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| ORIGINAL ARTICLE |
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| Ahead of print publication |
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Prostate Health Index (phi) and its derivatives predict Gleason score upgrading after radical prostatectomy among patients with low-risk prostate cancer
Jia-Qi Yan1, Da Huang1, Jing-Yi Huang1, Xiao-Hao Ruan1, Xiao-Ling Lin2, Zu-Jun Fang2, Yi Gao1, Hao-Wen Jiang2, Yi-Shuo Wu2, Rong Na1, Dan-Feng Xu1
1 Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
2 Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China
| Date of Submission | 20-Jun-2021 |
| Date of Acceptance | 12-Sep-2021 |
| Date of Web Publication | 12-Nov-2021 |
Correspondence Address:
Rong Na,
Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025
China
Yi-Shuo Wu,
Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040
China
 Source of Support: None, Conflict of Interest: None DOI: 10.4103/aja202174 PMID: 34782549
To analyze the performance of the Prostate Health Index (phi) and its derivatives for predicting Gleason score (GS) upgrading between prostate biopsy and radical prostatectomy (RP) in the Chinese population, an observational, prospective RP cohort consisting of 351 patients from two medical centers was established from January 2017 to September 2020. Pathological reclassification was determined by the Gleason Grade Group (GG). The area under the receiver operating characteristic curve (AUC) and logistic regression (LR) models were used to evaluate the predictive performance of predictors. In clinically low-risk patients with biopsy GG ≤2, phi (odds ratio [OR] = 1.80, 95% confidence interval [95% CI]: 1.14–2.82, P = 0.01) and its derivative phi density (PHID; OR = 2.34, 95% CI: 1.30–4.20, P = 0.005) were significantly associated with upgrading to GG ≥3 after RP, and the results were confirmed by multivariable analysis. Similar results were observed in patients with biopsy GG of 1 for the prediction of upgrading to RP GG ≥2. Compared to the base model (AUC = 0.59), addition of the phi or PHID could provide additional predictive value for GS upgrading in low-risk patients (AUC = 0.69 and 0.71, respectively, both P < 0.05). In conclusion, phi and PHID could predict GS upgrading after RP in clinically low-risk patients.
Keywords: Gleason score; prostate biopsy; prostate cancer; Prostate Health Index; radical prostatectomy; upgrading
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How to cite this URL:
Yan JQ, Huang D, Huang JY, Ruan XH, Lin XL, Fang ZJ, Gao Y, Jiang HW, Wu YS, Na R, Xu DF. Prostate Health Index (phi) and its derivatives predict Gleason score upgrading after radical prostatectomy among patients with low-risk prostate cancer. Asian J Androl [Epub ahead of print] [cited 2021 Dec 8]. Available from: https://www.ajandrology.com/preprintarticle.asp?id=330391 |
Jia-Qi Yan, Da Huang
These authors contributed equally to this work.
| Introduction | |  |
Discrepancies in the Gleason score (GS) between prostate biopsy and radical prostatectomy (RP) are common in prostate cancer (PCa) diagnosis.[1],[2] A meta-analysis reported an overall GS upgrading rate of 38% among patients with low-grade (GS 2–6) biopsy after RP.[3] Unlike a decade prior, this problem has become increasingly critical in the era of active surveillance, as invasive treatment is not preferred for low-risk individuals.[4] In the Johns Hopkins Active Surveillance cohort, approximately 20% of patients received interventions within 2 years after diagnosis due to disease progression.[5] The biopsy results of the reclassified patients were highly suspicious, which could have been due to incomplete sampling. Therefore, additional tests, such as imaging techniques,[6],[7] clinicopathological variables,8–10 and novel biomarkers,[11],[12] were applied to increase the accuracy of prostate biopsy as well as the predictive ability for GS upgrading.
[-2]proPSA (p2PSA), a precursor isoform of prostate-specific antigen (PSA), was introduced nearly a decade ago. The Prostate Health Index (phi), derived from total PSA (tPSA), free PSA (fPSA), and p2PSA, has shown significant benefits for predicting PCa as a supplement to PSAs.13–15 Guazzoni et al.[16] revealed that p2PSA and phi were also strong predictors of PCa characteristics at final pathology after RP. In addition, several studies have suggested that phi could significantly contribute to the prediction of GS upgrading between biopsy and RP in Caucasian and Korean males.16–19 Whether phi could predict pathological reclassifications after RP in Chinese patients has been poorly studied at this stage.
