Expected impact of MRI-targeted biopsy interreader variability among uropathologists on ProScreen prostate cancer screening trial: a pre-trial validation study.
Agreement
Grading
Interobserver
Kappa
Pathology
Journal
World journal of urology
ISSN: 1433-8726
Titre abrégé: World J Urol
Pays: Germany
ID NLM: 8307716
Informations de publication
Date de publication:
06 Apr 2024
06 Apr 2024
Historique:
received:
08
11
2023
accepted:
21
02
2024
medline:
6
4
2024
pubmed:
6
4
2024
entrez:
6
4
2024
Statut:
epublish
Résumé
Prostate cancer (PCa) histology, particularly the Gleason score, is an independent prognostic predictor in PCa. Little is known about the inter-reader variability in grading of targeted prostate biopsy based on magnetic resonance imaging (MRI). The aim of this study was to assess inter-reader variability in Gleason grading of MRI-targeted biopsy among uropathologists and its potential impact on a population-based randomized PCa screening trial (ProScreen). From June 2014 to May 2018, 100 men with clinically suspected PCa were retrospectively selected. All men underwent prostate MRI and 86 underwent targeted prostate of the prostate. Six pathologists individually reviewed the pathology slides of the prostate biopsies. The five-tier ISUP (The International Society of Urological Pathology) grade grouping (GG) system was used. Fleiss' weighted kappa (κ) and Model-based kappa for associations were computed to estimate the combined agreement between individual pathologists. GG reporting of targeted prostate was highly consistent among the trial pathologists. Inter-reader agreement for cancer (GG1-5) vs. benign was excellent (Model-based kappa 0.90, Fleiss' kappa κ = 0.90) and for clinically significant prostate cancer (csPCa) (GG2-5 vs. GG0 vs. GG1), it was good (Model-based kappa 0.70, Fleiss' kappa κ 0.67). Inter-reader agreement in grading of MRI-targeted biopsy was good to excellent, while it was fair to moderate for MRI in the same cohort, as previously shown. Importantly, there was wide consensus by pathologists in assigning the contemporary GG on MRI-targeted biopsy suggesting high reproducibility of pathology reporting in the ProScreen trial.
Identifiants
pubmed: 38581590
doi: 10.1007/s00345-024-04898-2
pii: 10.1007/s00345-024-04898-2
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
217Informations de copyright
© 2024. The Author(s).
Références
Hugosson J, Roobol MJ, Månsson M et al (2019) A 16-years 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
Welch HG, Albertsen PC (2020) Reconsidering prostate cancer mortality—the future of PSA screening. N Engl J Med 382(16):1557–1563. https://doi.org/10.1056/NEJMms1914228
doi: 10.1056/NEJMms1914228
pubmed: 32294352
Drost FJH, Osses DF, Nieboer D et al (2019) Prostate MRI, with or without MRI-targeted biopsy, and systematic biopsy for detecting prostate cancer. Cochrane Database Syst Rev 4(4):CD012663. https://doi.org/10.1002/14651858.CD012663.pub2
doi: 10.1002/14651858.CD012663.pub2
pubmed: 31022301
Nordström T, Discacciati A, Bergman M et al (2021) Prostate cancer screening using a combination of risk-prediction, MRI, and targeted prostate biopsies (STHLM3-MRI): a prospective, population-based, randomised, open-label, non-inferiority trial. Lancet Oncol 22(9):1240–1249. https://doi.org/10.1016/S1470-2045(21)00348-X
doi: 10.1016/S1470-2045(21)00348-X
pubmed: 34391509
