Bleeding and Thrombotic Risk Prediction in Acute Leukemia: Clinical Utility of the Siriraj Acute Myeloid/Lymphoblastic Leukemia (SiAML) Score Versus Established Hemostatic Tools

Acute leukemia is a blood cancer marked by rapid growth of immature cells, causing bone marrow failure and serious complications. Among these, thrombosis and bleeding are major concerns, significantly increasing illness and death. Venous thromboembolism (VTE) occurs in about 9% of patients, with some studies showing rates up to 13.6% within the first six months after diagnosis (1,2,3). Bleeding complications are also frequent, with 60-80% of acute leukemia patients developing thrombocytopenia, a major risk factor for life-threatening hemorrhagic events such as intracranial hemorrhage (ICH). In fact, up to 26% of patients may experience clinically significant bleeding during induction therapy, often within the first two weeks of treatment (4,5). The development of thrombosis and bleeding in acute leukemia is complex and involves multiple factors. Leukemic blasts promote clotting, while chemotherapy, infections, and use of central venous catheters further elevate the risk of both bleeding and thrombosis (1,6). Despite the clinical significance of these complications, predicting which patients are at highest risk remains challenging. Several predictive scores have been developed for VTE and bleeding in cancer patients, but their utility in acute leukemia is limited due to the unique risk profile of this population. Recent efforts have focused on developing and validating simplified, leukemia-specific predictive models that incorporate clinical and laboratory parameters to better stratify risk and guide management (1,7). Owattanapanich W. and his colleagues designed a new Siriraj Acute Myeloid/Lymphoblastic Leukemia (SiAML) bleeding and thrombosis scoring system for thrombohemorrhagic complications in newly diagnosed acute leukemia. They reported that this score might be valuable for prognosticating individuals at risk for bleeding and thrombotic complications. However, several limitations were identified: the small sample size, especially for APL cases, prevented analysis by leukemia subtype and may have led to underreporting of thrombohemorrhagic events. The retrospective design also resulted in missing patient data. Lastly, external validation in diverse populations is needed to confirm the accuracy of the scoring systems (7). Therefore, in our study, we aim to extend the previous work by including two additional scores: the ISTH-BAT and the Khorana score. We will compare the sensitivity and specificity of the ISTH-BAT, ISTH-DIC, Khorana, and siAML scores in relation to hemorrhagic and thrombotic complications in patients with acute leukemia. Our study also seeks to validate the clinical utility and accuracy of these scores in predicting both types of complications across all subtypes of acute leukemia, to make sure that analysis of all subtypes will be performed. Furthermore, by adopting a prospective design, we aim to minimize missing data and enhance the reliability of our findings.