Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cancer. Author manuscript; available in PMC 2013 May 15.
Published in final edited form as:
Published online 2011 October 17. doi:  10.1002/cncr.26396
PMCID: PMC3505607

Selective Detection of Histologically-Aggressive Prostate Cancer: an Early Detection Research Network (EDRN) Prediction Model to Reduce Unnecessary Prostate Biopsies with Validation in the Prostate Cancer Prevention Trial (PCPT)

Stephen B. Williams, M.D.,1,2,3 Simpa Salami, M.D., MPH,1 Meredith M. Regan, Sc.D.,3,4 Donna P. Ankerst, Ph.D.,5 John T. Wei, M.D.,6 Mark A. Rubin, M.D.,7 Ian M. Thompson, M.D.,5 and Martin G. Sanda, M.D.1,3



Limited survival benefit and excess treatment due to PSA screening in randomized trials suggests a need for more restricted selection of prostate biopsy candidates by discerning risk of histologically-aggressive versus indolent cancer before biopsy.


Subjects undergoing first prostate biopsy enrolled in a multi-center, prospective cohort of the NCI Early Detection Research Network (EDRN; N=635) were analyzed to develop a model for predicting histologically- aggressive prostate cancers. The control arm of the Prostate Cancer Prevention Trial (PCPT; N=3833) was used to validate the generalization of the predictive model.


The EDRN cohort was comprised of men among whom 57% had no cancer, 14% had indolent cancer and 29% had aggressive cancer. Age, body mass index, family history of prostate cancer, abnormal digital rectal exam (DRE) and prostate specific antigen density (PSAD) were associated with aggressive cancer (all P<0.001). The EDRN model outperformed PSA alone in predicting aggressive cancer (AUC=0.81 vs. 0.71, P<0.01). Model validation in the PCPT cohort accurately identified men at low (<10%) risk of aggressive cancer for whom biopsy could be averted (AUC=0.78; 95% CI .75–.80). Under criteria from the EDRN model, prostate biopsy can be restricted to men with PSAD > 0.1ng/ml/cc or abnormal DRE. When PSAD < 0.1ng/ml/cc, family history or obesity can identify biopsy candidates.


A predictive model incorporating age, family history, obesity, PSAD and DRE elucidates criteria whereby one-quarter of prostate biopsies can be averted while retaining high sensitivity in detecting aggressive prostate cancer.

Keywords: prostate cancer, biopsy, clinically-significant, indolent


Prostate specific antigen (PSA) screening has led to a significant increase in detection of clinically localized T1c prostate cancer with concomitant stage migration (1,2), and results from randomized trials of PSA screening have revealed limited to no survival benefit when simple PSA cut-offs were used for recommendation for or against prostate biopsy (3,4). These findings have raised questions as to whether strategies based simply on PSA and age cut-offs are sufficient for identifying suitable candidates for prostate biopsy when the ultimate goal of early detection is to identify aggressive disease that harbors lethal potential and yet is amenable to definitive treatment.

The ability to discern aggressive from indolent prostate cancer is a centerpiece of current efforts underway to refine prostate cancer detection, decision-making, and care. Epstein et al identified histological criteria in prostate biopsy specimens that discriminate indolent from clinically significant prostate cancer (5). As originally described, the histological criteria that define indolent disease on prostate biopsy include absence of Gleason pattern 4 or 5, cancer limited to 3 or fewer biopsy cores, and less than 50% tumor involvement in any individual core. Prospective studies have used these criteria to define eligibility for active surveillance (6,7,8).

Prior studies have used findings from biopsy to assess risk of indolent cancer at prostatectomy (9,10,11), but predictive tools to discern risk of aggressive versus indolent cancer before a patient undergoes prostate biopsy have not been extensively characterized. The Prostate Cancer Prevention Trial (PCPT) calculator facilitates individual assessment of prostate cancer risk in general and specific risk of high-grade disease for men who undergo a prostate biopsy (12), but does not discern the possibility of aggressive Gleason score 6 cancers, a limitation also inherent in a separate predictive nomogram developed based on a single-institution study (13).

