{"title":"Predictive Model of Gemtuzumab Ozogamicin Response in Childhood Acute Myeloid Leukemia on Event-Free Survival: Data Analysis Based on Trial AAML0531.","authors":"Kun-Yin Qiu, Xiong-Yu Liao, Jian-Pei Fang, Dun-Hua Zhou","doi":"10.3390/bioengineering12030297","DOIUrl":null,"url":null,"abstract":"<p><p><b>Purpose:</b> We aimed to develop a simple nomogram and online calculator that can identify the optimal subpopulation of pediatric acute myeloid leukemia (AML) patients who would benefit most from gemtuzumab ozogamicin (GO) therapy. <b>Methods:</b> Within the framework of the phase Ⅲ AAML0531 randomized trial for GO, the event-free survival (EFS) probability was calculated using a predictor-based nomogram to evaluate GO treatment impact on EFS in relation to baseline characteristics. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 500 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram. <b>Results:</b> A total of 705 patients were randomly assigned to two arms: the No-GO arm (n = 358) and the GO arm (n = 347). We performed a nomogram model for EFS among childhood AML. The AUC (C statistic) of the nomogram was 0.731 (95%CI: 0.614-0.762) in the development group and 0.700 (95% CI: 0.506-0.889) in the validation group. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0-0.75 and 0-0.75, respectively. Notably, an intriguing observation emerged wherein pediatric patients with AML exhibited a favorable outcome in the GO arm when the predicted 5-year EFS probability fell below 60%, demonstrating a superior EFS compared to the No-GO Arm. <b>Conclusions:</b> We have developed a nomogram and online calculator that can be used to predict EFS among childhood AML based on trial AAML0531, and this might help deciding which patients can benefit from GO.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939501/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioengineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/bioengineering12030297","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: We aimed to develop a simple nomogram and online calculator that can identify the optimal subpopulation of pediatric acute myeloid leukemia (AML) patients who would benefit most from gemtuzumab ozogamicin (GO) therapy. Methods: Within the framework of the phase Ⅲ AAML0531 randomized trial for GO, the event-free survival (EFS) probability was calculated using a predictor-based nomogram to evaluate GO treatment impact on EFS in relation to baseline characteristics. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 500 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram. Results: A total of 705 patients were randomly assigned to two arms: the No-GO arm (n = 358) and the GO arm (n = 347). We performed a nomogram model for EFS among childhood AML. The AUC (C statistic) of the nomogram was 0.731 (95%CI: 0.614-0.762) in the development group and 0.700 (95% CI: 0.506-0.889) in the validation group. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0-0.75 and 0-0.75, respectively. Notably, an intriguing observation emerged wherein pediatric patients with AML exhibited a favorable outcome in the GO arm when the predicted 5-year EFS probability fell below 60%, demonstrating a superior EFS compared to the No-GO Arm. Conclusions: We have developed a nomogram and online calculator that can be used to predict EFS among childhood AML based on trial AAML0531, and this might help deciding which patients can benefit from GO.
期刊介绍:
Aims
Bioengineering (ISSN 2306-5354) provides an advanced forum for the science and technology of bioengineering. It publishes original research papers, comprehensive reviews, communications and case reports. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. All aspects of bioengineering are welcomed from theoretical concepts to education and applications. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, four key features of this Journal:
● We are introducing a new concept in scientific and technical publications “The Translational Case Report in Bioengineering”. It is a descriptive explanatory analysis of a transformative or translational event. Understanding that the goal of bioengineering scholarship is to advance towards a transformative or clinical solution to an identified transformative/clinical need, the translational case report is used to explore causation in order to find underlying principles that may guide other similar transformative/translational undertakings.
● Manuscripts regarding research proposals and research ideas will be particularly welcomed.
● Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.
● We also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds.
Scope
● Bionics and biological cybernetics: implantology; bio–abio interfaces
● Bioelectronics: wearable electronics; implantable electronics; “more than Moore” electronics; bioelectronics devices
● Bioprocess and biosystems engineering and applications: bioprocess design; biocatalysis; bioseparation and bioreactors; bioinformatics; bioenergy; etc.
● Biomolecular, cellular and tissue engineering and applications: tissue engineering; chromosome engineering; embryo engineering; cellular, molecular and synthetic biology; metabolic engineering; bio-nanotechnology; micro/nano technologies; genetic engineering; transgenic technology
● Biomedical engineering and applications: biomechatronics; biomedical electronics; biomechanics; biomaterials; biomimetics; biomedical diagnostics; biomedical therapy; biomedical devices; sensors and circuits; biomedical imaging and medical information systems; implants and regenerative medicine; neurotechnology; clinical engineering; rehabilitation engineering
● Biochemical engineering and applications: metabolic pathway engineering; modeling and simulation
● Translational bioengineering