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Article of the week: External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Every week, the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to this post, there is an editorial written by a prominent member of the urological community and a visual abstract created by trainee urologists. Please use the comment buttons below to join the conversation.

If you only have time to read one article this week, we recommend this one. 

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Lukas Püllen*, Jan P. Radtke*, Manuel Wiesenfarth, Monique J. Roobol§, Jan F.M. Verbeek§, Axel Wetter, Nika Guberina, Abhishek Pandey**, Clemens Hüttenbrink**, Stephan Tschirdewahn*, Sascha Pahernik**, Boris A. Hadaschik* and Florian A. Distler**

*Department of Urology, University Hospital Essen, Nordrhein-Westfalen, Department of Radiology, German Cancer Research Centre (DKFZ), Division of Biostatistics, German Cancer Research Centre (DKFZ), Heidelberg, Germany, §Department of Urology, Erasmus University Medical Centre, Rotterdam, The Netherlands, Department of Radiology, University Hospital Essen, Nordrhein-Westfalen, and **Department of Urology, Paracelsus Medical University, Nuremberg, Nürnberg, Germany

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Abstract

Objectives

To validate, in an external cohort, three novel risk models, including the recently updated European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator, that combine multiparametric magnetic resonance imaging (mpMRI) and clinical variables to predict clinically significant prostate cancer (PCa).

Patients and Methods

We retrospectively analysed 307 men who underwent mpMRI prior to transperineal ultrasound fusion biopsy between October 2015 and July 2018 at two German centres. mpMRI was rated by Prostate Imaging Reporting and Data System (PI‐RADS) v2.0 and clinically significant PCa was defined as International Society of Urological Pathology Gleason grade group ≥2. The prediction performance of the three models (MRI‐ERSPC‐3/4, and two risk models published by Radtke et al. and Distler et al., ModRad and ModDis) were compared using receiver‐operating characteristic (ROC) curve analyses, with area under the ROC curve (AUC), calibration curve analyses and decision curves used to assess net benefit.

Fig. 4. Biopsies saved vs prostate cancer detected/missed using different risk thresholds for clinically significant prostate cancers (PCas) for the different models for a standardized number of 1000 men for the whole cohort (A) and the two analysed subgroups (biopsy‐naïve (B) and previous negative biopsy (C)); including a graphical presentation of biopsy saving vs. missing clinically significant PCas for two different thresholds (10% and 15%) for the validated nomograms. Green shading shows the number of saved biopsies. Red shading shows the number of clinically significant PCas missed. ModDis, risk model published by Distler et al.; ModRad, risk model published by Radtke et al.; MRI‐ERSPC‐3/4, updated ERSPC risk calculator 3/4.

Results

The AUCs of the three novel models (MRI‐ERSPC‐3/4, ModRad and ModDis) were 0.82, 0.85 and 0.83, respectively. Calibration curve analyses showed the best intercept for MRI‐ERSPC‐3 and ‐4 of 0.35 and 0.76. Net benefit analyses indicated clear benefit of the MRI‐ERSPC‐3/4 risk models compared with the other two validated models. The MRI‐ERSPC‐3/4 risk models demonstrated a discrimination benefit for a risk threshold of up to 15% for clinically significant PCa as compared to the other risk models.

Conclusion

In our external validation of three novel prostate cancer risk models, which incorporate mpMRI findings, a head‐to‐head comparison indicated that the MRI‐ERSPC‐3/4 risk model in particular could help to reduce unnecessary biopsies.

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Editorial: Magnetic resonance imaging as a personalised tool to safely avoid prostate biopsy

Identifying men at risk of developing clinically significant prostate cancer (csPCa) who are either biopsy naïve or have undergone a prior negative systematic biopsy remains a dilemma for urologists seeking to utilise clinical resources in a cost‐conscious and safe manner. Clinical and demographic factors including DRE findings, serum PSA concentrations, race/ethnicity, and family history, guide shared decision‐making to pursue an initial or repeat prostate biopsy. Despite thoughtful risk assessments, the screening tools implemented often lead to biopsies where a majority demonstrates benign pathology findings or indolent forms of PCa that would not mandate immediate, definitive intervention. Hence, various risk models (RMs) have been proposed to stratify men who have a greater likelihood of harbouring csPCa, and several now incorporate findings from multiparametric MRI (mpMRI) by assessing suspicious lesion characteristics into their algorithms. While promising, most of these models were generated using single‐institution retrospective data and lack the external validation that could make them more generalisable and widely adopted in clinical practice.

