Combined analysis of minimal residual disease at two time points and its value for risk stratification in childhood B-lineage acute lymphoblastic leukemia

Cui, Lei; Li, Zhigang; Wu, Minyuan; Li, Weijing; Gao, Chao; Deng, Guoren

doi:10.1016/j.leukres.2009.11.031

« Previous Next »Leukemia Research
Volume 34, Issue 10 , Pages 1314-1319, October 2010

Combined analysis of minimal residual disease at two time points and its value for risk stratification in childhood B-lineage acute lymphoblastic leukemia

Lei Cui
- Hematological Center, Beijing Children's Hospital Affiliated to Capital Medical University, 56 Nanlishi Road, Beijing 100045, China
Zhigang Li
- Hematological Center, Beijing Children's Hospital Affiliated to Capital Medical University, 56 Nanlishi Road, Beijing 100045, China
- Corresponding author. Tel.: +86 010 68028401x2622; fax: +86 010 68055864.
Minyuan Wu
- Hematological Center, Beijing Children's Hospital Affiliated to Capital Medical University, 56 Nanlishi Road, Beijing 100045, China
Weijing Li
- Hematological Center, Beijing Children's Hospital Affiliated to Capital Medical University, 56 Nanlishi Road, Beijing 100045, China
Chao Gao
- Hematological Center, Beijing Children's Hospital Affiliated to Capital Medical University, 56 Nanlishi Road, Beijing 100045, China
Guoren Deng
- School of Medicine, University of California, San Francisco, CA, USA

Received 16 November 2009; received in revised form 16 November 2009; accepted 30 November 2009. published online 07 March 2011.

Abstract

The study was aimed to explore the value of minimal residual disease (MRD) for risk stratification in childhood precursor-B-acute lymphoblastic leukemia. MRD was monitored at two time points (TP1, after induction and TP2, before consolidation therapy) by quantitative detection of monoclonal immunoglobulin heavy chain gene rearrangements. This study stratified 105 patients into three MRD risk groups: standard-risk, MRD<10⁻⁴ at both TP1 and TP2; high-risk, TP1≥10⁻² or TP2≥10⁻³; and others were classified as intermediate-risk. We incorporated this MRD risk information to refine risk stratification among these patients and developed a new classification system that predicted the treatment outcomes more successfully than did the traditional risk classification criteria.