Article Data

  • Views 314
  • Dowloads 142

Original Research

Open Access

A nomogram for predicting extraprostatic extension in prostate cancer based on extraprostatic extension grade and clinical characteristics

  • Quan Ma1,†
  • Wei Tian1,†
  • Shasha Lv2
  • Yongna Fu2
  • Hui Wang3
  • Jiansong He1
  • Yongliang Chen1,*,

1Department of Urology, Shaoxing Central Hospital, 312000 Shaoxing, Zhejiang, China

2Department of Radiology, Shaoxing Central Hospital, 312000 Shaoxing, Zhejiang, China

3Department of Pathology, Shaoxing Central Hospital, 312000 Shaoxing, Zhejiang, China

DOI: 10.22514/jomh.2024.070 Vol.20,Issue 5,May 2024 pp.48-56

Submitted: 06 October 2023 Accepted: 21 November 2023

Published: 30 May 2024

*Corresponding Author(s): Yongliang Chen E-mail: sxcentral@stu.hebmu.edu.cn

† These authors contributed equally.

Abstract

To assess the efficacy of a nomogram model derived from extraprostatic extension (EPE) grade on magnetic resonance imaging (MRI) and clinical features in forecasting pathological EPE in prostate cancer. We conducted a retrospective analysis of the clinical data from 232 prostate cancer patients. Patients were categorized into EPE and non-EPE groups based on the presence of pathological EPE. Subsequently, they were randomly allocated into a training set (162 cases) and a validation set (70 cases) at a 7:3 ratio. We gathered clinical attributes and EPE grades for all patients. Three predictive models—clinic, magnetic resonance (MR) and clinic + MR—were developed within the training set. The clinic + MR model was visualized through a nomogram. The models’ performance was assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Both univariate and multivariate logistic regression analyses identified the biopsy International Society of Urological Pathology (ISUP) category and biopsy maximum unilateral positive percentage as independent risk factors for EPE within the training set. The EPE grade exhibited consistent inter-observer agreement, evidenced by weighted Kappa values of 0.72 and 0.71 in the training and validation sets, respectively. Compared to the clinic and MR models, the clinic + MR model was the most effective in predicting pathological EPE, boasting area under the curves (AUCs) of 0.85 and 0.82 in the training and validation sets, respectively. Calibration curves from both sets demonstrated that the clinic + MR model provided accurate predictions for pathological EPE. Within the DCA, the clinic+ MR model surpassed the clinic and MR models in terms of clinical net benefit in both sets. The clinic + MR model excels in predicting the pathological EPE of prostate cancer. Its superiority over the clinic model underscores its clinical relevance and the potential for broader implementation.


Keywords

Extraprostatic extension; Prostate cancer; Magnetic resonance imaging; Nomogram; Diagnostic performance


Cite and Share

Quan Ma,Wei Tian,Shasha Lv,Yongna Fu,Hui Wang,Jiansong He,Yongliang Chen. A nomogram for predicting extraprostatic extension in prostate cancer based on extraprostatic extension grade and clinical characteristics. Journal of Men's Health. 2024. 20(5);48-56.

References

[1] Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians. 2021; 71: 209–249.

[2] Numbere N, Teramoto Y, Gurung PMS, Goto T, Yang Z, Miyamoto H. The clinical impact of pT3a lesions in patients with pT3b prostate cancer undergoing radical prostatectomy. Archives of Pathology & Laboratory Medicine. 2022; 146: 619–625.

[3] Jeong BC, Chalfin HJ, Lee SB, Feng Z, Epstein JI, Trock BJ, et al. The relationship between the extent of extraprostatic extension and survival following radical prostatectomy. European Urology. 2015; 67: 342–346.

[4] Zhu Z, Zhu Y, Xiao Y, Hu S. Indications for nerve-sparing surgery for radical prostatectomy: results from a single-center study. Frontiers in Oncology. 2022; 12: 896033.

[5] Morozov A, Barret E, Veneziano D, Grigoryan V, Salomon G, Fokin I, et al. A systematic review of nerve-sparing surgery for high-risk prostate cancer. Minerva Urology and Nephrology. 2021; 73: 283–291.

[6] Moretti TBC, Magna LA, Reis LO. Continence criteria of 193618 patients after open, laparoscopic, and robot-assisted radical prostatectomy. To be published in BJU International. 2023. [Preprint].

[7] Görgen ARH, Burttet LM, Cachoeira ET, Knijnik PG, Brum PW, De Oliveira Paludo A, et al. Association of nerve-sparing grading in robotic radical prostatectomy and trifecta outcome. World Journal of Urology. 2022; 40: 2925–2930.

[8] Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. European Urology. 2019; 76: 340–351.

[9] Schieda N, Quon JS, Lim C, El-Khodary M, Shabana W, Singh V, et al. Evaluation of the European society of urogenital radiology (ESUR) PI-RADS scoring system for assessment of extra-prostatic extension in prostatic carcinoma. European Journal of Radiology. 2015; 84: 1843–1848.

[10] Costa DN, Passoni NM, Leyendecker JR, de Leon AD, Lotan Y, Roehrborn CG, et al. Diagnostic utility of a likert scale versus qualitative descriptors and length of capsular contact for determining extraprostatic tumor extension at multiparametric prostate MRI. American Journal of Roentgenology. 2018; 210: 1066–1072.

[11] Freifeld Y, Diaz de Leon A, Xi Y, Pedrosa I, Roehrborn CG, Lotan Y, et al. Diagnostic performance of prospectively assigned likert scale scores to determine extraprostatic extension and seminal vesicle invasion with multiparametric MRI of the prostate. American Journal of Roentgenology. 2019; 212: 576–581.

