Prediction of outcomes in patients with Ph+ chronic myeloid leukemia in chronic phase treated with nilotinib after imatinib resistance/intolerance

E. Jabbour*, P. D. Le Coutre, J. Cortes, F. Giles, K. N. Bhalla, J. Pinilla-Ibarz, R. A. Larson, N. Gattermann, O. G. Ottmann, A. Hochhaus, T. P. Hughes, G. Saglio, J. P. Radich, D. W. Kim, G. Martinelli, J. Reynolds, R. C. Woodman, M. Baccarani, H. M. Kantarjian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

The purpose was to assess predictive factors for outcome in patients with chronic myeloid leukemia (CML) in chronic phase (CML-CP) treated with nilotinib after imatinib failure. Imatinib-resistant and-intolerant patients with CML-CP (n=321) were treated with nilotinib 400 mg twice daily. Of 19 baseline patient and disease characteristics and two response end points analyzed, 10 independent prognostic factors were associated with progression-free survival (PFS). In the multivariate analysis, major cytogenetic response (MCyR) within 12 months, baseline hemoglobin ≥120 g/l, baseline basophils <4%, and absence of baseline mutations with low sensitivity to nilotinib were associated with PFS. A prognostic score was created to stratify patients into five groups (best group: 0 of 3 unfavorable risk factors and MCyR by 12 months; worst group: 3 of 3 unfavorable risk factors and no MCyR by 12 months). Estimated 24-month PFS rates were 90%, 79%, 67% and 37% for patients with prognostic scores of 0, 1, 2 and 3, respectively, (no patients with score of 4). Even in the presence of poor disease characteristics, nilotinib provided significant clinical benefit in patients with imatinib-resistant or-intolerant CML. This system may yield insight on the prognosis of patients.

Original languageEnglish (US)
Pages (from-to)907-913
Number of pages7
JournalLeukemia
Volume27
Issue number4
DOIs
StatePublished - Apr 2013

Keywords

  • chronic myeloid leukemia
  • imatinib intolerance
  • imatinib resistance
  • multivariate analysis
  • nilotinib
  • predictive model

ASJC Scopus subject areas

  • Hematology
  • Oncology
  • Cancer Research

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