Predicting clinical outcome in CLL: how and why
- PMID: 20008228
- DOI: 10.1182/asheducation-2009.1.421
Predicting clinical outcome in CLL: how and why
Abstract
The clinical course of patients with chronic lymphocytic leukemia (CLL) is heterogeneous, with some patients experiencing rapid disease progression and others living for decades without requiring treatment. Clinical features and molecular/biologic factors such as ZAP-70, immunoglobulin heavy chain (IGHV) gene mutation status, and cytogenetic abnormalities on fluorescent in situ hybridization (FISH) have been found to be robust predictors of treatment-free survival and overall survival among newly diagnosed patients. Beyond their widely recognized value for providing insight into disease biology and utility for stratifying patient risk in clinical trials, these prognostic tools play an important role in the current counseling and management of patients with CLL. Recent studies have focused on how to combine the results of multiple prognostic assays into an integrated risk stratification system and explored how these characteristics influence response to treatment. This chapter reviews the available tools to stratify patient risk and discusses how these tools can be used in routine clinical practice to individualize patient counseling, guide the frequency of follow-up, and inform treatment selection.
Similar articles
-
Prognostic factors and risk stratification in chronic lymphocytic leukemia.Semin Oncol. 2016 Apr;43(2):233-40. doi: 10.1053/j.seminoncol.2016.02.009. Epub 2016 Feb 8. Semin Oncol. 2016. PMID: 27040701 Review.
-
Do biologic parameters affect the time to first treatment of clinical monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia Rai stage 0? Results of a prospective analysis.Clin Lymphoma Myeloma Leuk. 2015 Mar;15(3):e55-60. doi: 10.1016/j.clml.2014.09.003. Epub 2014 Sep 28. Clin Lymphoma Myeloma Leuk. 2015. PMID: 25445470
-
Clinical and laboratory prognostic indicators in chronic lymphocytic leukemia.Cancer Control. 2012 Jan;19(1):18-25. doi: 10.1177/107327481201900103. Cancer Control. 2012. PMID: 22143059 Review.
-
Predicting Prognosis in Chronic Lymphocytic Leukemia in the Contemporary Era.JAMA Oncol. 2015 Oct;1(7):965-74. doi: 10.1001/jamaoncol.2015.0779. JAMA Oncol. 2015. PMID: 26181643 Review.
-
Quantitative flow cytometry of ZAP-70 levels in chronic lymphocytic leukemia using molecules of equivalent soluble fluorochrome.Cytometry B Clin Cytom. 2006 Jul 15;70(4):218-26. doi: 10.1002/cyto.b.20078. Cytometry B Clin Cytom. 2006. PMID: 16456869
Cited by
-
Standardization of fluorescence in situ hybridization studies on chronic lymphocytic leukemia (CLL) blood and marrow cells by the CLL Research Consortium.Cancer Genet Cytogenet. 2010 Dec;203(2):141-8. doi: 10.1016/j.cancergencyto.2010.08.009. Cancer Genet Cytogenet. 2010. PMID: 21156226 Free PMC article.
-
The rs1001179 SNP and CpG methylation regulate catalase expression in chronic lymphocytic leukemia.Cell Mol Life Sci. 2022 Sep 16;79(10):521. doi: 10.1007/s00018-022-04540-7. Cell Mol Life Sci. 2022. PMID: 36112236 Free PMC article.
-
Limited value of routine follow-up visits in chronic lymphocytic leukemia managed initially by watch and wait: A North Denmark population-based study.PLoS One. 2018 Dec 27;13(12):e0208180. doi: 10.1371/journal.pone.0208180. eCollection 2018. PLoS One. 2018. PMID: 30589850 Free PMC article.
-
Using the geometric mean fluorescence intensity index method to measure ZAP-70 expression in patients with chronic lymphocytic leukemia.Onco Targets Ther. 2016 Feb 18;9:797-805. doi: 10.2147/OTT.S94613. eCollection 2016. Onco Targets Ther. 2016. PMID: 26937202 Free PMC article.
-
Modern treatment in chronic lymphocytic leukemia: impact on survival and efficacy in high-risk subgroups.Cancer Med. 2014 Jun;3(3):555-64. doi: 10.1002/cam4.226. Epub 2014 Mar 19. Cancer Med. 2014. PMID: 24648042 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Research Materials