Bone Marrow Lymphocytes: can they be an alternative for Bone Marrow Lymphoblasts as early predictors of relapse and remission in Acute Lymphoblastic Leukemia at the post-Induction chemotherapy phase?
DOI:
https://doi.org/10.34117/bjdv10n4-041Keywords:
Acute Lymphoblastic Leukemia, complete blood count, induction chemotherapy, bone marrow lymphoblast, bone marrow lymphocytesAbstract
Background: Acute Lymphoblastic Leukemia (ALL) is a hematological malignancy that arises due to unusual proliferation of lymphoid precursor cells in bone marrow. Induction chemotherapy is vital for achieving complete remission in ALL, but accurately predicting relapse risk and identifying patients likely to sustain remission remains challenging. Conventionally, bone marrow lymphoblasts have been used as the gold standard for assessing treatment response and predicting relapse in ALL. However, emerging evidence suggests that bone marrow lymphocytes may serve as alternative predictive biomarkers. Aim: This study aims to review the utility of bone marrow lymphocytes as early predictors of relapse and remission in ALL during the post-induction chemotherapy phase. It will explore the advantages and limitations of assessing lymphocytes compared to lymphoblasts and discuss the potential mechanisms underlying their prognostic significance. Patients and Methods: Total of 105 newly diagnosed ALL patients; 75 with B ALL and 30 with T ALL was selected to the study. Laboratory investigations included Complete Blood Count (CBC) with the manual differential count analysis and obtaining bone marrow parameters from myelogram reports. The patients were followed until the end of the induction phase and, the laboratory parameters were taken. Correlation bivariate analysis, Paired sample t-Test was performed to establish the associations between peripheral blood parameters with the bone marrow parameters. Receiver operating characteristic (ROC) curve analysis was performed to establish cutoff values for peripheral blood parameters and the bone marrow lymphocytes with aiming to investigate bone marrow response. All the analysis was performed using Microsoft Excel 2013.12 SPSS version 26. Results: In B ALL at Day 8, Lymphocytes% in Bone Marrow (L%_BM) showed a significant strong negative correlation (r =-0.357, p<0.05) with NLR. ROC curve analysis showed cut off values for Lymphocytes; NLR =<0.400 indicates the presence of L%_BM >10% in B ALL. When considering T ALL D8, the ALC>=1756/mm3 suggests the presence of >10% L%_BM in D8. Conclusion: Our research demonstrated strong correlations to predict the Lymphoblasts% in Bone Marrow (BL%_BM) & L%_BM by using peripheral blood parameters which is straight forward and easily obtainable. Moreover, we were successfully able to set up cut off peripheral blood parameter values to monitor the response of the Lymphocytes of the bone marrow. Before implementing the results, further studies could be carried out by increasing the sample size for both B & T ALL with the accurate monitoring of the patients.
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