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Sun Z, Zhang Y, Xia Y, Ba X, Zheng Q, Liu J, Kuang X, Xie H, Gong P, Shi Y, Mao N, Wang Y, Liu M, Ran C, Wang C, Wang X, Li M, Zhang W, Fang Z, Liu W, Guo H, Ma H, Song Y. Association between CT-based adipose variables, preoperative blood biochemical indicators and pathological T stage of clear cell renal cell carcinoma. Heliyon 2024; 10:e24456. [PMID: 38268833 PMCID: PMC10803934 DOI: 10.1016/j.heliyon.2024.e24456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 01/02/2024] [Accepted: 01/09/2024] [Indexed: 01/26/2024] Open
Abstract
Background Clear cell renal cell carcinoma (ccRCC) is corelated with tumor-associated material (TAM), coagulation system and adipocyte tissue, but the relationships between them have been inconsistent. Our study aimed to explore the cut-off intervals of variables that are non-linearly related to ccRCC pathological T stage for providing clues to understand these discrepancies, and to effectively preoperative risk stratification. Methods This retrospective analysis included 218 ccRCC patients with a clear pathological T stage between January 1st, 2014, and November 30th, 2021. The patients were categorized into two cohorts based on their pathological T stage: low T stage (T1 and T2) and high T stage (T3 and T4). Abdominal and perirenal fat variables were measured based on preoperative CT images. Blood biochemical indexes from the last time before surgery were also collected. The generalized sum model was used to identify cut-off intervals for nonlinear variables. Results In specific intervals, fibrinogen levels (FIB) (2.63-4.06 g/L) and platelet (PLT) counts (>200.34 × 109/L) were significantly positively correlated with T stage, while PLT counts (<200.34 × 109/L) were significantly negatively correlated with T stage. Additionally, tumor-associated material exhibited varying degrees of positive correlation with T stage at different cut-off intervals (cut-off value: 90.556 U/mL). Conclusion Preoperative PLT, FIB and TAM are nonlinearly related to pathological T stage. This study is the first to provide specific cut-off intervals for preoperative variables that are nonlinearly related to ccRCC T stage. These intervals can aid in the risk stratification of ccRCC patients before surgery, allowing for developing a more personalized treatment planning.
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Affiliation(s)
- Zehua Sun
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Yumei Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Yuanhao Xia
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
- Department of Radiology, Binzhou Medical University, Yantai, 264000, Shandong, China
| | - Xinru Ba
- Department of Radiology, Yantaishan Hospital, Yantai, 264000, Shandong, China
| | - Qingyin Zheng
- Department of Otolaryngology-Head & Neck Surgery, Case Western Reserve University, Cleveland, OH, 44106, United States
| | - Jing Liu
- Department of Pediatrics, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Xiaojing Kuang
- School of Basic Medicine, Qingdao University, Qingdao, 266021, Shandong, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Peiyou Gong
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Yongtao Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Ming Liu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Chao Ran
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Chenchen Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Xiaoni Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Min Li
- Department of Radiology, Yantai Traditional Chinese Medicine Hospital, Yantai, 264000, Shandong, China
| | - Wei Zhang
- Department of Radiology, Yantai Penglai People's Hospital, Yantai, 265600, Shandong, China
| | - Zishuo Fang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Wanchen Liu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Hao Guo
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Yang Song
- Department of Nutrition and Food Hygiene, School of Public Health, College of Medicine, Qingdao University, Qingdao, 266021, Shandong, China
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Zhang Y, Sun Z, Ma H, Wang C, Zhang W, Liu J, Li M, Zhang Y, Guo H, Ba X. Prediction of Fuhrman nuclear grade for clear cell renal carcinoma by a multi-information fusion model that incorporates CT-based features of tumor and serum tumor associated material. J Cancer Res Clin Oncol 2023; 149:15855-15865. [PMID: 37672076 DOI: 10.1007/s00432-023-05353-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/25/2023] [Indexed: 09/07/2023]
Abstract
PURPOSE Prediction of Fuhrman nuclear grade is crucial for making informed herapeutic decisions in clear cell renal cell carcinoma (ccRCC). The current study aimed to develop a multi-information fusion model utilizing computed tomography (CT)-based features of tumors and preoperative biochemical parameters to predict the Fuhrman nuclear grade of ccRCC in a non-invasive manner. METHODS 218 ccRCC patients confirmed by histopathology were retrospectively analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors and establish a model for predicting the Fuhrman grade in ccRCC. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration, the 10-fold cross-validation method, bootstrapping, the Hosmer-Lemeshow test, and decision curve analysis (DCA). RESULTS R.E.N.A.L. Nephrometry Score (RNS) and serum tumor associated material (TAM) were identified as independent predictors for Fuhrman grade of ccRCC through multivariate logistic regression. The areas under the ROC curve (AUC) for the multi-information fusion model composed of the above two factors was 0.810, higher than that of the RNS (AUC 0.694) or TAM (AUC 0.764) alone. The calibration curve and Hosmer-Lemeshow test showed the integrated model had a good fitting degree. The 10-fold cross-validation method (AUC 0.806) and bootstrap test (AUC 0.811) showed the good stability of the model. DCA demonstrated that the model had superior clinical utility. CONCLUSION A multi-information fusion model based on CT features of tumor and routine biochemical indicators, can predict the Fuhrman grade of ccRCC using a non-invasive approach. This model holds promise for assisting clinicians in devising personalized management strategies.
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Affiliation(s)
- Yumei Zhang
- Department of Radiology, Laishan Branch of Yantai Yuhuangding Hospital, Yantai, 264000, Shandong, China
| | - Zehua Sun
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Chenchen Wang
- Department of Radiology, Laishan Branch of Yantai Yuhuangding Hospital, Yantai, 264000, Shandong, China
| | - Wei Zhang
- Department of Radiology, Yantai Penglai People's Hospital, Yantai, 265600, Shandong, China
| | - Jing Liu
- Department of Pathology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China
| | - Min Li
- Department of Radiology, Yantai Hospital of Traditional Chinese Medicine, Yantai, 264000, Shandong, China
| | - Yuxia Zhang
- Department of Obstetrics and Gynecology, Yanzhou Hospital of TCM, Yanzhou, 272100, Shandong, China
| | - Hao Guo
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, 264000, Shandong, China.
| | - Xinru Ba
- Department of Radiology, Yantaishan Hospital, Yantai, 264000, Shandong, China.
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