A precision medicine classification for treatment of acute myeloid leukemia in older patients

Alice S Mims, Jessica Kohlschmidt, Uma Borate, James S Blachly, Shelley Orwick, Ann-Kathrin Eisfeld, Dimitrios Papaioannou, Deedra Nicolet, Krzysztof Mrόzek, Eytan Stein, Bhavana Bhatnagar, Richard M Stone, Jonathan E Kolitz, Eunice S Wang, Bayard L Powell, Amy Burd, Ross L Levine, Brian J Druker, Clara D Bloomfield, John C Byrd, Alice S Mims, Jessica Kohlschmidt, Uma Borate, James S Blachly, Shelley Orwick, Ann-Kathrin Eisfeld, Dimitrios Papaioannou, Deedra Nicolet, Krzysztof Mrόzek, Eytan Stein, Bhavana Bhatnagar, Richard M Stone, Jonathan E Kolitz, Eunice S Wang, Bayard L Powell, Amy Burd, Ross L Levine, Brian J Druker, Clara D Bloomfield, John C Byrd

Abstract

Background: 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.

Methods: 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.

Results: 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%.

Conclusions: 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).

Keywords: Acute myeloid leukemia; Cytogenetics; Mutation; Outcome; Precision medicine.

Conflict of interest statement

The authors declare no conflicts of or competing interest.

Figures

Fig. 1
Fig. 1
Genetic group assignment algorithm. Patients were assigned to a genetic group with initial run-through of the algorithm based on cytogenetic features or molecular mutational clones with VAF ≥ 0.3. For patients not assigned to any genetic group during the initial stratification, a second run-through of the algorithm was performed with assignment after assessing for a mutational clone with VAF ≥ 0.2. CBF, Core-Binding Factor; Complex, Complex karyotype
Fig. 2
Fig. 2
Oncoprint of co-occurring mutations found in older acute myeloid leukemia patients assigned to genetic groups. The top row colors depict each genetic group as outlined in the figure. Each column represents an individual patient and each row under the top row represents a single gene mutation. For the single gene mutation rows, the red color indicates that a gene was found to be mutated in the patient, gray indicates wild-type status of the gene, and white indicates unavailable gene mutation status. DM, double mutated
Fig. 3
Fig. 3
Kaplan–Meier curves depicting the a disease-free survival and b overall survival of older patients with acute myeloid leukemia classified into genetic groups. Each genetic group is identified by color as outlined in the figure
Fig. 4
Fig. 4
Kaplan–Meier curves depicting the overall survival of older patients with acute myeloid leukemia as treated per individual CALGB regimen. Each study is identified by color as outlined in the figure

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