Journal
HEMATOLOGICAL ONCOLOGY
Volume 29, Issue 2, Pages 91-99Publisher
WILEY
DOI: 10.1002/hon.959
Keywords
chronic lymphocytic leukaemia; prognosis; nomogram
Categories
Funding
- Ministero della Salute (Ricerca Finalizzata I.R.C.C.S. and 'Alleanza Contro il Cancro') Rome
- Associazione Italiana contro le Leucemie, linfomi e mielomi (A.I.L.), Venezia Section, Pramaggiore Group
- Ricerca Scientifica Applicata, Regione Friuli Venezia Giulia, Trieste
- Associazione Italiana per la Ricerca sul Cancro, Milan, Italy [IG-8701]
- Helmut Horten Foundation
- San Salvatore Foundation
- Fondazione per la Ricerca e la Cura sui Linfomi (Lugano, Switzerland)
- Swiss Cancer League (Krebsliga Schweiz) [KLS-01690-03-2005]
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We wish to validate in a multicentric CLL population a nomogram and a risk score recently developed to predict overall survival (OS). Complete records from 1037 CLL patients were retrospectively collected to estimate OS and time to treatment (TTT). Cox models were used to test the independence of age, beta-2-microglobulin, absolute lymphocyte count (ALC), sex, Rai stage and number of involved lymph node regions (LNR). Accuracy of prognostic models was tested with the concordance index (c-index). Median follow-up was 5.5 years, with 151 deaths and 475 treated patients. Median OS was not reached (65% survival rate at 13.9 years), median TTT was 6 years. We confirmed the ability of the prognostic score to predict OS and TTT in three risk groups, with results comparable with those reported in the original report. However, ALC and Rai stage were not independent predictors, whereas the Binet staging system, which incorporates LNR variable, showed independent predictive power; furthermore, both 5- and 10-year OS estimates from nomogram were lower compared to real data. When separately analysed, the impact of therapy on OS was not selected as independent predictor of OS in our series. According to these results, we proposed a simpler four-variable model (age, sex, Binet staging, beta-2-microglobulin) and a new nomogram. This model had a c-index of 0.78 versus 0.76 of the six-variable model (p = 0.043), showing better predictive accuracy. External validation and refinement are needed on independent data sets, possibly from cancer registry patients' series. Copyright (C) 2010 John Wiley & Sons, Ltd.
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