Minimal Residual Disease in Acute Lymphoblastic Leukaemia and Its Relationship with Other Prognostic Factors

微小残留病 残余物 医学 疾病 淋巴细胞白血病 儿科 肿瘤科 内科学 白血病 数学 算法
作者
Chinmayee Agrawal,Sri Lasya Boppana,Santhosh Kumar Devdas,V.V. Maka,Nalini Kilara,Swaratika Majumdar,Rasmi Palassery
出处
期刊:International journal of hematology-oncology and stem cell research [Tehran University of Medical Sciences]
标识
DOI:10.18502/ijhoscr.v19i1.17822
摘要

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.

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