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3. Optimizing detection and prediction of prostate cancer after positive MRI and negative biopsies

Author

Zattoni, F., primary, Gandaglia, G., additional, C N Van Den Bergh, R., additional, Marra, G., additional, Valerio, M., additional, Olivier, J., additional, Puche Sanzi, I., additional, Rajwa, P., additional, Maggi, M., additional, Campi, R., additional, Amparore, D., additional, De Cillis, S., additional, Guo, H., additional, Veccia, A., additional, Ditonno, F., additional, Pereira, L.J., additional, Barletta, F., additional, Leni, R., additional, Rivas, J.G., additional, Remmers, S., additional, Roobol M., J., additional, Antonelli, A., additional, Dal Moro, F., additional, and Novara, G., additional

Published
2024
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9. How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis

Author

N’Dow, J., Smith, E.J., Shepherd, R., Ribal, M., Mottet, N., Moris, L., Lardas, M., Willemse, P-P., Gandaglia, G., Campi, R., Nicoletti, Rossella, Gacci, M., Briganti, A., Ratti, M.M., Alleva, E., Leardini, L., Sisca, E.S., Bangma, R., Roobol, M., Remmers, S., Tilki, D., Visakorpi, T., Talala, K., Tammela, T., van Hemelrijck, M., Bayer, K., Lejeune, S., Byrne, S., Fialho, L., De Meulder, P. Palaiologou B., Auffray, C., Hijazy, A., Power, S., Kermani, N. Zounemat, van Bochove, K., Kalafati, M., Moinat, M., Voss, E., Horgan, D., Fullwood, L., Holtorf, M., Lancet, D., Bernstein, G., Omar, I., MacLennan, S., Maclennan, S., Tripathee, S., Wirth, M., Froehner, M., Brenner, B., Borkowetz, A., Thomas, C., Horn, F., Reiche, K., Kreux, M., Josefsson, A., Tandefekt, D. Gasi, Hugosson, J., Huisman, H., Schalken, J., Hofmacher, T., Lindgren, P., Andersson, E., Fridhammar, A., Zong, J., Butler-Ransohoff, J-E., Herrera, R., Maass, M., Torremante, P., Voss, M.D., Devecseri, Z., Abbott, T., Dau, C., Papineni, K., Snijder, R., Lambrecht, M., Wolfinger, R., Rogiers, S., Servan, A., Antoni, L., Pacoe, K., Robinson, P., Jaton, B., Bakkard, D., Turunen, H., Kilkku, O., Pohjanjousi, P., Voima, O., Nevalaita, L., Reich, C., Araujo, S., Longden-Chapman, E., Burke, D., Agapow, P., Derkits, S., Licour, M., McCrea, C., Payne, S., Yong, A., Thompson, L., Mare, S. Le, Bussmann, M, Kotik, D., Siltari, Aino, Lönnerbro, Ragnar, Pang, Karl, Shiranov, Kirill, Asiimwe, Alex, Evans-Axelsson, Susan, Franks, Billy, Kiran, Amit, Murtola, Teemu J., Schalken, Jack, Steinbeisser, Carl, Bjartell, Anders, and Auvinen, Anssi

Published
2023
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10. How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis

Author

Siltari, Aino, Lönnerbro, Ragnar, Pang, Karl, Shiranov, Kirill, Asiimwe, Alex, Evans-Axelsson, Susan, Franks, Billy, Kiran, Amit, Murtola, Teemu J., Schalken, Jack, Steinbeisser, Carl, Bjartell, Anders, Auvinen, Anssi, Roobol, M., Remmers, S., Siltari, Aino, Lönnerbro, Ragnar, Pang, Karl, Shiranov, Kirill, Asiimwe, Alex, Evans-Axelsson, Susan, Franks, Billy, Kiran, Amit, Murtola, Teemu J., Schalken, Jack, Steinbeisser, Carl, Bjartell, Anders, Auvinen, Anssi, Roobol, M., and Remmers, S.

Abstract

Objectives: Genome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men. Patients and methods: Data were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I2 scores. Publication bias was evaluated using funnel plots and Egger tests. Results: The ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I2 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident. Conclusion: Typically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone.

