Prostate Cancer Prevention Trial Calculator Research Articles

Evaluation of Prostate Cancer Risk Calculators for Shared Decision Making Across Diverse Urology Practices in Michigan

To compare the predictive performance of a logistic regression model developed with contemporary data from a diverse group of urology practices to that of the Prostate Cancer Prevention Trial (PCPT) Risk Calculator version 2.0. With data from all first-time prostate biopsies performed between January 2012 and March 2015 across the Michigan Urological Surgery Improvement Collaborative (MUSIC), we developed a multinomial logistic regression model to predict the likelihood of finding high-grade cancer (Gleason score ≥7), low-grade cancer (Gleason score ≤6), or no cancer on prostate biopsy. The performance of the MUSIC model was evaluated in out-of-sample data using 10-fold cross-validation. Discrimination and calibration statistics were used to compare the performance of the MUSIC model to that of the PCPT risk calculator in the MUSIC cohort. Of the 11,809 biopsies included, 4289 (36.3%) revealed high-grade cancer; 2027 (17.2%) revealed low-grade cancer; and the remaining 5493 (46.5%) were negative. In the MUSIC model, prostate-specific antigen level, rectal examination findings, age, race, and family history of prostate cancer were significant predictors of finding high-grade cancer on biopsy. The 2 models, based on similar predictors, had comparable discrimination (multiclass area under the curve = 0.63 for the MUSIC model and 0.62 for the PCPT calculator). Calibration analyses demonstrated that the MUSIC model more accurately predicted observed outcomes, whereas the PCPT risk calculator substantively overestimated the likelihood of finding no cancer while underestimating the risk of high-grade cancer in this population. The PCPT risk calculator may not be a good predictor of individual biopsy outcomes for patients seen in contemporary urology practices.

Prostate-Specific Antigen Testing and Shared Decision Making for Prostate Cancer Screening

To compare the predictive performance of a logistic regression model developed with contemporary data from a diverse group of urology practices to that of the Prostate Cancer Prevention Trial (PCPT) Risk Calculator version 2.0.With data from all first-time prostate biopsies performed between January 2012 and March 2015 across the Michigan Urological Surgery Improvement Collaborative (MUSIC), we developed a multinomial logistic regression model to predict the likelihood of finding high-grade cancer (Gleason score ≥7), low-grade cancer (Gleason score ≤6), or no cancer on prostate biopsy. The performance of the MUSIC model was evaluated in out-of-sample data using 10-fold cross-validation. Discrimination and calibration statistics were used to compare the performance of the MUSIC model to that of the PCPT risk calculator in the MUSIC cohort.Of the 11,809 biopsies included, 4289 (36.3%) revealed high-grade cancer; 2027 (17.2%) revealed low-grade cancer; and the remaining 5493 (46.5%) were negative. In the MUSIC model, prostate-specific antigen level, rectal examination findings, age, race, and family history of prostate cancer were significant predictors of finding high-grade cancer on biopsy. The 2 models, based on similar predictors, had comparable discrimination (multiclass area under the curve = 0.63 for the MUSIC model and 0.62 for the PCPT calculator). Calibration analyses demonstrated that the MUSIC model more accurately predicted observed outcomes, whereas the PCPT risk calculator substantively overestimated the likelihood of finding no cancer while underestimating the risk of high-grade cancer in this population.The PCPT risk calculator may not be a good predictor of individual biopsy outcomes for patients seen in contemporary urology practices.

MP69-12 ADDED VALUE OF GENETIC RISK SCORE TO THE PROSTATE CANCER PREVENTION TRIAL (PCPT) RISK CALCULATOR: FINDINGS FROM THE PCPT STUDY

whereas for men with PSA 2 ng/mL, reduction in cancer-mortality was large with a number needed to screen (NNS) and diagnose (NND) to avoid one prostate cancer death by 15 years being 16 and 3, respectively. CONCLUSIONS: The ratio of benefits to harms of PSA screening varies dramatically with levels of PSA in blood at age 60. Previous estimates of the effect of PSA-screening have been an average of very different subgroups with low and high risk. Our data suggest that men with a PSA 2 at age 60 seems very beneficial, with the number needed to screen and treat being extremely favorable.

