International journal of hematology-oncology and stem cell research · 2025
Minimal Residual Disease in Acute Lymphoblastic Leukaemia and Its Relationship with Other Prognostic Factors.
СтатьяНазвание и аннотация: Перевод в очереди
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Agrawal Chinmayee, Boppana Sai Madhuri, Devdas Santhosh K, Maka Vinayak V, Kilara Nalini, Majumdar Swaratika, Palassery Rasmi
Аннотация
Background: Minimal Residual Disease (MRD) assessment is crucial for directing treatment decisions in Acute Lymphoblastic Leukemia (ALL). In low- and middle-income countries, limited resources can present challenges to implementing MRD-guided therapy intensification for ALL. The study attempted to assess the relationship between MRD and other prognostic factors in ALL, focusing on treatment outcomes and disease progression. Materials and Methods: A retrospective observational study was conducted at Ramaiah Medical College and Hospital in Bengaluru, examining patient data from January 2021 to December 2021. MRD status was determined post-induction using flow cytometry. Patients were classified into various groups based on factors such as type of ALL (B-cell or T-cell), NCI risk status (standard or high), cytogenetic risk (favorable, poor, or intermediate), CNS status, prednisone response, and MRD levels at the end of induction. Results: Out of 72 patients, 25% were MRD-positive, with a male: female ratio of 2.13:1. B-ALL was diagnosed in 49 patients and T-ALL in 23, with 75% categorized as high-risk by NCI criteria. Cytogenetic analysis revealed a diverse profile (23.61% PR, 48.61% IR, 27.78% FR), and 58.33% exhibited a good prednisone response (GPR). At the end of the induction phase, 25% tested positive for MRD, with B-ALL showing a lower MRD rate at 15.2%. Age and NCI risk status significantly influenced MRD outcomes, with 75% of participants classified as high-risk. Conclusion: This study demonstrates a significant association between MRD positivity and factors such as age, NCI risk status, and B-ALL diagnosis, underscoring the complex interaction of these variables in predicting treatment outcomes for ALL patients.