Telomere length predicts for outcome to FCR chemotherapy in CLL

We have previously shown that dividing patients with CLL into those with telomeres inside the fusogenic range (TL-IFR) and outside the fusogenic range (TL-OFR) is powerful prognostic tool. Here, we used a high-throughput version of the assay (HT-STELA) to establish whether telomere length could pred...

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Bibliographic Details
Published in:Leukemia
Main Authors: Norris, Kevin, Hillmen, Peter, Rawstron, Andrew, Hills, Robert, Baird, Duncan M., Fegan, Christopher D., Pepper, Chris
Format: Text
Language:English
Published: Nature Publishing Group UK 2019
Subjects:
Article
Arctic
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6756045/
http://www.ncbi.nlm.nih.gov/pubmed/30700843
https://doi.org/10.1038/s41375-019-0389-9
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Summary:We have previously shown that dividing patients with CLL into those with telomeres inside the fusogenic range (TL-IFR) and outside the fusogenic range (TL-OFR) is powerful prognostic tool. Here, we used a high-throughput version of the assay (HT-STELA) to establish whether telomere length could predict for outcome to fludarabine, cyclophosphamide, rituximab (FCR)-based treatment using samples collected from two concurrent phase II studies, ARCTIC and ADMIRE (n = 260). In univariate analysis, patients with TL-IFR had reduced progression-free survival (PFS) (P < 0.0001; HR = 2.17) and shorter overall survival (OS) (P = 0.0002; HR = 2.44). Bifurcation of the IGHV-mutated and unmutated subsets according to telomere length revealed that patients with TL-IFR in each subset had shorter PFS (HR = 4.35 and HR = 1.48, respectively) and shorter OS (HR = 3.81 and HR = 2.18, respectively). In addition, the OS of the TL-OFR and TL-IFR subsets were not significantly altered by IGHV mutation status (P = 0.61; HR = 1.24 and P = 0.41; HR = 1.47, respectively). In multivariate modeling, telomere length was the dominant co-variable for PFS (P = 0.0002; HR = 1.85) and OS (P = 0.05; HR = 1.61). Taken together, our data suggest that HT-STELA is a powerful predictor of outcome to FCR-based treatment and could be used to inform the design of future risk-adapted clinical trials.

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