We sought to develop a predictive model to identify candidates for prostate biopsy based on multi-center data using pre-biopsy parameters to selectively discriminate risk of histologically-aggressive prostate cancer from no cancer or histo-pathologically indolent cancer.

Materials and Methods

The multi-center National Cancer Institute (NCI)/Early Detection Research Network (EDRN) prostate cancer detection cohort is a collaboration of several EDRN clinical validation centers that prospectively enroll and follow men without prior diagnosis of prostate cancer. Men enrolled at 6 clinical practice sites at Harvard, Michigan, and Cornell universities who had undergone their first prostate biopsy were identified. As part of participation in the EDRN cohort, all men had provided written informed consent and all prostate biopsies had been offered according to National Comprehensive Cancer Network (NCCN) guidelines (14). Demographic and pre-biopsy clinical data, including PSA history, digital rectal exam (DRE) results, prostate volume and all biopsy procedure details were ascertained on case report forms. All prostate biopsy results were reviewed with reports confirmed by institutional pathologists. All pathology reports included confirmed histology, number of cores and percent of each core involved with carcinoma, and primary and secondary Gleason patterns. At the time of this analysis, the EDRN cohort database comprised 902 subjects who enrolled between June 2005 and December 2007, 635 of whom had enrolled immediately prior to their first prostate biopsy and had complete, quality-controlled demographic, clinical and pathological data available. They are the subject of this analysis. Furthermore, 236 EDRN patients, enrolled January 2008 through April 2009, were also used to discern how many biopsies could be avoided if using the proposed model.

Histologically-aggressive prostate cancer was defined by Epstein’s histopathologic criteria: Gleason 7 or higher, or more than three cores positive, or ≥50% tumor involvement in any individual core; all other cancers (Gleason 6 or lower, and three cores or fewer positive, and <50% tumor involvement in any core) were deemed indolent (5).

In the EDRN analysis cohort, demographic and pre-biopsy clinical data were compared between men with histologically-aggressive prostate cancer and men with indolent or no prostate cancer using Wilcoxon rank sum tests for continuous variables and Fisher’s exact tests for categorical variables. Multivariable logistic regression models were fit that considered age, body mass index (BMI), race/ethnicity, family history of prostate cancer, abnormal/suspicious DRE result, PSA, prostate volume and PSA density (PSAD=PSA/(prostate volume)), the latter three risk factors with log-transformation to improve fit of the model. Model selection was performed to identify and include only statistically significant risk factors at the .05 level of statistical significance, in particular to identify the strongest predictor among the highly correlated measures of PSA, prostate volume and PSAD. Individual risks of histologically-aggressive prostate cancer were calculated using the inverse logistic function [exp(X′ β) / (1+exp(X′ β))], where X represents individual risk factors observed and β the associated log odds ratios for the individual risk factors estimated from the model. Discriminative performance of these predicted risks were then compared to two univariate models of PSA alone and PSAD alone using difference in the area under the receiver-operating characteristic (ROC) curve (AUC) with bootstrap 95% confidence intervals (CIs), which provides an optimistically biased internal validation since the same dataset was used to build the model underlying predicted risks.

Data from 3833 of 4734 participants in the control arm of the PCPT were used as a validating generalization set for the EDRN prediction model. The PCPT study served as a generalization set because unlike the EDRN cohort, the PCPT study was a screening study of older healthy and primarily Caucasian men with PSA < 3.0 ng/mL and normal DRE required at study entry, and PCPT participants had a required end-of-study biopsy regardless of PSA or DRE. PSA and DRE results either on the day of, but before the biopsy, or within a maximum of one year prior to biopsy were used. Because of missing details about biopsy cores, the definition of histologically-aggressive prostate cancer was modified to include greatest linear extent of cancer (>5mm as a surrogate for ≥50% tumor involvement in a core). In total, 901 patients were excluded because of missing BMI (0.9%), prostate volume (14%), or details about biopsy cores (5%). Sensitivity analyses assessed the impact of this exclusion by repeating the analysis using simple imputation of the median BMI or prostate volume, and by considering any patient with missing details about biopsy cores as having indolent cancer; the results were consistent and are not presented. Evaluation of the EDRN prediction model was assessed by ROC curve AUC, with bootstrap 95% CIs, and by calibration comparing average model risk and observed percentage with histologically-aggressive prostate cancer. All analyses were performed using SAS version 9.1.


