Head-to-head comparison of prostate cancer risk calculators predicting biopsy outcome

Pereira-Azevedo, Nuno; Verbeek, Jan; Nieboer, Daan; Bangma, Chris H.; Roobol, Monique J.

doi:10.21037/tau.2017.12.21

Cited by 31 publications

(33 citation statements)

References 33 publications

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“…However, its reliability as screening tool for PCa remains controversial due to its lack of specificity. Several non-malignant conditions of the prostate, such as BB, are associated with an increased PSA levels 35 www.nature.com/scientificreports www.nature.com/scientificreports/ STHLM3 test 23,24 , or RCs to assess the PCa risk of a patient 25 . However, their clinical applicability is controversial and remain a matter of personal choice whether to use it in daily clinical practice.…”

Section: Discussionmentioning

confidence: 99%

A predictive model for prostate cancer incorporating PSA molecular forms and age

Oto

Fernández-Pardo

Royo

et al. 2020

Sci Rep

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The diagnostic specificity of prostate specific antigen (PSA) is limited. We aimed to characterize eight anti-PSA monoclonal antibodies (mAbs) to assess the prostate cancer (PCa) diagnostic utility of different PSA molecular forms, total (t) and free (f) PSA and PSA complexed to α 1 -antichymotrypsin (complexed PSA). MAbs were obtained by immunization with PSA and characterized by competition studies, ELISAs and immunoblotting. With them, we developed sensitive and specific ELISAs for these PSA molecular forms and measured them in 301 PCa patients and 764 patients with benign prostate hyperplasia, and analyzed their effectiveness to discriminate both groups using ROC curves. The freeto-total (FPR) and the complexed-to-total PSA (CPR) ratios significantly increased the diagnostic yield of tPSA. Moreover, based on model selection, we constructed a multivariable logistic regression model to predictive PCa that includes tPSA, fPSA, and age as predictors, which reached an optimism-corrected area under the ROC curve (AUC) of 0.86. Our model outperforms the predictive ability of tPSA (AUC 0.71), used in clinical practice. In conclusion, The FPR and CPR showed better diagnostic yield than tPSA. In addition, the PCa predictive model including age, fPSA and complexed PSA, outperformed tPSA detection efficacy. Our model may avoid unnecessary biopsies, preventing harmful side effects and reducing health expenses.In Europe, prostate cancer (PCa) is the most common solid neoplasm in men, with an incidence rate of 25% of all newly diagnosed cancers and shows the highest death rate after lung and bronchus cancer 1 . Men surviving PCa are the largest population of male cancer survivors and comprise approximately 40% of all. Significant controversy concerning PCa overdetection and overtreatment has led to a search for better markers. Overdetection is a minor problem compared to underdetection. Overtreatment is an ethical problem that could be solved when effective tools to differentiate clinically significant from indolent tumours are adopted. Approximately 1.3 million of prostate biopsies are performed every year in the USA. Most of them are negative but 43% will require a new diagnostic biopsy in 3 years 2 . This situation involves side effects and unnecessary expenses.Prostate specific antigen (PSA), also known as human glandular kallikrein 3, is a member of the kallikrein family which also includes tissue kallikrein and human glandular kallikrein 2 (hK2). PSA is secreted by prostate epithelial cells 3 and is present in serum from patients with prostate disease 4 . High levels of PSA are a useful marker for PCa detection 4 , for monitoring follow-up and progression after radical prostatectomy 5 , and for monitoring local or systemic therapy 6,7 , However, levels of PSA are also increased in some patients with benign prostatic hyperplasia, acute prostatitis 8 or prostate manipulations, leading to unnecessary negative biopsies or to over detection of non-significant cancers. Nonetheless, PSA screening has saved the lives of many ...

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Section: Discussionmentioning

confidence: 99%

A predictive model for prostate cancer incorporating PSA molecular forms and age

Oto

Fernández-Pardo

Royo

et al. 2020

Sci Rep

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“…Biopsy indications based on PSA cut-off values can be modified using clinical variables such as the initial PSA, PSA velocity, free/total PSA ratio, other serum kallikreins, prostate volume, and other predictors such as age, family history, and race alone or in combination within multivariate risk prediction tools [21]. Furthermore, urine markers (i.e., PCA3 and SelectMDx), and even genomic analyses could aid in risk stratification for biopsy indication.…”

Section: Risk Assessment Based On Multivariate Risk Prediction Toolsmentioning

confidence: 99%

“…Four risk calculators have been shown to be able to predict the presence of clinically significant prostate cancer using biopsies, with areas under the curve (AUC; discrimination measure) values ranging from 0.71 to 0.77 in head-to-head comparisons, using patient data from a multicenter European and Australian population [21]. The RPCRC showed the highest discrimination [AUC 0.77 (95% CI: 0.73, 0.80)] indicating its benefit for daily practice [21]. Adjusting the calibration to prevalence improves the value of incorporating multivariable risk prediction tools in clinical decision-making.…”

Section: Prediction Of Clinically Significant Prostate Cancermentioning

confidence: 99%

Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated?

