Multivariable model for time to first treatment in patients with chronic lymphocytic leukemia

William G. Wierda, Susan O'Brien, Xuemei Wang, Stefan Faderl, Alessandra Ferrajoli, Kim Anh Do, Guillermo Garcia-Manero, Jorge Cortes, Deborah Thomas, Charles A. Koller, Jan A. Burger, Susan Lerner, Ellen Schlette, Lynne Abruzzo, Hagop M. Kantarjian, Michael J. Keating

Research output: Contribution to journalArticlepeer-review

115 Scopus citations


Purpose: The clinical course for patients with chronic lymphocytic leukemia (CLL) is diverse; some patients have indolent disease, never needing treatment, whereas others have aggressive disease requiring early treatment. We continue to use criteria for active disease to initiate therapy. Multivariable analysis was performed to identify prognostic factors independently associated with time to first treatment for patients with CLL. Patients and Methods: Traditional laboratory, clinical prognostic, and newer prognostic factors such as fluorescent in situ hybridization (FISH), IGHV mutation status, and ZAP-70 expression evaluated at first patient visit to MD Anderson Cancer Center were correlated by multivariable analysis with time to first treatment. This multivariable model was used to develop a nomogram - a weighted tool to calculate 2- and 4-year probability of treatment and estimate median time to first treatment. Results: There were 930 previously untreated patients who had traditional and new prognostic factors evaluated; they did not have active CLL requiring initiation of treatment within 3 months of first visit and were observed for time to first treatment. The following were independently associated with shorter time to first treatment: three involved lymph node sites, increased size of cervical lymph nodes, presence of 17p deletion or 11q deletion by FISH, increased serum lactate dehydrogenase, and unmutated IGHV mutation status. Conclusion: We developed a multivariable model that incorporates traditional and newer prognostic factors to identify patients at high risk for progression to treatment. This model may be useful to identify patients for early interventional trials.

Original languageEnglish (US)
Pages (from-to)4088-4095
Number of pages8
JournalJournal of Clinical Oncology
Issue number31
StatePublished - Nov 1 2011
Externally publishedYes

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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