Publications by authors named "Siwei Qian"

3 Publications

  • Page 1 of 1

Development and Validation of Prognostic Nomogram for Young Patients with Kidney Cancer.

Int J Gen Med 2021 1;14:5091-5103. Epub 2021 Sep 1.

Department of Urology, Zhongda Hospital, Southeast University, Nanjing, 210009, People's Republic of China.

Background: The aim of this study was to establish a nomogram model to evaluate the prognosis of early-onset kidney cancer (EOKC) in terms of overall survival (OS) and cancer-specific survival (CSS).

Methods: Patients with EOKC diagnosed between 2004 and 2015 were collected from Surveillance, Epidemiology and End Results (SEER) and randomly assigned to the training and validation set at a ratio of 2 to 1. Important variables for constructing nomograms were screened by univariate and multivariate Cox analysis. The nomogram model was evaluated using concordance index (C-index), decision curve analysis (DCA) curves, and receiver operating characteristic (ROC) curves.

Results: A total of 12,526 EOKC patients were included in the study. OS nomogram was constructed based on gender, age, race, grade, AJCC stage, TNM stage, histology, chemotherapy and radiotherapy. CSS nomogram was constructed based on listed above except gender. In the external validation, the C-index for the OS nomogram was 0.855 (95% CI 0.834-0.976), and the C-index for the CSS nomogram was 0.938 (0.925-0.951). High-quality calibration curves were noted in both OS and CSS nomogram models. ROC and DCA curves showed that nomograms had better predictive performance than TNM stage and SEER stage.

Conclusion: The nomogram model provides an applicable tool for evaluating the OS and CSS prognosis of EOKC.
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http://dx.doi.org/10.2147/IJGM.S331627DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420796PMC
September 2021

Polycyclic Aromatic Hydrocarbons and the Risk of Kidney Stones in US Adults: An Exposure-Response Analysis of NHANES 2007-2012.

Int J Gen Med 2021 21;14:2665-2676. Epub 2021 Jun 21.

Department of Urology, Zhongda Hospital, Southeast University, Nanjing, 210009, People's Republic of China.

Background: Polycyclic aromatic hydrocarbons (PAHs) exposure may cause various diseases. However, the association between PAHs exposure and kidney stones remains unclear. The purpose of this study was to examine the relationship between PAHs and the risk of kidney stones in the US population.

Methods: The study included a total of 30,442 individuals (≥20 years) from the 2007-2012 National Health and Nutrition Examination Survey (NHANES). Nine urinary PAHs were included in this study. Logistic regression and dose-response curves were used to evaluate the association between PAHs and the risk of kidney stones.

Results: We selected 4385 participants. The dose-response curves showed a significant positive association between total PAHs, 2-hydroxynaphthalene, 1-hydroxyphenanthrene, 2-hydroxyphenanthrene, 9-hydroxyfluorene and the risk of kidney stones after adjusting for confounding factors. Compared with the low group, an increased risk of kidney stones was observed in the high group of total PAHs [OR (95% CI), 1.32 (1.06-1.64), P=0.013], 2-hydroxynaphthalene [OR (95% CI), 1.37 (1.10-1.71), P=0.005], 1-hydroxyphenanthrene [OR (95% CI), 1.24 (1.00-1.54), P=0.046] and 9-hydroxyfluorene [OR (95% CI), 1.36 (1.09-1.70), P=0.007].

Conclusion: High levels of PAHs were positively associated with the risk of kidney stones in the US population.
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http://dx.doi.org/10.2147/IJGM.S319779DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232959PMC
June 2021

Integrative Analysis of DNA Methylation Identified 12 Signature Genes Specific to Metastatic ccRCC.

Front Oncol 2020 8;10:556018. Epub 2020 Oct 8.

Department of Urology, Zhongda Hospital, Southeast University, Nanjing, China.

Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Bioinformatic analysis of DNA methylation data provides broad prospects for discovery of epigenetic biomarkers. However, there is short of exploration of methylation-driven genes of ccRCC. Gene expression data and DNA methylation data in metastatic ccRCC were sourced from the Gene Expression Omnibus (GEO) database. Differentially methylated genes (DMGs) at 5'-C-phosphate-G- 3' (CpG) sites and differentially expressed genes (DEGs) were screened and the overlapping genes in DMGs and DEGs were then subject to gene set enrichment analysis. Next, the weighted gene co-expression network analysis (WGCNA) was used to search hub DMGs associated with ccRCC. Cox regression and ROC analyses were performed to screen potential biomarkers and develop a prognostic model based on the screened hub genes. Three hundred and fourteen overlapping DMGs were obtained from two independent GEO datasets. The turquoise module contained 79 hub DMGs, which represent the most significant module screened by WGCNA. Furthermore, a total of 12 hub genes (, and ) were identified in the TCGA database by multivariate Cox regression analyses. All the 12 genes were then used to generate the model for diagnosis and prognosis of ccRCC. ROC analysis showed that these genes exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Furthermore, the prognostic model with the 12 methylation-driven genes demonstrated a good prediction of 5-year survival rates for ccRCC patients. Integrative analysis of DNA methylation data identified 12 signature genes, which could be used as epigenetic biomarkers for prognosis of metastatic ccRCC. This prognostic model has a good prediction of 5-year survival for ccRCC patients.
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http://dx.doi.org/10.3389/fonc.2020.556018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578385PMC
October 2020
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