Usefulness of Discriminant Analysis to Identify Metastatic status using clinical data in Clear Cell Renal Cell Carcinoma

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Abstract The main aim of our study was to assess the associations of clinical profiles and with metastatic clear cell renal cell carcinoma(ccRCC). A univariate analysis and discriminant study were performed on the clinical data retrieved from The Cancer Image Archive with two categories of the presence or absence of distant metastases of patients with ccRCC. Patients with ccRCC with distant metastases demonstrated larger tumors(without missing data), higher serum calcium level (with missing data), and higher two-tiered Fuhrman nuclear grade(without missing data) than those without distant metastases. A literature review found that Paner chromophobe tumor grading system and WHO/ISUP grading system were validated for prediction of outcomes of chromophobe RCC and papillary RCC, respectively. Occupational exposure to asbestos, petroleum byproducts and cadmium are linked with renal cell carcinoma. The dichotomous higher Fuhrman nuclear grades and larger Tumor size are statistically significant to distinguish the metastatic or non-metastatic groups of ccRCC by univariate and discriminant analysis.
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Usefulness of Discriminant Analysis to Identify Metastatic status using clinical data in Clear Cell Renal Cell Carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Usefulness of Discriminant Analysis to Identify Metastatic status using clinical data in Clear Cell Renal Cell Carcinoma Jenn Yeu Wang, Shing-Han Chen, Chun Ming Lo, Yuh Feng Lin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7263840/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The main aim of our study was to assess the associations of clinical profiles and with metastatic clear cell renal cell carcinoma(ccRCC). A univariate analysis and discriminant study were performed on the clinical data retrieved from The Cancer Image Archive with two categories of the presence or absence of distant metastases of patients with ccRCC. Patients with ccRCC with distant metastases demonstrated larger tumors(without missing data), higher serum calcium level (with missing data), and higher two-tiered Fuhrman nuclear grade(without missing data) than those without distant metastases. A literature review found that Paner chromophobe tumor grading system and WHO/ISUP grading system were validated for prediction of outcomes of chromophobe RCC and papillary RCC, respectively. Occupational exposure to asbestos, petroleum byproducts and cadmium are linked with renal cell carcinoma. The dichotomous higher Fuhrman nuclear grades and larger Tumor size are statistically significant to distinguish the metastatic or non-metastatic groups of ccRCC by univariate and discriminant analysis. Health sciences/Medical research/Outcomes research Biological sciences/Cancer/Urological cancer/Renal cancer/Renal cell carcinoma occupational exposure ccRCC grade metastasis subtypes Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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