2 resultados para Multivariable logistic regression

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Objective The objective of this study was to develop a clinical nomogram to predict gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (68Ga-PSMA-11-PET/CT) positivity in different clinical settings of PSA failure. Materials and methods Seven hundred three (n = 703) prostate cancer (PCa) patients with confirmed PSA failure after radical therapy were enrolled. Patients were stratified according to different clinical settings (first-time biochemical recurrence [BCR]: group 1; BCR after salvage therapy: group 2; biochemical persistence after radical prostatectomy [BCP]: group 3; advanced stage PCa before second-line systemic therapies: group 4). First, we assessed 68Ga-PSMA-11-PET/CT positivity rate. Second, multivariable logistic regression analyses were used to determine predictors of positive scan. Third, regression-based coefficients were used to develop a nomogram predicting positive 68Ga-PSMA-11-PET/CT result and 200 bootstrap resamples were used for internal validation. Fourth, receiver operating characteristic (ROC) analysis was used to identify the most informative nomogram’s derived cut-off. Decision curve analysis (DCA) was implemented to quantify nomogram’s clinical benefit. Results 68Ga-PSMA-11-PET/CT overall positivity rate was 51.2%, while it was 40.3% in group 1, 54% in group 2, 60.5% in group 3, and 86.9% in group 4 (p < 0.001). At multivariable analyses, ISUP grade, PSA, PSA doubling time, and clinical setting were independent predictors of a positive scan (all p ≤ 0.04). A nomogram based on covariates included in the multivariate model demonstrated a bootstrap-corrected accuracy of 82%. The nomogram-derived best cut-off value was 40%. In DCA, the nomogram revealed clinical net benefit of > 10%. Conclusions This novel nomogram proved its good accuracy in predicting a positive scan, with values ≥ 40% providing the most informative cut-off in counselling patients to 68Ga-PSMA-11-PET/CT. This tool might be important as a guide to clinicians in the best use of PSMA-based PET imaging.

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Purpose: to quantify the mRNA levels of MMP-3, MMP-9, VEGF and Survivin in peripheral blood and the serum levels of CA-125, Ca19-9 in women with and without endometriosis and to investigate the performance of these markers to differentiate between deep and ovarian endometriosis. Methods: a case controls study enrolled a series of 60 patients. Twenty controls have been matched with 20 cases of ovarian and 20 cases of deep endometriosis. Univariable and multivariable performance of serum CA125 and CA19-9, mRNA for Survivin, MMP9, MMP3 and VEGF genes have been evaluated by means of ROC curves and logistic regression respectively. Results: No difference in markers concentration were detected between ovarian and deep endometriosis. In comparison with controls serum CA19 and CA125 yielded the better sensitivity followed by mRNA for Survivin gene (81.5%, 51.9% and 7.5% at 10% false positive rate respectively). Multivariable estimated odds of endometriosis yielded a sensitivity of 87% at the same false positive rate. Conclusions: A combination of serum and molecular markers could allow a better diagnosis of endometriosis.