Abstract:Objective: To investigate the prognostic factors of extensive-stage small cell lung cancer (ES-SCLC) and establish a prognostic prediction model based on 18F-FDG PET/CT, to provide more references for subsequent clinical prognosis prediction. Methods: A total of 142 patients with ES-SCLC who underwent 18F-FDG PET/CT examination in our hospital from January 2017 to January 2020 were retrospectively enrolled. The clinical characteristics, 18F-FDG PET/CT examination indicators and overall survival follow-up information were analyzed. Univariate and multivariate analyses of prognostic factors for ES-SCLC were performed. Establishment and prediction performance analysis of the prognostic prediction model for ES-SCLC based on 18F-FDG PET/CT. Results: The 142 patients were followed up for 15-34 months, with a median follow-up time of 24.0 months. A total of 85 patients died during follow-up, and the 1-year and 2-year overall survival rates were 59.2% and 34.0%, respectively. According to the patients' age, bone metastasis, liver metastasis, total MTV of the whole body, and total TLG of the whole body, the patients were divided into two groups. There was a statistically significant difference in the median overall survival time between the subgroups (P<0.05). Univariate and multivariate COX regression analysis results showed that age, whether there was bone and liver metastasis, total MTV of the whole body 2.5 and total TLG of the whole body 2.5 were all independent prognostic factors for overall survival of patients with ES-SCLC (P<0.05). A line chart model of the survival probability of patients at different time periods was constructed based on each independent risk factor, and the C-index was 0.763. The ROC curve was used to calculate the prediction of the survival status of patients at 1, 2, and 3 years, respectively, and the area under the curve was 0.631, 0.718, and 0.722, respectively. Conclusion: The prognosis of ES-SCLC is closely related to 18F-FDG PET/CT indicators in addition to age and bone metastasis; using the above indicators to predict the survival status of patients has a good effect.
冯昭, 王洋, 范志刚. 基于18F-FDG PET/CT对广泛期小细胞肺癌预后预测模型的构建[J]. 河北医学, 2024, 30(7): 1210-1215.
FENG Zhao, et al. Establishment of a Prognostic Prediction Model for Extensive-Stage Small Cell Lung Cancer Based on 18F-FDG PET/CT. HeBei Med, 2024, 30(7): 1210-1215.
[1] 周见远,朱小华.基于(18)F-FDG PET影像组学预测非小细胞肺癌病理亚型[J].中华核医学与分子影像杂志,2021,41(5):268-274 [2] Xu P,Wang Y.Application of (18)F-FDG PET/CT in evaluation of curative effect and prognosis for small cell lung cancer[J].Zhong Nan Da Xue Xue Bao Yi Xue Ban,2020,45(10):1255-1260. [3] Araz M,Soydal C,Ozkan E,et al.Prognostic value of metabolic parameters on baseline 18F-FDG PET/CT in small cell lung cancer[J].Q Nucl Med Mol Imaging,2022,66(1):61-66. [4] 胡瑶,孙晋.小细胞肺癌原发灶18F-FDG PET/CT代谢参数与外周血炎症标志物的相关性研究[J].南京医科大学学报(自然科学版),2023,43(4):536-541. [5] Hui Z,Wei F,Ren H,et al.Primary tumor standardized uptake value (SUVmax) measured on (18)F-FDG PET/CT and mixed NSCLC components predict survival in surgical-resected combined small-cell lung cancer[J].Cancer Res Clin Oncol,2020,146(10):2595-2605. [6] Martin SS,Muscogiuri E,Burchett PF,et al.Tumorous tissue characterization using integrated 18F-FDG PET/dual-energy CT in lung cancer:Combining iodine enhancement and glycolytic activity[J].Eur Radiol,2022,150(5):110116-110123. [7] Budak E,Yanarates A,Akgun A.The prognostic role of PET/CT in small-cell lung cancer[J].Rev Esp Med Nucl Imagen Mol (Engl Ed),2020,39(1):9-13. [8] Kirienko M,Sollini M,Corbetta M,et al.Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer[J].Eur Nucl Med Mol Imaging,2021,48(11):3643-3655. [9] Choi EK,Park M,Im JJ,et al.Prognostic value of (18)F-FDG PET/CT metabolic parameters in small cell lung cancer[J].Int Med Res,2020,48(4):2419-2426. [10] Ohno Y,Yoshikawa T,Takenaka D,et al.Small cell lung cancer staging:prospective comparison of conventional staging tests,FDG PET/CT,whole-body MRI,and coregistered FDG PET/MRI[J].AJR Am Roentgenol,2022,218(5):899-908.