1. 18 F-Fluorodeoxyglucose Positron Emission Tomography-Based Risk Score Model for Prediction of Five-Year Survival Outcome after Curative Resection of Non-Small-Cell Lung Cancer.
- Author
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Lim, Chae Hong, Um, Sang-Won, Kim, Hong Kwan, Choi, Yong Soo, Pyo, Hong Ryul, Ahn, Myung-Ju, and Choi, Joon Young
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RISK assessment ,RADIOPHARMACEUTICALS ,PREDICTION models ,RESEARCH funding ,DEOXY sugars ,MULTIPLE regression analysis ,FISHER exact test ,TREATMENT effectiveness ,POSITRON emission tomography ,RETROSPECTIVE studies ,DESCRIPTIVE statistics ,MULTIVARIATE analysis ,CHI-squared test ,MANN Whitney U Test ,ODDS ratio ,MEDICAL records ,ACQUISITION of data ,LUNG cancer ,SURVIVAL analysis (Biometry) ,CONFIDENCE intervals ,DATA analysis software ,COMPARATIVE studies ,PREDICTIVE validity - Abstract
Simple Summary: The
18 F-FDG PET parameters reflecting the intensity and distribution of glucose uptake by the tumor are associated with prognosis in non-small-cell lung cancer (NSCLC) patients. We developed and evaluated an imaging-based model utilizing these18 F-FDG PET-derived features for predicting the five-year survival in NSCLC patients after curative surgery. The PET-based risk score constructed using the LASSO logistic method outperformed the predictive performances of individual18 F-FDG PET parameters. The PET-based risk score was an independent prognostic factor for clinical variables. Additionally, it demonstrated better predictive performance when combined with clinical variables. The FDG PET-based imaging model could aid in risk stratification for personalized adjuvant treatment and follow-up management of NSCLC patients after surgery. The aim of our retrospective study is to develop and assess an imaging-based model utilizing18 F-FDG PET parameters for predicting the five-year survival in non-small-cell lung cancer (NSCLC) patients after curative surgery. A total of 361 NSCLC patients who underwent curative surgery were assigned to the training set (n = 253) and the test set (n = 108). The LASSO regression model was used to construct a PET-based risk score for predicting five-year survival. A hybrid model that combined the PET-based risk score and clinical variables was developed using multivariate logistic regression analysis. The predictive performance was determined by the area under the curve (AUC). The individual features with the best predictive performances were co-occurrence_contrast (AUC = 0.675) and SUL peak (AUC = 0.671). The PET-based risk score was identified as an independent predictor after adjusting for clinical variables (OR 5.231, 95% CI 1.987–6.932; p = 0.009). The hybrid model, which integrated clinical variables, significantly outperformed the PET-based risk score alone in predictive accuracy (AUC = 0.771 vs. 0.696, p = 0.022), a finding that was consistent in the test set. The PET-based risk score, especially when integrated with clinical variables, demonstrates good predictive ability for five-year survival in NSCLC patients following curative surgery. [ABSTRACT FROM AUTHOR]- Published
- 2024
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