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Construction of A Nomogram Prediction Model for PD-L1 Expression in Non-small Cell Lung Cancer Based on 18F-FDG PET/CT Metabolic Parameters.

Background and objective In recent years, immunotherapy represented by programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunosuppressants has greatly changed the status of non-small cell lung cancer (NSCLC) treatment. PD-L1 has become an important biomarker for screening NSCLC...

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Publicado en:Chinese Journal of Lung Cancer Vol. 26; no. 11; pp. 833 - 843
Autores principales: Luoluo HAO, Lifeng WANG, Mengyao ZHANG, Jiaming YAN, Feifei ZHANG
Formato: diagnostic images research tables/charts Journal Article
Publicado: Chinese Journal of Lung Cancer Nov2023
Acceso en línea:Ver este registro en EBSCOhost
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        10093419
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      jtl: Chinese Journal of Lung Cancer
      issn: 10093419
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    pubinfo:
      dt: Nov2023
      vid: 26
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      pid: 54191
      pub: Chinese Journal of Lung Cancer
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        174146779
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        10.3779/j.issn.1009-3419.2023.101.32
        174146779
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        atl: Construction of A Nomogram Prediction Model for PD-L1 Expression in Non-small Cell Lung Cancer Based on 18F-FDG PET/CT Metabolic Parameters.
      aug:
        au:
          Luoluo HAO
          Lifeng WANG
          Mengyao ZHANG
          Jiaming YAN
          Feifei ZHANG
        affil: Baotou Medical College, Inner Mongolia University of Science & Technology, Baotou 014040, China
      sug:
        subj:
          Carcinoma, Non-Small-Cell Lung Prognosis
          Prediction Models
          Programmed Cell Death Ligand 1
          Gene Expression
          Carcinoma, Non-Small-Cell Lung Drug Therapy
          Immunosuppressive Agents Therapeutic Use
          Fludeoxyglucose F 18 Diagnostic Use
          Positron-Emission Tomography Methods
          Human
          Retrospective Design
          Logistic Regression
          Chi Square Test
          ROC Curve
          Confidence Intervals
          Funding Source
      ab: Background and objective In recent years, immunotherapy represented by programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunosuppressants has greatly changed the status of non-small cell lung cancer (NSCLC) treatment. PD-L1 has become an important biomarker for screening NSCLC immunotherapy beneficiaries, but how to easily and accurately detect whether PD-L1 is expressed in NSCLC patients is a difficult problem for clinicians. The aim of this study was to construct a Nomogram prediction model of PD-L1 expression in NSCLC patients based on 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography/conputed tomography (PET/CT) metabolic parameters and to evaluate its predictive value. Methods Retrospective collection of 18F-FDG PET/CT metabolic parameters, clinicopatho-logical information and PD-L1 test results of 155 NSCLC patients from Inner Mongolia People's Hospital between September 2016 and July 2021. The patients were divided into the training group (n=117) and the internal validation group (n=38), and another 51 cases of NSCLC patients in our hospital between August 2021 and July 2022 were collected as the external validation group according to the same criteria. Then all of them were categorized according to the results of PD-L1 assay into PD-L1+ group and PD-L1- group. The metabolic parameters and clinicopathological information of patients in the training group were analyzed by univariate and binary Logistic regression, and a Nomogram prediction model was constructed based on the screened independent influencing factors. The effect of the model was evaluated by receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) in both the training group and the internal and external validation groups. Results Binary Logistic regression analysis showed that metabolic tumor volume (MTV), gender and tumor diameter were independent influences on PD-L1 expression. Then a Nomogram prediction model was constructed based on the above independent influences. The ROC curve for the model in the training group shows an area under the curve (AUC) of 0.769 (95%CI: 0.683-0.856) with an optimal cutoff value of 0.538. The AUC was 0.775 (95%CI: 0.614-0.936) in the internal validation group and 0.752 (95%CI: 0.612-0.893) in the external validation group. The calibration curves were tested by the Hosmer-Lemeshow test and showed that the training group (x2=0.040, P=0.979), the internal validation group (x2=2.605, P=0.271), and the external validation group (x2=0.396, P=0.820) were well calibrated. The DCA curves show that the model provides clinical benefit to patients over a wide range of thresholds (training group: 0.00-0.72, internal validation group: 0.00-0.87, external validation group: 0.00-0.66). Conclusion The Nomogram prediction model constructed on the basis of 18F-FDG PET/CT metabolic parameters has greater application value in predicting PD-L1 expression in NSCLC patients.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: Chinese
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