Demographic and pre-clinical data of the 635 men undergoing first prostate biopsy as part of the EDRN analysis cohort are summarized in Table 1. Three hundred sixty-one (57%) men had no cancer while 88 (14%) and 186 (29%) patients were identified with indolent and histologically-aggressive cancer, respectively. Only 22 of 186 men diagnosed with histologically-aggressive prostate cancer had Gleason 6 cancer with more than three cores positive or with at least one core containing ≥50% cancer; all others had Gleason 7 or greater disease. In univariate analyses, men diagnosed with histologically-aggressive prostate cancer were significantly older, had significantly higher PSA, smaller gland volume, higher PSAD and more often had abnormal DRE than men with indolent disease or no prostate cancer (each P<0.01).

Table 1
Demographic and pre-biopsy clinical characteristics of men undergoing first prostate biopsy for prostate cancer detection in the EDRN analysis and PCPT validation cohorts, according to biopsy result.

In multivariable modeling, age, BMI, family history of prostate cancer, abnormal DRE, and log of PSAD were significant predictors of histologically-aggressive cancer (each P<0.05) (Table 2). The AUC for model-predicted risks was 0.81 (95% CI, 0.77–0.84) (Figure 1). In contrast, the AUCs for PSA only or PSAD only were 0.71 (95% CI, 0.67 to 0.75) and 0.75 (95% CI, 0.71–0.80), respectively. When compared with PSA alone, at a sensitivity level of 90%, the multivariable model improved specificity from 32% to 42%. The predicted probabilities of histologically-aggressive prostate cancer for a range of risk factor values are presented in Table 3. Using our model, out of the 236 EDRN patients enrolled from January 2008 through April 2009, 24.6% of biopsies could be avoided.

Figure 1
Receiver operating characteristic (ROC) curves for the multivariable prediction model (A) versus PSA alone (B) for predicting histologically-aggressive prostate cancer in the EDRN analysis cohort (n=635), and for the model-predicted risks in the PCPT ...
Table 2
Multivariable model of demographic and pre-biopsy clinical characteristics for the presence of histologically-aggressive prostate cancer on first prostate biopsy in the EDRN analysis cohort.
Table 3
Predicted probabilities for the presence of histologically-aggressive prostate cancer on first prostate biopsy based on the EDRN analysis cohort, for a range of demographic and pre-biopsy clinical factors. The values are presented as percentages with ...

To assess the performance of the EDRN prediction model in identifying men with histologically-aggressive prostate cancer in the general population, we applied the prediction model to the control arm of the PCPT study. Among 3833 PCPT subjects, 324 (8%) had aggressive cancer on biopsy, 333 (9%) had indolent cancer, and the remainder had no cancer. The model performed well in predicting aggressive cancer (AUC = 0.78; 95% CI, 0.75–0.80). Although predicted and observed probabilities of prostate cancer diverged by over-predicting risk among patients at higher risk for aggressive cancer, the model performance was robust at lower levels of cancer risk (i.e., risk<10%; Table 4) and across most subgroups of the population (Table 5), confirming the predictive accuracy of this model in identifying men who can forego prostate biopsy while retaining 90% sensitivity in detection of aggressive cancer.

Table 4
Comparison of model-predicted risks with observed risks of histologically-aggressive prostate cancer in an initial prostate biopsy in the PCPT validation cohort. The values are presented as percentages.
Table 5
Comparison of average model-predicted risks with observed risks of histologically-aggressive prostate cancer in an initial prostate biopsy among subgroups of the PCPT validation cohort.


Stage migration related to widespread use of PSA screening has raised concerns regarding possible overdiagnosis and overtreatment of prostate cancer (1,2,15). In the EDRN cohort, nearly one-third of biopsy-detected cancers had histological features of indolent disease. Over-treatment of cancers that are diagnosed during an indolent phase early in the course of the disease could be averted by selective use of active surveillance (68, 1619). However, the use of active surveillance remains underutilized and definitive primary treatments are more commonly largely being employed, sometimes with adverse effects on quality of life (2, 20). Conversely, use of routine PSA cut-offs alone as a decision-point for identifying prostate biopsy can also lead to underdiagnosis or non-diagnosis of cancers that are histologically-aggressive but have PSA levels below routine thresholds. The use of simple PSA cut-offs as a sole focal decision-point for identifying candidates for prostate biopsy has therefore been challenged by recent changes in AUA best practice recommendations regarding prostate cancer screening and early detection (21).

