Incorporating PHI in decision making: external validation of the Rotterdam risk calculators for detection of prostate cancer.
Diagnosis
Prostate cancer
Prostate health index (PHI)
Prostate specific antigen (PSA)
Risk calculators
Rotterdam prostate cancer risk calculators (RPCRC)
Journal
World journal of urology
ISSN: 1433-8726
Titre abrégé: World J Urol
Pays: Germany
ID NLM: 8307716
Informations de publication
Date de publication:
13 Mar 2024
13 Mar 2024
Historique:
received:
25
09
2023
accepted:
16
01
2024
medline:
13
3
2024
pubmed:
13
3
2024
entrez:
13
3
2024
Statut:
epublish
Résumé
External validation of existing risk calculators (RC) to assess the individualized risk of detecting prostate cancer (PCa) in prostate biopsies is needed to determine their clinical usefulness. The objective was to externally validate the Rotterdam Prostate Cancer RCs 3 and 4 (RPCRC-3/4) and that incorporating PHI (RPCRC-PHI) in a contemporary Spanish cohort. Multicenter prospective study that included patients suspicious of harboring PCa. Men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate the performance of the prediction models: discrimination (receiver operating characteristic (ROC) curves), calibration and net benefit [decision curve analysis (DCA)] were calculated. These analyses were carried out for detection of any PCa and clinically significant (cs)PCa, defined as ISUP grade ≥ 2. Among the 559 men included, 337 (60.28%) and 194 (34.7%) were diagnosed of PCa and csPCa, respectively. RPCRC-PHI had the best discrimination ability for detection of PCa and csPCa with AUCs of 0.85 (95%CI 0.82-0.88) and 0.82 (95%CI 0.78-0.85), respectively. Calibration plots showed that RPCRC-3/4 underestimates the risk of detecting PCa showing the need for recalibration. In DCA, RPCRC-PHI shows the highest net benefit compared to biopsy all men. The RPCRC-PHI performed properly in a contemporary clinical setting, especially for prediction of csPCa.
Identifiants
pubmed: 38478041
doi: 10.1007/s00345-024-04833-5
pii: 10.1007/s00345-024-04833-5
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
141Subventions
Organisme : Berrikuntza + Ikerketa + Osasuna Eusko Fundazioa
ID : 2016111083
Investigateurs
Jose Gregorio Pereira Arias
(JG)
Pablo Arredondo Calvo
(P)
Luis Felipe Urdaneta Salegui
(LF)
Victor Escobal Tamayo
(V)
Juan Pablo Sanz Jaka
(JP)
Adrian Recio Ayesa
(A)
Javier Mar Medina
(J)
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Références
Sung H, Ferlay J, Siegel RL et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3):209–249. https://doi.org/10.3322/caac.21660
doi: 10.3322/caac.21660
pubmed: 33538338
Hugosson J, Roobol MJ, Månsson M et al (2019) A 16-yr follow-up of the european randomized study of screening for prostate cancer. Eur Urol 76(1):43–51. https://doi.org/10.1016/j.eururo.2019.02.009
doi: 10.1016/j.eururo.2019.02.009
pubmed: 30824296
pmcid: 7513694
Schröder FH, Hugosson J, Carlsson S et al (2012) Screening for prostate cancer decreases the risk of developing metastatic disease: findings from the European randomized study of screening for prostate cancer (ERSPC). Eur Urol 62(5):745–752. https://doi.org/10.1016/j.eururo.2012.05.068
doi: 10.1016/j.eururo.2012.05.068
pubmed: 22704366
Loeb S, Bjurlin MA, Nicholson J et al (2014) Overdiagnosis and overtreatment of prostate cancer. Eur Urol 65(6):1046–1055. https://doi.org/10.1016/j.eururo.2013.12.062
doi: 10.1016/j.eururo.2013.12.062