Published
2023

11. How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis

Author

Siltari, Aino, primary, Lönnerbro, Ragnar, additional, Pang, Karl, additional, Shiranov, Kirill, additional, Asiimwe, Alex, additional, Evans-Axelsson, Susan, additional, Franks, Billy, additional, Kiran, Amit, additional, Murtola, Teemu J., additional, Schalken, Jack, additional, Steinbeisser, Carl, additional, Bjartell, Anders, additional, Auvinen, Anssi, additional, N’Dow, J., additional, Smith, E.J., additional, Shepherd, R., additional, Ribal, M., additional, Mottet, N., additional, Moris, L., additional, Lardas, M., additional, Willemse, P-P., additional, Gandaglia, G., additional, Campi, R., additional, Nicoletti, Rossella, additional, Gacci, M., additional, Briganti, A., additional, Ratti, M.M., additional, Alleva, E., additional, Leardini, L., additional, Sisca, E.S., additional, Bangma, R., additional, Roobol, M., additional, Remmers, S., additional, Tilki, D., additional, Visakorpi, T., additional, Talala, K., additional, Tammela, T., additional, van Hemelrijck, M., additional, Bayer, K., additional, Lejeune, S., additional, Byrne, S., additional, Fialho, L., additional, De Meulder, P. Palaiologou B., additional, Auffray, C., additional, Hijazy, A., additional, Power, S., additional, Kermani, N. Zounemat, additional, van Bochove, K., additional, Kalafati, M., additional, Moinat, M., additional, Voss, E., additional, Horgan, D., additional, Fullwood, L., additional, Holtorf, M., additional, Lancet, D., additional, Bernstein, G., additional, Omar, I., additional, MacLennan, S., additional, Maclennan, S., additional, Tripathee, S., additional, Wirth, M., additional, Froehner, M., additional, Brenner, B., additional, Borkowetz, A., additional, Thomas, C., additional, Horn, F., additional, Reiche, K., additional, Kreux, M., additional, Josefsson, A., additional, Tandefekt, D. Gasi, additional, Hugosson, J., additional, Huisman, H., additional, Schalken, J., additional, Hofmacher, T., additional, Lindgren, P., additional, Andersson, E., additional, Fridhammar, A., additional, Zong, J., additional, Butler-Ransohoff, J-E., additional, Herrera, R., additional, Maass, M., additional, Torremante, P., additional, Voss, M.D., additional, Devecseri, Z., additional, Abbott, T., additional, Dau, C., additional, Papineni, K., additional, Snijder, R., additional, Lambrecht, M., additional, Wolfinger, R., additional, Rogiers, S., additional, Servan, A., additional, Antoni, L., additional, Pacoe, K., additional, Robinson, P., additional, Jaton, B., additional, Bakkard, D., additional, Turunen, H., additional, Kilkku, O., additional, Pohjanjousi, P., additional, Voima, O., additional, Nevalaita, L., additional, Reich, C., additional, Araujo, S., additional, Longden-Chapman, E., additional, Burke, D., additional, Agapow, P., additional, Derkits, S., additional, Licour, M., additional, McCrea, C., additional, Payne, S., additional, Yong, A., additional, Thompson, L., additional, Mare, S. Le, additional, Bussmann, M, additional, and Kotik, D., additional

Published
2023
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12. Development of a prediction model in female pure or predominant urge urinary incontinence: a retrospective cohort study

Author

Doorn, T. van, Reuvers, S.H.M., Roobol, M.J., Remmers, S., Verbeek, J.F.M., Scheepe, J.R., Wolterbeek, J.H., Schoot, D.K.E. van der, Nieboer, D., Hoen, L.A. t, Blok, B.F., Doorn, T. van, Reuvers, S.H.M., Roobol, M.J., Remmers, S., Verbeek, J.F.M., Scheepe, J.R., Wolterbeek, J.H., Schoot, D.K.E. van der, Nieboer, D., Hoen, L.A. t, and Blok, B.F.