In the present issue, Püllen et al. [1] evaluate three RMs that incorporate mpMRI findings using a cohort of 307 men who were biopsy naïve or had previously undergone a negative prostate biopsy. Risk of csPCa according to the MRI‐European Randomized Prostate Screening for Prostate Cancer Risk Calculators 3 and 4 (MRI‐ERSPC‐3/4) [2], Radtke’s RM (ModRAD) [3], and Distler’s RM (ModDis) [4] were compared to final pathology after TRUS‐guided perineal prostate biopsy with MRI‐fusion targeted sampling, as indicated using a Prostate Imaging‐Reporting and Data System version 2 (PI‐RADSv2) score ≥3 as the threshold.

The cohort had a median age of 67 years, median PSA concentration of 8.8 ng/mL, and there were 453 PI‐RADSv2 ≥3 lesions, which is consistent with a typical at‐risk screening population. Amongst these men, 134 (40%) harboured csPCa defined as a Gleason Grade Group ≥2. All three RMs performed similarly on receiver operating curve analyses with area under the curve for prediction nearing 0.85 for finding csPCa in both biopsy naïve and prior negative‐biopsy patients. Using a 15% risk threshold, the adapted MRI‐ERSPC‐3/4 RM would have safely avoided 30% of biopsies with 6% of csPCa diagnoses being missed, whereas the ModRad and ModDis RMs would have only avoided 17% and 6% of unnecessary biopsies, respectively, albeit with far fewer occult cases of csPCa.

The integration of mpMRI in the pre‐biopsy setting is being more widely adopted into the clinical landscape, with emerging support largely due to its value in detecting csPCa, but also the recognised high negative predictive value potentiating the safe avoidance or deferral of prostate biopsy [5]. Performing a prostate biopsy in all men with a clinical screening positive PSA and/or DRE carries a significant public health burden, and harbours recognised clinical morbidity without definitive overall survival benefit for many. Hence, integration of MRI findings, importantly the lack of highly suspicious lesions, is of interest in RM assessment to determine which patients would be benefited most from prostate biopsy while sparing some from biopsy, without compromising detection of csPCa and oncological outcomes.

For patients who forgo prostate biopsy based upon factors such as nomogram‐predicted risk of harbouring csPCa, the appropriate timing for performing repeat evaluation with biomarkers and/or MRI is not well defined. Various models have shown much higher rates of biopsy avoidance if accepting some level of missed csPCa [6]. With the awareness that some men who would theoretically avoid a biopsy based on these RMs may actually harbour csPCa, should these men undergo repeat MRI as standard or would serial PSA assessment drive biopsy detection of their csPCa with adequate lead time for definitive treatment? Prospective investigations assessing the clinical course of patients with negative MRI findings who avoid or defer biopsy are critical to determine the real‐world applicability of such RMs. The true value of these RMs and nomograms should balance their public health cost and morbidity benefit with potential oncological risk.

by Zachary A. Glaser and Soroush Rais‐Bahrami

References

  1. Püllen LRadtke JPWiesenfarth M et al. External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction. BJU Int 2020125407– 16
  2. Alberts ARRoobol MJVerbeek JFM et al. Prediction of high‐grade prostate cancer following multiparametric magnetic resonance imaging: improving the Rotterdam European randomized study of screening for prostate cancer risk calculators. Eur Urol 201975310– 8
  3. Radtke JPWiesenfarth MKesch C et al. Combined clinical parameters and multiparametric magnetic resonance imaging for advanced risk modeling of prostate cancer‐patient‐tailored risk stratification can reduce unnecessary biopsies. Eur Urol 201772888– 96
  4. Distler FARadtke JPBonekamp D et al. The value of PSA density in combination with PI‐RADS for the accuracy of prostate cancer prediction. J Urol 2017198575– 82
  5. Siddiqui MMRais‐Bahrami STurkbey B et al. Comparison of MR/ultrasound fusion‐guided biopsy with ultrasound‐guided biopsy for the diagnosis of prostate cancer. JAMA 2015313390– 7
  6. Mehralivand SShih JHRais‐Bahrami S et al. A Magnetic resonance imaging‐based prediction model for prostate biopsy risk stratification. JAMA Oncol 20184678– 85

