Nomograms for predicting local recurrence in prostate cancer patients with a positive resection margin

Background. Prostate cancer patients with a positive resection margin after radical prostatectomy are at risk of developing local recurrence. This risk should be carefully estimated in order to choose an optimal management strategy.

Aim. To develop a nomogram to predict the risk of local recurrence in patients with a positive resection margin using the data on patients who have undergone surgery.

Materials and methods. Routine pathomorphological examination of surgical specimens from 2255 patients with clinically significant local and locally advanced prostate cancer revealed 364 cases of positive resection margin. Statistical analysis allowed us to identify the most significant prognostic factors. Using selected preoperative factors and a mathematical model, we created a nomogram to predict local recurrence in patients with a positive resection margin.

Results. Our nomogram had an accuracy of 93% (area under the ROC curve (AUC) 0.9392; p <0.005), sensitivity of 0.99438, and specificity of 0.94545. The most significant prognostic factors included proportion of positive biopsy specimens, Gleason score (International Society of Urological Pathology (ISUP) grade estimated at routine pathomorphological examination), and presence and length of positive resection margin.

Conclusion. Our mathematical model and the nomogram based on it are highly accurate for predicting local recurrence and can therefore be used for choosing an optimal management strategy.

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