Development of a large database on prostate carcinoma

Buwenge, Milly (2020) Development of a large database on prostate carcinoma, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Oncologia, ematologia e patologia, 32 Ciclo.
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Abstract

The main aim of this study was to analyze the prognostic impact on outcome and toxicity of patients with prostate cancer [PCa] treated with radiotherapy [RT] in three different settings [curative, adjuvant, and salvage RT] based on a comprehensive analysis of parameters related to tumor, patients, and treatment characteristics. Furthermore, we aimed to develop simple risk stratification systems, based on real life data from a large patient population including the three different RT settings. Data on 2526 patients were collected. In the “curative RT” group we designed a prognostic model of the 5-year biochemical outcome using three PSA categories and 5 GS categories to define 15 different groups of patients. We arranged these 15 groups in only 4 categories based on 5-year bRFS values: group 1: very low-risk [bRFS > 90%], group 2: low risk [bRFS: 80-90%], group 3: intermediate risk [bRFS: 60-79.9%], group 4: high risk [bRFS < 60%]. In the “adjuvant RT” group we designed a predictive model of biochemical outcome using two age categories, two nodal stage categories, and four PSA categories to define 16 different groups of patients. These 16 groups were arranged in only 3 categories based on 5-year bRFS values: group 1: very low-risk [bRFS > 95%], group 2: low-intermediate risk [bRFS: 76-95%], group 3: high risk [bRFS: < 76%]. In the “salvage RT” group we designed a prognostic model using 4 GS categories, 2 nodal stage categories, and 2 nodal irradiation categories to define 16 different groups of patients. These 16 groups were arranged in only 4 categories based on 5-year bRFS values: group 1: low-risk [bRFS > 80%], group 2: intermediate risk [bRFS: 60-80%], group 3: high risk [bRFS: 40-< 59.9%], and group 4: very high risk [bRFS: < 40%].

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Buwenge, Milly
Supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Prostate Neoplasms, large database, predictive models, radiotherapy
URN:NBN
Data di discussione
26 Marzo 2020
URI

Altri metadati

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