 

 

Visual abstract: External validation of novel MRI-based models for prostate cancer prediction

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Article of the week: mpMRI and follow‐up to avoid prostate biopsy in 4259 men

Every week, the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an editorial written by a prominent member of the urological community and a video prepared by the authors. These are intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation. 

If you only have time to read one article this week, it should be this one.

Multiparametric magnetic resonance imaging and follow‐up to avoid prostate biopsy in 4259 men

Wulphert Venderink*, Annemarijke van Luijtelaar*, Marloes van der Leest*, Jelle O. Barentsz*, Sjoerd F.M. Jenniskens*, Michiel J.P. Sedelaar,Christina Hulsbergen-van de Kaa, Christiaan G. Overduin* and Jurgen J. Fütterer*

*Department of Radiology and Nuclear Medicine, Department of Urology, and Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands

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Abstract

Objective

To determine the proportion of men avoiding biopsy because of negative multiparametric magnetic resonance imaging (mpMRI) findings in a prostate MRI expert centre, and to assess the number of clinically significant prostate cancers (csPCa) detected during follow‐up.

Patients and method

Retrospective study of 4259 consecutive men having mpMRI of the prostate between January 2012 and December 2017, with either a history of previous negative transrectal ultrasonography‐guided biopsy or biopsy naïve. Patients underwent mpMRI in a referral centre. Lesions were classified according to Prostate Imaging Reporting And Data System (PI‐RADS) versions 1 and 2. Negative mpMRI was defined as an index lesion PI‐RADS ≤2. Follow‐up until 13 October 2018 was collected by searching the Dutch Pathology Registry (PALGA). Gleason score ≥3 + 4 was considered csPCa. Kaplan–Meier analysis and univariable logistic regression models were used in the cohort of patients with negative mpMRI and follow‐up.

Fig. 2. Distribution of PI‐RADS scored in the entire cohort.

Results

Overall, in 53.6% (2281/4259) of patients had a lesion classified as PI‐RADS ≤2. In 320 patients with PI‐RADS 1 or 2, follow‐up mpMRI was obtained after a median (interquartile range) of 57 (41–63) months. In those patients, csPCa diagnosis‐free survival (DFS) was 99.6% after 3 years. Univariable logistic regression analysis revealed age as a predictor for csPCa during follow‐up (P < 0.05). In biopsied patients, csPCa was detected in 15.8% (19/120), 43.2% (228/528) and 74.5% (483/648) with PI‐RADS 3, 4 and 5, respectively.

Conclusion

More than half of patients having mpMRI of the prostate avoided biopsy. In those patients, csPCa DFS was 99.6% after 3 years.

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Article of the month: Implementation of multiparametric MRI technology for evaluation of PCa in the clinic

Every month, the Editor-in-Chief selects an Article of the Month from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an editorial written by a prominent member of the urological community, and a podcast produced by our current Resident Podcasters. These are intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation. 

If you only have time to read one article this week, it should be this one.

Implementation of multiparametric magnetic resonance imaging technology for evaluation of patients with suspicion for prostate cancer in the clinical practice setting

Paras H. Shah*, Vinay R. Patel, Daniel M. Moreira, Arvin K. George§, Manaf Alom*, Zachary Kozel, Vidhu Joshi*, Eran Ben-Levi**, Robert Villani**, Oksana Yaskiv††Louis R. Kavoussi, Manish Vira, Carl O. Olsson‡‡ and Ardeshir R. Rastinehad

 

