Original Article
Integrated formulas to forecast prostate cancer: the parameters of influencing the prostate specific antigen level as an adjunct to prostate specific antigen and multi-parametric MRI to predict prostate cancer before biopsy
Abstract
Background: To determine the diagnostic value of a series of integrated formulas that combined with some easily accessible and economical indexes (age, weight and so on) for the detection of prostate cancer (Pca) compared with prostate specific antigen (PSA) and multi-parametric MRI (MP-MRI).
Methods: Eight hundred thirty patients who underwent trans-rectal ultrasound (TRUS) guided prostate biopsy between January 2010 and December 2016 in our institution were collected and retrospectively analyzed. Patient demographics and MP-MRI findings were collected and assessed by the statistical package for an association with Pca detection on biopsy.
Results: Compared with patients with no cancer, men with Pca being older, a higher PSA level, lighter, smaller volume of prostate and more nodules with abnormal signal on MP-MRI. According to those indexes, we derived a series of formulas (A and B) for detection of Pca with optimized thresholds. For formula A: PSA +0.9× Age +0.2× Weight −0.5× Volume >72. For formula B: 32× PSAD + Age +0.5× Weight +33× MRI −0.3× Volume >166. Composite formulas have great capacity for the detection of Pca with area under the curve (AUC) of 0.88 and 0.93, respectively (compared with 0.78 and 0.75 for PSA level and PSAD, respectively). In addition, composite formulas also achieved significantly better ability to detect higher biopsy Gleason score (≥7) than PSA and PSAD alone (AUC: 0.87 and 0.83 vs. 0.71 and 0.73, respectively), P<0.001.
Conclusions: The integrated formulas were superior to PSA alone for the detection of Pca. Moreover, it brought about improved performance for detecting clinically significant Pca without extras costs.
Methods: Eight hundred thirty patients who underwent trans-rectal ultrasound (TRUS) guided prostate biopsy between January 2010 and December 2016 in our institution were collected and retrospectively analyzed. Patient demographics and MP-MRI findings were collected and assessed by the statistical package for an association with Pca detection on biopsy.
Results: Compared with patients with no cancer, men with Pca being older, a higher PSA level, lighter, smaller volume of prostate and more nodules with abnormal signal on MP-MRI. According to those indexes, we derived a series of formulas (A and B) for detection of Pca with optimized thresholds. For formula A: PSA +0.9× Age +0.2× Weight −0.5× Volume >72. For formula B: 32× PSAD + Age +0.5× Weight +33× MRI −0.3× Volume >166. Composite formulas have great capacity for the detection of Pca with area under the curve (AUC) of 0.88 and 0.93, respectively (compared with 0.78 and 0.75 for PSA level and PSAD, respectively). In addition, composite formulas also achieved significantly better ability to detect higher biopsy Gleason score (≥7) than PSA and PSAD alone (AUC: 0.87 and 0.83 vs. 0.71 and 0.73, respectively), P<0.001.
Conclusions: The integrated formulas were superior to PSA alone for the detection of Pca. Moreover, it brought about improved performance for detecting clinically significant Pca without extras costs.
