A combined postoperative nomogram for survival prediction in clear cell renal carcinoma.
Purpose: To investigate and validate the prognostic value of nomogram models for predicting disease-free survival (DFS) and overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC). Methods: In this retrospective study, 223 patients (age 54.38 ± 10.93 years) with pathologically...
| Publicado en: | Abdominal Radiology Vol. 47; no. 1; pp. 297 - 310 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154792864&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154792864 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Jan2022 vid: 47 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 154792864 152984941 154792864 154792864 10.1007/s00261-021-03293-4 154792864 ppf: 297 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A combined postoperative nomogram for survival prediction in clear cell renal carcinoma. aug: au: Ming, Ying Chen, Xinyi Xu, Jingxu Zhan, Haiyu Zhang, Jie Ma, Teng Huang, Chencui Liu, Zhiling Huang, Zhaoqin affil: Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 324, Jingwu Road, Huaiyin District, 250012, Jinan, Shandong, China sug: subj: Prediction Models Carcinoma, Renal Cell Prognosis Disease-Free Survival Cancer Patients Human Retrospective Design Carcinoma, Renal Cell Surgery Lymph Node Excision Random Assignment Prospective Studies Tomography, X-Ray Computed Carcinoma, Renal Cell Pathology Univariate Statistics Multivariate Analysis Cox Proportional Hazards Model Regression Descriptive Statistics Data Management Radiographic Image Enhancement Adult Middle Age Aged Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years ab: Purpose: To investigate and validate the prognostic value of nomogram models for predicting disease-free survival (DFS) and overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC). Methods: In this retrospective study, 223 patients (age 54.38 ± 10.93 years) with pathologically confirmed ccRCC who underwent resection and lymph node dissection between March 2010 and September 2018 were investigated. All patients were randomly divided into training (n = 155) and validation (n = 68) cohorts. Radiomics features were extracted from computed tomography (CT) images in the unenhanced, corticomedullary, and nephrographic phases. Radiomic score was calculated and combined with clinicopathological factors for model construction and nomogram development. Clinicopathological factors and imaging features were collected at initial diagnosis. Univariate and multivariate Cox proportional hazards regression analyses were used to evaluate the relationship between the radiomics signature and prognosis outcomes. Results: There were four prognostic factors for predicting DFS and five factors for predicting OS in our nomogram model (P < 0.05). The radiomics signature correlated independently with DFS (hazard ratio = 27; P < 0.001) and OS (hazard ratio = 25; P < 0.001). The nomogram showed excellent performance (C-index = 0.825) for predicting DFS. The combined nomogram also showed the highest C-index for OS (C-index = 0.943), which was verified in the validation dataset. Conclusion: The combined nomogram model based on radiomics, clinicopathological factors, and preoperative CT features can accurately perform prognosis and survival analysis and can potentially be used for preoperative non-invasive survival prediction in ccRCC patients. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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