Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective: To analyze the prognostic significance of TP53, Bcl-2, Bcl-6, Myc proteins expression by immunohistochemical method (IHC) in diffuse large B cell Lymphoma (DLBCL) . Methods: Clinical and pathologic data of 223 patients with DLBCL hospitalized in Zhejiang First Hospital from March 2009 to June 2015 were retrospectively analyzed. Results: The 223 cases, a median age of 56 years old with a male predominance, had shown a 39.0% of TP53 positive expression, 38.6% of Myc, 69.1% of Bcl-2, 56.5% of Bcl-6, and 22.7% of Myc/Bcl-2 double expression. According to Hans’ classification, 27.4% were GCB and 72.6% were non-GCB. With a median follow-up of 38 (2-97) months, the 3 and 5 years survival rates were 70% and 66% , respectively. By multivariate analysis, TP53 over-expression and Myc/Bcl-2 double expression were independently associated with poor outcomes. 3-year and 5-year overall survival were 59% and 57% for patients with TP53 positive, 77% and 71% for patients with TP53 negative expression. Patients with non-GCB subtype receiving chemotherapy combined with rituximab had a higher OS than those without rituximab. But rituximab did not improve the prognosis of patients with TP53 positive. Conclusion Myc/Bcl-2 double expression and TP53 over-expression are poor prognosis for DLBCL patients. Patients with Myc/Bcl-2 double expression have shorter OS. Patients with non-GCB subtype who received chemotherapy combined with rituximab have a better OS than those without rituximab. But rituximab does not improve the prognosis of patients with TP53 positive.