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Novel Prognostic Model May Predict Outcomes in Early-Stage CLL

By: Joseph Fanelli
Posted: Wednesday, June 24, 2020

Findings from the prospective CLL1 trial presented in Leukemia introduce a novel prognostic model that may improve outcome predictions for patients with chronic lymphocytic leukemia (CLL) after early diagnosis. The model, which may prove to be particularly useful in stratifying patients with Binet stage A disease, includes a comprehensive set of clinical, biologic, and genetic markers, concluded Manuela A. Hoechstetter, MD, of the München Klinik Schwabing, Germany, and colleagues.

“Ultimately, the current score might be helpful for risk stratification of early-stage patients within the scope of clinical trials evaluating early intervention with novel compounds,” the authors noted.

In this multicenter trial, the authors observed 539 patients characterized with Binet stage A CLL until disease progression, first-line treatment, or death. A multivariate analysis revealed six independent factors associated with overall survival and time-to-first treatment: del(17p), unmutated IGHV, del(11q), ß2-microglobulin greater than 3.5 mg/dL, lymphocyte doubling time up to 12 months, and patients aged 60 and older. These factors were integrated into the prognostic model, which then stratified patients into four risk groups.

The authors found that the risk of treatment at 5 years for patients with very low (0 –1.5 scores), low (2–4 scores), high (4.5–6.5 scores), and very high–risk scores (7–14 scores) was 85.9%, 51.8%, 27.6%, and 11.3%, respectively. The authors emphasized that in addition to the CLL International Prognostic Index, their novel model substantiated del(11q) and lymphocyte doubling time as prognostic factors for patients with early-stage CLL.

“[Lymphocyte doubling time], which was described as a driver of disease in Binet stage A patients, was also identified as the most single independent factor for time-to-first treatment,” the authors wrote.

Disclosure: For full disclosures of the authors, visit nature.com.



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