Abstract

Contains fulltext : 252072.pdf (Publisher’s version ) (Open Access), Background: Urinary incontinence is a prevalent form of pelvic floor dysfunction, with a non-negligible impact on a patient's quality of life. There are several treatment options, varying from conservative to invasive. The aim of this study is to predict treatment outcomes of pure or predominant urge urinary incontinence (UUI) in women to support shared decision-making and manage patient expectations. Methods: Data on patient characteristics, disease history, and investigations of 512 consecutive women treated for UUI in three hospitals in the Netherlands were retrospectively collected. The predicted outcome was the short-term subjective continence outcome, defined as patient-reported continence 3 months after treatment categorized as cure (no urinary leakage), improvement (any degree of improvement of urinary leakage), and failure (no improvement or worsening of urinary leakage). Multivariable ordinal regression with backward stepwise selection was performed to analyze association between outcome and patient's characteristics. Interactions between patient characteristics and treatment were added to estimate individual treatment benefit. Discriminative ability was assessed with the ordinal c-statistic. Results: Conservative treatment was applied in 12% of the patients, pharmacological in 62%, and invasive in 26%. Subjective continence outcome was cure, improvement, and failure in 20%, 49%, and 31%, respectively. Number of incontinence episodes per day, voiding frequency during the day, subjective quantity of UI, coexistence of stress urinary incontinence (SUI), night incontinence, and bladder capacity and the interactions between these variables were included in the model. After internal validation, the ordinal c-statistic was 0.699. Conclusions: Six variables were of value to predict pure or predominant UUI treatment outcome in women. Further development into a comprehensive set of models for the use in various pelvic floor disorders and treatments is recommended t

Published
2022

13. A Prospective Multicenter Comparison Study of Risk-adapted Ultrasound-directed and Magnetic Resonance Imaging-directed Diagnostic Pathways for Suspected Prostate Cancer in Biopsy-naive Men

Author

Wagensveld, I.M., Osses, D.F., Groenendijk, P.M., Zijta, F.M., Busstra, M.B., Rociu, E., Barentsz, J.O., Sedelaar, J.P.M., Arbeel, B., Roeleveld, T., Geenen, R., Koeter, I., Meer, S.A. van der, Cappendijk, V., Somford, R., Klaver, S., Lely, H. Van der, Wolters, T., Hellings, W., Leter, M.R., Poel, H.G. van der, Heijmink, S., Debruyne, F., Immerzeel, J., Leijte, J., Roermund, J. van, Miclea, R., Planken, E., Vis, Andre N., Jong, I. de, Tijsterman, J., Wolterbeek, D., Claessen, A., Vrijhof, E., Nederend, J., Leenders, G. van, Bangma, Chris H., Krestin, G.P., Remmers, S., Schoots, I.G., Group, M.-M.W., Wagensveld, I.M., Osses, D.F., Groenendijk, P.M., Zijta, F.M., Busstra, M.B., Rociu, E., Barentsz, J.O., Sedelaar, J.P.M., Arbeel, B., Roeleveld, T., Geenen, R., Koeter, I., Meer, S.A. van der, Cappendijk, V., Somford, R., Klaver, S., Lely, H. Van der, Wolters, T., Hellings, W., Leter, M.R., Poel, H.G. van der, Heijmink, S., Debruyne, F., Immerzeel, J., Leijte, J., Roermund, J. van, Miclea, R., Planken, E., Vis, Andre N., Jong, I. de, Tijsterman, J., Wolterbeek, D., Claessen, A., Vrijhof, E., Nederend, J., Leenders, G. van, Bangma, Chris H., Krestin, G.P., Remmers, S., Schoots, I.G., and Group, M.-M.W.

Abstract

Contains fulltext : 283332.pdf (Publisher’s version ) (Open Access), BACKGROUND: European Association of Urology guidelines recommend a risk-adjusted biopsy strategy for early detection of prostate cancer in biopsy-naive men. It remains unclear which strategy is most effective. Therefore, we evaluated two risk assessment pathways commonly used in clinical practice. OBJECTIVE: To compare the diagnostic performance of a risk-based ultrasound (US)-directed pathway (Rotterdam Prostate Cancer Risk Calculator [RPCRC] #3; US volume assessment) and a magnetic resonance imaging (MRI)-directed pathway. DESIGN, SETTING, AND PARTICIPANTS: This was a prospective multicenter study (MR-PROPER) with 1:1 allocation among 21 centers (US arm in 11 centers, MRI arm in ten). Biopsy-naive men with suspicion of prostate cancer (age >/=50 yr, prostate-specific antigen 3.0-50 ng/ml, +/- abnormal digital rectal examination) were included. INTERVENTION: Biopsy-naive men with elevated risk of prostate cancer, determined using RPCRC#3 in the US arm and Prostate Imaging Reporting and Data System scores of 3-5 in the MRI arm, underwent systematic biopsies (US arm) or targeted biopsies (MRI arm). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was the proportion of men with grade group (GG) >/=2 cancer. Secondary outcomes were the proportions of biopsies avoided and GG 1 cancers detected. Categorical (nonparametric) data were assessed using the Mann-Whitney U test and chi(2) tests. RESULTS AND LIMITATIONS: A total of 1965 men were included in the intention-to-treat population (US arm n = 950, MRI arm n = 1015). The US and MRI pathways detected GG >/=2 cancers equally well (235/950, 25% vs 239/1015, 24%; difference 1.2%, 95% confidence interval [CI] -2.6% to 5.0%; p = 0.5). The US pathway detected more GG 1 cancers than the MRI pathway (121/950, 13% vs 84/1015, 8.3%; difference 4.5%, 95% CI 1.8-7.2%; p < 0.01). The US pathway avoided fewer biopsies than the MRI pathway (403/950, 42% vs 559/1015, 55%; difference -13%, 95% CI -17% to -8.3%; p < 0.01