Therefore, the objective of the present study was to evaluate the predictive utility of p2PSA and phi in terms of pathological reclassifications in a Chinese PCa cohort. An exploratory evaluation of the density of biomarkers (divided by the prostate volume) was also applied.
| Patients and Methods | | |
Study population
This was a prospective multicenter study in two PCa cohorts (Ruijin Hospital and Huashan Hospital, Shanghai, China). The study population included 351 consecutive PCa patients who were diagnosed by transrectal ultrasound-guided 12-core biopsies and then underwent laparoscopic RP between January 2017 and September 2020. Blood samples were collected for the measurement of PSAs prior to biopsies on the same day in a central laboratory as per the study protocol. All specimens were reviewed in the Department of Pathology at each hospital according to the new Gleason Grading System.[20] This study was approved by the institutional review board (IRB) of Ruijin Hospital and Huashan Hospital (central IRB No. KY2016-343, 24 Nov 2016, version 03), and written informed consent was obtained from each participant.
Patients were excluded if (1) the level of any serum antigen was unable to be tested due to poor serum sample quality (n = 11) or (2) had ever received neoadjuvant androgen deprivation therapy (n = 14).
Variables and outcomes
The clinicopathological variables included age, the number of biopsy-positive cores (>2 vs ≤2 [referent]), and the prostate volume (PV) which was measured by transrectal ultrasound and estimated using the prostate ellipsoid formula ([π/6] × length × width × height). Derivative variables were calculated as follows: (1) PSA density (PSAD): tPSA/PV; (2) p2PSAD: p2PSA/PV; (3) phi: (p2PSA/fPSA) × √tPSA; and (4) phi density (PHID): phi/PV.
Pathological reclassification between prostate biopsy and RP was determined by the Gleason Grade Group (GG, also known as GS pattern; [Table 1]). Outcomes were different across subsets: (1) GS upgrading was defined as the presence of RP GG ≥3 for patients with biopsy GG ≤2 (primary outcome) and RP GG ≥2 for patients with biopsy GG of 1 (secondary outcome); (2) GS downgrading was defined as RP GG ≤2 for patients with biopsy GG ≥3. | Table 1: Clinicopathological characteristics in the study cohorts across biopsy Gleason Grade Groups
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Statistical analysis
Baseline characteristics were compared using the Mann–Whitney U test (for continuous variables), Fisher's exact test (for categorical variables), and Cuzick's test (for trends across ordered groups, e.g., GG). To identify the independent predictors of GS upgrading or downgrading, we performed univariate and multivariate logistic regression (LR) analyses and calculated the crude odds ratio (cOR) and adjusted odds ratio (aOR), 95% confidence interval (95% CI), and P value for each covariate. The base model included age, the number of positive cores (categorical), and logarithmically transformed tPSA as covariates. We constructed receiver operating characteristic (ROC) curves to analyze the predictive abilities of the predictors and multivariate models. The areas under the curve (AUC) were compared using the DeLong method.[21]
All statistical analyses were performed using Stata 15.1 Special Edition (StataCorp, College Station, TX, USA). A two-tailed P < 0.05 was considered statistically significant.
| Results | | |
In this observational, prospective RP cohort, a total of 326 PCa patients were recruited based on the inclusion and exclusion criteria. The clinicopathological characteristics of the study cohort are shown in [Table 1]. Among 96 patients with biopsy GG of 1, 48 (50.0%) were reclassified to GG of 2 (3+4) after RP, and 16 (16.7%) were upgraded to high risk (GG ≥3). Among patients with biopsy GG of 2 (n = 73), 20 (27.4%) were upgraded after RP [Table 1].
