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dc.contributor.authorRendon, Ricardo Andres
dc.date.accessioned2012-08-23T17:20:57Z
dc.date.available2012-08-23T17:20:57Z
dc.date.issued2012-08-23
dc.identifier.urihttp://hdl.handle.net/10222/15337
dc.description.abstractObjective: To develop a predictive model for preoperative differentiation between benign (B) and malignant (M) histology in patients with renal masses (RM) using recursive partitioning. Methods: We analyzed preoperative patient and tumour characteristics in 395 subjects who had surgery for RM suspicious for renal cell carcinoma. Results: The model predicted B vs. M histology with an overall accuracy of 89.6% (95% CI 86.2,92.5). It assigned patients with smaller tumours (<5.67cc) and a predominantly (>45%) exophytic component a high risk of B disease (52.6%). Patients with symptoms, larger tumours (>5.67cc) and larger endophytic component (>35%) have a 0% risk of B disease. Conclusion: B vs. M disease can be predicted accurately. This predictive accuracy is higher than that shown in renal biopsy series. It is hypothesized that for smaller and exophytic RMs, a biopsy is indicated. Symptomatic, larger and endophytic RMs should be removed without further investigations.en_US
dc.language.isoenen_US
dc.subjectRenal cell carcinomaen_US
dc.subjectRenal massen_US
dc.subjectpredictionen_US
dc.subjectClassification treeen_US
dc.titleA PRE-OPERATIVE PREDICTIVE MODEL FOR THE CLASSIFICATION OF NEWLY DIAGNOSED RENAL MASSES LESS THAN 5 CM IN DIAMETER AS BENIGN OR MALIGNANTen_US
dc.date.defence2012-08-15
dc.contributor.departmentDepartment of Community Health & Epidemiologyen_US
dc.contributor.degreeMaster of Scienceen_US
dc.contributor.external-examinerN/Aen_US
dc.contributor.graduate-coordinatorKathleen MacPhersonen_US
dc.contributor.thesis-readerAndreou Pantelisen_US
dc.contributor.thesis-supervisorMohamed Abdolell and Susan Kirklanden_US
dc.contributor.ethics-approvalReceiveden_US
dc.contributor.manuscriptsNoen_US
dc.contributor.copyright-releaseNoen_US
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