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  • Review
  • Open Access

Positive surgical margin is associated with biochemical recurrence risk following radical prostatectomy: a meta-analysis from high-quality retrospective cohort studies

  • 1Email author,
  • 1,
  • 1,
  • 1,
  • 1 and
  • 1
Contributed equally
World Journal of Surgical Oncology201816:124

https://doi.org/10.1186/s12957-018-1433-3

  • Received: 30 January 2018
  • Accepted: 26 June 2018
  • Published:

Abstract

Background and purpose

Although numerous studies have shown that positive surgical margin (PSM) is linked to biochemical recurrence (BCR) in prostate cancer (PCa), the research results have been inconsistent. This study aimed to explore the association between PSM and BCR in patients with PCa following radical prostatectomy (RP).

Materials and methods

In accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), PubMed, EMBASE and Wan Fang databases were searched for eligible studies from inception to November 2017. The Newcastle–Ottawa Scale was used to assess the risk of bias of the included studies. Meta-analysis was performed by using Stata 12.0. Combined hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) were calculated using random-effects or fixed-effects models.

Results

Ultimately, 41 retrospective cohort studies of high quality that met the eligibility criteria, comprising 37,928 patients (94–3294 per study), were included in this meta-analysis. The results showed that PSM was associated with higher BCR risk in both univariate analysis (pooled HR = 1.56; 95% CI 1.46, 1.66; p < 0.001) and multivariate analysis (pooled HR = 1.35; 95% CI 1.27, 1.43; p < 0.001). Moreover, no potential publication bias was observed among the included studies in univariate analysis (p-Begg = 0.971) and multivariate analysis (p-Begg = 0.401).

Conclusions

Our meta-analysis demonstrated that PSM is associated with a higher risk of BCR in PCa following RP and could serve as an independent prognostic factor in patients with PCa.

Keywords

  • Positive surgical margin
  • Prostate cancer
  • Radical prostatectomy
  • Biochemical recurrence
  • Meta-analysis

Background

Prostate cancer (PCa) is the most diagnosed malignancy and the second leading cause of cancer-related deaths among men in Western countries [1]. Radical prostatectomy (RP) has been shown to have a cancer-specific survival benefit for men with clinically localised PCa [2]. Although many patients are disease-free after surgery, nearly 30% [3] of patients still continue to experience biochemical recurrence (BCR). Defined as a detectable prostate-specific antigen (PSA) level following RP in the absence of clinical progression, BCR is the most common pattern of disease relapse [4]. Patients with BCR have a considerably worse prognosis, often develop metastasis, and can die of the disease [3, 4]. Therefore, identifying prognostic predictors of BCR after RP to assist clinicians in predicting outcomes for decision making is required.

Numerous nomograms including pathological tumour stage [5], Gleason’s score [6], seminal vesicle invasion [7], and lymphatic invasion [8] have been developed to predict subsequent risk of BCR after RP. Unfortunately, because the collective prognostic value of these factors is unsatisfactory, better biomarkers are urgently needed. Positive surgical margin (PSM) is defined as the histological presence of cancer cells at the inked margin on the RP specimen [9]. Although PSM is frequently reported in radical prostatectomy series, their clinical relevance remains uncertain despite extensive investigation. A number of studies have demonstrated an association between PSM and BCR [5, 10, 11], while others have observed insignificant or even contrary correlations [1214].

Previously, Yossepowitch [15] systematically reviewed related studies on PSM reporting survival of surgical treatment for patients with PCa. These studies suggested that PSM in PCa should be considered an adverse oncological outcome. Nevertheless, a meta-analysis was not performed because of low-quality evidence and potential risks of bias. A meta-analysis utilises statistical methods to contrast and combine results from multiple studies, increasing the statistical power and reproducibility compared with individual studies [16]. Hence, to obtain the most conclusive results, we conducted a meta-analysis with high-quality retrospective cohort studies to assess the prognostic value of PSM in BCR.

Methods

Literature search

This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search of the literature in PubMed, EMBASE, and Wan Fang databases up to November 2017 was performed using a combined text and MeSH heading search strategy with the following terms: (“prostate cancer” or “prostate AND neoplasms”) and (“radical prostatectomy”) and (“positive surgical margin”) and (“biochemical recurrence” OR “biochemical failure”). In addition, reference lists in the recent reviews, meta-analysis, and included articles were manually searched to identify related articles. The language of the publications was limited to English and Chinese.