pubmed: 24439788
pmcid: 4113338
Arnsrud Godtman R, Holmberg E, Lilja H, Stranne J, Hugosson J (2015) Opportunistic testing versus organized prostate-specific antigen screening: outcome after 18 years in the Göteborg randomized population-based prostate cancer screening trial. Eur Urol 68(3):354–360. https://doi.org/10.1016/j.eururo.2014.12.006
doi: 10.1016/j.eururo.2014.12.006
pubmed: 25556937
Roobol MJ (2018) Screening for prostate cancer: are organized screening programs necessary? Transl Androl Urol 7(1):4–11. https://doi.org/10.21037/tau.2017.12.10
doi: 10.21037/tau.2017.12.10
pubmed: 29594014
pmcid: 5861275
Roobol MJ, van Vugt HA, Loeb S et al (2012) Prediction of prostate cancer risk: the role of prostate volume and digital rectal examination in the ERSPC risk calculators. Eur Urol 61(3):577–583. https://doi.org/10.1016/j.eururo.2011.11.012
doi: 10.1016/j.eururo.2011.11.012
pubmed: 22104592
Roobol MJ, Vedder MM, Nieboer D et al (2015) Comparison of two prostate cancer risk calculators that include the prostate health index. Eur Urol Focus 1(2):185–190. https://doi.org/10.1016/j.euf.2015.06.004
doi: 10.1016/j.euf.2015.06.004
pubmed: 28723432
Semjonow A, Köpke T, Eltze E, Pepping-Schefers B, Bürgel H, Darte C (2010) Pre-analytical in-vitro stability of [-2]proPSA in blood and serum. Clin Biochem 43(10–11):926–928. https://doi.org/10.1016/j.clinbiochem.2010.04.062
doi: 10.1016/j.clinbiochem.2010.04.062
pubmed: 20450900
Rius Bilbao L, Valladares Gomez C, Aguirre Larracoechea U et al (2023) Do PHI and PHI density improve detection of clinically significant prostate cancer only in the PSA gray zone? Clin Chim Acta 542:117270. https://doi.org/10.1016/j.cca.2023.117270
doi: 10.1016/j.cca.2023.117270
pubmed: 36893880
Schröder F, Kattan MW (2008) The comparability of models for predicting the risk of a positive prostate biopsy with prostate-specific antigen alone: a systematic review. Eur Urol 54(2):274–290. https://doi.org/10.1016/j.eururo.2008.05.022
doi: 10.1016/j.eururo.2008.05.022
pubmed: 18511177
Gayet M, Mannaerts CK, Nieboer D et al (2018) Prediction of prostate cancer: external validation of the erspc risk calculator in a contemporary dutch clinical cohort. Eur Urol Focus 4(2):228–234. https://doi.org/10.1016/j.euf.2016.07.007
doi: 10.1016/j.euf.2016.07.007
pubmed: 28753781
Pereira-Azevedo N, Verbeek JFM, Nieboer D, Bangma CH, Roobol MJ (2018) Head-to-head comparison of prostate cancer risk calculators predicting biopsy outcome. Transl Androl Urol 7(1):18–26. https://doi.org/10.21037/tau.2017.12.21
doi: 10.21037/tau.2017.12.21
pubmed: 29594016
pmcid: 5861294
Van Calster B, McLernon DJ, van Smeden M, Wynants L, Steyerberg EW (2019) Topic Group ‘evaluating diagnostic tests and prediction models of the STRATOS initiative calibration: the achilles heel of predictive analytics. BMC Med 17(1):230. https://doi.org/10.1186/s12916-019-1466-7
doi: 10.1186/s12916-019-1466-7
pubmed: 31842878
pmcid: 6912996
Hagens MJ, Stelwagen PJ, Veerman H et al (2023) External validation of the rotterdam prostate cancer risk calculator within a high-risk Dutch clinical cohort. World J Urol 41(1):13–18. https://doi.org/10.1007/s00345-022-04185-y
doi: 10.1007/s00345-022-04185-y
pubmed: 36245015
Agnello L, Vidali M, Giglio RV et al (2022) Prostate health index (PHI) as a reliable biomarker for prostate cancer: a systematic review and meta-analysis. Clin Chem Lab Med. 60(8):1261–1277. https://doi.org/10.1515/cclm-2022-0354
