Despite the fact that radical prostatectomy is linked to favorable long-term oncological outcomes, about 30% of patients experience biochemical recurrence, necessitating salvage therapies. Therefore, it was crucial from a clinical standpoint to identify new molecular biomarkers that can predict cancer behavior. For patients who underwent radical prostatectomy, researchers created a novel prognostic model based on microRNA (miRNA).
After 295 patients underwent radical prostatectomy between 2009 and 2017, they retrospectively looked into their medical records. These examples were included in either the training or validation sets at random. Then, using Fisher linear discriminant analysis on the training set, they created the prognostic model, and on the validation set, they assessed its performance.
Biochemical recurrence occurred in 72 individuals overall. Three miRNAs (miR-3147, miR-4513, and miR-4728-5p) were combined with two pathological variables to create a prediction model (pathological T stage and Gleason score). The model’s prediction abilities were verified to be precise in the validation set (area under the receiver operating characteristic curve: 0.80; sensitivity: 0.78; specificity: 0.76). Furthermore, Kaplan-Meier analysis demonstrated that patients with a low prediction index had a considerably longer recurrence-free survival than those with a high index (P<0.001).
The ability to predict recurrence following prostatectomy was possible with the help of circulating miRNA profiles. Therefore, physicians may find the model helpful in selecting patient follow-up plans.