Inclusion and exclusion criteria

We defined the inclusion and exclusion criteria for study selection at the initiation of the search. The following inclusion criteria were used: (1) included definitive diagnosis of PCa and PSM assessed by pathologists; (2) all patients underwent RP treatment; (3) BCR after RP was defined; (4) the risk of BCR was estimated as hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) or the risk could be calculated from the reported data; and (5) published in English or Chinese. The following exclusion criteria were used: (1) letters, reviews, case reports, editorials, and author responses; (2) non-human studies; (3) studies that did not analyse the outcome after PSM and BCR; (4) studies with duplicated patient populations that had been reported in previous publications; or (5) articles contained elements that were inconsistent with the inclusion criteria.

Data extraction and quality assessment

Two investigators (Zhenlei Zha and Hu Zhao) independently extracted the data from all eligible publications. Any differences among evaluators were resolved by discussion with a third investigator (BinWu). The following data were extracted from the included studies using a standardised data collection protocol (Table 1, Table 2): first author’s name, year of publication, country, recruitment period, sample size, patient’s age, preoperative PSA level, Gleason score, pathological stage, positive percentage of PSM and BCR, definition of BCR, follow-up time, and the HRs (95% CIs) of PSM in univariate or multivariate Cox analyses for BCR. The quality of the eligible studies was evaluated according to the Newcastle–Ottawa Scale (NOS), which include three domains (selection of the study population, comparability of the groups, ascertainment of the outcome). We identified articles of “high quality” as those with NOS scores of 6–9, whereas scores of 0–5 were considered to indicate poor quality.
Table 1

Primary characteristics of the included studies

Author

Year

Country

No. of patients

Recruitment period

Age

(years)

p-PSA

(ng/ml)

Follow-up (months)

Surgical approach

Wettstein et al. [35]

2017

Switzerland

371

2008–2015

Median (range)

63 (41–78)

Median (range)

6.79 (0.43–81.4)

Median (range)

28 (1–64)

NA

Xun et al. [6]

2017

China

172

2003–2014

Median (IQR)

68 (62–72)

Median (IQR)

16.1 (10.9–28.3)

Median (IQR)

46.4 (33.4–62.4)

NA

Meyer et al. [36]

2017

Germany

903

1992–2005

Median (IQR)

63 (59–66)

Median (IQR)

6.4 (4.6–9.0)

Median (IQR)

133 (97–157)

NA

Gandaglia et al. [37]

2017

Multi-centred

94

2011–2015

Median (IQR)

64.3 (57.1–68.9)

Median (IQR)

9.7 (5.1–17.5)

Median (IQR)

23.5 (18.7–27.3)

Robot-assisted RP

Shangguan et al. [33]

2016

China

172

2003–2014

Median (range)

68 (62–72)

Median (range)

16.1 (10.9–28.3)

Median (IQR)

46.4 (33.4–62.4)

Open and laparoscopic RP

Zhang et al. [34]

2016

China

168

2006–2011

Median (range)

69 (53–85)

Median (range)

13.31 (4.59–36.12)

Median (range)

68 (7–98)

Laparoscopic RP

Simon et al. [12]

2016

Multi-centres

411

2001–2013

Mean ± SD

61 ± 6.1

NA

Median

63

NA

Sevcenco et al. [38]

2016

Multi-centres

7205

2000–2011

Median (IQR)

61 (57–66)

Median (IQR)

6 (4–9)

Median (IQR)

27 (19–48)

NA

Pagano et al. [20]

2016

USA

180

1990–2011

Median (range)

63.7 (58.8–67.6)

Median (range)

9.1 (6.3–17.1)

Median (range)

26.7 (8.8–66)

NA

Moschini et al. [39]

2016

USA

1011

1987–2012

NA

Median

12.0

Median

211.2

NA

Mortezavi et al. [40]

2016

Switzerland

100

1999–2007

Mean ± SD

63.5 ± 6.5

Mean ± SD

9.6 ± 8.3

Median (range)

126 (60–176)

Laparoscopic RP

Mao et al. [41]

2016

China

106

2008–2009

Mean (range)

68.1 (48–83)

Mean (range)

25.1 (3.1–104.3)

Median (range)

