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Blood, 1 June 2007, Vol. 109, No. 11, pp. 4679-4685.
Prepublished online as a Blood First Edition Paper on February 13, 2007; DOI 10.1182/blood-2005-12-051458.
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Submitted December 28, 2005
Accepted January 22, 2007
Prognostic nomogram and index for overall survival in
previously untreated patients with chronic lynmphocytic
leukmeia
William G. Wierda*, Susan O'Brien, Xuemei Wang, Stefan Faderl, Alessandra Ferrajoli, Kim-Anh Do, Jorge Cortes, Deborah Thomas, Guillermo Garcia-Manero, Charles Koller, Miloslav Beran, Francis Giles, Farhad Ravandi, Susan Lerner, Hagop Kantarjian, and Michael Keating
Department of Leukemia, U.T. MD Anderson Cancer Center, Houston, TX
Department of Biostatistics and Applied Mathematics, U.T. MD Anderson Cancer Center, Houston, TX
* Corresponding author; email: wwierda{at}mdanderson.org.
The clinical course for patients with chronic lymphocytic leukemia is extremely heterogeneous. The Rai and Binet staging systems have been used to risk-stratify patients, most patients present with early-stage disease. We evaluated a group of previously untreated patients with CLL at initial presentation to UT MD Anderson Cancer Center to identify independent characteristics that predict for overall survival. Clinical and routine laboratory characteristics for 1674 previously untreated patients who presented for evaluation of CLL from 1981 to 2004 were included. Univariate and multivariate analyses identified several patient characteristics at presentation that predicted for overall survival in previously untreated patients with CLL. A multivariate Cox proportional hazards model was developed including the following independent characteristics: age, beta-2 microglobulin, absolute lymphocyte count, gender, Rai stage, and number of involved lymph node groups. Inclusion of patients from a single institution and the proportion of patients younger than 65 yrs may limit this model. A weighted prognostic model, or nomogram, predictive for overall survival was constructed using these six characteristics for 5- and 10-year survival probability and estimated median survival time. This prognostic model may help patients and clinicians in clinical decision-making as well as in clinical research and clinical trial design.
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