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Jiang L, Tong Y, Jiang J, Zhao D. Individualized assessment predictive models for risk and overall survival in elderly patients of primary kidney cancer with bone metastases: A large population-based study. Front Med (Lausanne) 2023; 10:1127625. [PMID: 37181371 PMCID: PMC10167023 DOI: 10.3389/fmed.2023.1127625] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 04/06/2023] [Indexed: 05/16/2023] Open
Abstract
Background Elderly people are at high risk of metastatic kidney cancer (KC), and, the bone is one of the most common metastatic sites for metastatic KC. However, studies on diagnostic and prognostic prediction models for bone metastases (BM) in elderly KC patients are still vacant. Therefore, it is necessary to establish new diagnostic and prognostic nomograms. Methods We downloaded the data of all KC patients aged more than 65 years during 2010-2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses were used to study independent risk factors of BM in elderly KC patients. Univariate and multivariate Cox regression analysis for the study of independent prognostic factors in elderly KCBM patients. Survival differences were studied using Kaplan-Meier (K-M) survival analysis. The predictive efficacy and clinical utility of nomograms were assessed by receiver operating characteristic (ROC) curve, the area under curve (AUC), calibration curve, and decision curve analysis (DCA). Results A final total of 17,404 elderly KC patients (training set: n = 12,184, validation set: n = 5,220) were included to study the risk of BM. 394 elderly KCBM patients (training set: n = 278, validation set: n = 116) were included to study the overall survival (OS). Age, histological type, tumor size, grade, T/N stage and brain/liver/lung metastasis were identified as independent risk factors for developing BM in elderly KC patients. Surgery, lung/liver metastasis and T stage were identified as independent prognostic factors in elderly KCBM patients. The diagnostic nomogram had AUCs of 0.859 and 0.850 in the training and validation sets, respectively. The AUCs of the prognostic nomogram in predicting OS at 12, 24 and 36 months were: training set (0.742, 0.775, 0.787), and validation set (0.721, 0.827, 0.799), respectively. The calibration curve and DCA also showed excellent clinical utility of the two nomograms. Conclusion Two new nomograms were constructed and validated to predict the risk of developing BM in elderly KC patients and 12-, 24-, and 36-months OS in elderly KCBM patients. These models can help surgeons provide more comprehensive and personalized clinical management programs for this population.
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Affiliation(s)
| | | | | | - Dongxu Zhao
- Department of Orthopedics, The China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
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Yu X, Gao L, Zhang S, Sun C, Zhang J, Kang B, Wang X. Development and validation of A CT-based radiomics nomogram for prediction of synchronous distant metastasis in clear cell renal cell carcinoma. Front Oncol 2023; 12:1016583. [PMID: 36686790 PMCID: PMC9846314 DOI: 10.3389/fonc.2022.1016583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023] Open
Abstract
Background Early identification of synchronous distant metastasis (SDM) in patients with clear cell Renal cell carcinoma (ccRCC) can certify the reasonable diagnostic examinations. Methods This retrospective study recruited 463 ccRCC patients who were divided into two cohorts (training and internal validation) at a 7:3 ratio. Besides, 115 patients from other hospital were assigned external validation cohort. A radiomics signature was developed based on features by means of the least absolute shrinkage and selection operator method. Demographics, laboratory variables and CT findings were combined to develop clinical factors model. Integrating radiomics signature and clinical factors model, a radiomics nomogram was developed. Results Ten features were used to build radiomics signature, which yielded an area under the curve (AUC) 0.882 in the external validation cohort. By incorporating the clinical independent predictors, the clinical model was developed with AUC of 0.920 in the external validation cohort. Radiomics nomogram (external validation, 0.925) had better performance than clinical factors model or radiomics signature. Decision curve analysis demonstrated the superiority of the radiomics nomogram in terms of clinical usefulness. Conclusions The CT-based nomogram could help in predicting SDM status in patients with ccRCC, which might provide assistance for clinicians in making diagnostic examinations.