69 (8–84)

Laparoscopic RP

Whalen et al. [29]

2015

USA

609

2005–2011

Mean ± SD

61.2 ± 7.3

Mean ± SD

6.8 ± 6.3

Median (range)

20.5 (1–80)

NA

Song et al. [42]

2015

Korea

2137

1988–2011

Median (IQR)

67 (63–71)

Median (IQR)

6.9 (4.7–11.2)

Mean (range)

39.4 (8–1834)

NA

Reeves et al. [43]

2015

Australia

1479

2005–2012

Median

62

NA

Median

14

NA

Hashimoto et al. [5]

2015

Japan

837

2006–2013

Median (range)

65 (39–78)

Median (range)

6.9 (3–47.4)

Median (range)

20.5 (1.3–91.3)

Robot-assisted RP

Alvin et al. [44]

2015

Singapore

725

2003–2013

Median (range)

62 (37–79)

Median (range)

7.9 (0.79–72.9)

Mean (range)

28.5 (6–116)

Robot-assisted RP

Touijer et al. [13]

2014

USA

369

1988–2010

Median (IQR)

62 (57–66)

Median (IQR)

8 (5–15)

Median

48

NA

Ritch et al. [45]

2014

USA

979

2003–2009

Median

62

NA

Median

47

Open and robot-assisted RP

Kang et al. [21]

2014

Korea

3034

2004–2011

Mean ± SD

65.9 ± 6.6

Mean ± SD

11.6 ± 12.2

Median

47

NA

Fairey et al. [14]

2014

USA

229

1987–2008

Median (range)

65 (41–83)

NA

Median (range)

174 (2.4–253.2)

NA

Turker et al. [46]

2013

Turkey

331

1993–2009

Mean ± SD

62.79 ± 6.4

Mean ± SD

11.1 ± 10.5

Mean ± SD

29.7 ± 33.2

NA

Sammon et al. [10]

2013

USA

794

1993–2010

Mean ± SD

63.4 ± 8.1

Mean ± SD

5.6 ± 3.6

Median (IQR)

26.4(12.2–54.6)

NA

Chen et al. [30]

2013

China

152

2004–2011

NA

NA

Median (range)

48 (12–87)

Laparoscopic RP

Sooriakumaran et al. [11]

2012

Sweden

944

2002–2006

Median (IQR)

62.2 (58.2–65.8)

Median (IQR)

6.4(4.8–9.0)

Median (IQR)

75.6(67.2–86.4)

Robot-assisted RP

Lu et al. [31]

2012

China

894

1993–1999

Median (IQR)

62 (57–66)

Median (IQR)

6.0 (4.5–8.6)

Median (IQR)

9.9 (6.1–11.3)

NA

Iremashvili et al. [47]

2012

USA

1444

2003–2010

Mean (range)

61.3 (56–66.3)

Mean (range)

5.7 (4.5–8.0)

Median (range)

43.2 (3–216)

Open and robot-assisted RP

Connolly et al. [48]

2012

Australia

160

1988–1997

Mean ± SD

63.1 ± 6.3

Median (IQR)

9.95 (6.0–21.4)

Median (IQR)

26.2 (5.5–37.3)

Robot-assisted RP

Busch et al. [49]

2012

Germany

1845

1999–2007

Mean ± SD

62.0 ± 5.9

Median (range)

26.3 (17.0–42.1)

Median (range)

56 (0–35)

Laparoscopic RP

Berge et al. [50]

2012

Norway

577

2002–2008

Mean (range)

61.5 (42–76)

Mean (range)

8.4 (0.3–31)

Median (range)

36 (3–72)

Laparoscopic RP

Lee et al. [51]

2011

Korea

1000

2003–2009

Median (range)

66 (37–82)

Median (range)

7.8 (0.1–261.8)

Mean

39.4

NA

Alenda et al. [23]

2011

France

1248

1998–2008

Mean (range)

63 (44–78)

Mean (range)

10.9 (0.9–134)

Median

23.4

NA

Fukuhara et al. [52]

2010

Japan

364

2000–2009

Median (range)

66 (52–78)

Median (range)

8.1 (1.7–77.7)

Median (range)

33 (10–109)

NA

Cho et al. [53]

2010

Korea

171

2005–2009

Mean (range)

64.4 (49–80)

NA

Mean (range)