Kohestani K, Månsson M, Arnsrud Godtman R et al (2021) The GÖTEBORG prostate cancer screening 2 trial: a prospective, randomised, population-based prostate cancer screening trial with prostate-specific antigen testing followed by magnetic resonance imaging of the prostate. Scand J Urol 55(2):116–124. https://doi.org/10.1080/21681805.2021.1881612
doi: 10.1080/21681805.2021.1881612
pubmed: 33612068
pmcid: 8376217
Auvinen A, Rannikko A, Taari K et al (2017) A randomized trial of early detection of clinically significant prostate cancer (ProScreen): study design and rationale. Eur J Epidemiol 32(6):521–527. https://doi.org/10.1007/s10654-017-0292-5
doi: 10.1007/s10654-017-0292-5
pubmed: 28762124
van Leenders GJLH, van der Kwast TH, Grignon DJ et al (2020) The 2019 International society of urological pathology (ISUP) consensus conference on grading of prostatic carcinoma. Am J Surg Pathol 44(8):e87–e99. https://doi.org/10.1097/PAS.0000000000001497
doi: 10.1097/PAS.0000000000001497
pubmed: 32459716
pmcid: 7382533
Hietikko R, Kilpeläinen TP, Kenttämies A et al (2020) Expected impact of MRI-related interreader variability on ProScreen prostate cancer screening trial: a pre-trial validation study. Cancer Imaging 20(1):72. https://doi.org/10.1186/s40644-020-00351-w
doi: 10.1186/s40644-020-00351-w
pubmed: 33036660
pmcid: 7547469
Gleason DF (1966) Classification of prostatic carcinomas. Cancer Chemother Rep 50(3):125–128
pubmed: 5948714
Nelson KP, Edwards D (2015) Measures of agreement between many raters for ordinal classifications. Stat Med 34(23):3116–3132. https://doi.org/10.1002/sim.6546
doi: 10.1002/sim.6546
pubmed: 26095449
pmcid: 4560692
Egevad L, Delahunt B, Berney DM et al (2018) Utility of pathology imagebase for standardisation of prostate cancer grading. Histopathology 73(1):8–18. https://doi.org/10.1111/his.13471
doi: 10.1111/his.13471
pubmed: 29359484
pmcid: 7838555
Batouche AO, Czeizler E, Lehto TP et al (2024) MRI-targeted prostate biopsy introduces grade inflation and overtreatment. medRxiv. https://doi.org/10.1101/2024.01.10.24300922
doi: 10.1101/2024.01.10.24300922
pubmed: 38260466
pmcid: 10802666
Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA (2016) The 2014 International society of urological pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma. Am J Surg Pathol 40(2):244–252. https://doi.org/10.1097/PAS.0000000000000530
doi: 10.1097/PAS.0000000000000530
pubmed: 26492179
Pinsky PF, Miller E, Prorok P, Grubb R, Crawford ED, Andriole G (2019) Extended follow-up for prostate cancer incidence and mortality among participants in the prostate, lung, colorectal and ovarian randomized cancer screening trial. BJU Int 123(5):854–860. https://doi.org/10.1111/bju.14580
doi: 10.1111/bju.14580
pubmed: 30288918
Kasivisvanathan V, Rannikko AS, Borghi M et al (2018) MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med 378(19):1767–1777. https://doi.org/10.1056/NEJMoa1801993
doi: 10.1056/NEJMoa1801993
pubmed: 29552975
pmcid: 9084630
Klotz L, Chin J, Black PC et al (2021) Comparison of multiparametric magnetic resonance imaging-targeted biopsy with systematic transrectal ultrasonography biopsy for biopsy-naive men at risk for prostate cancer. JAMA Oncol 7(4):534. https://doi.org/10.1001/jamaoncol.2020.7589
doi: 10.1001/jamaoncol.2020.7589
pubmed: 33538782
pmcid: 7863017
Bryant RJ, Sjoberg DD, Vickers AJ et al (2015) Predicting high-grade cancer at ten-core prostate biopsy using four Kallikrein markers measured in blood in the ProtecT study. J Natl Cancer Inst 107(7):95. https://doi.org/10.1093/jnci/djv095
doi: 10.1093/jnci/djv095
