A Predicted Model for Refractory/Recurrent Cytomegalovirus Infection in Acute Leukemia Patients After Haploidentical Hematopoietic Stem Cell Transplantation

Overview

Journal Front Cell Infect Microbiol

Specialties Cell Biology
Infectious Diseases
Microbiology

Date 2022 Apr 8

PMID 35392613

Authors

Meng-Zhu Shen

Shen-Da Hong

Jie Wang

Xiao-Hui Zhang

Lan-Ping Xu

Yu Wang

Chen-Hua Yan

Huan Chen

Yu-Hong Chen

Wei Han

Feng-Rong Wang

Jing-Zhi Wang

Kai-Yan Liu

Xiao-Jun Huang

Xiao-Dong Mo

Affiliations

Soon will be listed here.

Abstract

Objective: We aimed to establish a model that can predict refractory/recurrent cytomegalovirus (CMV) infection after haploidentical donor (HID) hematopoietic stem cell transplantation (HSCT).

Methods: Consecutive acute leukemia patients receiving HID HSCT were enrolled (n = 289). We randomly selected 60% of the entire population (n = 170) as the training cohort, and the remaining 40% comprised the validation cohort (n = 119). Patients were treated according to the protocol registered at https://clinicaltrials.gov (NCT03756675).

Results: The model was as follows: Y = 0.0322 × (age) - 0.0696 × (gender) + 0.5492 × (underlying disease) + 0.0963 × (the cumulative dose of prednisone during pre-engraftment phase) - 0.0771 × (CD34+ cell counts in graft) - 1.2926. The threshold of probability was 0.5243, which helped to separate patients into high- and low-risk groups. In the low- and high-risk groups, the 100-day cumulative incidence of refractory/recurrent CMV was 42.0% [95% confidence interval (CI), 34.7%-49.4%] vs. 63.7% (95% CI, 54.8%-72.6%) ( < 0.001) for total patients and was 50.5% (95% confidence interval (CI), 40.9%-60.1%) vs. 71.0% (95% CI, 59.5%-82.4%) ( = 0.024) for those with acute graft-versus-host disease. It could also predict posttransplant mortality and survival.

Conclusion: We established a comprehensive model that could predict the refractory/recurrent CMV infection after HID HSCT.

Clinical Trial Registration: https://clinicaltrials.gov, identifier NCT03756675.

Citing Articles

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