23.3 (2–51)

NA

Alkhateeb et al. [26]

2010

Canada

1268

1992–2008

Mean ± SD

62.0 ± 6.6

Median (range)

6.2 (0.1–65.9)

Mean (range)

78.1 (3–192)

NA

Jeon et al. [54]

2009

Korea

237

1995–2004

Mean (range)

64.5 (44–86)

Mean (range)

11.5 (0.2–98)

Median (range)

21.6 (2–88)

NA

Schroeck et al. [55]

2008

USA

3194

1988–2007

Median (IQR)

62.6(57.2–67.9)

Median (IQR)

6.3(4.5–9.6)

Median

31.2

NA

Pavlovich et al. [56]

2008

USA

508

2001–2005

Mean ± SD

57.6 ± 6.7

Mean (range)

6.0 (0.3–27)

Median (range)

12 (2–52)

Laparoscopic RP

Hong et al. [57]

2008

Korea

372

2003–2007

Mean (range)

64.2 (37–72)

Mean (range)

8.7 (0.2–104.2)

NA

NA

Cheng et al. [8]

2005

Indiana

504

1990–1998

Mean (range)

62 (34–80)

NA

Mean (range)

44 (1.5–144)

NA

Shariat et al. [58]

2004

USA

630

1994–2002

Median (range)

60.9 (40–75)

Mean (range)

6.1 (0.1–99)

Median (range)

21.4 (1–101.3)

NA

p-PSA preoperative prostate-specific antigen, SD standard deviation, IQR interquartile range, NA data not applicable

Table 2

Tumour characteristics of the included studies

Author

Specimen

GS  7/˃ 7

Staging system

T stage

1–2/3–4

SM+/ SM−

No. of BCR (%)

Definition of BCR

Wettstein et al. [35]

292 /79

WHO/ISUP 2016

263/108

133/238

49 (13.2%)

Rising and verified PSA levels > 0.1 ng/ml

Xun et al. [6]

131/41

TNM 2002

NA

62/110

80 (46.5%)

The date of the first PSA elevated to 0.2 ng/ml

Meyer et al. [36]

879/24

TNM 2002

903/0

37/206

137(15.2%)

PSA level of  0.2 ng/ml and rising after RP

Gandaglia et al. [37]

55/39

TNM 2002

22/72

30/64

24 (25.5%)

Two consecutive increases in PSA  0.2 ng/ml

Shangguan et al. [33]

131/41

NA

NA

62/110

NA

Two consecutive increases in PSA  0.2 ng/ml

Zhang et al. [34]

136/32

TNM 2012

NA

30/138

NA

First PSA elevated to 0.2 ng/ml

Simon et al. [12]

368/43

NA

NA

353/58

70 (17%)

Single PSA concentration of > 0.2, two concentrations at 0.2 ng/ml

Sevcenco et al. [38]

6645/560

TNM 2009

NA

6137/1074

798 (11.1%)

Two consecutive increases in PSA  0.2 ng/ml

Pagano et al. [20]

90/90

TNM 2002

NA

74/106

120 (66.5%)

Two postoperative PSA values of  0.2 ng/ml

Moschini et al. [39]

647/364

NA

355/657

566/445

697 (69%)

PSA 0.4 ng/ml or greater

Mortezavi et al. [40]

86/14

NA

79/21

25/75

12 (12%)

Two consecutive increases in PSA  0.2 ng/ml

Mao et al. [41]

78/28

TNM 2002

63/43

20/86

31 (29.2%)

Two consecutive increases in PSA  0.2 ng/ml

Whalen et al. [29]

516/93

TNM 1997

435/174

483/126

73 (12%)

Two consecutive increases in PSA  0.2 ng/ml

Song et al. [42]

1722/415

NA

1899/248

2132/13,433

466 (21.8%)

Greater than 0.2 ng/ml

Reeves et al. [43]

1306/142

NA

1042/454

390/1089

238 (20.5%)

Greater than 0.2 ng/ml

Hashimoto et al. [5]

634/373

WHO 2004

677/160

243/594

102 (12.2%)

Two consecutive increases in PSA  0.2 ng/ml

Alvin et al. [44]

663/58

TNM 2010

497/228

311/414

104 (14%)

Two consecutive increases in PSA  0.2 ng/ml

Touijer et al. [13]

