TY - JOUR
T1 - Using prognostic models in CLL to personalize approach to clinical care
T2 - Are we there yet?
AU - Mina, Alain
AU - Sandoval Sus, Jose
AU - Sleiman, Elsa
AU - Pinilla-Ibarz, Javier
AU - Awan, Farrukh T.
AU - Kharfan-Dabaja, Mohamed A.
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2018/3
Y1 - 2018/3
N2 - Four decades ago, two staging systems were developed to help stratify CLL into different prognostic categories. These systems, the Rai and the Binet staging, depended entirely on abnormal exam findings and evidence of anemia and thrombocytopenia. Better understanding of biologic, genetic, and molecular characteristics of CLL have contributed to better appreciating its clinical heterogeneity. New prognostic models, the GCLLSG prognostic index and the CLL-IPI, emerged. They incorporate biologic and genetic information related to CLL and are capable of predicting survival outcomes and cases anticipated to need therapy earlier in the disease course. Accordingly, these newer models are helping develop better informed surveillance strategies and ultimately tailor treatment intensity according to presence (or lack thereof) of certain prognostic markers. This represents a step towards personalizing care of CLL patients. We anticipate that as more prognostic factors continue to be identified, the GCLLSG prognostic index and CLL-IPI models will undergo further revisions.
AB - Four decades ago, two staging systems were developed to help stratify CLL into different prognostic categories. These systems, the Rai and the Binet staging, depended entirely on abnormal exam findings and evidence of anemia and thrombocytopenia. Better understanding of biologic, genetic, and molecular characteristics of CLL have contributed to better appreciating its clinical heterogeneity. New prognostic models, the GCLLSG prognostic index and the CLL-IPI, emerged. They incorporate biologic and genetic information related to CLL and are capable of predicting survival outcomes and cases anticipated to need therapy earlier in the disease course. Accordingly, these newer models are helping develop better informed surveillance strategies and ultimately tailor treatment intensity according to presence (or lack thereof) of certain prognostic markers. This represents a step towards personalizing care of CLL patients. We anticipate that as more prognostic factors continue to be identified, the GCLLSG prognostic index and CLL-IPI models will undergo further revisions.
KW - Chronic lymphocytic leukemia
KW - Prognostic staging systems
KW - Survival
UR - http://www.scopus.com/inward/record.url?scp=85032986874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032986874&partnerID=8YFLogxK
U2 - 10.1016/j.blre.2017.10.003
DO - 10.1016/j.blre.2017.10.003
M3 - Review article
C2 - 29122300
AN - SCOPUS:85032986874
SN - 0268-960X
VL - 32
SP - 159
EP - 166
JO - Blood Reviews
JF - Blood Reviews
IS - 2
ER -