Published
2022

23. Clinical characterization and outcomes of prostate cancer patients undergoing immediate vs. conservative management: A PIONEER study

Author

Gandaglia, G., primary, Omar, M.I., additional, Maresca, G., additional, Golozar, A., additional, Remmers, S., additional, Roobol, M.J., additional, Steinbeisser, C., additional, Hulsen, T., additional, Van Bochove, K., additional, Katharina, B., additional, Van Hemelrijck, M., additional, Willemse, P-P.M., additional, Oja, M., additional, Tamm, S., additional, Reisberg, S., additional, Gomez Rivas, J., additional, Van Den Bergh, R., additional, Kinnaird, A., additional, Asiimwe, A., additional, Bjartell, A., additional, Smith, E.J., additional, and N'Dow, J., additional

Published
2022
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25. Identification of pathologic factors associated with intraoperative positive surgical margins at NeuroSAFE for clinical decision-making on nerve-sparing surgery

Author

van der Slot, M.A., primary, Den Bakker, A., additional, Busstra, M., additional, Gan, M., additional, Klaver, O.S., additional, Rietbergen, J.B.W., additional, Remmers, S., additional, Kweldam, C., additional, Bangma, C.H., additional, Roobol, M.J., additional, and Van Leenders, G.J.L.H., additional

Published
2022
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29. Continence after introducing NeuroSAFE in radical prostatectomy

Author

van der Slot, M.A., primary, Remmers, S., additional, Van Leenders, G.J.L.H, additional, Muijlaert, D., additional, Busstra, M.B., additional, Gan, M., additional, Klaver, O.S., additional, Rietbergen, J.B.W., additional, Den Bakker, M.A., additional, Kweldam, C.F., additional, Bangma, C.H., additional, Roobol, M.J., additional, and Venderbos, L.D.F, additional

Published
2022
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34. A Prospective Multicenter Comparison Study of Risk-adapted Ultrasound-directed and Magnetic Resonance Imaging-directed Diagnostic Pathways for Suspected Prostate Cancer in Biopsy-naïve Men

Author

Wagensveld, I.M., Osses, D.F., Groenendijk, P.M., Zijta, F.M., Busstra, M.B., Rociu, E., Barentsz, J.O., Sedelaar, J.P.M., Arbeel, B., Roeleveld, T., Geenen, R., Koeter, I., Meer, S.A. van der, Cappendijk, V., Somford, R., Klaver, S., Lely, H. Van der, Wolters, T., Hellings, W., Leter, M.R., Poel, H.G. van der, Heijmink, S., Debruyne, F., Immerzeel, J., Leijte, J., Roermund, J. van, Miclea, R., Planken, E., Vis, Andre N., Jong, I. de, Tijsterman, J., Wolterbeek, D., Claessen, A., Vrijhof, E., Nederend, J., Leenders, G. van, Bangma, Chris H., Krestin, G.P., Remmers, S., Schoots, I.G., Group, M.-M.W., Urology, CCA - Imaging and biomarkers, MUMC+: MA Urologie (9), MUMC+: MA AIOS Urologie (9), MUMC+: DA BV Medisch Specialisten Radiologie (9), RS: FHML non-thematic output, and Radiology & Nuclear Medicine

Subjects
Image-Guided Biopsy, Male, SDG 3 - Good Health and Well-being, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Urology, Urological cancers Radboud Institute for Molecular Life Sciences [Radboudumc 15], Prostate, Humans, Prostatic Neoplasms, Prospective Studies, Magnetic Resonance Imaging
Abstract