184/185

TNM 2010

46/323

138/231

201 (54%)

PSA  0.1 ng/ml with confirmatory rise

Ritch et al. [45]

783/196

TNM 2002

955/24

335/644

317 (32.4%)

Greater than 0.2 ng/ml

Kang et al. [21]

2575/459

TNM 2009

NA

974/2060

NA

A serum PSA value of 0.4 ng/ml or greater after RP

Fairey et al. [14]

133/96

TNM 2002

0/229

105/124

83 (36.2%)

Detectable PSA (ng/ml) followed by two consecutive confirmatory (1988–1994: PSA  0.3; 1995–2005: PSA  0.05; 2006–present: PSA  0.03)

Turker et al. [46]

167/164

TNM 1994

NA

80/251

70 (21%)

Higher than 0.2 ng/ml on 2 separate measurements 1 month apart

Sammon et al. [10]

760/34

AJCC 2002

592/202

162/632

107 (13.5%)

Two consecutive increases in PSA  0.2 ng/ml

Chen et al. [30]

109/43

NA

0/152

27/125

80 (52.6%)

Two consecutive increases in PSA  0.2 ng/ml

Sooriakumaran et al. [11]

900/44

NA

651/230

194/704

135 (15.2%)

Greater than 0.2 ng/ml

Lu et al. [31]

796/98

TNM 2010

703/191

250/644

277 (31%)

PSA  0.1 ng/ml with confirmatory rise

Iremashvili et al. [47]

1286/258

NA

NA

479/965

210 (15%)

Greater than 0.2 ng/ml

Connolly et al. [48]

95/65

NA

65/95

60/100

88 (55%)

Greater than 0.2 ng/ml

Busch et al. [49]

1538/307

NA

1802/9

537/1308

450 (24.4%)

PSA  0.1 ng/ml with confirmatory rise

Berge et al. [50]

553/24

TNM 2002

441/136

168/409

91 (16%)

Two consecutive increases in PSA  0.2 ng/ml

Lee et al. [51]

236/764

NA

NA

337/663

99 (9.9%)

Two consecutive increases in PSA  0.2 ng/ml

Alenda et al. [23]

1248/0

NA

NA

400/843

176 (16.9%)

PSA > 0.2 ng/mL

Fukuhara et al. [52]

332/32

TNM 2002

275/89

157/207

66 (18.1%)

Two consecutive increases in PSA  0.2 ng/ml

Cho et al. [53]

153/14

TNM 2002

126/45

58/109

15 (8.8%)

A serum PSA value of 0.4 ng/ml or greater after RP

Alkhateeb et al. [26]

1159/109

NA

853/415

264/1004

NA

A serum PSA value of 0.4 ng/ml or greater after RP

Jeon et al. [54]

190/45

TNM 2002

145/92

86/151

67 (28.3%)

Two consecutive increases in PSA  0.2 ng/ml

Schroeck et al. [55]

2855/359

NA

1991/1166

982/2212

706 (25.7%)

Greater than 0.2 ng/ml

Pavlovich et al. [56]

494/14

TNM 2002

416/92

69/439

102 (20%)

Two consecutive increases in PSA  0.2 ng/ml

Hong et al. [57]

361/11

TNM 2002

371/0

46/326

NA

First value greater than 0.2 ng/ml

Cheng et al. [8]

410/94

TNM 1997

348/156

174/330

157 (21.2%)

Two consecutive increases in PSA  0.1 ng/ml

Shariat et al. [58]

565/65

TNM 1997

NA

179/451

80 (12.7%)

First value greater than 0.2 ng/ml

GS Gleason score, SM+/SM surgical margin positive/surgical margin negative, BCR biochemical recurrence, NA data not applicable

Statistical analyses

All statistical analyses in this meta-analysis were performed by Stata 12.0 software (Stat Corp, College Station, TX, USA). The association between PSM and BCR outcome was presented as summary relative risk estimates (SRREs) and 95% CIs. Heterogeneity between studies was calculated by the chi-square-based Q test and I2. A value of p < 0.10 or I2 > 50% was considered as statistically significant heterogeneity. A random-effects model was used if heterogeneity was significant, and otherwise, a fixed-effects model was used. Sensitivity analysis was used to estimate the reliability of the pooled results via the sequential omission of each study. Subgroup analysis was performed to check whether the pooled HR was influenced by the region, publication year, mean age, sample size, mean preoperative PSA (p-PSA), median follow-up, and the cut-off value for BCR. To assess the stability of the combined HR, sensitivity analysis was performed by removing individual studies from the meta-analysis. Publication bias was assessed by funnel plots and was statistically determined by Egger’s linear regression. Statistical significance was defined as a two-tailed value of p < 0.05, except for the heterogeneity tests.

