Introduction to Risk-based Treatment
Children with acute lymphoblastic leukemia (ALL) are usually treated according to risk groups defined by both clinical and laboratory features. The intensity of treatment required for favorable outcome varies substantially among subsets of children with ALL. Risk-based treatment assignment is utilized in children with ALL so that patients with favorable clinical and biological features who are likely to have a very good outcome with modest therapy can be spared more intensive and toxic treatment, while a more aggressive, and potentially more toxic, therapeutic approach can be provided for patients who have a lower probability of long-term survival.[1,2,3]
Certain ALL study groups, such as the Children's Oncology Group (COG), use a more or less intensive induction regimen based on a subset of pretreatment factors, while other groups give a similar induction regimen to all patients. Factors used by the COG to determine the intensity of induction include immunophenotype and the National Cancer Institute (NCI) risk group classification. The NCI risk group classification stratifies risk according to age and white blood cell (WBC) count:
- Standard risk—WBC count less than 50,000/μL and age 1 to younger than 10 years.
- High risk—WBC count 50,000/μL or greater and/or age 10 years or older.
All study groups modify the intensity of postinduction therapy based on a variety of prognostic factors, including NCI risk group, immunophenotype, early response determinations, and cytogenetics.
Risk-based treatment assignment requires the availability of prognostic factors that reliably predict outcome. For children with ALL, a number of factors have demonstrated prognostic value, some of which are described below. The factors described are grouped into the following three categories:
- Patient characteristics affecting prognosis.
- Leukemic cell characteristics affecting prognosis.
- Response to initial treatment affecting prognosis.
As in any discussion of prognostic factors, the relative order of significance and the interrelationship of the variables are often treatment dependent and require multivariate analysis to determine which factors operate independently as prognostic variables.[5,6] Because prognostic factors are treatment dependent, improvements in therapy may diminish or abrogate the significance of any of these presumed prognostic factors.