The Impact of Prostate Volume, Number of Biopsy Cores and American Urological Association Symptom Score on the Sensitivity of Cancer Detection Using the Prostate Cancer Prevention Trial Risk Calculator

We assessed the independent predictive value of prostate volume, number of biopsy cores and AUASS (American Urological Association symptom score) compared to risk factors included in the PCPTRC (Prostate Cancer Prevention Trial risk calculator for prostate cancer) and PCPTHG (Prostate Cancer Prevention Trial risk calculator for high grade cancer [Gleason grade 7 or greater]). Of 5,519 PCPT (Prostate Cancer Prevention Trial) participants used to construct the PCPTRC 4,958 with AUASS and prostate specific antigen 10 ng/ml or less were included on logistic regression analysis. Risk algorithms were evaluated in 571 EDRN (Early Detection Research Network) participants using the ROC AUC. A total of 1,094 participants (22.1%) had prostate cancer, of whom 232 (21.2%) had high grade disease. For prostate cancer prediction higher prostate specific antigen, abnormal digital rectal examination, family history of prostate cancer and number of cores were associated with increased risk, while volume was associated with decreased risk. Excluding prostate volume and number of cores, a history of negative biopsy and increased AUASS were also associated with lower risk. For high grade cancer higher prostate specific antigen, abnormal digital rectal examination, black race and number of cores were associated with increased risk and volume, while AUASS was associated with decreased risk. The AUC of the PCPTRC adjusted for volume and number of cores was 72.7% (using EDRN data), 68.2% when adjusted for AUASS alone and 67.6% PCPTRC. For high grade disease the AUCs were 74.8%, 74.0% and 73.5% (PCPTHG), respectively. Adjusted PCPT risk calculators for volume, number of cores and AUASS improve cancer detection.

Prostate Cancer Detection in the “Grey Area” of Prostate-Specific Antigen Below 10 ng/ml: Head-to-Head Comparison of the Updated PCPT Calculator and Chun’s Nomogram, Two Risk Estimators Incorporating Prostate Cancer Antigen 3

BackgroundProstate cancer antigen 3 (PCA3) holds promise in diagnosing prostate cancer (PCa), but no consensus has been reached on its clinical use. Multivariable predictive models have shown increased accuracy over individual risk factors. ObjectiveTo compare the performance of the two available risk estimators incorporating PCA3 in the detection of PCa in the “grey area” of prostate-specific antigen (PSA) <10 ng/ml: the updated Prostate Cancer Prevention Trial (PCPT) calculator and Chun’s nomogram. Design, setting, and participantsTwo hundred eighteen patients presenting with an abnormal PSA (excluding those with PSA >10 ng/ml) and/or abnormal digital rectal examination were prospectively enrolled in a multicentre Italian study between October 2008 and October 2009. All patients underwent ≥12-core prostate biopsy. MeasurementsPCA3 scores were assessed using the Progensa assay (Gen-Probe, San Diego, CA, USA). Comparisons between the two models were performed using tests of accuracy (area under the receiver operating characteristic curve [AUC-ROC]), calibration plots, and decision curve analysis. Biopsy predictors were identified by univariable and multivariable logistic regression. In addition, performance of PCA3 was analysed through AUC-ROC and predictive values. Results and limitationsPCa was detected in 73 patients (33.5%). Among predictors included in the models, only PCA3, PSA, and prostate volume retained significant predictive value. AUC-ROC was higher for the updated PCPT calculator compared to Chun’s nomogram (79.6% vs 71.5%; p=0.043); however, Chun’s nomogram displayed better overall calibration and a higher net benefit on decision curve analysis. Using a probability threshold of 25%, no high-grade cancers would be missed; the PCPT calculator would save 11% of biopsies, missing no cancer, whereas Chun’s nomogram would save 22% of avoidable biopsies, although missing 4.1% non–high-grade cancers. The small number of patients may account for the lack of statistical significance in the predictive value of individual variables or model comparison. ConclusionsBoth Chun’s nomogram and the PCPT calculator, by incorporating PCA3, can assist in the decision to biopsy by assignment of an individual risk of PCa, specifically in the PSA levels <10ng/ml.