Contains fulltext : 283332.pdf (Publisher’s version ) (Open Access) BACKGROUND: European Association of Urology guidelines recommend a risk-adjusted biopsy strategy for early detection of prostate cancer in biopsy-naive men. It remains unclear which strategy is most effective. Therefore, we evaluated two risk assessment pathways commonly used in clinical practice. OBJECTIVE: To compare the diagnostic performance of a risk-based ultrasound (US)-directed pathway (Rotterdam Prostate Cancer Risk Calculator [RPCRC] #3; US volume assessment) and a magnetic resonance imaging (MRI)-directed pathway. DESIGN, SETTING, AND PARTICIPANTS: This was a prospective multicenter study (MR-PROPER) with 1:1 allocation among 21 centers (US arm in 11 centers, MRI arm in ten). Biopsy-naive men with suspicion of prostate cancer (age >/=50 yr, prostate-specific antigen 3.0-50 ng/ml, +/- abnormal digital rectal examination) were included. INTERVENTION: Biopsy-naive men with elevated risk of prostate cancer, determined using RPCRC#3 in the US arm and Prostate Imaging Reporting and Data System scores of 3-5 in the MRI arm, underwent systematic biopsies (US arm) or targeted biopsies (MRI arm). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was the proportion of men with grade group (GG) >/=2 cancer. Secondary outcomes were the proportions of biopsies avoided and GG 1 cancers detected. Categorical (nonparametric) data were assessed using the Mann-Whitney U test and chi(2) tests. RESULTS AND LIMITATIONS: A total of 1965 men were included in the intention-to-treat population (US arm n = 950, MRI arm n = 1015). The US and MRI pathways detected GG >/=2 cancers equally well (235/950, 25% vs 239/1015, 24%; difference 1.2%, 95% confidence interval [CI] -2.6% to 5.0%; p = 0.5). The US pathway detected more GG 1 cancers than the MRI pathway (121/950, 13% vs 84/1015, 8.3%; difference 4.5%, 95% CI 1.8-7.2%; p < 0.01). The US pathway avoided fewer biopsies than the MRI pathway (403/950, 42% vs 559/1015, 55%; difference -13%, 95% CI -17% to -8.3%; p < 0.01). Among men with elevated risk, more GG >/=2 cancers were detected in the MRI group than in the US group (52% vs 43%; difference 9.2%, 95% CI 3.0-15%; p < 0.01). CONCLUSIONS: Risk-adapted US-directed and MRI-directed pathways detected GG >/=2 cancers equally well. The risk-adapted US-directed pathway performs well for prostate cancer diagnosis if prostate MRI capacity and expertise are not available. If prostate MRI availability is sufficient, risk assessment should preferably be performed using MRI, as this avoids more biopsies and detects fewer cases of GG 1 cancer. PATIENT SUMMARY: Among men with suspected prostate cancer, relevant cancers were equally well detected by risk-based pathways using either ultrasound or magnetic resonance imaging (MRI) to guide biopsy of the prostate. If prostate MRI availability is sufficient, risk assessment should be performed with MRI to reduce unnecessary biopsies and detect fewer irrelevant cancers.

Published
2021
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36. Development and validation of patient-level prediction models for symptoms, hospitalization and treatment initiation amongst prostate cancer patients on watchful waiting

Author

Zounemat-Kermani N, Hui Lly, Cornford P, Schimmelpfennig C, Remmers S, Kreuz M, Willemsen P, and Mottet N

Subjects
medicine.medical_specialty, Prostate cancer, Text mining, business.industry, medicine.medical_treatment, medicine, Intensive care medicine, business, medicine.disease, Predictive modelling, Watchful waiting, 3. Good health
Abstract

The objective of this study is to develop and validate patient-level prediction models for patients on watchful waiting (WW) estimating the risk of developing symptomatic progression, hospitalization, ER visit, initiation of curative or palliative treatment, and survival. Estimation for all clinical models will be done based on 1) age and clinical measurements (e.g., PSA) 6 months before diagnosis, 2) age, clinical measurements 6 months before diagnosis, and clinical conditions one year before diagnosis. Finally, a clinically usable model will be developed based on expert clinical input. All prediction models will be implemented using Lasso logistic regression for the time at risk analyses.

