DEMOGRAPHIC AND CLINICAL PROFILE OF CHRONIC MYELOID LEUKEMIA PATIENTS IN A RESOURCE-LIMITED SETTING: A COMPREHENSIVE ANALYSIS

Objective: Chronic Myeloid Leukemia (CML) is a global healthcare burden, especially in resource-poor areas with limited access to modern treatment. This study will extensively analyze CML patients' demographic and clinical characteristics in such settings. We analyze CML prevalence, age distribution, illness presentation, treatment trends, and outcomes using [insert data source(s)]. We also examine how healthcare institutions manage CML with limited resources. This study aims to inspire personalized therapies and maximize healthcare resource allocation for improved patient outcomes by highlighting the nuanced landscape of CML in resource-limited settings. Methodology: Demographic and clinical data from 410 CML patients were evaluated. Age distribution, gender, regional representation, clinical data (spleen size, WBC counts, hemoglobin levels, platelet counts), illness phase, molecular studies (PCR, FISH), risk stratification, treatment modalities, and patient outcomes were considered. Results: Demographics: The mean age of 410 CML patients was 38.31 years, ranging from 11 to 80. Age distribution showed significant participation in the 31-50 age group (53.41%), followed by 12-30 (29.76%) and 51-70 (16.59%) groups. The gender split was 57.56% male and 42.44% female. AJK (50.49%), Punjab (27.80%), and Khyber Pakhtunkhwa (4.15%) contributed most. Clinical and Hematological Parameters: Spleen size examination showed mild (4.63%), moderate (47.80%), and major (>8 cm) enlargement. Over 100,000 (31.22%) and 300,000 (17.80%) WBC counts showed diversity. Low hemoglobin (11.95%) to high hemoglobin (16.10%). Platelet counts ranged from 350,000 (37.56%). Disease Phase and Molecular Analysis: Chronic phase distribution was 92.68%, accelerated phase 7.07%, and blast phase 0.24%. Quantitative PCR showed positive results in 88.29%, negative results in 2.44%, and 9.27% not tested. FISH analysis showed positive results in 6.83% and negative results in 0.49%, with 92.68% not tested. Risk stratification and treatment: SOKAL score-based risk stratification classified 10.73% as low, 64.63% as intermediate, and 24.63% as high. Treatments comprised imatinib (40.49%) and nilotinib (59.51%). CHR was achieved by 85.37% of 86.83% with follow-up data. Conclusion: This study covers varied demographics and clinical features of Chronic Myeloid Leukemia (CML) in a resource-limited healthcare setting. The study's findings show that controlling CML in limited settings is complicated by disease stages, risk stratification, and treatment regimens. Complete Hematological Response (CHR) rates are promising. These findings suggest age-, gender-, and regional-specific treatments to optimize patient care in resource-limited settings. The study emphasizes adaptable techniques in the face of changing demographic and clinical circumstances, adding to CML management discourse.