Body Mass Index Adjusted Prostate-specific Antigen and Its Application for Prostate Cancer Screening

The prostate cancer prevention trial (PCPT) prostate cancer risk calculator was developed to aid physicians in counseling men for consideration of prostate biopsy based on prostate-specific antigen (PSA) and other clinical risk factors. This study investigated the role of body mass index (BMI) in this assessment. BMI category was defined as < 25 (under/normal weight), 25.0-29.9 (overweight), 30.0-34.9 (obese [OB] I), 35.0-39.9 (OB II), and ≥ 40 (OB III). BMI-adjusted PSA for a man was determined by multiplying his PSA to the ratio of the geometrical mean of PSA for BMI < 25 to the geometrical mean of PSA for his BMI category. Operating characteristics of PSA and BMI-adjusted PSA were compared with PCPT risks using area underneath the receiver operating characteristic curve (AUC). Statistical tests of differences between AUCs for different diagnostic tests were performed with the nonparametric U-statistic method. BMI-adjusted PSA equaled to unadjusted PSA multiplying 1.09, 1.20, 1.50, and 1.71 for men in overweight, OBI, OBII, and OBIII categories, respectively. The AUC for BMI-adjusted PSA values (0.84) did not differ from PSA; that of the PCPT calculator with BMI-adjusted PSA (0.87) did not differ from the calculator with PSA. Of 2816 men with a PSA less than or equal to 2.5 ng/mL who did not undergo biopsy, 126 (4.5%) would have a BMI-adjusted PSA exceeding 2.5 ng/mL. Because of lower levels of PSA, overweight and obese men may have diminished cancer detection opportunities when undergoing PSA-based screening.

Prostate Cancer Prevention Trial and European Randomized Study of Screening for Prostate Cancer Risk Calculators: A Performance Comparison in a Contemporary Screened Cohort

BackgroundSeveral models can predict the risk of prostate cancer (PCa) on biopsy. ObjectiveTo evaluate the performance of the Prostate Cancer Prevention Trial (PCPT) and European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculators in detecting PCa in a contemporary screened cohort. Design, setting, and participantsWe analyzed prebiopsy characteristics of 525 consecutive screened patients submitted to biopsy, as required by the risk calculators, in one European center between 2006 and 2007. MeasurementsComparisons were done using tests of accuracy (area under the receiver operating characteristic curve [AUC-ROC]), calibration plots, and decision curve analysis. Biopsy predictors were identified by univariate and multivariate logistic regression. Results and limitationsPCa was detected in 35.2% of the subjects. Among predictors included in the calculators, the logarithmic transformations of prostate volume and prostate-specific antigen (PSA), digital rectal examination, previous biopsy status, and age were significantly associated with PCa; transrectal ultrasound abnormalities and family history were not. AUC-ROC for the ERSPC calculator was significantly higher than the PCPT calculator and PSA alone (80.1%, 74.4%, and 64.3%, respectively). Calibration plots showed better performance for the ERSPC calculator; nevertheless, ERSPC may underestimate risk, while PCPT tends to overestimate predictions. Decision curve analysis displayed higher net benefit for the ERSPC calculator; 9% and 23% unnecessary biopsies can be avoided if a threshold probability of 20% and 30%, respectively, is adopted. In contrast, the PCPT model displayed very limited benefit. Our findings apply to a screened European cohort submitted to extended biopsy schemes; consequently, caution should be exerted when considering different populations. ConclusionsThe ERSPC risk calculator, by incorporating several risks factors, can aid in the estimation of individual PCa risk and in the decision to perform biopsy. The ERSPC calculator outperformed the PCPT model, which is of very limited value, in a contemporary cohort of screened patients.

Evaluation of the Prostate Cancer Prevention Trial Risk calculator in a high‐risk screening population

Diagnostic (exploratory cohort). 2b. To evaluate the Prostate Cancer Prevention Trial (PCPT) risk calculator in a screening cohort of young, racially diverse, high-risk men with a low baseline prostate-specific antigen (PSA) level and enrolled in the Prostate Cancer Risk Assessment Program (PRAP). The PCPT calculator provides an assessment of prostate cancer risk based on age, PSA level, race, previous biopsy, and family history. Eligibility for PRAP includes men aged 35-69 years who are African-American, have a family history of prostate cancer, or have a known BRCA1/2 mutation. PCPT risk scores were determined for PRAP participants, and were compared to observed prostate cancer rates. In all, 624 participants were evaluated, including 382 (61.2%) African-American men and 242 (38.7%) men with a family history of prostate cancer; the median (range) age was 49.0 (34.0-69.0) years and the median PSA level 0.9 (0.1-27.2) ng/mL. The PCPT risk score correlated with prostate cancer diagnosis, as the median baseline risk score in patients diagnosed with prostate cancer was 31.3%, vs 14.2% in patients not diagnosed with prostate cancer (P < 0.001). The PCPT calculator similarly stratified the risk of diagnosis of Gleason score > or =7 disease, as the median risk score was 36.2% in patients diagnosed with Gleason > or =7 prostate cancer vs 15.2% in all other participants (P < 0.001). The PCPT risk calculator score was found to stratify prostate cancer risk in a cohort of young, primarily African-American men with a low baseline PSA level. These results support further evaluation of this predictive tool for assessing the risk of prostate cancer in high-risk men.