Published
2021
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38. Cribriform and intraductal carcinoma do not improve the nomogram-based selection of prostate cancer patients for pelvic lymph node dissection

Author

De Barros, H.A., primary, Remmers, S., additional, Luiting, H.B., additional, Van Leenders, G.J.L.H., additional, Roobol, M.J., additional, Bekers, E.M., additional, Amin, A., additional, Haynes, A.M., additional, Delprado, W., additional, Stricker, P.D., additional, Van Der Poel, H.G., additional, Van Der Kwast, T.H., additional, and Van Leeuwen, P.J., additional

Published
2021
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40. Introducing PIONEER: a project to harness big data in prostate cancer research

Author

Omar M. I., Roobol M. J., Ribal M. J., Abbott T., Agapow P. -M., Araujo S., Asiimwe A., Auffray C., Balaur I., Beyer K., Bernini C., Bjartell A., Briganti A., Butler-Ransohoff J. -E., Campi R., Cavelaars M., De Meulder B., Devecseri Z., Voss M. D., Dimitropoulos K., Evans-Axelsson S., Franks B., Fullwood L., Horgan D., Smith E. J., Kiran A., Kivinummi K., Lambrecht M., Lancet D., Lindgren P., MacLennan S., Nogueira M. M., Moen F., Moinat M., Papineni K., Reich C., Reiche K., Rogiers S., Sartini C., van Bochove K., van Diggelen F., Van Hemelrijck M., Van Poppel H., Zong J., N'Dow J., Andersson E., Arala H., Auvinen A., Bangma C., Burke D., Cardone A., Casariego J., Cuperus G., Dabestani S., Esperto F., Fossati N., Fridhammar A., Gandaglia G., Tandefelt D. G., Horn F., Huber J., Hugosson J., Huisman H., Josefsson A., Kilkku O., Kreuz M., Lardas M., Lawson J., Lefresne F., Lejeune S., Longden-Chapman E., McVie G., Moris L., Mottet N., Murtola T., Nicholls C., Pang K. H., Pascoe K., Picozzi M., Plass K., Pohjanjousi P., Reaney M., Remmers S., Robinson P., Schalken J., Schravendeel M., Seisen T., Servan A., Shiranov K., Snijder R., Steinbeisser C., Taibi N., Talala K., Tilki D., Van den Broeck T., Vassilev Z., Voima O., Vradi E., Waldeck R., Weistra W., Willemse P. -P., Wirth M., Wolfinger R., Kermani N. Z., Omar, M. I., Roobol, M. J., Ribal, M. J., Abbott, T., Agapow, P. -M., Araujo, S., Asiimwe, A., Auffray, C., Balaur, I., Beyer, K., Bernini, C., Bjartell, A., Briganti, A., Butler-Ransohoff, J. -E., Campi, R., Cavelaars, M., De Meulder, B., Devecseri, Z., Voss, M. D., Dimitropoulos, K., Evans-Axelsson, S., Franks, B., Fullwood, L., Horgan, D., Smith, E. J., Kiran, A., Kivinummi, K., Lambrecht, M., Lancet, D., Lindgren, P., Maclennan, S., Nogueira, M. M., Moen, F., Moinat, M., Papineni, K., Reich, C., Reiche, K., Rogiers, S., Sartini, C., van Bochove, K., van Diggelen, F., Van Hemelrijck, M., Van Poppel, H., Zong, J., N'Dow, J., Andersson, E., Arala, H., Auvinen, A., Bangma, C., Burke, D., Cardone, A., Casariego, J., Cuperus, G., Dabestani, S., Esperto, F., Fossati, N., Fridhammar, A., Gandaglia, G., Tandefelt, D. G., Horn, F., Huber, J., Hugosson, J., Huisman, H., Josefsson, A., Kilkku, O., Kreuz, M., Lardas, M., Lawson, J., Lefresne, F., Lejeune, S., Longden-Chapman, E., Mcvie, G., Moris, L., Mottet, N., Murtola, T., Nicholls, C., Pang, K. H., Pascoe, K., Picozzi, M., Plass, K., Pohjanjousi, P., Reaney, M., Remmers, S., Robinson, P., Schalken, J., Schravendeel, M., Seisen, T., Servan, A., Shiranov, K., Snijder, R., Steinbeisser, C., Taibi, N., Talala, K., Tilki, D., Van den Broeck, T., Vassilev, Z., Voima, O., Vradi, E., Waldeck, R., Weistra, W., Willemse, P. -P., Wirth, M., Wolfinger, R., Kermani, N. Z., Publica, and Urology

Subjects
0301 basic medicine, Prioritization, Knowledge management, Urology, media_common.quotation_subject, education, Big data, Disease, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Multidisciplinary approach, Urological cancers Radboud Institute for Molecular Life Sciences [Radboudumc 15], Medicine, Quality (business), media_common, business.industry, Patient-centered outcomes, medicine.disease, 3. Good health, Patient management, 030104 developmental biology, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], 030220 oncology & carcinogenesis, business
Abstract

Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. In this Perspectives article, the authors introduce the PIONEER project and describe its aims and plans for ultimately improving prostate cancer care through the use of big data.

