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Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Biomarker-adapted treatment in high-risk large B-cell lymphoma
Sirpa Leppä1,2, Leo Meriranta1,2, Maare Arffman1,2
1Department of Oncology Helsinki University Hospital Comprehensive Cancer Centre Helsinki Finland.
High-risk large B-cell lymphoma (LBCL) patients showed improved survival with biomarker-guided therapy. Circulating tumor DNA (ctDNA) and TP53 status are key prognostic indicators for treatment response.
Area of Science:
- Hematology
- Oncology
- Genetics
Background:
- High-risk large B-cell lymphoma (LBCL) presents inadequate survival rates, especially with specific biological risk factors.
- Current treatment strategies require refinement to improve outcomes for these patients.
Purpose of the Study:
- To evaluate a biomarker-driven phase II trial for high-risk LBCL patients.
- To assess the efficacy of R-CHOEP-14 and DA-EPOCH-R regimens based on biological risk profiles.
- To investigate the prognostic value of circulating tumor DNA (ctDNA) kinetics and genetic aberrations.
Main Methods:
- A phase II trial enrolled 123 high-risk LBCL patients (aged 18-64).
- Patients received R-CHOEP-14 or DA-EPOCH-R based on biological risk factors (e.g., C-MYC translocation, TP53 deletion, MYC/BCL2 co-expression).
- Circulating tumor DNA (ctDNA) levels and kinetics were monitored during therapy.
Main Results:
- Three-year failure-free survival (FFS) and overall survival (OS) were 79% and 88% for the entire cohort.
- DA-EPOCH-R did not show improved survival compared to R-CHOEP-14 in high-risk patients.
- High pretreatment ctDNA, TP53 deletion/mutations, and end-of-therapy (EOT) ctDNA positivity correlated with worse outcomes.
- EOT ctDNA negativity indicated a cure and resolved false positive PET scans.
Conclusions:
- Biomarker-guided therapy shows promising survival for high-risk LBCL patients.
- TP53 aberrations and high ctDNA levels (pretreatment or EOT) predict poor prognosis.
- ctDNA kinetics serve as a valuable tool for monitoring treatment response and predicting outcomes.
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