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Affiliation(s)
- Xinxin Yu
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China,School of Medicine, Shandong University, Jinan, China
| | - Lin Gao
- Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China,School of Medicine, Shandong First Medical University, Jinan, China
| | - Shuai Zhang
- School of Medicine, Shandong First Medical University, Jinan, China
| | - Cong Sun
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Juntao Zhang
- GE Healthcare, PDx GMS Advanced Analytics, Shanghai, China,*Correspondence: Ximing Wang, ; Bing Kang, ; Juntao Zhang,
| | - Bing Kang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China,*Correspondence: Ximing Wang, ; Bing Kang, ; Juntao Zhang,
| | - Ximing Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China,School of Medicine, Shandong University, Jinan, China,*Correspondence: Ximing Wang, ; Bing Kang, ; Juntao Zhang,
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Tang J, Wang J, Pan X, Liu X, Zhao B. A Web-Based Prediction Model for Cancer-Specific Survival of Middle-Aged Patients With Non-metastatic Renal Cell Carcinoma: A Population-Based Study. Front Public Health 2022; 10:822808. [PMID: 35284377 PMCID: PMC8907592 DOI: 10.3389/fpubh.2022.822808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 01/17/2022] [Indexed: 11/13/2022] Open
Abstract
Background Renal cell carcinoma (RCC) is one of the most common cancers in middle-aged patients. We aimed to establish a new nomogram for predicting cancer-specific survival (CSS) in middle-aged patients with non-metastatic renal cell carcinoma (nmRCC). Methods The clinicopathological information of all patients from 2010 to 2018 was downloaded from the SEER database. These patients were randomly assigned to the training set (70%) and validation set (30%). Univariate and multivariate COX regression analyses were used to identify independent risk factors for CSS in middle-aged patients with nmRCC in the training set. Based on these independent risk factors, a new nomogram was constructed to predict 1-, 3-, and 5-year CSS in middle-aged patients with nmRCC. Then, we used the consistency index (C-index), calibration curve, and area under receiver operating curve (AUC) to validate the accuracy and discrimination of the model. Decision curve analysis (DCA) was used to validate the clinical application value of the model. Results A total of 27,073 patients were included in the study. These patients were randomly divided into a training set (N = 18,990) and a validation set (N = 8,083). In the training set, univariate and multivariate Cox regression analysis indicated that age, sex, histological tumor grade, T stage, tumor size, and surgical method are independent risk factors for CSS of patients. A new nomogram was constructed to predict patients' 1-, 3-, and 5-year CSS. The C-index of the training set and validation set were 0.818 (95% CI: 0.802-0.834) and 0.802 (95% CI: 0.777-0.827), respectively. The 1 -, 3 -, and 5-year AUC for the training and validation set ranged from 77.7 to 80.0. The calibration curves of the training set and the validation set indicated that the predicted value is highly consistent with the actual observation value, indicating that the model has good accuracy. DCA also suggested that the model has potential clinical application value. Conclusion We found that independent risk factors for CSS in middle-aged patients with nmRCC were age, sex, histological tumor grade, T stage, tumor size, and surgery. We have constructed a new nomogram to predict the CSS of middle-aged patients with nmRCC. This model has good accuracy and reliability and can assist doctors and patients in clinical decision making.