Published
2020

41. Author Correction: Introducing PIONEER: a project to harness big data in prostate cancer research (Nature Reviews Urology, (2020), 17, 6, (351-362), 10.1038/s41585-020-0324-x)

Author

Omar M. I., Roobol M. J., Ribal M. J., Abbott T., Agapow P. -M., Araujo S., Asiimwe A., Auffray C., Balaur I., Beyer K., Bernini C., Bjartell A., Briganti A., Butler-Ransohoff J. -E., Campi R., Cavelaars M., De Meulder B., Devecseri Z., Voss M. D., Dimitropoulos K., Evans-Axelsson S., Franks B., Fullwood L., Horgan D., Smith E. J., Kiran A., Kivinummi K., Lambrecht M., Lancet D., Lindgren P., MacLennan S., Nogueira M. M., Moen F., Moinat M., Papineni K., Reich C., Reiche K., Rogiers S., Sartini C., van Bochove K., van Diggelen F., Van Hemelrijck M., Van Poppel H., Zong J., N'Dow J., Andersson E., Arala H., Auvinen A., Bangma C., Burke D., Cardone A., Casariego J., Cuperus G., Dabestani S., Esperto F., Fossati N., Fridhammar A., Gandaglia G., Tandefelt D. G., Horn F., Huber J., Hugosson J., Huisman H., Josefsson A., Kilkku O., Kreuz M., Lardas M., Lawson J., Lefresne F., Lejeune S., Longden-Chapman E., McVie G., Moris L., Mottet N., Murtola T., Nicholls C., Pang K. H., Pascoe K., Picozzi M., Plass K., Pohjanjousi P., Reaney M., Remmers S., Robinson P., Schalken J., Schravendeel M., Seisen T., Servan A., Shiranov K., Snijder R., Steinbeisser C., Taibi N., Talala K., Tilki D., Van den Broeck T., Vassilev Z., Voima O., Vradi E., Waldeck R., Weistra W., Willemse P. -P., Wirth M., Wolfinger R., Kermani N. Z., Omar, M. I., Roobol, M. J., Ribal, M. J., Abbott, T., Agapow, P. -M., Araujo, S., Asiimwe, A., Auffray, C., Balaur, I., Beyer, K., Bernini, C., Bjartell, A., Briganti, A., Butler-Ransohoff, J. -E., Campi, R., Cavelaars, M., De Meulder, B., Devecseri, Z., Voss, M. D., Dimitropoulos, K., Evans-Axelsson, S., Franks, B., Fullwood, L., Horgan, D., Smith, E. J., Kiran, A., Kivinummi, K., Lambrecht, M., Lancet, D., Lindgren, P., Maclennan, S., Nogueira, M. M., Moen, F., Moinat, M., Papineni, K., Reich, C., Reiche, K., Rogiers, S., Sartini, C., van Bochove, K., van Diggelen, F., Van Hemelrijck, M., Van Poppel, H., Zong, J., N'Dow, J., Andersson, E., Arala, H., Auvinen, A., Bangma, C., Burke, D., Cardone, A., Casariego, J., Cuperus, G., Dabestani, S., Esperto, F., Fossati, N., Fridhammar, A., Gandaglia, G., Tandefelt, D. G., Horn, F., Huber, J., Hugosson, J., Huisman, H., Josefsson, A., Kilkku, O., Kreuz, M., Lardas, M., Lawson, J., Lefresne, F., Lejeune, S., Longden-Chapman, E., Mcvie, G., Moris, L., Mottet, N., Murtola, T., Nicholls, C., Pang, K. H., Pascoe, K., Picozzi, M., Plass, K., Pohjanjousi, P., Reaney, M., Remmers, S., Robinson, P., Schalken, J., Schravendeel, M., Seisen, T., Servan, A., Shiranov, K., Snijder, R., Steinbeisser, C., Taibi, N., Talala, K., Tilki, D., Van den Broeck, T., Vassilev, Z., Voima, O., Vradi, E., Waldeck, R., Weistra, W., Willemse, P. -P., Wirth, M., Wolfinger, R., and Kermani, N. Z.

