Abstract
Objective
To develop a nomogram for selecting the “unreal” Gleason score (GS) 3 + 3 patients in biopsy GS 3 + 3 prostate cancer (PCa) patients.
Methods
Patients who were newly diagnosed with PCa by biopsy and underwent radical prostatectomy in the First Affiliated Hospital of Nanjing Medical University from January 2009 to October 2018 were enrolled. Comparisons were made between GS 3 + 3 and higher grade PCa patients. Logistic regression analysis was performed to determine the risk factors for the “unreal” GS 3 + 3 PCa in biopsy GS 3 + 3 patients. Then, a nomogram was developed to predict the probability of “unreal” GS 3 + 3 PCa according to the results of multivariate analysis. Finally, receiver operating characteristic and decision curve analysis (DCA) curves were structured to identify the efficiency of the predictive model.
Results
Compared to higher GS grade, biopsy GS 3 + 3 had greater upgrade risk (P < 0.05) while a lower proportion of positive surgical margins, seminal vesicle invasion, extra-prostatic extension, lymph node invasion, and nerve invasion (all P < 0.05). Multivariate analysis showed that age, PSAD, prostate imaging reporting and data system (PI-RADS) score and biopsy positive cores were significant risk factors for “unreal” GS 3 + 3. A nomogram was developed utilizing these factors with high prediction performance (area under curve = 0.924). Furthermore, DCA curve suggested that this predictive model was effective.
Conclusions
The nomogram identified the probability of “unreal” GS 3 + 3 PCa in biopsy GS 3 + 3 PCa patients, which was of great value for clinical guidance in low risk PCa therapy.
Acknowledgments
The authors acknowledge the Development of Pathology for the support in systematic grading.
Declaration of interest
The authors declare that they have no conflict of interest.
Supplementary material
Supplemental data for this article can be accessed on the publisher’s website.
Ethical statement
The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Informed consent was obtained from all patients to use data from clinical evaluations performed and from their medical records for this natural history study.
Additional information
Notes on contributors
Feng Qi
Lixin Hua designed the study; Yifei Cheng analyzed the data; Gong Cheng and Feng Qi drafted the article; Kai Zhu was responsible for language correction. All authors finally approved the paper. Feng Qi, Kai Zhu and Yifei Ceng, contributed equally to the work and should be regarded as co-first authors.
Kai Zhu
Lixin Hua designed the study; Yifei Cheng analyzed the data; Gong Cheng and Feng Qi drafted the article; Kai Zhu was responsible for language correction. All authors finally approved the paper. Feng Qi, Kai Zhu and Yifei Ceng, contributed equally to the work and should be regarded as co-first authors.
Yifei Cheng
Lixin Hua designed the study; Yifei Cheng analyzed the data; Gong Cheng and Feng Qi drafted the article; Kai Zhu was responsible for language correction. All authors finally approved the paper. Feng Qi, Kai Zhu and Yifei Ceng, contributed equally to the work and should be regarded as co-first authors.
Lixin Hua
Lixin Hua designed the study; Yifei Cheng analyzed the data; Gong Cheng and Feng Qi drafted the article; Kai Zhu was responsible for language correction. All authors finally approved the paper. Feng Qi, Kai Zhu and Yifei Ceng, contributed equally to the work and should be regarded as co-first authors.
Gong Cheng
Lixin Hua designed the study; Yifei Cheng analyzed the data; Gong Cheng and Feng Qi drafted the article; Kai Zhu was responsible for language correction. All authors finally approved the paper. Feng Qi, Kai Zhu and Yifei Ceng, contributed equally to the work and should be regarded as co-first authors.