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Risk Estimation of Metastatic Recurrence After Prostatectomy: A Model Using Preoperative Magnetic Resonance Imaging and Targeted Biopsy

BACKGROUND: The risk of prostate cancer metastatic is correlated with its volume and grade. These parameters are now best estimated preoperatively with magnetic resonance imaging (MRI) and MRI-guided biopsy. OBJECTIVE: To estimate the risk of metastatic recurrence after radical prostatectomy (RP) in...

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Detalles Bibliográficos
Autores principales: Bommelaere, Thomas, Villers, Arnauld, Puech, Philippe, Ploussard, Guillaume, Labreuche, Julien, Drumez, Elodie, Leroy, Xavier, Olivier, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9257652/
https://www.ncbi.nlm.nih.gov/pubmed/35813259
http://dx.doi.org/10.1016/j.euros.2022.04.011
Descripción
Sumario:BACKGROUND: The risk of prostate cancer metastatic is correlated with its volume and grade. These parameters are now best estimated preoperatively with magnetic resonance imaging (MRI) and MRI-guided biopsy. OBJECTIVE: To estimate the risk of metastatic recurrence after radical prostatectomy (RP) in our model versus conventional clinical European Association of Urology (EAU) classification. The secondary objective is biochemical recurrence (BCR). DESIGN, SETTING, AND PARTICIPANTS: A retrospective study was conducted of a cohort of 713 patients having undergone MRI-guided biopsies and RP between 2009 and 2018. The preoperative variables included prostate-specific antigen, cT stage, tumor volume (TV) based on the lesion’s largest diameter at MRI, percentage of Gleason pattern 4/5 (%GP4/5) at MRI-guided biopsy, and volume of GP4/5 (VolGP4/5) calculated as TV × %GP4/5. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The variables’ ability to predict recurrence was determined in univariable and multivariable Fine-and-Gray models, according to the Akaike information criterion (AIC) and Harrell’s C-index. RESULTS AND LIMITATIONS: Overall, 176 (25%), 430 (60%), and 107 (15%) patients had low, intermediate, and high-risk disease, respectively, according to the EAU classification. During a median follow-up period of 57 mo, metastatic recurrence was observed in 48 patients with a 5-yr probability of 5.6% (95% confidence interval [CI] 3.9–7.7). VolGP4/5 (categories: <0.5, 0.5–1.0, 1.01–3.2, and >3.2 ml) was the parameter with the lowest AIC and the highest C-index for metastatic recurrence of 0.82 (95% CI 0.76–0.88), and for BCR it was 0.73 (95% CI 0.68–0.78). In a multivariable model that included %GP4/5 and TV, C-index values were 0.86 (95% CI 0.79–0.91) for metastatic recurrence and 0.77 (0.72–0.82) for BCR. The same results for EAU classification were 0.74 (0.67–0.80) and 0.67 (0.63–0.72), respectively. Limitations are related to short follow-up and expertise of radiologists and urologists. CONCLUSIONS: We developed a preoperative risk tool integrating the VolGP4/5 based on MRI and MRI-guided biopsies to predict metastatic recurrence after RP. Our model showed higher accuracy than conventional clinical risk models. These findings might enable physicians to provide more personalized patient care. PATIENT SUMMARY: Aggressiveness of prostate cancer evaluated before treatment by incorporating magnetic resonance imaging (MRI) and MRI-guided biopsy results gives a better estimate of the risk of metastatic recurrence than previous parameters not based on MRI.