Low-dose lenalidomide plus cytarabine in very elderly, unfit acute myeloid leukemia patients: Final result of a phase II study. (November 2017)

• Record Type: Journal Article
• Authors: Visani, Giuseppe; Ferrara, Felicetto; Di Raimondo, Francesco; Loscocco, Federica; Fuligni, Fabio; Paolini, Stefania; Zammit, Valentina; Spina, Eleonora; Rocchi, Marco; Visani, Axel; Piccaluga, Pier Paolo; Isidori, Alessandro
• Is Part Of: Leukemia research. Volume 62(2017:Nov.)
• Page Start: 77
• Page End: 83
• Publication Date: 2017-11
• Subjects: Acute myeloid leukemia -- Elderly -- Unfit -- Low-dose therapy -- Gene expression profile -- Biomarker -- Complete remission; Leukemia -- Periodicals; Leukemia -- Periodicals; Leucémie -- Périodiques; Leukemia; Periodicals; Electronic journals; Electronic journals; 616.9941905
• DOI: 10.1016/j.leukres.2017.09.019
• Languages: English
• ISSNs: 0145-2126

Abstract

Highlights: Older AML patients need novel therapeutic agents, which proves a survival advantage. A goal when testing new drugs is to predict clinical responses by biomarkers. Low-dose lenalidomide and cytarabine combo induces 36.3% CR rate and improves OS. Based on the expression of 16 genes, we predicted CR with 88% overall accuracy. In this combo CR was efficiently predicted by GEP. Abstract: Outcome for elderly patients with acute myeloid leukemia (AML) is extremely poor. Intensive induction chemotherapy is often unsuitable. Sixty-six newly diagnosed AML patients (median age: 76 years), ineligible for standard therapy, were consecutively treated with low-dose lenalidomide (10 mg/day orally, days 1–21) plus 10 mg/m 2 low-dose cytarabine, subcutaneously, twice a day (days 1–15) every six weeks, up to 6 cycles. Complete remission (CR) rate was 36.3% according to intention-to-treat. Responding patients had a longer median overall survival than non-responders (517 vs. 70 days, P < 0.001). The achievement of CR was not predicted by bone marrow blast count, cytogenetics, molecular markers, prior MDS, white blood cell count. Conversely, by studying the global gene expression profile, we identified a molecular signature, including 309 genes associated with clinical response (CR versus no CR). Based on the expression of a minimal set of 16 genes, we developed an algorithm to predict treatment response, that was successfully validated by showing an overall accuracy of 88%. We met the primary endpoint of the study, by beating the estimated successful CR rate (P1) fixed at 30%. Moreover, CR induced by this 2-drug combo was efficiently predicted by genetic profiling, identifying a biomarker that warrants validation in independent series.