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2020

42. Secondary treatment for men with localized prostate cancer: A pooled analysis of PRIAS and ERSPC-Rotterdam datasets within the PIONEER data platform

Author

Beyer, K., primary, Remmers, S., additional, Straten, V., additional, Maclennan, S., additional, Maclennan, S.J., additional, Willemse, P.P., additional, Herrera, R., additional, Omar, M.I., additional, Russell, B., additional, Huber, J., additional, Kreuz, M., additional, Abbott, T., additional, Asiimwe, A., additional, Briganti, A., additional, Van Hemelrijck, M., additional, and Roobol, M.J., additional

Published
2021
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43. Prostate cancer specific mortality in the ERSPC trial: What is the role of screening result and adherence

Author

Wetterauer, C., primary, Remmers, S., additional, Hugosson, J., additional, Tammela, T., additional, Zappa, M., additional, Nelen, V., additional, Lujan, M., additional, Denis, L.J., additional, Paez, A., additional, Puliti, D., additional, Arnaud, V., additional, Rebillard, X., additional, Ansrud Godtman, R., additional, Bangma, C., additional, Schröder, F.H., additional, Auvinen, A., additional, Manka, L., additional, Prause, L.W., additional, Seifert, H.H., additional, Wyler, S.F., additional, Roobol, M.J., additional, and Kwiatkowski, M., additional

Published
2021
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46. Outcomes after introducing intraoperative NeuroSAFE technique in robot-assisted radical prostatectomy

Author

van der Slot, M.A., primary, Den Bakker, M.A., additional, Kweldam, C.F., additional, Remmers, S., additional, Tan, T., additional, Klaver, O.S., additional, Kliffen, M., additional, Busstra, M.B., additional, Rietbergen, J.B.W., additional, Gan, M., additional, Hamoen, K.E., additional, Budel, L.M., additional, Goemaere, N.T., additional, Bangma, C.H., additional, Helleman, J., additional, Roobol, M.J., additional, and Van Leenders, G.J.L.H., additional

Published
2021
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50. Reducing Biopsies and Magnetic Resonance Imaging Scans During the Diagnostic Pathway of Prostate Cancer: Applying the Rotterdam Prostate Cancer Risk Calculator to the PRECISION Trial Data

Author

Remmers, S., Kasivisvanathan, V, Verbeek, J.F.M., Moore, C.M., Roobol, M.J., Remmers, S., Kasivisvanathan, V, Verbeek, J.F.M., Moore, C.M., and Roobol, M.J.

Abstract

Item does not contain fulltext, BACKGROUND: Risk stratification in the diagnostic pathway of prostate cancer (PCa) can be used to reduce biopsies and magnetic resonance imaging (MRI) scans, while maintaining the detection of clinically significant PCa (csPCa). The use of highly discriminating and well-calibrated models will generate better clinical outcomes if context-dependent thresholds are used. OBJECTIVE: To retrospectively assess the effect of the upfront use of the Rotterdam Prostate Cancer Risk Calculator (RPCRC) developed in a screening cohort and the RPCRC-MRI developed in a clinical cohort while exploring the need to adapt thresholds in biopsy-naive men in the PRECISION (Prostate Evaluation for Clinically Important Disease: Sampling Using Image Guidance or Not?) trial. DESIGN SETTING AND PARTICIPANTS: In the transrectal ultrasonography arm, we evaluated 188 men; in the MRI arm, we evaluated 206 (for the reduction of MRI scans) and 137 (for the reduction of targeted biopsies) men. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Performance was assessed by discrimination, calibration, and clinical utility. RESULTS AND LIMITATIONS: The performance of the RPCRC was good. However, intercept adjustment was warranted. Net benefit was observed from a recalibrated probability of 32% for any PCa and 10% for csPCa. After recalibration and applying a threshold of 20% for any PCa or 10% for csPCa, 28% of all biopsies could have been reduced, missing five cases of csPCa. The uncalibrated RPCRC could reduce 35% of all MRI scans, with a threshold of 20% for any PCa or 4% for csPCa. In the MRI arm, performance was good without stressing recalibration. Net benefit was observed from a probability of 22% for any PCa and 7% for csPCa. With a threshold of 20% for any PCa or 4% for csPCa, 9% of all targeted biopsies could be reduced, missing one grade group 2 PCa. CONCLUSIONS: The performance of the RPCRC and RPCRC-MRI in men included in the PRECISION trial was good, but recalibration and adaptation of the risk

Published
2021

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