Risk Stratification in Patients of Acute Leukaemia Presenting to a Tertiary Care Hospital in North India


Risk Factors, Bone Marrow, Leukemia, Myeloid, Acute, Precursor Cell Lymphoblastic Leukemia-Lymphoma

BACKGROUND Clinically and pathologically, leukaemia is subdivided into various groups. The first division is between its acute and chronic forms. This hospital based cross sectional study in a tertiary care armed forces hospital aims at studying the profile of acute leukaemia patients and study the correlation between patient profile and disease prognosis. METHODS This observational study included 60 cases of newly diagnosed acute leukaemia presenting between October 2011 to March 2013. All patients underwent routine diagnostic workup for acute leukaemias. Patients were divided into three sub groups – High, Intermediate and Standard risk. Data was analysed after assessing bone marrow response 28 days after starting therapy. Variables such as age, TLC at presentation, immunophenotype, cytogenetics, and extramedullary involvement were taken into account in correlating whether these had any effect on prognosis. RESULTS Out of a total of 60 patients, 30 patients had acute myeloid leukaemia and 30 patients had acute lymphoblastic leukaemia. In AML, older patients are more likely to have more comorbidities and have a poorer performance status than younger patients. Extra-medullary infiltrates at diagnosis is associated with poor remission rates and poor overall survival. Outcomes remain poor with extremely high initial WBC counts. Specific secondary chromosome aberrations might affect prognosis of patients. In ALL, 2 out of 6 patients (33%) of high risk (>30 yrs.) achieved remission. High WBC counts at presentation were associated with lower survival. Survival is influenced by immunophenotype: 38% at 3 years for those with the expression of B-lineage antigens compared with 69% for those with T-lineage antigen expression. Patients with high risk cytogenetics were associated with poor outcome even when more intensive therapeutic regimens were used. CONCLUSIONS A number of clinical and biological features predict prognosis in AML, but prognosis is also determined by interactions between age, extramedullary disease, leukocyte count at presentation, cytogenetics, and response to therapy etc. In ALL, age, WBC count at presentation and response to therapy have remained strong prognostic indicators of outcome, as have immunophenotypic features and cytogenetics.