Abstract
A nomogram that incorporates traditional and newer prognostic factors to identify patients with chronic lymphocytic leukemia (CLL) who are at high risk of receiving therapy was developed by investigators at The University of Texas M. D. Anderson Cancer Center (MDACC). Because the model required validation before its extensive use could be recommended, the authors sought to externally validate the nomogram in an independent, community-based cohort of patients with CLL. In total, 328 previously untreated patients with newly diagnosed, asymptomatic, Binet stage A CLL from different primary hematology centers who were registered on a prospective basis during 2006 to 2010 on an observational database of the Italian Lymphoma Study Group were considered suitable for external validation of the model. A total point score was calculated for each patient using a formula proposed by MDACC investigators, and the median score was 19.9 (range, 0-69.5). Furthermore, when the score was evaluated as continuous variable (ie, by measuring the risk of each point increase), the total point score was associated with the time to first treatment (hazard ratio [HR], 1.04; 95% confidence interval [CI], 1.02-1.05; P < .0001). Receiver operating characteristic analysis identified a point score of 25 (area under curve; 0.64; sensitivity, 61.5; specificity, 72.1; P < .0001) as the best threshold capable of separating patients who needed therapy from patients who did not (HR, 3.27; 95% CI, 2,07-5.18; P < .0001). The prognostic index category also remained a predictor of the time to first treatment when the analysis was limited to patients with Rai stage 0 disease (HR, 4.05; 95% CI, 2.25-7.52; P < .0001). Finally, a goodness-of-fit test demonstrated that the nomogram model had a significantly good fit at 2 years (correlation coefficient [r(2) ] = 0.966; P = .002). The current results confirmed the ability of a newly developed prognostic index to predict the time to first treatment among previously untreated patients with CLL who had early disease and extended the utility of the model to those with Rai stage 0 disease. In addition, the actual and predicted time to first treatment outcomes revealed good agreement, suggesting that, externally, the results provided by the model are well calibrated. Cancer 2013. © 2012 American Cancer Society.
Highlights
In parallel with significant improvements in treatment outcomes, there has been dramatic progress in understanding the biology of chronic lymphocytic leukemia (CLL), and several new prognostic factors have been identified.[1]
We extended the utility of the index to patients with Rai stage 0 disease, who represent approximately 70% of patients with newly diagnosed early CLL in nonreferral primary hematology centers in Italy.[5]
Evaluations of newer prognostic factors, including immunoglobulin heavy-chain variable gene (IgHV) mutation status, cluster of differentiation 38 (CD38) expression, and f-chain–associated protein kinase 70 (ZAP-70) expression, by flow cytometry and Western blot analysis were centralized at the National Institute of Cancer Laboratory in Genoa; and the study of chromosome abnormalities by fluorescence in situ hybridization (FISH) analysis was centralized at the Research Center for the Study of Leukemia, Institute for Cancer Research and Treatment Foundation at the University of Milan
Summary
In parallel with significant improvements in treatment outcomes, there has been dramatic progress in understanding the biology of chronic lymphocytic leukemia (CLL), and several new prognostic factors have been identified.[1]. A nomogram that incorporates traditional and newer prognostic factors to identify patients with chronic lymphocytic leukemia (CLL) who are at high risk of receiving therapy was developed by investigators at The University of Texas M. METHODS: In total, 328 previously untreated patients with newly diagnosed, asymptomatic, Binet stage A CLL from different primary hematology centers who were registered on a prospective basis during 2006 to 2010 on an observational database of the Italian Lymphoma Study Group were considered suitable for external validation of the model. CONCLUSIONS: The current results confirmed the ability of a newly developed prognostic index to predict the time to first treatment among previously untreated patients with CLL who had early disease and extended the utility of the model to those with Rai stage 0 disease.
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