*Department of Urology, Mayo Clinic, Rochester, MN, Department of Urology, Icahn Smith Institute for Urology, Northwell Health, New York, NY, Department of Urology, University of Illinois at Chicago, Chicago, IL, §Department of Urology, University of Michigan, Ann Arbor, MI, Department of Urology, Smith Institute for Urology, Northwell Health, **Department of Radiology, Hofstra Northwell School of Medicine, ††Department of Pathology, Hofstra Northwell School of Medicine, New Hyde Park, and ‡‡Integrated Medical Professionals, Melville, NY, USA

 

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Abstract

Objectives

To investigate the impact of implementing magnetic resonance imaging (MRI) and ultrasonography fusion technology on biopsy and prostate cancer (PCa) detection rates in men presenting with clinical suspicion for PCa in the clinical practice setting.

Patients and Methods

We performed a review of 1 808 consecutive men referred for elevated prostate‐specific antigen (PSA) level between 2011 and 2014. The study population was divided into two groups based on whether MRI was used as a risk stratification tool. Univariable and multivariable analyses of biopsy rates and overall and clinically significant PCa detection rates between groups were performed.

Results

The MRI and PSA‐only groups consisted of 1 020 and 788 patients, respectively. A total of 465 patients (45.6%) in the MRI group and 442 (56.1%) in the PSA‐only group underwent biopsy, corresponding to an 18.7% decrease in the proportion of patients receiving biopsy in the MRI group (P < 0.001). Overall PCa (56.8% vs 40.7%; P < 0.001) and clinically significant PCa detection (47.3% vs 31.0%; P < 0.001) was significantly higher in the MRI vs the PSA‐only group. In logistic regression analyses, the odds of overall PCa detection (odds ratio [OR] 1.74, 95% confidence interval [CI] 1.29–2.35; P < 0.001) and clinically significant PCa detection (OR 2.04, 95% CI 1.48–2.80; P < 0.001) were higher in the MRI than in the PSA‐only group after adjusting for clinically relevant PCa variables.

Conclusion

Among men presenting with clinical suspicion for PCa, addition of MRI increases detection of clinically significant cancers while reducing prostate biopsy rates when implemented in a clinical practice setting.

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Article of the Week: Cost‐effectiveness of MRI and targeted fusion biopsy for early detection of prostate cancer

Every Week, the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

If you only have time to read one article this week, it should be this one.

Cost‐effectiveness of magnetic resonance imaging and targeted fusion biopsy for early detection of prostate cancer

Christine L. Barnett* , Matthew S. Davenport, Jeffrey S. Montgomery, John T. WeiJames E. Montie‡ and Brian T. Denton*

 

*Departments of Industrial and Operations Engineering, Radiology, and Urology, University of Michigan, Ann Arbor, MI, USA

 

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Objective

To determine how best to use magnetic resonance imaging (MRI) and targeted MRI/ultrasonography fusion biopsy for early detection of prostate cancer (PCa) in men with elevated prostate‐specific antigen (PSA) concentrations and whether it can be cost‐effective.

Methods

A Markov model of PCa onset and progression was developed to estimate the health and economic consequences of PCa screening with MRI. Patients underwent PSA screening from ages 55 to 69 years. Patients with elevated PSA concentrations (>4 ng/mL) underwent MRI, followed by targeted fusion or combined (standard + targeted fusion) biopsy on positive MRI, and standard or no biopsy on negative MRI. Prostate Imaging Reporting and Data System (PI‐RADS) score on MRI was used to determine biopsy decisions. Deaths averted, quality‐adjusted life‐years (QALYs), cost and incremental cost‐effectiveness ratio (ICER) were estimated for each strategy.


Results

With a negative MRI, standard biopsy was more expensive and had lower QALYs than performing no biopsy. The optimum screening strategy (ICER $23 483/QALY) recommended combined biopsy for patients with PI‐RADS score ≥3 and no biopsy for patients with PI‐RADS score <3, and reduced the number of screening biopsies by 15%. Threshold analysis suggests MRI continues to be cost‐effective when the sensitivity and specificity of MRI and combined biopsy are simultaneously reduced by 19 percentage points.

