Using prognostic models in CLL to personalize approach to clinical care: Are we there yet?
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Churchill Livingstone
Abstract
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. © 2017 Elsevier Ltd
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Keywords
Chronic lymphocytic leukemia, Prognostic staging systems, Survival, Biomarkers, tumor, Disease management, Hematopoietic stem cell transplantation, High-throughput nucleotide sequencing, Humans, Leukemia, lymphocytic, chronic, b-cell, Mutation, Neoplasm staging, Neoplasm, residual, Precision medicine, Prognosis, Transplantation, homologous, Adp ribosyl cyclase/cyclic adp ribose hydrolase 1, Protein kinase zap 70, Tumor marker, Allogeneic hematopoietic stem cell transplantation, Cancer prognosis, Cancer staging, Cancer survival, Cd38 gene, Chronic lymphatic leukemia, Clinical practice, Dna methylation, Gene, Gene expression, Gene mutation, Gene overexpression, Genetics, Human, Ighv gene, Leukemia remission, Next generation sequencing, Personalized medicine, Priority journal, Review, Somatic mutation, Zap 70 gene, Allotransplantation, High throughput sequencing, Minimal residual disease, Procedures