[Table 2] shows the baseline characteristics of patients with biopsy GG ≤2 with and without upgrading after RP. All the biomarkers and derivatives in the upgraded patients (from biopsy GG ≤2 to RP GG ≥3) were significantly higher than those in the nonupgraded patients (all P < 0.05; [Table 2]). However, in patients with biopsy GG of 1 (3+3), PHID was the only variable that remained significant upon comparison of the upgraded and nonupgraded groups (median: 1.4 vs 0.7, P = 0.003; [Table 2]). | Table 2: Descriptive characteristics of low-risk patients (biopsy Gleason Grade Group ≤2) with and without upgrading after radical prostatectomy
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Univariable and multivariable LR analyses were also performed to evaluate the associations between the predictors and pathological reclassifications [Table 3]. After adjusting for age, the number of positive cores, and tPSA values, p2PSAD (aOR = 2.79, 95% CI: 1.20–6.51, P = 0.02), phi (aOR = 3.36, 95% CI: 1.34–8.38, P = 0.009), and PHID (aOR = 2.73, 95% CI: 1.29–5.77, P = 0.009) were found to be independent predictors for upgrading after RP among patients with biopsy GG ≤2 [Table 3]. However, in patients with biopsy GG = 1, only phi (aOR = 7.95, 95% CI: 2.03–31.18, P = 0.003) and PHID (aOR = 2.91, 95% CI: 1.18–7.14, P = 0.02) remained significant and independent predictors for upgrading in the multivariable analysis [Table 3]. In contrast, p2PSA, p2PSAD, phi, and PHID were all independent protective factors (aOR <1, all P < 0.05) for the prediction of downgrading after RP (from biopsy GG ≥3 to RP GG ≤2; [Supplementary Table 1 [Additional file 2]]). | Table 3: Univariable and multivariable logistic regression analyses for prediction of upgrading after radical prostatectomya
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ROC curve analyses were then performed to evaluate the predictive abilities of different predictors and models in patients with biopsy GG ≤2 [Figure 1]. The AUCs of PSAD, phi, and PHID were all higher than those of PSA but did not reach statistical significance (0.66, 0.67, and 0.69, respectively, compared to 0.61 [referent], all P > 0.05; [Figure 1]a). However, the multivariable LR models incorporating phi or PHID significantly outperformed the base model (all P < 0.05; [Figure 1]b). Among patients with biopsy GG of 1, both phi and PHID had significantly higher AUCs than PSA for predicting upgrading after RP (0.70 and 0.71, respectively, compared to 0.50 [referent], both P < 0.05; [Figure 2]a), but incorporation of the phi or PHID did not improve the overall predictive values of the base model in the multivariable analysis (both P > 0.05; [Figure 2]b). Neither phi nor PHID significantly outperformed PSA or provided additional value to the base model for the prediction of downgrading [Supplementary Figure 1 [Additional file 1]]. | Figure 1: ROC curves of (a) predictors and (b) multivariable models for prediction of upgrading after RP in patients with biopsy GG ≤2. *Statistically significant (P < 0.05). Upgrading was defined as the presence of RP GG ≥3. aBase model = age + number of positive cores (categorical) + logarithmically transformed total PSA. ROC: receiver operating characteristic; RP: radical prostatectomy; AUC: area under ROC curve; 95% CI: 95% confidence interval; PSA: prostate-specific antigen; PSAD: PSA density; phi: Prostate Health Index; PHID: phi density; ref: reference; GG: Gleason Grade Group.
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 | Figure 2: ROC curves of (a) predictors and (b) multivariable models for prediction of upgrading after RP in patients with biopsy GG of 1. *Statistically significant (P < 0.05). Upgrading was defined as the presence of RP GG ≥2. aBase model = age + number of positive cores (categorical) + logarithmically transformed total PSA. The definitions of the abbreviations are shown in the legend of Figure 1.
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Upgrading rates were compared between the groups stratified by different cutoff values of phi and PHID [Figure 3]. Among patients with biopsy GG ≤2, men with a phi ≥35 had a 3.3-fold higher risk of upgrading after RP than those with a phi <35 (25.4% vs 7.7%, P = 0.02). Similarly, patients with PHID ≥1.0 had a 3.2-fold higher risk of upgrading than others (25.6% vs 8.0%, P = 0.01; [Figure 3]a). Similar results were found for PHID in patients with biopsy GG of 1, but no significant difference in upgrading rates was observed when using the commonly used cutoffs of phi [Figure 3]b. | Figure 3: Upgrading rates for patients with biopsy (a) GG ≤2 and (b) GG = 1 under different cutoff values of phi or PHID. *P < 0.05; **P < 0.01; ***P < 0.001. Upgrading was defined as the presence of RP GG ≥3 for patients with biopsy GG ≤2 (primary outcome), and RP GG ≥2 for patients with biopsy GG of 1 (secondary outcome). RP: radical prostatectomy; GG: Gleason Grade Group; GS: Gleason score; phi: Prostate Health Index; PHID: phi density; NS: no statistical significance.
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| Discussion | | |
The present study investigated the association between phi, as well as its derivative PHID, and pathological reclassification after RP. We found that phi and PHID could well predict GS upgrading in the Chinese population. Despite the low utilization of active surveillance in China,[22],[23] the results are critical to low-risk patients with biopsy GG ≤2 for classification as those at “real” clinical risk.
