Cardiac-Related Lesions in Newly Diagnosed Patients With Acute Leukemia: A Chinese Population-Based Real-World Study

Cardiotoxicity in Acute Myeloid Leukemia in Adults: A Scoping Study

Introduction: According to the National Cancer Institute of the NIH, acute myeloid leukemia (AML) is a rapidly growing cancer with a large quantity of myeloblasts. AML is most often observed in adults over the age of 35, accounting for 1% of all cancer types. In 2023, the number of new cases being reported was estimated to reach around 20,380 in total and the rate of mortality in the same year was 1.9%, or 11,310 cases, in the US. Purpose: This scoping study aims to extensively assess and explore the degree of cardiotoxicity in patients with AML that can be caused due to pharmaceutical treatments prescribed by hematologists. This is achieved by performing extensive searches of different scientific databases including PubMed, Scopus, and ScienceDirect. Results: A variety of options are available that are summarized in tables included herein, with each having their advantages and risks of adverse effects, among these being cardiotoxicity. Important medications found to play a significant role include gemtuzumab ozogamicin, venetoclax, and vyxeos. Conclusions: It is understandable that being familiar with all the treatment options available and every potential adverse effect is impossible. However, hematologists and, in general, physicians must try to be updated with the most recent information released to improve the quality of life of their patients and minimize the risk of additional complications.

Development of a risk assessment model for cardiac injury in patients newly diagnosed with acute myeloid leukemia based on a multicenter, real-world analysis in China

BACKGROUND

Studies have revealed that acute myeloid leukemia (AML) patients are prone to combined cardiac injury. We aimed to identify hematological risk factors associated with cardiac injury in newly diagnosed AML patients before chemotherapy and develop a personalized predictive model.

METHODS

The population baseline, blood test, electrocardiogram, echocardiograph, and genetic and cytogenetic data were collected from newly diagnosed AML patients. The data were subdivided into training and validation cohorts. The independent risk factors were explored by univariate and multivariate logistic regression analysis respectively, and data dimension reduction and variable selection were performed using the least absolute shrinkage and selection operator (LASSO) regression models. The nomogram was generated and the reliability and generalizability were verified by receiver operating characteristic (ROC) curves, the area under the curve (AUC) and calibration curves in an external validation cohort.

RESULTS

Finally, 499 AML patients were included. After univariate logistic regression, LASSO regression and multivariate logistic regression analysis, abnormal NT-proBNP, NPM1 mutation, WBC, and RBC were independent risk factors for cardiac injury in AML patients (all P < 0.05). The nomogram was constructed based on the above four variables with high accuracy. The area under the curve was 0.742, 0.750, and 0.706 in the training, internal validation, and external validation cohort, respectively. The calibration curve indicated that the model has good testing capability. The Kaplan-Meier curve showed that the higher the risk of combined cardiac injury in AML patients, the lower their probability of survival.

CONCLUSIONS

This prediction nomogram identifies hematological risk factors associated with cardiac injury in newly diagnosed AML patients and can help hematologists identify the risk and provide precise treatment options.

Development of a risk assessment model for cardiac injury in patients newly diagnosed with acute myeloid leukemia based on a multicenter, real-world analysis in China

Background

Studies have revealed that acute myeloid leukemia (AML) patients are prone to combined cardiac injury. We aimed to identify hematological risk factors associated with cardiac injury in newly diagnosed AML patients before chemotherapy and develop a personalized predictive model.

Methods

The population baseline, blood test, electrocardiogram, echocardiograph, and genetic and cytogenetic data were collected from newly diagnosed AML patients. The data were subdivided into training and validation cohorts. The independent risk factors were explored by univariate and multivariate logistic regression analysis respectively, and data dimension reduction and variable selection were performed using the least absolute shrinkage and selection operator (LASSO) regression models. The nomogram was generated and the reliability and generalizability were verified by receiver operating characteristic (ROC) curves, the area under the curve (AUC) and calibration curves in an external validation cohort.

Results

Finally, 499 AML patients were included. After univariate logistic regression, LASSO regression and multivariate logistic regression analysis, abnormal NT-proBNP, NPM1 mutation, WBC, and RBC were independent risk factors for cardiac injury in AML patients (all P < 0.05). The nomogram was constructed based on the above four variables with high accuracy. The area under the curve was 0.742, 0.750, and 0.706 in the training, internal validation, and external validation cohort, respectively. The calibration curve indicated that the model has good testing capability. The Kaplan-Meier curve showed that the higher the risk of combined cardiac injury in AML patients, the lower their probability of survival.

Conclusions

This prediction nomogram identifies hematological risk factors associated with cardiac injury in newly diagnosed AML patients and can help hematologists identify the risk and provide precise treatment options.