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Affiliation(s)
- Jie Tang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenyang Medical College, Shenyang, China
| | - Jinkui Wang
- Department of Urology, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, National Clinical Research Center for Child Health and Disorders (Chongqing), Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xiudan Pan
- Department of Biostatistics and Epidemiology, School of Public Health, Shenyang Medical College, Shenyang, China
| | - Xiaozhu Liu
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Binyi Zhao
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Binyi Zhao
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Wang J, Zhanghuang C, Tan X, Mi T, Liu J, Jin L, Li M, Zhang Z, He D. Development and Validation of a Nomogram to Predict Distant Metastasis in Elderly Patients With Renal Cell Carcinoma. Front Public Health 2022; 9:831940. [PMID: 35155365 PMCID: PMC8831843 DOI: 10.3389/fpubh.2021.831940] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 12/24/2021] [Indexed: 12/09/2022] Open
Abstract
BackgroundRenal cell carcinoma (RCC) is the most common renal malignant tumor in elderly patients. The prognosis of renal cell carcinoma with distant metastasis is poor. We aim to construct a nomogram to predict the risk of distant metastasis in elderly patients with RCC to help doctors and patients with early intervention and improve the survival rate.MethodsThe clinicopathological information of patients was downloaded from SEER to identify all elderly patients with RCC over 65 years old from 2010 to 2018. Univariate and multivariate logistic regression analyzed the training cohort's independent risk factors for distant metastasis. A nomogram was established to predict the distant metastasis of elderly patients with RCC based on these risk factors. We used the consistency index (C-index), calibration curve, and area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to assess the clinical application value of the model.ResultsA total of 36,365 elderly patients with RCC were included in the study. They were randomly divided into the training cohort (N = 25,321) and the validation cohort (N = 11,044). In the training cohort, univariate and multivariate logistic regression analysis suggested that race, tumor histological type, histological grade, T stage, N stage, tumor size, surgery, radiotherapy, and chemotherapy were independent risk factors for distant metastasis elderly patients with RCC. A nomogram was constructed to predict the risk of distant metastasis in elderly patients with RCC. The training and validation cohort's C-indexes are 0.949 and 0.954, respectively, indicating that the nomogram has excellent accuracy. AUC of the training and validation cohorts indicated excellent predictive ability. DCA suggested that the nomogram had a better clinical application value than the traditional TN staging.ConclusionThis study constructed a new nomogram to predict the risk of distant metastasis in elderly patients with RCC. The nomogram has excellent accuracy and reliability, which can help doctors and patients actively monitor and follow up patients to prevent distant metastasis of tumors.
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Affiliation(s)
- Jinkui Wang
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Chenghao Zhanghuang
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Urology, Yunnan Key Laboratory of Children's Major Disease Research, Kunming Children's Hospital (Children's Hospital Affiliated to Kunming Medical University), Kunming, China
| | - Xiaojun Tan
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Urology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical University, Nanchong, China
| | - Tao Mi
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Jiayan Liu
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Liming Jin
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Mujie Li
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Zhaoxia Zhang
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Dawei He
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Dawei He
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Milman T, Magan T, Pradeep T, Tuluc M, Bilyk J. Ocular adnexal metastases from renal cell carcinoma: An update and comprehensive literature review. Saudi J Ophthalmol 2021; 35:209-216. [PMID: 35601855 PMCID: PMC9116086 DOI: 10.4103/sjopt.sjopt_96_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 05/20/2021] [Indexed: 11/23/2022] Open
Abstract
PURPOSE: The purpose of this study was to review the clinical presentation, systemic work-up, and outcomes of all previously reported ocular adnexal (OA) metastases from renal cell carcinoma (RCC). METHODS: This was a literature review. PubMed and Google Scholar databases were searched for all well-documented cases of OA metastases from RCC. RESULTS: Final analysis identified 44 patients with either biopsy-confirmed (41/44, 93%) or treatment response-documented (3/44, 6%) OA metastases from RCC. Thirty-four (77%) patients were male. The median age was 60 years (mean: 60, range: 22–87 years). The most common presenting signs were proptosis (19/44, 43%) and OA mass (14/44, 32%). Metastases most frequently involved the orbital bones (10/44, 23%) and adjacent extraconal fat, extending from the sinonasal tract in 7/10 (70%) of these cases. OA metastases were initial manifestation of RCC in 18/44 (41%) patients. At the time of primary tumor diagnosis, 22 of 30 (73%) patients had American Joint Committee on Cancer Stage IV disease with metastases to 2 or more sites in 13 (57%) patients. Seventeen of 42 (40%) patients underwent local therapy only, which most commonly included excision/exenteration with margin control (10/17, 59%). Twenty-five of 42 (60%) patients had systemic therapy, which included biologic agents and chemotherapy. The absolute 5-year survival rate was 66% with significantly improved survival in patients reported after 2006 (92% vs. 42%, P = 0.04) and in those with isolated OA metastases (100% vs. 27%, P = 0.02) at 30 months. CONCLUSION: Although RCC metastases to OA occur in a setting of advanced disease, the recent advances in diagnostic modalities and targeted therapies resulted in improved survival.
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