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Review
. 2020 Sep 7:8:40.
doi: 10.1186/s40364-020-00222-3. eCollection 2020.

Recent progress of prognostic biomarkers and risk scoring systems in chronic lymphocytic leukemia

Xiaoya Yun  1   2   3   4   5 , Ya Zhang  1   2   3   4   5 , Xin Wang  1   2   3   4   5
Affiliations
Review

Recent progress of prognostic biomarkers and risk scoring systems in chronic lymphocytic leukemia

Xiaoya Yun et al. Biomark Res. .

Abstract

Chronic lymphocytic leukemia (CLL) is the most prevalent adult leukemia with high heterogeneity in the western world. Thus, investigators identified a number of prognostic biomarkers and scoring systems to guide treatment decisions and validated them in the context of immunochemotherapy. A better understanding of prognostic biomarkers, including serum markers, flow cytometry outcomes, IGHV mutation status, microRNAs, chromosome aberrations and gene mutations, have contributed to prognosis in CLL. Del17p/ TP53 mutation, NOTCH1 mutation, CD49d, IGHV mutation status, complex karyotypes and microRNAs were reported to be of predictive values to guide clinical decisions. Based on the biomarkers above, classic prognostic models, such as the Rai and Binet staging systems, MDACC nomogram, GCLLSG model and CLL-IPI, were developed to improve risk stratification and tailor treatment intensity. Considering the presence of novel agents, many investigators validated the conventional prognostic biomarkers in the setting of novel agents and only TP53 mutation status/del 17p and CD49d expression were reported to be of prognostic value. Whether other prognostic indicators and models can be used in the context of novel agents, further studies are required.

Keywords: Chronic lymphocytic leukemia; Prognosis; Prognostic biomarkers; Risk scoring systems.

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Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The percentage of common chromosome aberrations tested by fluorescence in situ hybridization
Fig. 2
Fig. 2
Comparison of fluorescence in situ hybridization (FISH), karyotype analysis and IGHV mutation test between 2008 and 2014
Fig. 3
Fig. 3
The risk factors of the classical prognostic models or staging systems. The Rai and Binet staging systems, MDACC nomogram, GCLLSG, CLL-IPI are the base of other prognostic models. It can be seen that the risk factors altered from the combination of clinical features and laboratory features to the combination of clinical and laboratory features with cytogenetic features
See this image and copyright information in PMC

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