Prostate biopsy does not come without inherent risks which include the physical morbidity, emotional uncertainty regarding being diagnosed with indolent cancer and cost to the health care system. Up to 2% of patients undergoing prostate biopsy develop a febrile UTI, bacteremia or acute prostatitis requiring hospitalization, complicated by recent emergence of fluoroquinolone resistance, among other possible biopsy-related complications (22,23). The emotional sequelae of identifying indolent cancer and the decision to undergo treatment or active surveillance, as well as the cost of biopsy (approximately $347.24/man in the U.S.) (24) – together with the unmeasured cost of cancers missed due to underdiagnosis among some men with normal PSA levels - further elevate societal costs of poorly discriminant algorithms to identify candidates for prostate biopsy. Urological practice, patient outcomes, and cost effectiveness of health care would each benefit from new targeted strategies, such as nomograms that improve prediction of aggressive cancers, to enable selective identification of candidates for prostate biopsy, that would improve the yield of clinically-significant, histologically-aggressive cancers warranting subsequent definitive treatment.

Recognizing the value of avoiding unnecessary biopsy by predicting individual probability of a prostate cancer diagnosis, Thompson et al. used data from the control arm of the Prostate Cancer Prevention Trial (PCPT) to develop the prostate cancer risk calculator (12). The PCPT calculator uses a combination of other risk factors with PSA (age, family history, and DRE) to specify risk of prostate cancer prior to biopsy. The PCPT risk calculator was also used for predicting high-grade cancers. However, the PCPT calculator has not been optimized and validated specifically for the measurement of risk of histologically-aggressive disease as defined by the Epstein criteria (that include amount of cancer on biopsy), and does not provide the capability of considering high volume Gleason 6 cancers as aggressive tumors, together with higher Gleason score cancers, as proposed and validated by the model that we have developed in this study.

Post-biopsy, pre-prostatectomy nomograms have been developed that used pathology findings at biopsy to predict the probability of indolent prostate cancer at prostatectomy (9,10). The Kattan post-biopsy nomogram used studied sextant biopsy results in radical prostatectomy patients to predict indolent disease at prostatectomy and was recalibrated in a screening population from the European Randomized Study on Screening for Prostate Cancer and in a single practice tertiary care US setting (9,10,25). Although both nomograms predict indolent disease with adequate discrimination, it requires pathology results of prostate biopsy to predict prostatectomy endpoints, and therefore has limited utility in decision-making regarding which patients should undergo prostate biopsy in the first place. With our predictive model, we propose bringing the strategy of a predictive model ‘upstream’ in the urological care process, to help improve selection for men for prostate biopsy.

Nam et al. previously demonstrated a multivariate model of known prostate cancer risk factors to be significantly improve the positive predictive value of PSA (13). In an attempt to individualize prostate cancer risk at the time of first PSA and DRE, Nam et al. developed a predictive nomogram from men who underwent prostate biopsy (26). The nomogram incorporated age, ethnicity, family history of prostate cancer, presence of urinary symptoms, total PSA, free:total PSA and DRE to identify risk of prostate cancer at first biopsy. The AUC for the nomogram in predicting overall (0.74 vs. 0.62) and specifically high-grade cancer (0.77 vs. 0.69) was significantly greater than AUC using PSA and DRE alone. Although the nomogram proposed by Nam et al. was an improved predictor for high-grade prostate cancer (Gleason score 7 or higher), this criteria for identifying clinically-significant disease does not obey the criteria previously identified by Epstein. Moreover, the PCPT and Nam nomograms did not elucidate practical cutpoints or criteria based on the predictive models to guide specific decision as to when a biopsy may be averted. Roobol et al. have proposed an individualized screening algorithm based on pre-biopsy information of which applying an additional biopsy cut-off of 12.5% would lead to a 33% reduction in unnecessary biopsies (27).