Conclusions

Our analysis suggests MRI followed by targeted MRI/ultrasonography fusion biopsy can be a cost‐effective approach to the early detection of PCa.

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Editorial: MRI with targeted fusion biopsy: is the time now?

The current standard of performing TRUS‐guided systematic biopsy in men with a PSA of 4–10 ng/mL results in a considerable number of unnecessary prostate biopsies and overtreatment of clinically indolent disease, both of which are costly from the patient and healthcare system perspectives [1]. Two recent studies document that incorporating multiparametric (mp)MRI into prostate cancer screening has the potential to reduce overdiagnosis and overtreatment. Ahmed et al. [2] performed mpMRI followed by TRUS biopsy and template prostate mapping biopsy in 576 men with a PSA level of 4–14 ng/mL or an abnormal DRE. They found that using mpMRI to triage men would result in 27% fewer men undergoing biopsy while diagnosing 5% fewer clinically insignificant cancers. Furthermore, if subsequent TRUS biopsies were directed by mpMRI findings, 18% more cases of clinically significant cancer might be detected compared with traditional screening biopsies. Using a similar randomized study design, Kasivisvanathan et al. [3] found the use of mpMRI for screening reduced the biopsy rate by 28%, while lowering the rate of clinically insignificant cancer by 13% and improving the detection rate of clinically significant cancer by 12% [3]. While the addition of mpMRI to the screening armamentarium clearly provides clinical value, it also adds considerable increased costs, begging the question: is it worth it?

In the current issue of BJUI, Barnett et al. [1] evaluated the cost‐effectiveness of prostate MRI in a screening setting in order to determine whether MRI may be able to mitigate prostate biopsies in biopsy‐naïve men with a negative imaging study. They found that, when using the generally accepted threshold of $100 000/quality‐adjusted life year (QALY), the most cost‐efficient strategy consisted of obtaining prostate MRI in men with PSA >4 mg/mL. This was followed by either systematic and targeted fusion biopsy if the MRI showed a Prostate Imaging Reporting and Data System (PI‐RADS) score ≥3 lesion or continued observation if the MRI did not show a PI‐RADS score ≥3 lesion. Altogether, this strategy resulted in 5.9 prostate cancer deaths averted, 60.7 QALYs gained, and 72.6 life‐years gained for every 1000 patients screened. The number‐needed‐to‐treat to prevent one prostate cancer death with this approach was 169.

While the results are informative, the reader should interpret the study’s findings carefully as there is not agreement among policy makers on what is the optimal incremental willingness‐to‐pay threshold to determine what is truly cost‐effective. Furthermore, this study does not address the potential negative impact that detection of clinically insignificant prostate cancer may have on health‐state utilities and quality of life. Barnett et al. also predominantly obtained costs from Medicare data, but as previously reported, these costs are often rough estimates that are derived more from revenue or reimbursement than from the true cost of treating the disease process. The cost‐effectiveness estimates presented in this report, therefore, will probably vary from country to country. To examine the true cost, Laviana et al. [4] previously explored the cost of prostate MRI using time‐driven activity‐based costing and found the cost of MRI and mpMRI/TRUS to be $670 and $1,072 US dollars, respectively. These are significantly cheaper than the Medicare reported costs of $964.21 and $3,019.35 for MRI and mpMRI/TRUS, respectively. This implies that MRI and targeted biopsy may actually be even more cost‐effective than reported in the present study.

We must remember that, while the present study shows that MRI in prostate cancer screening may be cost‐effective, the base case population only included men with a PSA >4 mg/mL. This study does not address the cost‐effectiveness of a screening MRI in the larger population of all men at risk of prostate cancer, although previous data by Nam et al. [5] suggest MRI may be a potentially better primary screening tool than PSA. Of course, population‐wide prostate MRI screening would result in greatly increased upfront costs and, as such, the strategy would first need to be proven cost‐effective before MRI could replace PSA as the front‐line test in prostate cancer screening.

In conclusion, Burnett et al. elegantly demonstrate that an upfront MRI, in men with a PSA of >4 ng/mL, may ultimately be a cost‐effective approach depending on your willingness‐to‐pay threshold. Policymakers and payers worldwide should recognize that prostate MRI is here to stay and should be made more widely available to those with a PSA >4 ng/mL who are at risk of prostate cancer.

