PMID: 9529026Apr 7, 1998Paper

Predicting the outcome of radiotherapy for prostate carcinoma: a model-building strategy

Cancer
E Ben-JosefJ D Forman

Abstract

Clinical research of prostate carcinoma could be enhanced by models that allow early and reliable prediction of outcome. In this study, the authors describe a model-building strategy and compare different models. The sample population was comprised of 158 patients treated definitively with radiotherapy. Univariate and multivariate logistic regression analyses were conducted to identify prognostic factors and select the best predictive model. Variables included age, race, method of diagnosis (needle biopsy vs. transurethral resection of the prostate), stage, grade, pretreatment prostate specific antigen (PSA), in-treatment PSA (PSA(tx)), posttreatment PSA (PSA(post)), and nadir PSA. The following indices were used to compare discriminatory power: log-likelihood function, Akaike information criterion, the generalized coefficient of determination, and the area under the receiver operating characteristic curve. At last follow-up, 49 patients (31%) had recurrence of carcinoma. By univariate analysis, the failure rate was significantly higher in patients with advanced stage, higher grade, higher pretherapy PSA, and nadir PSA > 1 ng/mL (P < 0.0001). Pretherapy PSA was associated significantly with stage, age, and nadir PSA (P = 0.001,...Continue Reading

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Citations

Sep 2, 2010·The Korean journal of laboratory medicine·Sang Hyun HwangKwan Jeh Lee
Jun 25, 2005·Statistics in Medicine·John M KittelsonScott S Emerson
Oct 3, 2006·Japanese Journal of Ophthalmology·Kenichiro BesshoTetsuro Oshika
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Jan 23, 1999·American Journal of Industrial Medicine·J R WilkinsT L Bean
Jun 1, 2000·Radiology·S GrippR Willers

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