Partin Tables in the Contemporary Era

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Article of the Month: Partin Tables in the Contemporary Era

May 3, 2017/by admin Z.9

Every Month the Editor-in-Chief selects an Article of the Month from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

If you only have time to read one article this week, it should be this one.

Prediction of pathological stage based on clinical stage, serum prostate-specific antigen, and biopsy Gleason score: Partin Tables in the contemporary era

Jeffrey J. Tosoian, Meera Chappidi, Zhaoyong Feng, Elizabeth B. Humphreys, Misop Han, Christian P. Pavlovich, Jonathan I. Epstein, Alan W. Partin and Bruce J. Trock

The James Buchanan Brady Urological Institute and Department of Urology at the Johns Hopkins University School of Medicine, Baltimore, MD, USA

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How to Cite this Article

Tosoian, J. J., Chappidi, M., Feng, Z., Humphreys, E. B., Han, M., Pavlovich, C. P., Epstein, J. I., Partin, A. W. and Trock, B. J. (2017), Prediction of pathological stage based on clinical stage, serum prostate-specific antigen, and biopsy Gleason score: Partin Tables in the contemporary era. BJU International, 119: 676–683. doi: 10.1111/bju.13573

Abstract

Objective

To update the Partin Tables for prediction of pathological stage in the contemporary setting and examine trends in patients treated with radical prostatectomy (RP) over the past three decades.

Patients and Methods

From January 2010 to October 2015, 4459 men meeting inclusion criteria underwent RP and pelvic lymphadenectomy for histologically confirmed prostate cancer at the Johns Hopkins Hospital. Preoperative clinical stage, serum prostate-specific antigen (PSA) level, and biopsy Gleason score (i.e. prognostic Grade Group) were used in a polychotomous logistic regression model to predict the probability of pathological outcomes categorised as: organ-confined (OC), extraprostatic extension (EPE), seminal vesicle involvement (SV+), or lymph node involvement (LN+). Preoperative characteristics and pathological findings in men treated with RP since 1983 were collected and clinical-pathological trends were described.

Results

The median (range) age at surgery was 60 (34–77) years and the median (range) PSA level was 4.9 (0.1–125.0) ng/mL. The observed probabilities of pathological outcomes were: OC disease in 74%, EPE in 20%, SV+ in 4%, and LN+ in 2%. The probability of EPE increased substantially when biopsy Gleason score increased from 6 (Grade Group 1, GG1) to 3 + 4 (GG2), with smaller increases for higher grades. The probability of LN+ was substantially higher for biopsy Gleason score 9–10 (GG5) as compared to lower Gleason scores. Area under the receiver operating characteristic curves for binary logistic models predicting EPE, SV+, and LN+ vs OC were 0.724, 0.856, and 0.918, respectively. The proportion of men treated with biopsy Gleason score ≤6 cancer (GG1) was 47%, representing a substantial decrease from 63% in the previous cohort and 77% in 2000–2005. The proportion of men with OC cancer has remained similar during that time, equalling 73–74% overall. The proportions of men with SV+ (4.1% from 3.4%) and LN+ (2.3% from 1.4%) increased relative to the preceding era for the first time since the Partin Tables were introduced in 1993.

Conclusions

The Partin Tables remain a straightforward and accurate approach for projecting pathological outcomes based on readily available clinical data. Acknowledging these data are derived from a tertiary care referral centre, the proportion of men with OC disease has remained stable since 2000, despite a substantial decline in the proportion of men with biopsy Gleason score 6 (GG1). This is consistent with the notion that many men with Gleason score 6 (GG1) disease were over treated in previous eras.

Editorial: Is there a role for pure clinical prediction models in prostate cancer in the contemporary era?

May 3, 2017/1 Comment/by Giorgio Gandaglia

The identification of men with localised prostate cancer at higher risk of adverse pathological outcomes after radical prostatectomy (RP) would assist physicians in preoperative patient counselling and in tailoring the most appropriate treatment strategy. In this issue of the BJUI, Tosoian et al. [1] have updated the Partin Tables in contemporary patients with localised prostate cancer. The authors should be commended for undertaking a well-performed study evaluating a large cohort of patients treated at a high-volume centre. Notably, they were able to show that the Partin Tables still represent an accurate tool for identifying men at higher risk of adverse pathological features [1]. Having said this, the first question we should ask ourselves is whether preoperative models based on clinical variables only still play a role in contemporary patients. The Partin Tables were developed in 1993 and since then they have undergone a series of updates, all of which are based on virtually the same variables included in the original analyses [1]. However, recent implementations, including biomarkers and imaging, have been introduced to better stage prostate cancer. These novel approaches are usually added to clinical variables to improve patient risk stratification. Multi-parametric MRI (mp-MRI) represents the major game changer in this setting, being now recommended for prostate cancer staging in all men with high-risk disease and in those with less favourable intermediate-risk prostate cancer [2]. In the era of modern and sophisticated approaches, are models using clinical variables only still clinically valuable? To answer this question, we can consider two major settings, namely nodal and local staging.

