{"title":"Predictive value of peri-chemotherapy hematological parameters for febrile neutropenia in patients with cancer.","authors":"Hongyuan Jia, Long Liang, Xue Chen, Wenzhong Zha, Wei Diao, Wei Zhang","doi":"10.3389/fonc.2024.1380195","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to compare hematological parameters pre- and early post-chemotherapy, and evaluate their values for predicting febrile neutropenia (FN).</p><p><strong>Methods: </strong>Patients diagnosed with malignant solid tumors receiving chemotherapy were included. Blood cell counts peri-chemotherapy and clinical information were retrieved from the hospital information system. We used the least absolute shrinkage and selection operator (LASSO) method for variable selection and fitted selected variables to a logistic model. We assessed the performance of the prediction model by the area under the ROC curve.</p><p><strong>Results: </strong>The study population consisted of 4,130 patients with common solid tumors receiving a three-week chemotherapy regimen in Sichuan Cancer Hospital from February 2019 to March 2022. In the FN group, change percentage of neutrophil count decreased less (-0.02, CI: -0.88 to 3.48 vs. <i>-</i>0.04, CI: -0.83 to 2.24). Among hematological parameters, lower post-chemotherapy lymphocyte count (OR 0.942, CI: 0.934-0.949), change percentage of platelet (OR 0.965, CI: 0.955-0.975) and higher change percentage of post-chemotherapy neutrophil count (OR 1.015, CI: 1.011-1.018), and pre-chemotherapy NLR (OR 1.002, CI: 1.002-1.002) predicted an increased risk of FN. These factors improved the predicting model based on clinical factors alone. The AUC of the combination model was 0.8275.</p><p><strong>Conclusion: </strong>Peri-chemotherapy hematological markers improve the prediction of FN.</p>","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11366635/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fonc.2024.1380195","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: The aim of this study was to compare hematological parameters pre- and early post-chemotherapy, and evaluate their values for predicting febrile neutropenia (FN).
Methods: Patients diagnosed with malignant solid tumors receiving chemotherapy were included. Blood cell counts peri-chemotherapy and clinical information were retrieved from the hospital information system. We used the least absolute shrinkage and selection operator (LASSO) method for variable selection and fitted selected variables to a logistic model. We assessed the performance of the prediction model by the area under the ROC curve.
Results: The study population consisted of 4,130 patients with common solid tumors receiving a three-week chemotherapy regimen in Sichuan Cancer Hospital from February 2019 to March 2022. In the FN group, change percentage of neutrophil count decreased less (-0.02, CI: -0.88 to 3.48 vs. -0.04, CI: -0.83 to 2.24). Among hematological parameters, lower post-chemotherapy lymphocyte count (OR 0.942, CI: 0.934-0.949), change percentage of platelet (OR 0.965, CI: 0.955-0.975) and higher change percentage of post-chemotherapy neutrophil count (OR 1.015, CI: 1.011-1.018), and pre-chemotherapy NLR (OR 1.002, CI: 1.002-1.002) predicted an increased risk of FN. These factors improved the predicting model based on clinical factors alone. The AUC of the combination model was 0.8275.
Conclusion: Peri-chemotherapy hematological markers improve the prediction of FN.
期刊介绍:
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.