We found age, obesity (as measured by BMI), family history, abnormal DRE and PSA density (PSAD) as the principal factors associated with histologically-aggressive cancer (all p<0.001). By using model-defined parameters at 90% sensitivity to evaluate a subsequent cohort of 236 consecutively-enrolled men in the EDRN study we found that 58/236 (24.6%) of biopsies would have been avoided. Averting one-quarter of prostate biopsy while retaining 90% sensitivity for detecting aggressive cancers as could be guided by this EDRN model would have the potential to significantly reduce the burden of excess detection and treatment of indolent prostate cancers.

The association of the factors identified in the current study with prostate cancer severity has been previously established in other settings, and supports the external validity of our findings. Age, family history, and DRE had also been found to be significant determinants for presence or absence of cancer in the PCPT calculator (12). Of note, obesity as measured by BMI was a significant predictor for clinically significant cancer and this factor has not been included in other tools used to discern indolent from aggressive cancers (5,9,10,12,25). The relationship of obesity with aggressiveness of treated prostate cancers, however, is well established, and with the increasing prevalence of obesity worldwide, this variable may become ever more meaningful in decision-making during routine urological practice.

The biological basis for PSAD as predictive of cancer severity is reflected by larger prostate being associated with higher serum PSA due to PSA produced by benign prostatic hyperplasia (BPH) in the absence of any cancer (2831). PSAD has previously been found to be superior to PSA alone in discerning cancer from benign pathology in patients with PSA between 4 to 10ng/mL (29,30), and had also been found to be associated with probability of recurrence-free survival after prostatectomy (29,30). Indeed, in his initial report defining indolent cancers, Epstein determined that PSAD < 0.1 ng/mL/gm complemented histological criteria in predicting indolent cancer at prostatectomy. Our observed association of PSAD with detection of histologically-aggressive cancer validates this component of Epstein’s original findings and extends its use, when combined with family history, age, DRE findings, and BMI, to the identification of patients that are candidates for initial prostate biopsy.

There are several limitations to our study. We used Epstein’s original histological criteria to discern indolent from aggressive cancers, and long-term clinical outcomes of these patients to verify indolent behavior are limited (5, 7). We used <5mm tumor involvement per core in the PCPT cohort because actual percent tumor involvement per core was not recorded and therefore we could not extrapolate percent tumor involvement per core. Prior studies have suggested the role of percentage and tumor length in prostate biopsy cores as predictors for more aggressive disease at radical prostatectomy and hence clinically significant disease (32). Although our predictive model has not been externally validated by others, the model was derived from multiple institutions to avoid single institution, practice-specific, or regional biases, and was validated in the PCPT study representing the general population. Nevertheless, further external validation is warranted to determine whether the model can be applied to other clinical populations. Selection bias may be inherent in our cohort, as enrollment focused on patients who had been referred to a Urology practice; therefore our findings are more relevant to decision-making by Urologists in evaluating patients referred from a primary care provider rather than decision making at the primary care setting. Our study did not include %free PSA, that has been found to be associated with prostate cancer aggressiveness (11), because %free PSA is validated for use only when total serum PSA is between 4 to 10 ng/ml, whereas our model targets cancer detection across an unrestricted spectrum of total PSA results. The patient population has limited racial diversity, with 14% of men self-reporting as non-Caucasian comprised of 7% African-American and 7% mix of Hispanic, Asian, middle- or southeast-Asian, and Cape Verdean, and an association of race with aggressive cancer, independent of the other model factors, was not detected; it is possible that racial effects may be significant in more diverse study cohorts or clinical settings. Over-diagnosis is a problem in prostate cancer and this could addressed by either refining who we biopsy or by better selection of patients for active surveillance. The purpose of our study is to better identify patients who may be harboring clinically significant prostate cancer who may benefit from earlier intervention and may improve current active surveillance selection protocols. Finally, accepting a false-negative rate of 10% thereby avoiding 25% of biopsies may be viewed as excessively high. Up to 30% of men with insignificant cancer at first biopsy ultimately are discovered to have significant cancer (either at subsequent biopsy or surgery), thus the real false-negative rate could be much higher for the predictive model. However, the strategy of avoiding biopsy at initial evaluation does not preclude the possibility that patients with false negative initial screening results could be detected during follow-up screening in subsequent years. In light of these limitations, more extensive evaluation of our model may be warranted to justify further broader acceptance of averting biopsy.


