Risk Factor Analysis and Predictive Model Construction for Thrombohemorrhagic Events in Patients with Acute Promyelocytic Leukemia

Juan QIU; Xuan HE

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Juan QIU, Xuan HE. Risk Factor Analysis and Predictive Model Construction for Thrombohemorrhagic Events in Patients with Acute Promyelocytic Leukemia[J]. Journal of Kunming Medical University.

Citation:

Juan QIU, Xuan HE. Risk Factor Analysis and Predictive Model Construction for Thrombohemorrhagic Events in Patients with Acute Promyelocytic Leukemia[J]. Journal of Kunming Medical University.

Juan QIU, Xuan HE. Risk Factor Analysis and Predictive Model Construction for Thrombohemorrhagic Events in Patients with Acute Promyelocytic Leukemia[J]. Journal of Kunming Medical University.

Citation:

Juan QIU, Xuan HE. Risk Factor Analysis and Predictive Model Construction for Thrombohemorrhagic Events in Patients with Acute Promyelocytic Leukemia[J]. Journal of Kunming Medical University.

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Risk Factor Analysis and Predictive Model Construction for Thrombohemorrhagic Events in Patients with Acute Promyelocytic Leukemia

Juan QIU,
Xuan HE

Department of Hematology，West China Hospital of Sichuan University，Chengdu Sichuan 610000，China

Received Date: 2026-02-25
Available Online: 2026-06-06

Abstract

Abstract

Objectiv To analyze the risk factors of thrombohemorrhagic events in patients with acute promyelocytic leukemia （APL） and to establish a risk prediction model. Methods 275 APL patients initially presenting with bleeding symptoms, admitted to West China Hospital of Sichuan University between May 2020 and December 2023 were retrospectively analyzed, and the patients were randomly divided into a training set （n = 165） and a validation set （n = 110） in a ratio of 3∶2. Patients in the training set were further categorized into a thrombotic hemorrhage group and a non-thrombotic hemorrhage group based on the occurrence of thrombohemorrhagic events. Multivariate logistic regression was used to identify factors associated with thrombohemorrhagic events, and a nomogram-based predictive model was constructed. Receiver Operating characteristic （ROC） curve, calibration diagram and decision curve analysis （DCA） were drawn to evaluate and verify the model. Result Among the 275 APL patients, 75 experienced thrombotic bleeding events, yielding an incidence rate of 27.27%. Compared with the non-thrombohemorrhagic group, the thrombohemorrhagic group had higher proportions of patients with white blood cell count （WBC） > 10×10⁹/L, fibrinogen （FIB） < 1.5 g/L, the proportion of bone marrow promyelocytes > 60%, as well as higher levels of prothrombin time （PT）, lactate dehydrogenase （LDH）, and D-dimer （P < 0.05）. Multivariate logistic regression showed that WBC > 10×109/L, the proportion of promyelocytes in bone marrow > 60%, increased LDH and D-dimer levels were risk factors for thrombotic and hemorrhagic events in APL patients （P < 0.05）. The ROC curve analysis results showed that the model predicted thrombohemorrhagic events with an AUC of 0.756 （95%CI: 0.662～0.835） in the training set and 0.833 （95%CI: 0.746～0.899） in the validation set. Internal validation using 1, 000 bootstrap resampling yielded Hosmer-Lemeshow test P > 0.05 for both sets, indicating good calibration. Decision curve analysis （DCA） showed a favorable net benefit across a wide range of threshold probabilities. Conclusion WBC, bone marrow promyelocyte proportion, LDH and D-dimer are risk factors for thrombotic and hemorrhagic events in APL patients. The model based on these indicators demonstrates good predictive efficiency and may assist in the early identification of high-risk groups in clinical practice.
- Acute promyelocytic leukemia,
- Thrombus bleeding,
- Risk factors,
- Predictive model

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References(22)

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