Analyzing continuous minimum residual disease (MRD) and patient genetics as associated risk factors may play a key role in the development and improvement of algorithms assessing the risk of relapse among pediatric patients with acute lymphoblastic leukemia (ALL), according to a study published in the Journal of Clinical Oncology.1

Previous studies demonstrated that MRD and genetic abnormalities are critical predictors of relapse in ALL, but current algorithms view MRD and genetics as independent variables when assessing risk.

For this study, researchers evaluated the outcomes of 3113 patients with ALL. Patients underwent MRD evaluation and were assigned to 1 of 4 genetic subtypes as revealed by cytogenetic and fluorescence in situ hybridization testing: cytogenetic good risk (CYTO-GR), cytogenetic intermediate risk (CYTO-IR), cytogenetic high risk (CYTO-HR), or T cell ALL (T-ALL).

The MRD distributions of patients with distinct genetic subtypes were different (P < .001). Patients in the CYTO-GR had the fastest disease clearance, while patients the CYTO-HR and T-ALL subgroups responded more slowly.

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MRD kinetics corresponded with the risk of relapse: the risk of relapse decreased by 20% with each log reduction in disease level (hazard ratio [HR], 0.80; 95% CI, 0.77-0.83; P < .001). The MRD level was directly proportional to the risk of relapse in each genetic subtype, but the absolute relapse rate associated with a specific MRD value was significantly different in each genetic risk group.

Although noting that further investigation is required, the authors concluded that “[o]nce validated, the concept of truly integrating MRD and genetics via subtype-specific MRD thresholds, as demonstrated by the integrated risk groups…will improve risk algorithms that are used to allocate treatment.”

Reference

  1. O’Connor D, Enshaei A, Bartram J, et al. Genotype-specific minimal residual disease interpretation improves stratification in pediatric acute lymphoblastic leukemia. J Clin Oncol. 2017 Nov 13. doi: 10.1200/JCO.2017.74.0449 [Epub ahead of print]