Report of a chronic myeloid leukemia registry in a low-and middle-income setting.

person Nicolas Anthony Othieno-Abinya Nairobi Hospital Cancer Centre, Nairobi, Kenya info_outline Nicolas Anthony Othieno-Abinya, Walter Mwanda, Miriam Claire Mutebi, Mary Flaviane Nyangasi, Valerian Mwenda, Peter Omondi Oyiro, Angela Awino MCLIGEYO, Mohammed Shabbir Ezzi, Andrew Oluoch Odhiambo, Matilda Ong'ondi, Sitna Ali Mwanzi, Ebrahim Adamjee, Magdalene Induli

Authors person Nicolas Anthony Othieno-Abinya Nairobi Hospital Cancer Centre, Nairobi, Kenya info_outline Nicolas Anthony Othieno-Abinya, Walter Mwanda, Miriam Claire Mutebi, Mary Flaviane Nyangasi, Valerian Mwenda, Peter Omondi Oyiro, Angela Awino MCLIGEYO, Mohammed Shabbir Ezzi, Andrew Oluoch Odhiambo, Matilda Ong'ondi, Sitna Ali Mwanzi, Ebrahim Adamjee, Magdalene Induli Organizations Nairobi Hospital Cancer Centre, Nairobi, Kenya, University of Nairobi, Nairobi, Kenya, Aga Khan University Hospital, Nairobi, Kenya, Field Epidemiology and Laboratory Training Programme, Ministry of Health, Kenya, Nairobi, Kenya, Kenyatta University, Nairobi, Kenya, Kenyatta National Hospital, Nairobi, Kenya, Novartis Kenya Limited, Nairobi, Kenya Abstract Disclosures Research Funding Pharmaceutical/Biotech Company Novartis Kenya Limited Background: Treatment of chronic myeloid leukaemia (CML) in Kenya has been supported since the year 2002 by a collaboration between the Max Foundation and Novartis Pharmaceuticals in the Glivec International Patient Assistance Program (GIPAP). In November 2020 this was transitioned to Max Access Solutions (MAS) that brought in the Ministry of Health as a partner. A broad range of BCR-ABL tyrosine kinase inhibitors are available. We wanted to describe epidemiology, treatment and outcome of CML in the country. Methods: Patients’ records were reviewed and data entered in a database. Key variables included age, sex, BMI, diet, disease phase at diagnosis, treatment, and outcome. Continuous variables were summarized using mean (standard deviation) or median (interquartile range). Categorical variables were summarized using counts and percentages. Bivariate comparisons of treatment outcome were done using chi-square or Fisher’s exact test. Analysis of variance (ANOVA) or Kruskal-Wallis test was used for continuous variables. Results: 1347 patients-males 748 (55.5%), females 599 (44.5%). Mean age was 44.5 years. Seventy (9.0%) were underweight, 88 (11.4%) obese. Mean body surface area (BSA) was 1.75m 2 . Chronic phase cases were 1177 (96.2%), accelerated phase 46 (3.8%), blastic phase 1 (0.1%). Mean bone marrow blast count was 5.25%, BCR-ABL/ABL was 63.7%, haemoglobin 10.8g/dl, total wbc count 225 x 10 9 /litre, platelets 392.5 x 10 9 /litre. Imatinib was administered upfront to 1319 patients (99.8%). Two hundred and six (15.3%) were switched to second line; 100 (48.8%) to dasatinib, 50 (24.4%) to bosutinib. Transformation was registered in 26 cases (1.9%) - accelerated in 13 (72.2%), blastic in 5 (27.8%), 4 (80.0%) being myeloid and 1 (20%) lymphoblastic. Those alive are 1151 (85.4%) and 185 (13.7%) lost to follow-up. Deaths were recorded in 11 (0.8%). Those with lower BSA were more likely to die (p = 0.01). Conclusions: CML in Kenya occurs at a younger age-group with a slight male preponderance. With availability of a range of BCR-ABL tyrosine kinase inhibitors, treatment outcome is close to what is documented in high-income settings.