When assessing the risk of lymph node invasion (LNI) at diagnosis, mp-MRI and positron emission tomography/CT scan are characterised by a low sensitivity and, therefore, are not recommended for the identification of patients who should receive a lymph node dissection (LND) [2, 3]. Conversely, the updated Partin Tables depicted a remarkably high accuracy (>90%) in predicting LNI. This supports what is currently recommended by virtually all guidelines, which indicate that candidates for extended LND (eLND) should still be identified according to a combination of clinical variables only. However, although the Partin Tables might assist clinicians in identifying patients more likely to harbour LNI, the lack of the uniform adoption of an eLND template might have resulted in a substantial under-estimation of the real LNI risk [4]. Other tools specifically developed to predict LNI among men treated with eLND could better assist clinicians in identifying men who should receive an eLND [2, 5].

Similarly, when considering local staging, mp-MRI is characterised by a high specificity but a relatively low sensitivity in detecting small, microscopic foci of extracapsular extension and seminal vesicle invasion (SVI) [6]. Conversely, the updated Partin Tables depicted a predictive accuracy of >80% in predicting SVI, despite the lack of individualised data on the extent and volume of extraprostatic extension. For all these reasons, clinical risk models still represent the cornerstone for the identification of men at higher risk of adverse pathological findings. Additional data coming from sophisticated imaging modalities may further improve individualised risk predictions [6] and better assist clinicians in tailoring the most appropriate treatment approach. However, imaging and biomarkers should complement, rather than substitute, currently available clinical risk models.

In conclusion, preoperative predictive tools based on clinical parameters still play an important role in the management of patients with clinically localised prostate cancer. Any staging model including additional approaches, such as imaging and/or biomarkers, is welcomed only when it is shown to improve prostate cancer staging in terms of both accuracy and cost-effectiveness.

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How to Cite

Gandaglia, G., Fossati, N., Dell’Oglio, P., Montorsi, F. and Briganti, A. (2017), Is there a role for pure clinical prediction models in prostate cancer in the contemporary era?. BJU International, 119: 652–653. doi: 10.1111/bju.13833

Giorgio Gandaglia,*† Nicola Fossati,*†Paolo Dell’Oglio,*†Francesco Montorsi,*† and Alberto Briganti*†

*Division of Oncology/Unit of Urology, Urological Research Institute, L’ Istituto di Ricovero e Cura a Carattere Scientiﬁco (IRCCS), Ospedale San Raffaele, and †Vita-Salute San Raffaele University, Milan, Italy

References

1 TosoianJJ, Chappidi M, Feng Z et al. Prediction of pathological stage based on clinical stage, serum prostate-speciﬁc antigen, and biopsy Gleason score: Partin Tables in the contemporary era. BJU Int 2017; 119: 676– 83

2 Mottet N, Bellmunt J, Bolla M et al. EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent. Eur Urol 2017; 71: 618–29

3 Budaus L, Leyh-Bannurah SR, Salomon G et al. Initial experience of (68) Ga-PSMA PET/CT imaging in high-risk prostate cancer patients prior to radical prostatectomy. Eur Urol 2016; 69: 393–6

4 Kluth LA, Abdollah F, Xylinas E et al. Pathologic nodal staging scores in patients treated with radical prostatectomy: a postoperative decision tool. Eur Urol 2014; 66: 439–46

5 Briganti A, Larcher A, Abdollah F et al. Updated nomogram predicting lymph node invasion in patients with prostate cancer undergoing extended pelvic lymph node dissection: the essential importance of percentage of positive cores. Eur Urol 2012; 61: 480–7

6 de Rooij M, Hamoen EH, Witjes JA, Barentsz JO, Rovers MM . Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis. Eur Urol 2016; 70: 233–45

Infographic: Partin Tables in the Contemporary Era