doi: 10.1515/cclm-2022-0354
pubmed: 35567430
Foley RW, Maweni RM, Gorman L et al (2016) European randomised study of screening for prostate cancer (ERSPC) risk calculators significantly outperform the prostate cancer prevention trial (PCPT) 2.0 in the prediction of prostate cancer: a multi-institutional study. BJU Int 118(5):706–713. https://doi.org/10.1111/bju.13437
doi: 10.1111/bju.13437
pubmed: 26833820
Loeb S, Shin SS, Broyles DL et al (2017) Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer. BJU Int 120(1):61–68. https://doi.org/10.1111/bju.13676
doi: 10.1111/bju.13676
pubmed: 27743489
Mottet N, van den Bergh RCN, Briers E et al (2021) Guidelines on prostate cancer-2020 update part 1: screening diagnosis, and local treatment with curative intent. Eur Urol. 79(2):243–262. https://doi.org/10.1016/j.eururo.2020.09.042
doi: 10.1016/j.eururo.2020.09.042
pubmed: 33172724
Schoots IG, Padhani AR (2020) Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated? World J Urol 38(3):531–545. https://doi.org/10.1007/s00345-019-02899-0
doi: 10.1007/s00345-019-02899-0
pubmed: 31399825
Rouvière O, Souchon R, Melodelima C (2018) Pitfalls in interpreting positive and negative predictive values: application to prostate multiparametric magnetic resonance imaging. Diagn Interv Imaging 99(9):515–518. https://doi.org/10.1016/j.diii.2018.07.008
doi: 10.1016/j.diii.2018.07.008
pubmed: 30177449
Remmers S, Kasivisvanathan V, Verbeek JFM, Moore CM, Roobol MJ, ERSPC Rotterdam Study Group PRECISION Investigators Group (2021) 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. Eur Urol Open Sci. 36(1):8. https://doi.org/10.1016/j.euros.2021.11.002
doi: 10.1016/j.euros.2021.11.002
Davik P, Remmers S, Elschot M, Roobol MJ, Bathen TF, Bertilsson H (2022) Reducing prostate biopsies and magnetic resonance imaging with prostate cancer risk stratification. BJUI Compass 3(5):344–353. https://doi.org/10.1002/bco2.146
doi: 10.1002/bco2.146
pubmed: 35950035
pmcid: 9349589
Kim L, Boxall N, George A et al (2020) Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study. BMC Med 18(1):95. https://doi.org/10.1186/s12916-020-01548-3
doi: 10.1186/s12916-020-01548-3
pubmed: 32299423
pmcid: 7164355
Moldovan PC, Van den Broeck T, Sylvester R et al (2017) What Is the negative predictive value of multiparametric magnetic resonance imaging in excluding prostate cancer at biopsy? A systematic review and meta-analysis from the European association of urology prostate cancer guidelines panel. Eur Urol 72(2):250–266. https://doi.org/10.1016/j.eururo.2017.02.026
doi: 10.1016/j.eururo.2017.02.026
pubmed: 28336078
Mo LC, Zhang XJ, Zheng HH et al (2022) Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI. Front Oncol 12:1068893. https://doi.org/10.3389/fonc.2022.1068893
doi: 10.3389/fonc.2022.1068893
pubmed: 36523980
pmcid: 9745809
Zhou Y, Fu Q, Shao Z et al (2023) Nomograms combining PHI and PI-RADS in detecting prostate cancer: a multicenter prospective study. J Clin Med. 12(1):339. https://doi.org/10.3390/jcm12010339
doi: 10.3390/jcm12010339
pubmed: 36615138
pmcid: 9821430
Van Poppel H, Hogenhout R, Albers P, van den Bergh RCN, Barentsz JO, Roobol MJ (2021) A European model for an organised risk-stratified early detection programme for prostate cancer. Eur Urol Oncol 4(5):731–739. https://doi.org/10.1016/j.euo.2021.06.006
doi: 10.1016/j.euo.2021.06.006
pubmed: 34364829