A comparison of 3 on-line nomograms with the detection of primary circulating prostate cells to predict prostate cancer at initial biopsy

INTRODUCTION

The use of nomograms which include the PSA may improve the predictive power of obtaining a prostate biopsy (PB) positive for cancer. We compare the use of three on-line nomagrams with the detection of primary malignant circulating prostate cells (CPCs) to predict the results of an initial PB in men with suspicion of prostate cancer.

METHODS AND PATIENTS

Consecutive men with suspicion of prostate cancer underwent a 12 core TRUS prostate biopsy; age, total serum PSA, percent free PSA, family history, ethnic origin and prostate ultrasound results were used for risk assessment using the online nomograms. Mononuclear cells were obtained by differential gel centrifugation from 8ml of blood and CPCs were identified using double immunomarcation with anti-PSA and anti-P504S. A CPC was defined as a cell expressing PSA and P504S and defined as negative/positive. Biopsies were classified as cancer/no-cancer. Areas under the curve (AUC) for each parameter were calculated and compared and diagnostic yields were calculated.

RESULTS

1,223 men aged>55 years participated, 467 (38.2%) had a biopsy positive for cancer of whom 114/467 (24.4%) complied with the criteria for active observation. Area under the curve analysis showed CPC detection to be superior (p<0.001), avoiding 57% of potential biopsies while missing 4% of clinically significant prostate cancers.

CONCLUSIONS

The CPC detection was superior to the nomograms in predicting the presence of prostate cancer at initial biopsy; its high negative predictive value potentially reduces the number of biopsies while missing few significant cancers, being superior to the nomograms in this aspect. Being a positive/negative test the detection of CPCs avoids defining a cutoff value which may differ between populations.

Predicting results of daily-practice cystoscopies

OBJECTIVE

Our objective was to elaborate a predictive model of bladder cancer, in an unselected clinical population submitted to cystoscopy.

MATERIALS AND METHODS

We recruited consecutive patients that underwent cystoscopy due to suspicion of bladder cancer or surveillance of a previously diagnosed bladder cancer. Urine cytology and a BTA-stat® (BTA) test were carried out for all patients. To avoid an assessment bias, the BTA-tests, cytologies and cystoscopies were conducted in a blinded fashion. We used logistic regression to predict cystoscopy results from cytology, BTA-test and clinical variables.

RESULTS

From August 2011 to July 2012, we recruited 244 patients and 237 were valid for analysis. Newly diagnosed and surveillance cases were 13% and 87% respectively. Cytology and BTA-test sensitivities were 57.9% (CI 95: 42.2-72.1) and 63.2% (CI 95: 47.3-76.6) with specificities of 84.4% (CI 95: 78.7-88.8) and 82.9% (CI 95: 77.1-87.5). The predictive model included the BTA-test, cytology, time since previous tumour, and treatment with mitomicin or BGC during the last three months. The model predictive accuracy (AUC) was .85 (.78-.92), and dropped to 0.79 when excluding the BTA-test (P=.026). For the surveillance of bladder cancer, a 10% threshold on the model predicted probabilities resulted in an overall negative predictive value of 95.7%, and 95.0% in low grade tumours.

CONCLUSION

In a cost containment environment, our prediction model could be used to space out cystoscopies in patients with previous, low grade tumours, resulting in a more efficient use of resources in the healthcare system.