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A predictive model for prostate cancer incorporating PSA molecular forms and age
Julia Oto1, Álvaro Fernández-Pardo1, Montserrat Royo1
1Haemostasis, Thrombosis, Atherosclerosis and Vascular Biology Research Group, Medical Research Institute Hospital La Fe (IIS La Fe), Valencia, 46026, Spain.
Scientific Reports
|February 14, 2020
Summary
New prostate cancer (PCa) biomarkers, including free-to-total PSA (prostate-specific antigen) ratio and complexed PSA, show improved diagnostic accuracy over total PSA alone. A predictive model incorporating these markers and age enhances PCa detection efficacy.
Area of Science:
- Biochemistry
- Oncology
- Immunology
Background:
- The diagnostic specificity of prostate-specific antigen (PSA) for prostate cancer (PCa) is limited, necessitating improved diagnostic markers.
- Different molecular forms of PSA, including total (tPSA), free (fPSA), and complexed PSA, may offer enhanced diagnostic utility.
Purpose of the Study:
- To characterize anti-PSA monoclonal antibodies (mAbs).
- To assess the diagnostic utility of various PSA molecular forms and their ratios for distinguishing PCa from benign prostate hyperplasia (BPH).
- To develop and validate a predictive model for PCa detection.
Main Methods:
- Monoclonal antibodies against PSA were generated and characterized using competition studies, ELISAs, and immunoblotting.
- Sensitive ELISAs were developed for tPSA, fPSA, and complexed PSA.
- PSA forms and ratios were measured in 301 PCa patients and 764 BPH patients, with diagnostic accuracy analyzed using ROC curves.
- A multivariable logistic regression model incorporating age, tPSA, fPSA, and complexed PSA was constructed.
Main Results:
- The free-to-total PSA (FPR) and complexed-to-total PSA (CPR) ratios significantly improved the diagnostic yield compared to tPSA alone.
- A multivariable predictive model including age, fPSA, and complexed PSA achieved an optimism-corrected AUC of 0.86, outperforming tPSA (AUC 0.71).
- The developed model demonstrated superior predictive ability for PCa detection.
Conclusions:
- FPR and CPR exhibit better diagnostic yield than tPSA for differentiating PCa.
- A PCa predictive model incorporating age, fPSA, and complexed PSA significantly outperforms tPSA detection efficacy.
- This enhanced predictive model holds potential to reduce unnecessary biopsies, mitigate harmful side effects, and lower healthcare costs.
