Prediction Nomogram for 68Ga-PSMA-11 PET/CT in different clinical settings of PSA failure after radical treatment for Prostate Cancer

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.

Development and validation of an echocardiography score for diagnosis of cardiac masses

Background Echocardiography is the cornerstone in the evaluation of cardiac masses and provides accurate characterization. Despite, its accuracy in diagnosis of cardiac masses (CM) remains challenging and, up to date, no validated diagnostic algorithm is validated. Purpose The aim of our study was to evaluate the diagnostic accuracy of echocardiography, to identify the echocardiographic predictors of malignancy and to develop and then validate a multiparametric echocardiographic score that could be used to estimate the likelihood of the histological nature of a CM. Materials and methods The final sample consisted of 273 consecutive patients who had a 2D-echocardiographic evaluation and a histologic diagnosis. Logistic regression was performed to evaluate the ability of echocardiographic findings to discriminate benign versus malignant masses, then a scoring system was developed and validated in a separate test cohort. Results Of the 322 patients initially included in the Bologna Cardiac Masses Registry, 13 with a poor acoustic window, 27 with no histological examination patients and 9 extra-cardiac masses were excluded. In the remaining 273 patients, classical 2-D echocardiogram identified 249 masses with a diagnostic accuracy of 88%. A weighted score [Diagnostic Echocardiographic Mass (DEM) Score] ranging from 0 to 9 was obtained from 6 variables: infiltration, polylobate mass, moderate-severe pericardial effusion. The AUC for the score was 0.965 (95% CI [0.938-0.993]). In a logistic regression analysis using the DEM score as a predictor, the likelihood of malignant CM increased more than 4 times for a 1-unit increase in the score (OR=4.468; 95% CI 2.733-7.304). A score < 3 denoted a high probability of a benign diagnosis, and a score ≥ 5 points corresponded to a higher risk of malignancy. Conclusion 2D-Echocardiography provides a high diagnostic accuracy in identifying cardiac masses and our multiparametric echocardiographic score could be useful to predict the histological nature of cardiac masses.