Nam RK, Oliver TK, Vickers AJ et al (2012) Prostate-specific antigen test for prostate cancer screening: American Society of Clinical Oncology Provisional Clinical Opinion. J Oncol Pract 8(5):315–317. https://doi.org/10.1200/JOP.2012.000715
doi: 10.1200/JOP.2012.000715
pubmed: 23277770
pmcid: 3439233
Bibbins-Domingo K, Grossman DC, Curry SJ (2017) The US preventive services task force 2017 draft recommendation statement on screening for prostate cancer. JAMA 317(19):1949. https://doi.org/10.1001/jama.2017.4413
doi: 10.1001/jama.2017.4413
pubmed: 28397958
Engers R (2007) Reproducibility and reliability of tumor grading in urological neoplasms. World J Urol 25(6):595–605. https://doi.org/10.1007/s00345-007-0209-0
doi: 10.1007/s00345-007-0209-0
pubmed: 17828603
Ozkan TA, Eruyar AT, Cebeci OO, Memik O, Ozcan L, Kuskonmaz I (2016) Interobserver variability in Gleason histological grading of prostate cancer. Scand J Urol 50(6):420–424. https://doi.org/10.1080/21681805.2016.1206619
doi: 10.1080/21681805.2016.1206619
pubmed: 27416104
Griffiths DFR, Melia J, McWilliam LJ et al (2006) A study of Gleason score interpretation in different groups of UK pathologists; techniques for improving reproducibility. Histopathology 48(6):655–662. https://doi.org/10.1111/j.1365-2559.2006.02394.x
doi: 10.1111/j.1365-2559.2006.02394.x
pubmed: 16681680
Al Nemer AM, Elsharkawy T, Elshawarby M, Al-Tamimi D, Kussaibi H, Ahmed A (2017) The updated grading system of prostate carcinoma: an inter-observer agreement study among general pathologists in an academic practice. APMIS 125(11):957–961. https://doi.org/10.1111/apm.12741
doi: 10.1111/apm.12741
pubmed: 28913842
Thomsen FB, Marcussen N, Berg KD et al (2015) Repeated biopsies in patients with prostate cancer on active surveillance: clinical implications of interobserver variation in histopathological assessment. BJU Int 115(4):599–605. https://doi.org/10.1111/bju.12820
doi: 10.1111/bju.12820
pubmed: 24903618
Hugosson J, Månsson M, Wallström J et al (2022) Prostate cancer screening with PSA and MRI followed by targeted biopsy only. N Engl J Med 387(23):2126–2137. https://doi.org/10.1056/NEJMoa2209454
doi: 10.1056/NEJMoa2209454
pubmed: 36477032
pmcid: 9870590
Egevad L, Swanberg D, Delahunt B et al (2020) Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading. Virchows Arch 477(6):777–786. https://doi.org/10.1007/s00428-020-02858-w
doi: 10.1007/s00428-020-02858-w
pubmed: 32542445
pmcid: 7683442
Kweldam CF, Nieboer D, Algaba F et al (2016) Gleason grade 4 prostate adenocarcinoma patterns: an interobserver agreement study among genitourinary pathologists. Histopathology 69(3):441–449. https://doi.org/10.1111/his.12976
doi: 10.1111/his.12976
pubmed: 27028587
Zhou M, Li J, Cheng L et al (2015) Diagnosis of “poorly formed glands” Gleason pattern 4 prostatic adenocarcinoma on needle biopsy. Am J Surg Pathol 39(10):1331–1339. https://doi.org/10.1097/PAS.0000000000000457
doi: 10.1097/PAS.0000000000000457
pubmed: 26099009
Baydoun A, Jia AY, Zaorsky NG et al (2024) Artificial intelligence applications in prostate cancer. Prostate Cancer Prostatic Dis 27(1):37–45. https://doi.org/10.1038/s41391-023-00684-0
doi: 10.1038/s41391-023-00684-0
pubmed: 37296271
Ren J, Melamed J, Taneja SS et al (2023) Prostate magnetic resonance imaging-targeted biopsy global grade correlates better than highest grade with prostatectomy grade. Prostate 83(4):323–330. https://doi.org/10.1002/pros.24464
doi: 10.1002/pros.24464
pubmed: 36461793