Results

Literature search and study characteristics

The full process of the systematic literature review is shown in Fig. 1. In accordance with the PRISMA search strategy, 1048 relevant studies were initially identified. After carefully reading each article, 780 studies were excluded for the following reasons: duplicates, letters, or reviews; or contained no evaluated margin status and focus on BCR. After the remaining studies (n = 268) were reviewed, additional studies were excluded because certain cohorts were studied more than once or relevant data were lacking. Forty-one high-quality retrospective studies comprising 37,928 patients (94–3294 per study) were ultimately included in the meta-analysis.
Fig. 1
Fig. 1

Flow diagram of the study selection process for this meta-analysis

The primary characteristics of the included studies are summarised in Table 1. All studies were published between 2004 and 2017. Of these, 19 studies were conducted in an Asian country, and 12 were conducted in North America; the rest were conducted in Europe (7) or in multiple countries (3). The median follow-up period of the studies ranged from 14 to 174 months. All included studies were published in English, except for two that were in Chinese. Of all of the studies, 8 used laparoscopic RP, 7 used robot-assisted RP, and 3 used open RP. BCR was defined using different cut-off values (0.1 ng/ml, 0.2 ng/ml, 0.4 ng/ml) among the included studies, and the incidence of BCR after RP ranged from 8.8 to 66.5% according to the reported values (Table 2). NOS [17] was applied to assess the quality of the included studies, and the results showed that all of the studies were of high quality with an NOS score ≥ 7. (Additional file 1: Table S1).

Meta-analysis

The forest plots of the meta-analysis in our study demonstrated that PSM was associated with poorer BCR in RP patients by univariate analysis (random-effects model, pooled HR = 1.56; 95% CI 1.46, 1.66; p < 0.001; Fig. 2) and multivariate analysis (random-effects model, pooled HR = 1.35; 95% CI 1.27, 1.43; p < 0.001; Fig. 3). Given the large heterogeneity between the studies, subgroup analyses were performed by region, publication year, mean age, sample size, mean preoperative PSA (p-PSA), median follow-up, and the cut-off value for BCR. Although no significant modifiers accounting for the inter-study heterogeneity were detected, the results of subgroup analyses were consistent with the primary findings (Table 3).
Fig. 2
Fig. 2

Forest plots of the association between PSM and BCR risk in the stratification analysis by univariate mode

Fig. 3
Fig. 3

Forest plots of the association between PSM and BCR risk in the stratification analysis by multivariate mode

Table 3

Overall analyses and subgroup analyses for the included studies

Analysis specification

No. of studies

Study heterogeneity

Effects model

Pooled HR (95% CI)

p value

I2 (%)

p heterogeneity

Univariate analysis (BCR)

 Overall

25

70.9

< 0.001

Random

1.56 (1.46,1.66)

< 0.001

 Geographical region

  Asia

12

72.1

< 0.001

Random

1.61 (1.43,182)

< 0.001

  Europe and North America

12

70.8

< 0.001

Random

1.50 (1.37,1.65)

< 0.001

 Date of publication

  ≥ 2014

13

81.8

< 0.001

Random

1.52 (1.36,1.70)

< 0.001

  < 2014

12

18.5

0.262

Fixed

1.61 (1.52,1.71)

< 0.001

 Mean age (years)

  ≥ 64

9

84

< 0.001

Random

1.62 (1.34,1.97)

< 0.001

  < 64

15

55.6

0.005

Random

1.54 (1.45,1.64)

< 0.001

 Sample size (cases)

  ≥ 500

10

40.1

0.09

Random

1.61 (1.52,1.70)

< 0.001

  < 500

15

76.9

< 0.001

Random

1.51 (1.33,1.71)

< 0.001

 Mean p-PSA (ng/ml)

  ≥ 10

7

81

< 0.001

Random

1.65 (1.38,1.97)

