{"title":"Baseline <sup>18</sup>F-FDG PET/CT parameters in predicting the efficacy of immunotherapy in non-small cell lung cancer.","authors":"Lu Zheng, Yanzhu Bian, Yujing Hu, Congna Tian, Xinchao Zhang, Shuheng Li, Xin Yang, Yanan Qin","doi":"10.3389/fmed.2025.1477275","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To analyse positron emission tomography/ computed tomography (PET/CT) imaging and clinical data from patients with non-small cell lung cancer (NSCLC), to identify characteristics of survival beneficiaries of immune checkpoint inhibitors (ICIs) treatment and to establish a survival prediction model.</p><p><strong>Methods: </strong>A retrospective analysis was conducted on PET/CT imaging and clinical parameters of 155 NSCLC patients who underwent baseline PET/CT examination at the Department of Nuclear Medicine, Hebei General Hospital. The Kaplan-Meier curve was employed to compare progression-free survival (PFS) and overall survival (OS) between the ICIs and non-ICIs group and to assess the impact of variables on PFS and OS in the ICIs group. Multivariate Cox proportional hazards regression analysis was conducted with parameters significantly associated with survival in univariate analysis.</p><p><strong>Results: </strong>Significant differences were observed in PFS (<i>χ<sup>2</sup></i> = 11.910, <i>p</i> = 0.0006) and OS (<i>χ<sup>2</sup></i> = 8.343, <i>p</i> = 0.0039). Independent predictors of PFS in the ICIs group included smoking history[hazard ratio (HR) = 2.522, 95% confidence interval (CI): 1.044 ~ 6.091, <i>p</i> = 0.0398], SUVmax of the primary lesion(HR = 0.2376, 95%CI: 0.1018 ~ 0.5548, <i>p</i> = 0.0009), MTVp (HR = 0.0755, 95%CI: 0.0284 ~ 0.2003, <i>p</i> < 0.001), and TLGp (HR = 0.1820, 95%CI: 0.0754 ~ 0.4395, <i>p</i> = 0.0002). These were also independent predictors of OS in the ICIs group[HR(95%CI) were 2.729 (1.125 ~ 6.619), 0.2636 (0.1143 ~ 0.6079), 0.0715 (0.0268 ~ 0.1907), 0.2102 (0.0885 ~ 0.4992), both <i>p</i> < 0.05)]. Age was an additional independent predictor of OS (HR = 0.4140, 95%CI: 0.1748 ~ 0.9801, <i>p</i> = 0.0449).</p><p><strong>Conclusion: </strong>Smoking history, primary lesion SUVmax, MTVp, and TLGp were independent predictors of PFS, whilst age, smoking history, SUVmax, MTVp, and TLGp were independent predictors of OS in the ICIs group. Patients without a history of smoking and with SUVmax ≤19.2, MTVp ≤20.745cm<sup>3</sup>, TLGp ≤158.62 g, and age ≤ 60 years benefited more from ICI treatment.</p>","PeriodicalId":12488,"journal":{"name":"Frontiers in Medicine","volume":"12 ","pages":"1477275"},"PeriodicalIF":3.1000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11825783/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fmed.2025.1477275","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: To analyse positron emission tomography/ computed tomography (PET/CT) imaging and clinical data from patients with non-small cell lung cancer (NSCLC), to identify characteristics of survival beneficiaries of immune checkpoint inhibitors (ICIs) treatment and to establish a survival prediction model.
Methods: A retrospective analysis was conducted on PET/CT imaging and clinical parameters of 155 NSCLC patients who underwent baseline PET/CT examination at the Department of Nuclear Medicine, Hebei General Hospital. The Kaplan-Meier curve was employed to compare progression-free survival (PFS) and overall survival (OS) between the ICIs and non-ICIs group and to assess the impact of variables on PFS and OS in the ICIs group. Multivariate Cox proportional hazards regression analysis was conducted with parameters significantly associated with survival in univariate analysis.
Results: Significant differences were observed in PFS (χ2 = 11.910, p = 0.0006) and OS (χ2 = 8.343, p = 0.0039). Independent predictors of PFS in the ICIs group included smoking history[hazard ratio (HR) = 2.522, 95% confidence interval (CI): 1.044 ~ 6.091, p = 0.0398], SUVmax of the primary lesion(HR = 0.2376, 95%CI: 0.1018 ~ 0.5548, p = 0.0009), MTVp (HR = 0.0755, 95%CI: 0.0284 ~ 0.2003, p < 0.001), and TLGp (HR = 0.1820, 95%CI: 0.0754 ~ 0.4395, p = 0.0002). These were also independent predictors of OS in the ICIs group[HR(95%CI) were 2.729 (1.125 ~ 6.619), 0.2636 (0.1143 ~ 0.6079), 0.0715 (0.0268 ~ 0.1907), 0.2102 (0.0885 ~ 0.4992), both p < 0.05)]. Age was an additional independent predictor of OS (HR = 0.4140, 95%CI: 0.1748 ~ 0.9801, p = 0.0449).
Conclusion: Smoking history, primary lesion SUVmax, MTVp, and TLGp were independent predictors of PFS, whilst age, smoking history, SUVmax, MTVp, and TLGp were independent predictors of OS in the ICIs group. Patients without a history of smoking and with SUVmax ≤19.2, MTVp ≤20.745cm3, TLGp ≤158.62 g, and age ≤ 60 years benefited more from ICI treatment.
期刊介绍:
Frontiers in Medicine publishes rigorously peer-reviewed research linking basic research to clinical practice and patient care, as well as translating scientific advances into new therapies and diagnostic tools. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
In addition to papers that provide a link between basic research and clinical practice, a particular emphasis is given to studies that are directly relevant to patient care. In this spirit, the journal publishes the latest research results and medical knowledge that facilitate the translation of scientific advances into new therapies or diagnostic tools. The full listing of the Specialty Sections represented by Frontiers in Medicine is as listed below. As well as the established medical disciplines, Frontiers in Medicine is launching new sections that together will facilitate
- the use of patient-reported outcomes under real world conditions
- the exploitation of big data and the use of novel information and communication tools in the assessment of new medicines
- the scientific bases for guidelines and decisions from regulatory authorities
- access to medicinal products and medical devices worldwide
- addressing the grand health challenges around the world