Three previous studies in Caucasians reported that phi was a valuable independent predictor of GS upgrading (from GS 6 to GS ≥7) after RP.16–18 Moreover, addition of the phi might increase the predictive accuracy of a base multivariable model by 5.0%–5.7%.[16],[17] However, Park et al.[19] revealed an increase in the AUC of up to 13.1% in Koreans, consistent with our results based on the Chinese population (0.79 vs 0.66; [Figure 2]b). Furthermore, this was the first study to estimate the predictors of GG reclassification between biopsy and RP (from GG ≤2 to ≥3). Due to the significantly better prognosis of GG 2 (3+4) than GG 3 (4+3), the results of the present study might be important to current clinical practice.
Phi profiling has yet to be applied for patients undergoing active surveillance. Nearly 20% of patients fail to remain in active surveillance due to progression within 2 years.[5] The clinical risk of these patients could be misclassified by sampling bias associated with prostate biopsy. Our results, together with those from previous studies, provide preliminary evidence that patients with elevated phi values are at a higher risk of GS upgrading after RP. We also evaluated the reclassification effects at a specific cutoff of phi or PHID. The results might indicate that patients under active surveillance with a high phi or PHID should reconsider their strategy for disease management. We believe that this topic is important and worth investigating in an active surveillance cohort in future.
Several limitations should be noted. First, the sample size of the present study was relatively small. However, it is thus far the largest observational prospective study in a Chinese cohort. Confirmation of the study results in a large-scale cohort is necessary before further application. Second, due to the low utilization rate of active surveillance for clinically low-risk PCa patients in China,[22],[23] it is difficult to evaluate the association between phi or PHID and pathological reclassification in these patients. Such an evaluation is critical for the further implementation of our findings and application of phi testing for patients under active surveillance as a monitoring method.
| Conclusion | | |
Phi and its derivative PHID could predict GS upgrading in clinically low-risk patients with biopsy GG ≤2. Our findings might have clinical significance for treatment decisions in patients with low-risk PCa classified by biopsy results.
| Author Contributions | | |
RN and YSW conceived and designed the study. JQY, DH, XLL, ZJF, YG, and HWJ contributed materials and collected data. DH, JQY, JYH, XHR, and RN analyzed the data. DH and JQY drafted the manuscript. RN, DFX, and YSW revised the manuscript. All authors have read and approved the final manuscript and agree with the order of presentation of the authors.
| Competing Interests | | |
In the present study, we declare that Beckman Coulter, Inc., provided the tests for tPSA, fPSA, and p2PSA, but did not participate in the study design, data analysis and interpretation, and manuscript writing. There are no other potential competing interests to be declared.
| Acknowledgment | | |
We thank all the participants included in this study. This work was supported by grants from the National Natural Science Foundation of China (No. 81772741 and No. 81972645), Shanghai Jiao Tong University School of Medicine Gaofeng-Clinical Medicine Grant Support (No. 20181701), Shanghai Municipal Human Resources and Social Security Bureau (No. 2018052) to RN, and the Clinical Research Project of Shanghai Health Commission (No. 20214Y0511) to YSW.
Supplementary Information is linked to the online version of the paper on the Asian Journal of Andrology website.
| References | | |
| 1. | Vellekoop A, Loeb S, Folkvaljon Y, Stattin P. Population based study of predictors of adverse pathology among candidates for active surveillance with Gleason 6 prostate cancer. J Urol 2014; 191: 350–7.  |
| 2. | Yang DD, Mahal BA, Muralidhar V, Nezolosky MD, Vastola ME, et al. Risk of upgrading and upstaging among 10 000 patients with Gleason 3+4 favorable intermediate-risk prostate cancer. Eur Urol Focus 2019; 5: 69-76. |
| 3. | Cohen MS, Hanley RS, Kurteva T, Ruthazer R, Silverman ML, et al. Comparing the Gleason prostate biopsy and Gleason prostatectomy grading system: the Lahey Clinic Medical Center experience and an international meta-analysis. Eur Urol 2008; 54: 371–81. |
| 4. | |