Validation in a Multiple Urology Practice Cohort of the Prostate Cancer Prevention Trial Calculator for Predicting Prostate Cancer Detection

The Prostate Cancer Prevention Trial prostate cancer risk calculator was developed in a clinical trial cohort that does not represent men routinely referred for prostate biopsy. We assessed the generalizability of the Prostate Cancer Prevention Trial calculator in a cohort more representative of patients referred for consideration of prostate biopsy in American urology practice. Patients undergoing prostate biopsy by 12 urologists at 5 sites were enrolled in an Early Detection Research Network cohort. The Prostate Cancer Prevention Trial risk calculator was validated by examining area underneath the receiver operating characteristic curve, sensitivity, specificity and calibration comparing observed vs predicted risk of prostate cancer detection. Cancer incidence was greater (43% vs 22%, p = 0.001) in the Early Detection Research Network validation cohort (645) compared to the Prostate Cancer Prevention Trial group (5,519). Early Detection Research Network participants were younger and more racially diverse, and had more abnormal digital rectal examinations and higher prostate specific antigen than Prostate Cancer Prevention Trial participants (all p <0.001). Cancer severity was worse in the Early Detection Research Network cohort than in the Prostate Cancer Prevention Trial (Gleason 7 or higher 60% vs 21%, p <0.001). Nevertheless, the Prostate Cancer Prevention Trial risk calculator was superior to prostate specific antigen alone for predicting cancer in the Early Detection Research Network (AUC 0.691 vs 0.655, p = 0.009) and calibration confirmed that the Prostate Cancer Prevention Trial risk score accurately predicted individual risks in the Early Detection Research Network cohort. Differences between the Early Detection Research Network validation cohort and the Prostate Cancer Prevention Trial cohort underscore the importance of validating calculator performance in the multicenter urology practice setting. Our findings extend the applicability of the Prostate Cancer Prevention Trial calculator for measuring the risk of prostate cancer detection on biopsy to the routine American urology practice setting.

External validation of the Prostate Cancer Prevention Trial risk calculator in a screened population

Objectives To evaluate the recently developed Prostate Cancer Prevention Trial (PCPT) prostate cancer risk calculator in the San Antonio Center of Biomarkers of Risk for Prostate Cancer (SABOR) cohort of the Early Detection Research Network, a younger and more ethnically diverse population than that in the PCPT. Methods From 3488 SABOR participants, we identified 446 who had undergone prostate biopsy and had undergone prostate-specific antigen measurement and digital rectal examination before biopsy. Most biopsies were performed for abnormal digital rectal examination findings, a prostate-specific antigen level of more than 2.5 ng/mL, or elevated risk because of a first-degree relative with prostate cancer. We evaluated the operating characteristics of the PCPT calculator for detecting prostate cancer in this cohort of SABOR participants. Of the 446 men in this cohort, 24% were younger than 55 years of age. Results Of the 446 men who had undergone biopsy, 148 (33.2%) had prostate cancer. The observed SABOR prostate cancer rates increased with increasing PCPT risk: 15.7%, 39.0%, 48.8%, and 100.0% for a PCPT risk calculator value of less than 25%, 25% to 50%, 50% to 75%, and greater than 75%, respectively. The PCPT risk calculator had an area under the receiver operating characteristic curve of 65.5% (95% confidence interval 60.2% to 70.8%, P <0.0001), was greater in African-American men (area under curve of 80.0%, 95% confidence interval 67.8% to 92.2%) than in other races ( P = 0.02), and was not different in Hispanic men ( P >0.05). Conclusions The results of our study have shown that the PCPT risk calculator, available from the Internet and incorporating the current best panel of risk factors, is valid in other, more diverse, populations.