New Model Helps Guide Treatment Options in CLL

Ben Leach
Published: Monday, Feb 27, 2012

Dr. William G. Wierda

William G. Wierda, MD, PhD

While the watch-and-wait method is frequently employed in patients with chronic lymphocytic leukemia (CLL), there are a number of prognostic factors that can help identify those at a high risk for disease progression who may benefit from early intervention.

William G. Wierda, MD, PhD, an associate professor in the Department of Leukemia at The University of Texas MD Anderson Cancer Center in Houston, discussed these factors in a presentation at the 16th Annual International Congress on Hematologic Malignancies.

Wierda and colleagues developed a weighted multivariate model for identifying high-risk patients, published recently in the Journal of Clinical Oncology (2011;29(31):4088-4095). The model was used to develop a nomogram that calculates 2- and 4-year probabilities of treatment and estimates the median time to first treatment.

Data for the model came from 930 patients with CLL who did not have active disease requiring treatment within three months of the start of the trial, conducted between January 2004 and December 2009.

The model incorporates traditional laboratory and clinical factors such as age, platelet counts, and hemoglobin levels with newer prognostic factors such as chromosome abnormalities measured by fluorescent in situ hybridization (FISH), immunoglobulin heavy chain variable gene (IGHV) mutation status, and ZAP-70 leukemia cell expression evaluated at first patient visit.

The presence of chromosomal abnormalities involving the 11q deletion or the 17p deletion as determined through FISH was associated with high-risk categories.  Other factors may include IGHV mutation status, the involvement of three lymph node sites, increased size of cervical lymph nodes, and higher levels of serum lactate dehydrogenase.

However, the degree in which each of these prognostic factors affects individual patients can vary.

"Not all of these factors are important for each patient group," Wierda said. "Not all prognostic factors are created equally."

In another study, Wierda and colleagues evaluated pretreatment characteristics in 595 previously untreated patients who had National Cancer Institute Working Group indications to initiate front-line therapy for predictors of complete response (CR), time to treatment failure (TTF), and overall survival (OS). Like the other study, multivariable models were developed for all three endpoints. (J Clin Oncol. 2009;27(10):1637-1643).

In the retrospective analysis, the study authors found that front-line treatment regimen was a significant independent predictive factor for all three endpoints and that chemoimmunotherapy was the superior treatment regimen.

When the front-line treatment was taken into consideration, independent patient characteristics associated with CR included age and beta(2)-microglobulin (beta-2M) levels. TTF was independently associated with age, beta-2M, percent lymphocytes in bone marrow, and treatment regimen. Improved OS was independently associated with younger age, lower beta-2M, and treatment regimen.

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