Schoots

Padhani

2019

World J Urol

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Risk-based patient selection for systematic biopsy in prostate cancer diagnosis has been adopted in daily clinical practice, either by clinical judgment and PSA testing, or using multivariate risk prediction tools. The use of multivariable risk prediction tools can significantly reduce unnecessary systematic biopsies, without compromising the detection of clinically significant disease. Increasingly multi-parametric magnetic resonance imaging (MRI) is performed, not only in men with a persistent suspicion of prostate cancer after prior negative systematic biopsy, but also at initial screening before the first biopsy. The combination of MRI and multivariate risk prediction tools could potentially enhance prostate cancer diagnosis using multivariate MRI incorporated risk-based models to decide on the need for prostate MRI, but also using MRI results to adjusted risk-based models, and to guide MRI-directed biopsies. In this review, we discuss the diagnostic work-up for clinically significant prostate cancer, where the combination of MRI and multivariate risk prediction tools is integrated, and how together they can contribute to personalized diagnosis.Keywords Prostate cancer · Biopsy · Magnetic resonance imaging (MRI) · Risk stratification · Multivariate risk prediction · Risk calculator · NomogramThe following relevant activities related to the submitted work: Ivo G. Schoots is a full panel member of the EAU-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer, and a full panel member of the PI-RADS Steering committee. Anwar R. Padhani is Co-Chair of the PI-RADS Steering committee.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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“…Case identification combines clinical features including family history, clinical assessment (digital rectal examination (DRE)) together with laboratory tests (prostate‐specific antigen (PSA)) . Ultrasound guided prostate biopsy is currently the gold standard in PCa diagnosis, but large‐scale international studies report a wide range of positive biopsy rates, anywhere from 24% to 48% . A significant challenge in the diagnosis of PCa is that it remains one of the few cancers to be diagnosed with non‐targeted tissue sampling .…”

Section: Introductionmentioning

confidence: 99%

“…2 Ultrasound guided prostate biopsy is currently the gold standard in PCa diagnosis, but largescale international studies report a wide range of positive biopsy rates, anywhere from 24% to 48%. 3,4 A significant challenge in the diagnosis of PCa is that it remains one of the few cancers to be diagnosed with non-targeted tissue sampling. 5 The traditional blinded procedure has resulted in high false-negative rates for clinically significant disease and overdetection of low-risk incidental cancer.…”

Section: Introductionmentioning

confidence: 99%

Fifteen‐year analysis of prostate biopsies in Western Australia including recent impact of multiparametric magnetic resonance imaging

England

Li²,

Cohen

2019

ANZ Journal of Surgery

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Background The number of men undergoing prostate biopsy and subsequent cancer detection rates has changed significantly over the past 15 years. We aim to evaluate changes in the diagnostic pathway of prostate cancer between 2003 and 2018. Methods A total of 13 844 Western Australian biopsy‐naive men were assessed to determine trends in age, prostate‐specific antigen levels, number of core samples, positive cores and tumour grade (Gleason) between 2003 and 2018. Further, in 2018, the impact of pre‐biopsy multiparametric magnetic resonance imaging (mpMRI) was also assessed. Results Between 2003 and 2012, the number of men undergoing biopsy increased from 1445 to 3100. During this time, the prostate cancer detection rate (%) remained unchanged. However, in 2018, 2042 men underwent prostate biopsy (reduction of 34.1%) and the detection rate increased to 72.6%. The incidence of low‐grade cancer (Gleason score <7) increased from 28.1% in 2003 to 36.2% in 2012, but it decreased significantly to 15.1% by 2018. High‐grade cancer (Gleason score >7) declined from 21.3% in 2003 to 15.2% in 2012 but then increased to 35.7% in 2018. The use of mpMRI in 2018 improved the detection rate of high‐grade cancer. However, its specificity remains low (29.7%) and a considerable proportion of low Prostate Imaging Reporting and Data System score lesions was later diagnosed with cancer unsuitable for active surveillance. Conclusion In recent years, there has been a significant increase in the diagnosis high‐grade cancer and a reduction in cancer suitable for active surveillance. mpMRI identifies high‐grade tumours but is not a reliable alternative to prostate biopsy.

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Head-to-head comparison of prostate cancer risk calculators predicting biopsy outcome

Cited by 31 publications

References 33 publications

A predictive model for prostate cancer incorporating PSA molecular forms and age

A predictive model for prostate cancer incorporating PSA molecular forms and age

Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated?

Fifteen‐year analysis of prostate biopsies in Western Australia including recent impact of multiparametric magnetic resonance imaging

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