< 0.001

  < 10

14

58.5

0.003

Random

1.59 (1.48,1.71)

< 0.001

 Median follow-up

  ≥ 36 months

11

77.1

< 0.001

Random

1.49 (1.33,1.67)

< 0.001

  < 36 months

14

59.8

0.002

Random

1.61 (1.49,1.74)

< 0.001

 BCR (ng/ml)

  Cutoff value 0.1

4

0

0.775

Fixed

1.61 (1.49,1.72)

< 0.001

  Cutoff value 0.2

20

72

< 0.001

Random

1.58 (1.46,1.70)

< 0.001

  Cutoff value 0.4

1

Multivariate analysis (BCR)

 Overall

32

79.2

< 0.001

Random

1.35 (1.27,1.43)

< 0.001

 Geographical region

  Asia

14

67

< 0.001

Random

1.42 (1.29,1.55)

< 0.001

  Europe and North America

15

84.7

< 0.001

Random

1.31 (1.19,1.43)

< 0.001

  Multi-centred

3

71.9

0.029

Random

1.33 (1.00,1.78)

0.053

 Date of publication

  ≥ 2014

16

82.9

< 0.001

Random

1.27 (1.17,1.39)

< 0.001

  < 2014

16

67.2

< 0.001

Random

1.44 (1.32,1.56)

< 0.001

 Mean age (years)

  ≥ 64

8

62.5

0.009

Random

1.56 (1.32,1.85)

< 0.001

  < 64

22

81.5

< 0.001

Random

1.33 (1.24,1.43)

< 0.001

 Sample size (cases)

  ≥ 500

18

77.1

< 0.001

Random

1.40 (1.32,1.49)

< 0.001

  < 500

14

76.8

< 0.001

Random

1.28 (1.12,1.47)

< 0.001

 Mean p-PSA (ng/ml)

  ≥ 10

7

80.8

< 0.001

Random

1.36 (1.22,1.57)

< 0.001

  < 10

19

79

< 0.001

Random

1.35 (1.24,1.48)

< 0.001

 Median follow-up

  ≥ 36 months

16

79.6

< 0.001

Random

1.36 (1.24,1.46)

< 0.001

  < 36 months

15

79.8

< 0.001

Random

1.34 (1.21,1.47)

< 0.001

 BCR (ng/ml)

  Cutoff value 0.1

5

87.7

< 0.001

Random

1.22 (1.01,1.48)

0.044

  Cutoff value 0.2

23

71.3

< 0.001

Random

1.39 (1.30,1.48)

< 0.001

  Cutoff value 0.4

4

82.2

0.001

Random

1.34 (1.15,1.57)

< 0.001

The sensitivity analysis and publication bias

With a sensitivity analysis, the overall significance did not change when any single study was omitted. The summary relative risk estimate (SRRE) for BCR ranged from 1.52 (95% CI, 1.44–1.62) to 1.58 (95% CI, 148–1.68) (Fig. 4a) in univariate analysis and 1.34 (95% CI, 1.26–1.42) to 1.37 (95% CI, 1.29–1.45) (Fig. 4b) in multivariate analysis. These results indicated that the findings were reliable and robust. To test for publication bias, Egger’s linear regression was performed. No significant publication bias was detected between these studies regarding HR of BCR in univariate analysis (p-Begg = 0.971; Fig. 5a) and multivariate analysis (p-Begg = 0.401; Fig. 5b), respectively.
Fig. 4
Fig. 4

Sensitivity analysis of the association between PSM and BCR risk in PCa patients. a Univariate analysis mode. b Multivariate analysis mode

Fig. 5
Fig. 5

Funnel plots and Begg’s tests for the evaluation of potential publication bias. a Univariate analysis mode. b Multivariate analysis mode

Discussion

With the increased public awareness and wide use of PSA-based screening, the number of patients diagnosed with PCa annually has been increasing [6]. Because RP provides superior cancer control and functional outcomes, this surgery has become a standard first-line treatment for eligible patients [18]. However, despite various advances in surgical technology, BCR has been reported in approximately 25–35% patients after RP and even more patients with intermediate–high risk [19]. Because BCR reportedly leads to distant metastasis and cancer death [20], it is necessary for men with BCR to undergo salvage radiation or hormonal therapy [11]. Therefore, identifying modifiable factors that affect the progression of BCR may help physicians in the selection of patients who are more likely to benefit from adjuvant multimodal therapy.

