typically is not available for intensive induction for individual genomic groups and therefore difficult to compare outcomes with targeted therapeutics. This Alliance data supported the use of this algorithm for patient assignment at the initiation of the Beat AML study. This outcome data was also used for statistical design for Beat AML substudies for individual genomic groups to determine goals for improvement from intensive induction and hopefully lead to more rapid approval of new therapies. Trial registration ClinicalTrials.gov Identifiers: NCT00048958 (CALGB 8461), NCT00900224 (CALGB 20202), NCT00003190 (CALGB 9720), NCT00085124 (CALGB 10201), NCT00742625 (CALGB 10502), NCT01420926 (CALGB 11002), NCT00039377 (CALGB 10801), and NCT01253070 (CALGB 11001).

中文翻译:

老年急性髓系白血病治疗的精准医学分类

患有急性髓性白血病 (AML) 的老年患者(≥ 60 岁)通常具有多个顺序获得的体细胞突变,这些突变会驱动白血病发生并与不良结果相关。Beat AML 是白血病和淋巴瘤协会赞助的多中心综合研究,该研究根据细胞遗传学和显性分子异常(变异等位基因频率 (VAF) ≥ 0.2)在算法上将 AML 患者分离到不同的队列中,以选择靶向治疗。在 Beat AML 设计的构思过程中,需要一个历史数据集来帮助设计用于患者分配的基因组算法,并作为 Beat AML 研究的个体基因组治疗子研究统计设计的基础。我们根据相同的基因组算法在癌症和白血病 B 组进行的试验中对 563 名新诊断的接受标准强化化疗的老年 AML 患者进行分类并评估临床结果。我们的分类确定核心结合因子和 NPM1 突变/FLT3-ITD 阴性组具有最佳结果,30 天早期死亡 (ED) 率分别为 0% 和 20%,中位总生存期 (OS) 为> 1 年和 3 年 OS 率 ≥ 20%。所有其他基因组组的 ED 率为 17-42%,中位 OS ≤ 1 年和 3 年 OS 率≤ 15%。通过这种基因组算法对患者进行分类,非算法、非主导 VAF 方法的结果很差,而且并不出人意料。例外情况是 30 天 ED 率通常不适用于单个基因组组的强化诱导,因此难以将结果与靶向治疗进行比较。该联盟数据支持在 Beat AML 研究开始时使用该算法进行患者分配。该结果数据还用于针对个别基因组组的 Beat AML 子研究的统计设计,以确定强化诱导的改进目标,并有望更快地批准新疗法。试验登记ClinicalTrials.gov标识符:NCT00048958(CalgB 8461),NCT00900224(CALGB 20202),NCT00003190(CALGB 9720),NCT00085124(CALG10201),NCT00742625(CALGB 10502),NCT01420926(CALGB 11002),NCT00039377(CALGB 10801),以及NCT01253070 (CALGB 11001)。该联盟数据支持在 Beat AML 研究开始时使用该算法进行患者分配。该结果数据还用于针对个别基因组组的 Beat AML 子研究的统计设计,以确定强化诱导的改进目标,并有望更快地批准新疗法。试验登记ClinicalTrials.gov标识符:NCT00048958(CalgB 8461),NCT00900224(CALGB 20202),NCT00003190(CALGB 9720),NCT00085124(CALG10201),NCT00742625(CALGB 10502),NCT01420926(CALGB 11002),NCT00039377(CALGB 10801),以及NCT01253070 (CALGB 11001)。该联盟数据支持在 Beat AML 研究开始时使用该算法进行患者分配。该结果数据还用于针对个别基因组组的 Beat AML 子研究的统计设计,以确定强化诱导的改进目标,并有望更快地批准新疗法。试验登记ClinicalTrials.gov标识符:NCT00048958(CalgB 8461),NCT00900224(CALGB 20202),NCT00003190(CALGB 9720),NCT00085124(CALG10201),NCT00742625(CALGB 10502),NCT01420926(CALGB 11002),NCT00039377(CALGB 10801),以及NCT01253070 (CALGB 11001)。该结果数据还用于针对个别基因组组的 Beat AML 子研究的统计设计,以确定强化诱导的改进目标,并有望更快地批准新疗法。试验登记ClinicalTrials.gov标识符:NCT00048958(CalgB 8461),NCT00900224(CALGB 20202),NCT00003190(CALGB 9720),NCT00085124(CALG10201),NCT00742625(CALGB 10502),NCT01420926(CALGB 11002),NCT00039377(CALGB 10801),以及NCT01253070 (CALGB 11001)。该结果数据还用于针对单个基因组组的 Beat AML 子研究的统计设计,以确定强化诱导的改进目标,并有望更快地批准新疗法。试验登记ClinicalTrials.gov标识符:NCT00048958(CalgB 8461),NCT00900224(CALGB 20202),NCT00003190(CALGB 9720),NCT00085124(CALG10201),NCT00742625(CALGB 10502),NCT01420926(CALGB 11002),NCT00039377(CALGB 10801),以及NCT01253070 (CALGB 11001)。
更新日期:2021-06-23
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