[12] Fütterer JJ, Engelbrecht MR, Huisman HJ, Jager GJ, Hulsbergen-van De Kaa CA, Witjes JA, et al. Staging prostate cancer with dynamic contrast-enhanced endorectal MR imaging prior to radical prostatectomy: experienced versus less experienced readers. Radiology. 2005; 237: 541–549.

[13] Mehralivand S, Shih JH, Harmon S, Smith C, Bloom J, Czarniecki M, et al. A grading system for the assessment of risk of extraprostatic extension of prostate cancer at multiparametric MRI. Radiology. 2019; 290: 709–719.

[14] van Leenders GJLH, van der Kwast TH, Grignon DJ, Evans AJ, Kristiansen G, Kweldam CF, et al. The 2019 international society of urological pathology (ISUP) consensus conference on grading of prostatic carcinoma. American Journal of Surgical Pathology. 2020; 44: e87–e99.

[15] de Rooij M, Hamoen EHJ, Witjes JA, Barentsz JO, Rovers MM. Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis. European Urology. 2016; 70: 233–245.

[16] Park KJ, Kim M, Kim JK. Extraprostatic tumor extension: comparison of preoperative multiparametric MRI criteria and histopathologic correlation after radical prostatectomy. Radiology. 2020; 296: 87–95.

[17] Asfuroğlu U, Asfuroğlu BB, Özer H, Gönül İI, Tokgöz N, İnan MA, et al. Which one is better for predicting extraprostatic extension on multiparametric MRI: ESUR score, Likert scale, tumor contact length, or EPE grade? European Journal of Radiology. 2022; 149: 110228.

[18] Kongnyuy M, Sidana A, George AK, Muthigi A, Iyer A, Ho R, et al. Tumor contact with prostate capsule on magnetic resonance imaging: a potential biomarker for staging and prognosis. Urologic Oncology: Seminars and Original Investigations. 2017; 35: 30.e1–30.e8.

[19] Reisæter LAR, Halvorsen OJ, Beisland C, Honoré A, Gravdal K, Losnegård A, et al. Assessing extraprostatic extension with multiparametric MRI of the prostate: mehralivand extraprostatic extension grade or extraprostatic extension likert scale? Radiology: Imaging Cancer. 2020; 2: e190071.

[20] Eissa A, Elsherbiny A, Zoeir A, Sandri M, Pirola G, Puliatti S, et al. Reliability of the different versions of Partin tables in predicting extraprostatic extension of prostate cancer: a systematic review and meta-analysis. Minerva Urology and Nephrology. 2019; 71: 457–478.

[21] Zanelli E, Giannarini G, Cereser L, Zuiani C, Como G, Pizzolitto S, et al. Head‐to‐head comparison between multiparametric MRI, the Partin tables, memorial Sloan Kettering cancer center nomogram, and CAPRA score in predicting extraprostatic cancer in patients undergoing radical prostatectomy. Journal of Magnetic Resonance Imaging. 2019; 50: 1604–1613.

[22] Offermann A, Hupe MC, Sailer V, Merseburger AS, Perner S. The new ISUP 2014/who 2016 prostate cancer grade group system: first résumé 5 years after introduction and systemic review of the literature. World Journal of Urology. 2020; 38: 657–662.

[23] Wang J, Huang B, Huang L, Zhang X, He P, Chen J. Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters. Frontiers in Oncology. 2023; 13: 1229552.

[24] Kunju LP, Daignault S, Wei JT, Shah RB. Multiple prostate cancer cores with different Gleason grades submitted in the same specimen container without specific site designation: should each core be assigned an individual Gleason score? Human Pathology. 2009; 40: 558–564.

[25] Rocco B, Sighinolfi MC, Sandri M, Eissa A, Elsherbiny A, Zoeir A, et al. Is extraprostatic extension of cancer predictable? A review of predictive tools and an external validation based on a large and a single center cohort of prostate cancer patients. Urology. 2019; 129: 8–20.

[26] Xu L, Zhang G, Zhang X, Bai X, Yan W, Xiao Y, et al. External validation of the extraprostatic extension grade on MRI and its incremental value to clinical models for assessing extraprostatic cancer. Frontiers in Oncology. 2021; 11: 655093.

[27] Kim SH, Cho SH, Kim WH, Kim HJ, Park JM, Kim GC, et al. Predictors of extraprostatic extension in patients with prostate cancer. Journal of Clinical Medicine. 2023; 12: 5321.


Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,200 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Directory of Open Access Journals (DOAJ) DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

SCImago The SCImago Journal & Country Rank is a publicly available portal that includes the journals and country scientific indicators developed from the information contained in the Scopus® database (Elsevier B.V.)

Publication Forum - JUFO (Federation of Finnish Learned Societies) Publication Forum is a classification of publication channels created by the Finnish scientific community to support the quality assessment of academic research.

Scopus: CiteScore 0.9 (2023) Scopus is Elsevier's abstract and citation database launched in 2004. Scopus covers nearly 36,377 titles (22,794 active titles and 13,583 Inactive titles) from approximately 11,678 publishers, of which 34,346 are peer-reviewed journals in top-level subject fields: life sciences, social sciences, physical sciences and health sciences.

Norwegian Register for Scientific Journals, Series and Publishers Search for publication channels (journals, series and publishers) in the Norwegian Register for Scientific Journals, Series and Publishers to see if they are considered as scientific. (https://kanalregister.hkdir.no/publiseringskanaler/Forside).

Submission Turnaround Time

Conferences

Top