Prior predictive nomograms or risk calculators have not sought to identify men who should undergo prostate biopsy with the goal of improving selective detection of significantly aggressive prostate cancer, while avoiding biopsy that would detect indolent disease. Our multivariable, predictive model improved the specificity of PSA alone in detecting such histologically-aggressive cancers and elucidated practical cutpoints or criteria to guide specific decision as to when a biopsy may be averted while retaining 90% sensitivity for detection of histologically-aggressive prostate cancer. Generalizability of these findings was verified in the control arm of the PCPT cohort. Our findings suggest that 90% sensitivity for detecting significant cancer can be retained while averting prostate biopsy in men that meet each of the following criteria: normal DRE, no family history of prostate cancer, PSAD is <0.1 ng/mL/cc, and BMI < 25 kg/m2. These criteria would avoid biopsy in approximately one-quarter of biopsy-eligible men.


Funding: NCI-EDRN U01 CA11391


1. Potosky AL, Miller BA, Albertsen PC, et al. The role of increasing detection in the rising incidence of prostate cancer. JAMA. 1995;273:548. [PubMed]
2. Cooperberg MR, Park S, Carroll PR. The changing face of low-risk prostate cancer: trends in clinical presentation and primary management. J Clin Oncol. 2004;22:2141–2149. [PMC free article] [PubMed]
3. Schröder FH, Hugosson J, Roobol MJ, et al. Screening and prostate-cancer mortality in a randomized European study. N Engl J Med. 2009 Mar 26;360(13):1320–1328. Epub 2009 Mar 18. PubMed PMID: 19297566. [PubMed]
4. Andriole GL, Crawford ED, Grubb RL, 3rd, et al. Mortality results from a randomized prostate-cancer screening trial. N Engl J Med. 2009 Mar 26;360(13):1310–1319. Epub 2009 Mar 18. Erratum in: N Engl J Med. 2009 Apr 23;360(17):1797. PubMed PMID: 19297565. [PMC free article] [PubMed]
5. Epstein JI, Walsh PC, Carmichael M, et al. Pathologic and clinical findings to predict tumor extent of non-palpable (stage T1c) prostate cancer. JAMA. 1994;271:368. [PubMed]
6. Klotz L. Active surveillance with selective delayed intervention: using natural history to guide treatment in good risk prostate cancer. J Urol. 2004;172:S48–S50. discussion S50-S51. [PubMed]
7. Warlick C, Trock BJ, Landis P, et al. Delayed versus immediate surgical intervention and prostate cancer outcome. J Natl Cancer Inst. 2006;98:355. [PMC free article] [PubMed]
8. Dall’Era MA, Konety BR, Cowan JE, et al. Active surveillance for the management of prostate cancer in a contemporary cohort. Cancer. 2008;112:2664–2670. [PubMed]
9. Kattan MW, Eastham JA, Wheeler TM, et al. Counseling men with prostate cancer: a nomogram for predicting the presence of small, moderately differentiated, confined tumors. J Urol. 2003;170:1792. [PubMed]
10. Steyerberg EW, Roobol MJ, Kattan MW, et al. Prediction of indolent prostate cancer: validation and updating of a prognostic nomogram. J Urol. 2007;177:107. [PubMed]
11. Epstein JI, Chan DW, Sokoll LJ, et al. Nonpalpable stage T1c prostate cancer: Prediction of insignificant disease using free/total prostate specific antigen levels and needle biopsy findings. J Urol. 1998;160(pt 2):2407–2411. [PubMed]
12. Thompson IM, Ankerst DP, Chi C, et al. Assessing prostate cancer risk: results from the Prostate Cancer Prevention Trial. J Natl Cancer Inst. 2006;98(8):529–534. [PubMed]
13. Nam RK, Toi A, Klotz LH, et al. Assessing individual risk for prostate cancer. J Clin Oncol. 2007;25:3582–3588. [PubMed]
14. Kawachi MH, Bahnson RR, Barry M, et al. NCCN. Prostate cancer early detection. Clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2007;5:714–736. [PubMed]
