Predicting Survival in CLL: The Power of Measurable Residual Disease

A recent study highlights the predictive power of measurable residual disease (MRD) in determining progression-free survival (PFS) among patients with chronic lymphocytic leukemia (CLL).¹

MRD has emerged as a useful metric for assessing disease prognosis.^2,3 The study, published in Clinical and Translational Science, included a comprehensive review of published data to explore the utility of MRD in predicting PFS.¹

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The research focused on 2 primary analyses: a model-based meta-regression analysis and a joint modeling approach. These analyses aimed to quantify the relationship between MRD levels and PFS outcomes in CLL, providing a framework for using MRD rates in peripheral blood to potentially guide future therapeutic strategies for CLL.

The meta-regression analysis leveraged data from 8 clinical trials and included 2689 patients. It established a statistically significant correlation between undetectable MRD (uMRD) rates and median PFS. Specifically, the model indicated that each percentage increase in uMRD rate was associated with an extension of approximately 0.59 months in median PFS (95% CI, 0.47–0.72; P < .001). The researchers noted, "We have shown that uMRD rates at 3–6 months post-follow-up are highly correlated to PFS," and added that "more than 90% of the variability in PFS can be explained by uMRD rates." 

The study also applied the meta-regression model to 2 smaller, independent cohorts to validate these findings. The first, a nonrandomized phase 2 trial, assessed rituximab maintenance therapy and found that the observed uMRD rate at 3 months was 76% (45/59 patients). The model predicted a median PFS of 57 months (95% PI, 47–67), which closely aligned with the reported median PFS of 60 months.

The second, a small prospective study consisting of 35 patients, evaluated the effectiveness of graft-versus-leukemia activity from allogeneic stem cell transplants (allo-SCT) compared to autologous stem cell transplants (auto-SCT) in CLL patients with unmutated VH gene status. At 3 months, the uMRD rate was 100% for the allo-SCT group (n = 9) and 29% for the auto-SCT group (n = 26). The model predicted a median PFS of 29 months for the auto-SCT group, while the actual reported median PFS was 48 months, outside the predicted range of 20 to 38 months. For the allo-SCT group, the model predicted a median PFS of 71 months (95% PI, 60-83), with the median PFS not being reached during the study's maximum median follow-up of 29 months (range, 14–41 months).

In addition to the meta-regression analysis, the study explored the application of joint modeling techniques to assess the utility of MRD metrics for predicting individual patient risk of progression. This approach incorporated both baseline MRD levels and longitudinal changes in MRD to predict individual patient risk of progression. By integrating baseline MRD values and instantaneous MRD measurements into survival models, the researchers found that continuous monitoring of MRD provided a more accurate prediction of PFS compared with models that relied solely on baseline MRD levels. "This analysis suggests that incorporating MRD is likely to better inform individual progression predictions," the authors noted.

"Incorporating MRD-derived metrics such as baseline levels and longitudinal changes offers a robust method for predicting PFS at both population and individual levels," the authors concluded.

There are many potential implications of these finding for clinical practice. By utilizing MRD as a surrogate marker for PFS, clinicians can make more informed decisions regarding patient management, potentially leading to earlier interventions and better-tailored treatment strategies. For clinical trials, using MRD could facilitate the more rapid evaluation of new therapies, reducing the time and resources required to determine their efficacy.

References

1. Tettamanti FA, Kimko H, Sharma S, Di Veroli G. Predicting progression-free survival from measurable residual disease in chronic lymphocytic leukemia. Clin Transl Sci. 2024;17(8):e13905. doi:10.1111/cts.13905
2. Molica S, Giannarelli D, Montserrat E. Minimal residual disease and survival outcomes in patients with chronic lymphocytic leukemia: A systematic review and meta-analysis. Clin Lymphoma Myeloma Leuk. 2019;19(7):423-430. doi:10.1016/j.clml.2019.03.014
3. Böttcher S, Ritgen M, Fischer K, Stilgenbauer S, Busch RM, Fingerle-Rowson G. et al. Minimal residual disease quantification is an independent predictor of progression-free and overall survival in chronic lymphocytic leukemia: a multivariate analysis from the randomized GCLLSG CLL8 trial. J Clin Oncol. 2012;30(9):980-988. doi:10.1200/JCO.2011.36.9348