Aaron A. Laviana* and David F. Penson*
*Department of Urological Surgery, Vanderbilt University, and VA Tennessee Valley Geriatric Research, Education and Clinical Centre, Nashville, TN, USA

 

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References
  1. Barnett C, Davenport M, Montgomery J et al. Cost‐effectiveness of magnetic resonance imaging and targeted fusion biopsy for early detection of prostate cancer. BJU Int 2018122: 50–8
  2. Ahmed HU, El‐Shater BA, Brown LC et al. Diagnostic accuracy of multi‐parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 2017389: 815–22
  3. Kasivisvanathan V, Rannikko AS, Borghi M et al. MRI‐targeted or standard biopsy for prostate‐cancer diagnosis. N Engl J Med 2018; 378: 1767-77
  4. Laviana AA, Ilg AM, Veruttipong D et al. Utilizing time‐driven activity‐based costing to understand the short‐ and long‐term costs of treating localized, low‐risk prostate cancer. Cancer 2016122: 447–55
  5. Nam RK, Wallis CJD, Stojcic‐Bendavid J et al. A pilot study to evaluate the role of magnetic resonance imaging for prostate cancer screening in the general population. J Urol 2016192: 361–6

 

Article of the Week: A mpMRI-based risk model to determine the risk of prostate cancer prior to biopsy

Every Week the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

If you only have time to read one article this week, it should be this one.

A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy

Pim J. van Leeuwen*, Andrew Hayen, James E. Thompson*†‡, Daniel Moses§Ron Shnier§, Maret Bohm, Magdaline Abuodha, Anne-Maree HaynesFrancis Ting*†‡, Jelle Barentsz, Monique Roobol**, Justin Vass††, Krishan Rasiah††Warick Delprado‡‡ and Phillip D. Stricker*†‡

 

*St. Vincents Prostate Cancer Centre, Garvan Institute of Medical Research/The Kinghorn Cancer Centre, Darlinghurst, School of Public Health and Community Medicine, §School of Medicine, University of New South Wales, Kensington, New South Wales, Australia, Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, **Department of Urology, Erasmus University Medical Center, Rotterdam, the Netherlands, ††Department of Urology, Royal North Shore Private Hospital, St Leonards, and ‡‡Douglass Hanly Moir Pathology and University of Notre Dame, Darlinghurst, New South Wales, Australia

 

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Abstract

Objective

To develop and externally validate a predictive model for detection of significant prostate cancer.

Patients and Methods

Development of the model was based on a prosp   ctive cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling.

Results

In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P < 0.001). The model was well calibrated in internal and external validation. Decision analysis showed that use of the advanced model in practice would improve biopsy outcome predictions. Clinical application of the model would reduce 28% of biopsies, whilst missing 2.6% significant prostate cancer.

Conclusions

Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed.

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Editorial: Novel risk stratification nomograms for counseling patients on the need for prostate biopsy

Contemporary recommendations for prostate screening incorporate the measurement of serum PSA levels into shared decision making [1]. PSA is limited by a low specificity for prostate cancer and exposes a certain number of men to unnecessary prostate biopsies. Moreover, it has been attributed to an over-diagnosis and over treatment of this disease, especially in indolent cancer that may never affect a man’s longevity [2].

Prostate cancer risk stratification and aggressiveness is necessary in both the pre-biopsy clinical counselling, as well as the decision-making process. It is clear that such an important approach cannot be accomplished based on PSA alone. In order to enhance prostate cancer screening and detection, other clinical variables such as PSA density, prostate volume, percentage free PSA, and DRE, are routinely considered in conjunction with PSA for determining the need for prostate biopsy.

Increasing evidence supports the use of MRI in prostate cancer detection when used as a localisation tool to guide MRI-targeted biopsy techniques such as MRI-ultrasonography fusion-targeted biopsy [3-5]. Pre-biopsy MRI not only allows accurate tumour localisation, but also provides an assessment of cancer suspicion using an MRI suspicion score, and thus provides accurate prediction of the likelihood of prostate cancer on prostate biopsy [6].

