A nomogram for prediction of prostate cancer on multi-core biopsy using age, serum prostate-specific antigen, prostate volume and digital rectal examination in Singapore

Prognostic significance of surgery and radiotherapy in elderly patients with localized prostate cancer: establishing and time-based external validation a nomogram from SEER-based study

OBJECTIVE

Prostate cancer (PC) is a significant disease affecting men's health worldwide. More than 60% of patients over 65 years old and more than 80% are diagnosed with localized PC. The current choice of treatment modalities for localized PC and whether overtreatment is controversial. Therefore, we wanted to construct a nomogram to predict the risk factors associated with cancer-specific survival (CSS) and overall survival (OS) in elderly patients with localized PC while assessing the survival differences in surgery and radiotherapy for elderly patients with localized PC.

METHODS

Data of patients with localized PC over 65 years were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for CSS and OS. Nomograms predicting CSS and OS were built using multivariate Cox regression models. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to test the potential clinical value of this model.

RESULTS

A total of 90,434 patients over 65 years and diagnosed with localized PC from 2010 to 2018 were included in the study. All patients were randomly assigned to the training set (n = 63,328) and the validation set (n = 27,106). Univariate and multivariate Cox regression model analysis showed that age, race, marriage, T stage, surgical, radiotherapy, prostate-specific antigen (PSA), and Gleason score (GS) were independent risk factors for predicting CSS in elderly patients with localized PC. Age, race, marriage, surgery, radiotherapy, PSA, and GS were independent risk factors for predicting OS in elderly patients with localized PC. The c-index of the training and validation sets for the predicted CSS is 0.802(95%CI:0.788-0.816) and 0.798(95%CI:0.776-0.820, respectively). The c-index of the training and validation sets for predicting OS is 0.712(95%:0.704-0.720) and 0.724(95%:0.714-0.734). It shows that the nomograms have excellent discriminatory ability. The AUC and the calibration curves also show good accuracy and discriminability.

CONCLUSION

We have developed new nomograms to predict CSS and OS in elderly patients with localized PC. After internal validation and external temporal validation with reasonable accuracy, reliability and potential clinical value, the model can be used for clinically assisted decision-making.

The influence of prostate volume on clinical parameters in prostate cancer screening

PURPOSE

The purpose of the study was to evaluate the diagnostic significance of two new and a few clinical markers for prostate cancer (PCa) at various prostate volumes (PV).

METHODS

The study subjects were divided into two groups. Among them, there were 70 cases in the PV ≤30 ml group (benign prostatic hyperplasia [BPH]: 32 cases, PCa: 38 cases) and 372 cases in the PV > 30 ml group (BPH: 277 cases, PCa: 95 cases). SPSS 26.0 and GraphPad Prism 8.0 were used to construct their receiver operating characteristic (ROC) curves for diagnosing PCa and calculating their area under the ROC curve (AUC).

RESULTS

In the PV ≤30 ml group, the diagnostic parameters based on prostate-specific antigen (PSA) had a decreased diagnostic significance for PCa. In the PV > 30 ml group, PSAD (AUC = 0.709), AVR (AVR = Age/PV, AUC = 0.742), and A-PSAD (A-PSAD = Age×PSA/PV, AUC = 0.736) exhibited moderate diagnostic significance for PCa, which was better than PSA-AV (AUC = 0.672), free PSA (FPSA, AUC = 0.509), total PSA (TPSA, AUC = 0.563), (F/T) PSA (AUC = 0.540), and (F/T)/PSAD (AUC = 0.663). Compared with AVR, A-PSAD exhibited similar diagnostic significance for PCa, but higher than PSA density (PSAD).

CONCLUSIONS

Choosing appropriate indicators for different PVs could contribute to the early screening and diagnosis of PCa. The difference in the diagnostic value of two new indicators (A-PSAD and AVR), and PSAD for PCa may require further validation by increasing the sample size.

Significant Diagnostic Value of Free-Serum PSA (FPSA)/Prostate-Specific Antigen Density (PSAD) and (F/T)/PSAD for Prostate Cancer of the Chinese Population in a Single Institution

BACKGROUND The aim of this study was to investigate the diagnostic value of (F/T)/PSAD for prostate cancer detection in the Chinese population. MATERIAL AND METHODS Data were collected retrospectively from patients with prostate cancer or benign prostatic hyperplasia from July 2009 to September 2014. SPSS 19.0 software was used for the receiver operating characteristic curve (ROC), and calculating sensitivity, specificity, and positive predictive values (PPV) and negative predictive values (NPV), respectively. Comparison of the area under ROC (AUC) was performed using the MedCalc v. 10.4.7.0 software. RESULTS A total of 660 patients (including 251 patients with prostate cancer and 409 patients with prostatic hyperplasia) were included. Prostate volume (PV), prostate-specific antigen density (PSAD), free-serum PSA (FPSA)/PSAD, and free-to-total PSA (F/T)/PSAD had similar AUC (P>0.05), and had significantly higher AUC (P<0.001) than F/T, total-serum PSA (TPSA), and free-serum PSA (FPSA). Based on the optimal cutoff value, the sensitivity of (F/T)/PSAD and FPSA/PSAD was similar (P>0.05), and significantly higher than the PV and PSAD (P<0.05). The logistic regression model using a combination of age, FPSA, PV, PSAD, FPSA/PSAD, and (F/T)/PSAD showed higher AUC than each one alone (P<0.001). CONCLUSIONS (F/T)/PSAD can be used as a predictor for prostate cancer in the Chinese population aged >50 years and has a significantly lower false negative rate than PSAD and PV with a cutoff value of ≤0.731. A new parameter, FPSA/PSAD, has similar diagnostic accuracy comparable to (F/T)/PSAD. The diagnostic value of a combination of age, FPSA, PV, PSAD, FPSA/PSAD, and (F/T)/PSAD needs further investigation.