| 5. | Tosoian JJ, Trock BJ, Landis P, Feng Z, Epstein JI, et al. Active surveillance program for prostate cancer: an update of the Johns Hopkins experience. J Clin Oncol 2011; 29: 2185–90. |
| 6. | Zhao Y, Deng FM, Huang H, Lee P, Lepor H, et al. Prostate cancers detected by magnetic resonance imaging-targeted biopsies have a higher percentage of Gleason pattern 4 component and are less likely to be upgraded in radical prostatectomies. Arch Pathol Lab Med 2019; 143: 86–91. |
| 7. | Kim H, Kim JK, Hong SK, Jeong CW, Ku JH, et al. Role of multiparametric magnetic resonance imaging to predict postoperative Gleason score upgrading in prostate cancer with Gleason score 3+4. World J Urol 2021; 39: 1825–30. |
| 8. | Moussa AS, Li J, Soriano M, Klein EA, Dong F, et al. Prostate biopsy clinical and pathological variables that predict significant grading changes in patients with intermediate and high grade prostate cancer. BJU Int 2009; 103: 43–8. |
| 9. | Jansson F, Folkvaljon F, Stattin P, Bratt O, Akre O. Risk of postoperative up staging or upgrading among men with low risk familial prostate cancer. J Urol 2020; 204: 79–81. |
| 10. | Wang X, Zhang Y, Zhang F, Ji Z, Yang P, et al. Predicting Gleason sum upgrading from biopsy to radical prostatectomy pathology: a new nomogram and its internal validation. BMC Urol 2021; 21: 3. |
| 11. | Pichon A, Neuzillet Y, Botto H, Raynaud JP, Radulescu C, et al. Preoperative low serum testosterone is associated with high-grade prostate cancer and an increased Gleason score upgrading. Prostate Cancer Prostatic Dis 2015; 18: 382–7. |
| 12. | Tang B, Han CT, Lu XL, Wan FN, Zhang CZ, et al. Preoperative prostate health index predicts poor pathologic outcomes of radical prostatectomy in patients with biopsy-detected low-risk patients prostate cancer: results from a Chinese prospective cohort. Prostate Cancer Prostatic Dis 2018; 21: 64–70. |
| 13. | Catalona WJ, Partin AW, Sanda MG, Wei JT, Klee GG, et al. A multicenter study of [-2]pro-prostate specific antigen combined with prostate specific antigen and free prostate specific antigen for prostate cancer detection in the 2.0 to 10.0 ng/ml prostate specific antigen range. J Urol 2011; 185: 1650–5. |
| 14. | Guazzoni G, Nava L, Lazzeri M, Scattoni V, Lughezzani G, et al. Prostate-specific antigen (PSA) isoform p2PSA significantly improves the prediction of prostate cancer at initial extended prostate biopsies in patients with total PSA between 2.0 and 10 ng/ml: results of a prospective study in a clinical setting. Eur Urol 2011; 60: 214–22. |
| 15. | Na R, Ye D, Qi J, Liu F, Helfand BT, et al. Prostate health index significantly reduced unnecessary prostate biopsies in patients with PSA 2-10 ng/mL and PSA >10 ng/mL: results from a multicenter study in China. Prostate 2017; 77: 1221–9. |
| 16. | Guazzoni G, Lazzeri M, Nava L, Lughezzani G, Larcher A, et al. Preoperative prostate-specific antigen isoform p2PSA and its derivatives, %p2PSA and prostate health index, predict pathologic outcomes in patients undergoing radical prostatectomy for prostate cancer. Eur Urol 2012; 61: 455–66. |
| 17. | Novak V, Vesely S, Luksanová H, Prusa R, Capoun O, et al. Preoperative prostate health index predicts adverse pathology and Gleason score upgrading after radical prostatectomy for prostate cancer. BMC Urol 2020; 20: 144. |
| 18. | Heidegger I, Klocker H, Pichler R, Pircher A, Prokop W, et al. ProPSA and the Prostate Health Index as predictive markers for aggressiveness in low-risk prostate cancer-results from an international multicenter study. Prostate Cancer Prostatic Dis 2017; 20: 271–5. |
| 19. | Park H, Lee SW, Song G, Kang TW, Jung JH, et al. Preoperative prostate health index and %p2PSA as the significant biomarkers of postoperative pathological outcomes of prostate cancer in Korean males: a prospective multi-institutional study. Investig Clin Urol 2020; 61: 42–50. |
| 20. | Epstein JI, Zelefsky MJ, Sjoberg DD, Nelson JB, Egevad L, et al. A contemporary prostate cancer grading system: a validated alternative to the Gleason score. Eur Urol 2016; 69: 428–35. |
| 21. | DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988; 44: 837–45. |
| 22. | Wei Y, Liu L, Li X, Song W, Zhong D, et al. Current treatment for low-risk prostate cancer in China: a national network survey. J Cancer 2019; 10: 1496–502. |
| 23. | Zhao F, Shen J, Yuan Z, Yu X, Jiang P, et al. Trends in treatment for prostate cancer in China: preliminary patterns of care study in a single institution. J Cancer 2018; 9: 1797–803. |
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]
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