In this study, van Leeuwen et al. [7] developed and externally validated a set of nomograms predicting clinically significant prostate cancer by incorporating prostate MRI. The performance characteristics of the nomograms were maximised by inclusion of MRI results. The authors determined that clinical application of the model would reduce 28% of biopsies, while missing 2.6% of clinically significant prostate cancer. Ultimately incorporating these nomograms into the clinical decision-making process could result in a considerable reduction in unnecessary biopsies and reduction in the risk of over-detection of clinically insignificant disease at the cost of a small increase in the number of significant cancers missed.

The authors should be commended for their predictive nomograms, in that they may further aid in the decision to perform biopsy in men with clinical suspicion of prostate cancer. However, the findings of this study should be interpreted with caution. In formulating nomograms, the obvious clinical goal is the creation of a tool that improves the selection of men in need of biopsy. Unless nomograms are derived from general ‘at risk’ populations, including men with low- and high-risk of prostate cancer, the tool may be limited in its prediction. As an example, if all men in the training cohort have an elevated PSA level, the predictive value of PSA in the nomogram may be reduced. In this case, the training and validation cohort are not well described, but it seems to be a referral population, and the PSA range is relatively narrow. As such, it’s applicability to all men presenting for prostate cancer may be questionable.

We also have had difficulty modelling a nomogram from our MRI-targeted biopsy dataset because the power of MRI-suspicion score in predicting cancer tends to minimise the effect of other variables such as PSA, age, and gland size. The authors did not compare their multivariable predictive models to MRI alone, and this may have been the most relevant comparison. In this study, the gland size and PSA level contribute significantly to the nomogram score, but one might question the findings. For example, a man with a Prostate Imaging Reporting and Data System (PI-RADS) score of 4 or 5, a large gland and a low PSA level, has a similar or lower risk as a man with a PSA level of 15 ng/mL, a moderate gland, and a PI-RADS score of 3. This is not consistent with our clinical experience and draws concern in the reliability of the nomogram at extremes of PSA and age. Men with PI-RADS 5 have high rates of clinically significant prostate cancer, regardless of PSA or age. This also may reflect variability in the predictive accuracy of MRI depending upon MRI interpretation.

Another limitation of the study, as the authors cite, is that patients were biopsied using a transperineal mapping with a median of 30 cores. This biopsy strategy is not routinely used in most institutions, and consequently limits the generalisability of the nomograms.

Selective use of prostate biopsy among men with elevated PSA levels through further refinement of cancer risk is highly desirable. The novel risk stratification nomograms developed by van Leeuwen et al. [7] add to the tools we may use to counsel our patients on the need for prostate biopsy. Further evaluation of these nomograms on additional independent patient cohorts is warranted prior to implementation in clinical practice.

Marc A. Bjurlinand Samir S. Taneja
*Division of Urology, Department of Surgery, NYU Lutheran Medical Center, NYU Langone Health System, New York, NY, USA and Division of Urologic Oncology, Department of Urology, NYU Langone Medical Center, New York, NY, US

 

References

 

1 Carter HBAlbertsen PCBarry MJ et al. Early detection of prostate cancer: AUA Guideline. J Urol2013; 190: 41926

 

2 Loeb SBjurlin MANicholson J et al. Overdiagnosis and overtreatment of prostate cancer. Eur Urol
2014; 65: 104655

 

3 Mendhiratta NMeng XRosenkrantz AB et al. Prebiopsy MRI and MRI-ultrasound fusion-targeted prostate biopsy in men with previous negative biopsies: impact on repeat biopsy strategies. Urology 2015; 86: 11928

 

 

5 Meng XRosenkrantz ABMendhiratta N et al. Relationship between prebiopsy multiparametric magnetic resonance imaging (MRI), biopsy indication, and MRI-ultrasound fusion-targeted prostate biopsy outcomes. Eur Urol 2016; 69: 51217

 

 

7 van Leeuwen PJHayan AThompson JE et al. A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy. BJU Int 2017; 120: 7748

 

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