15. Etzioni R, Penson DF, Legler JM, et al. Overdiagnosis due to prostate-specific antigen screening: lessons from U.S. prostate cancer screening trends. J Natl Cancer Inst. 2002;94:981–990. [PubMed]
16. Zietman AL, Thakral H, Wilson L, Schellhammer P. Conservative management of prostate cancer in the prostate specific antigen era: the incidence and time course of subsequent therapy. J Urol. 2001;166(5):1702–1706. [PubMed]
17. Carter HB, Walsh PC, Landis P, et al. Expectant management of nonpalpable prostate cancer with curative intent: preliminary results. J Urol. 2002;167:1231–1234. [PubMed]
18. Carter CA, Donahue T, Sun L, et al. Temporary deferred therapy (watchful waiting) for men younger than 70 years with low-risk localized prostate cancer in the prostate specific antigen era. J Clin Oncol. 2003;21:4001–4008. [PubMed]
19. Patel MI, DeConcini DT, Lopez-Corona E, et al. An analysis of men with clinically localized prostate cancer who deferred definitive therapy. J Urol. 2004;171:1520–1524. [PubMed]
20. Sanda MG, Dunn RL, Michalski J, et al. Quality of life and satisfaction with outcome among prostate cancer survivors. N Eng J Med. 2008;358:1250–1261. [PubMed]
21. Carroll P, Albertsen PC, Greene K, Babaian RK, Carter HB, Gann PH, Han M, Kuban DA, Sartor AO, Stanford JL, Zietman A. Prostate-Specific Antigen Best Practice Statement: 2009 Update. American Urological Association Office of Education and Research. 2009
22. Kapoor DA, Klimberg IW, Malek JH, et al. Single dose ciprofloxacin versus placebo for prophylaxis during transrectal ultrasound prostate biopsy. Urology. 1998;52:552–558. [PubMed]
23. Feliciano J, Teper E, Ferrandino M, et al. The incidence of flouroquinolone resistant infections after prostate biopsy- are flouroquinolones still effective prophylaxis? J Urol. 2008;179:952–955. [PubMed]
24. Ekwueme DU, Stroud LA, Chen Y. Cost analysis for screening, diagnosing and staging prostate cancer based on a systematic review of published studies. Prev Chron Dis. 2007;4:A100. [PMC free article] [PubMed]
25. Dong F, Kattan MW, Steyerberg EW, et al. Validation of pretreatment nomograms for predicting indolent prostate cancer: efficacy in contemporary urological practice. J Urol. 2008;180:150–154. [PubMed]
26. Nam RK, Toi A, Trachtenberg J, et al. Making sense of prostate specific antigen: improving its predictive value in patients undergoing prostate biopsy. J Urol. 2006;175:489–494. [PubMed]
27. Roobol MJ, Steyerberg EW, Kranse R, et al. A risk-based strategy improves prostate-specific antigen-driven detection of prostate cancer. Euro Urol. 2010;57:79–85. [PubMed]
28. Benson MC, Olsson CA. Prostate specific antigen and prostate specific antigen density: Roles in patient evaluation and treatment. Cancer. 1994;74:1667–1673. [PubMed]
29. Bretton PR, Evans WP, Borden JD, et al. The use of prostate specific anigen density to improve the sensitivity of prostate specific antigen in detecting prostate carcinoma. Cancer. 1994;74:2991–2995. [PubMed]
30. Seaman EK, Wang IS, Cooner W, et al. Predictive value of prostate specific antigen density for the presence of micrometastatic carcinoma of the prostate. Urology. 1994;43:645–648. [PubMed]
31. Brassell SA, Tzu-Cheg K, Sun L, et al. Prostate specific antigen versus prostate specific antigen density as predictor of tumor volume, margin status, pathologic stage, and biochemical recurrence of prostate cancer. Urology. 2005;66:1229–1233. [PubMed]
32. Naya Y, Slaton JW, Troncoso P, Okihara K, Babaian RJ. Tumor length and location of cancer on biopsy predict for side specific extraprostatic cancer extension. J Urol. 2004;171:1093–1097. [PubMed]