A number of nomograms have been developed to predict BCR after RP using either preoperative or postoperative variables [21]. Several clinical and pathologic factors have been included in these models, most of which cannot be altered by the treating physician (preoperative PSA [22], pathological T stage [5], pathological Gleason score [23]). The D’Amico risk stratification scheme [20] and Cancer of the Prostate Risk Assessment (CAPRA) score [24] have also been adopted in the urological community to predict the probability of BCR. Although these nomograms have been internationally validated, unfortunately, only a small number of them have predicted the probability of 5-year BCR with more than 70% accuracy [25]. Thus, efforts to improve existing outcome prediction tools for PCa are always encouraged.

PSM is a frequent situation encountered after radical prostatectomy (RP) for localised PCa with an occurrence ranging from 6 to 41% [9, 26, 27]. The incidence of PSM depends on various factors, including tumour biology, patient characteristics, pathological assessment method, and surgical technique [28]. We reported an overall PSM rate of 45.7% (17,339/37,928), which was slightly higher than other large series. Because the goal of surgical procedures is the complete removal of the tumour, the presence of PSM after RP is considered to be an adverse outcome associated with failure of the surgery to cure the PCa. However, the effects of PSM on clinical outcomes and the risk of BCR are still unclear. Several studies concluded that a PSM is an independent factor of BCR in patients with PCa after RP [11, 2931]. However, not all patients with PSM show recurrence according to other studies [27, 28, 32]. Moreover, several reports showed that the effect of PSMs on prognosis depends on certain clinical and pathological features of the disease [26].

To the best of our knowledge, this study is the most up-to-date and informative meta-analysis on the association between PSM and BCR risk. The results obtained in our meta-analysis are in line with the previous systematic review by Yossepowitch et al. In addition, our study presented a series of advancements in comparison with previous studies. First, we included more eligible studies with high quality. The search by Yossepowitch et al. included studies up to 2013. However, our search included 21 additional studies published from 2014 to 2017, thereby improving the evaluation on the effect and enabling more subgroup analyses. In addition, the studies retrieved for our analysis were not limited to English; two Chinese articles [33, 34] also met the criteria for inclusion. Similar to Yossepowitch et al., we identified a significant relationship between PSM and BCR in RP. However, we also found that the pooled result of PSM had a large heterogeneity in both univariate (I2 = 70.9%) and multivariate (I2 = 79.2%) analyses. Even though the cut-offs varied among the included studies (0.1 ng/ml, 0.2 ng/ml, 0.4 ng/ml), the subgroup analyses achieved results similar to both univariate and multivariate analyses (Table 3). Meanwhile, the sensitivity analysis of our study revealed that the omission of each study did not have a significant impact on the merged value of HR.

However, several limitations of this study should be considered. First and foremost, all included studies were retrospective; therefore, the data extracted from those studies may have led to potential inherent bias. Second, the criteria to determine the presence of PSM in the pathological specimen were inconsistent in the included studies, which may have potentially contributed to heterogeneity. Thus, rigorous morphological criteria should be established to standardise the diagnosis of PSM. Third, substantial heterogeneity was observed in the meta-analysis, and although we used the random-effects model according to heterogeneity, it still existed in our studies. Moreover, from the subgroup analyses, we believed that the heterogeneity was caused by differences in factors such as patient and tumour characteristics. Finally, studies with negative results tend to be unsubmitted or unpublished; grey literature was not included, meaning that language bias may have been present in this study.

Conclusions

In conclusion, this meta-analysis demonstrates that PSM has a detrimental effect on BCR risk in patients with PCa after RP and could therefore be considered to be an independent prognostic factor of BCR. Due to PSM’s excellent feasibility and low cost, this method should be more widely employed for BCR risk stratification and BCR prediction in patients with PCa. Given the inherent limitations of retrospective studies, further research is warranted, preferably with a longer follow-up period, to elucidate the potential role of PSM in influencing BCR risk.

Notes

Declarations

Availability of data and materials

All data generated or analysed during this study are included in this published article (and its supplementary information files).

Authors’ contributions

LZ and BW contributed to the conceptualization. ZZ, HZ, and BW contributed to the literature search. YJ and YJ contributed to the data analysis. ZZ, HZ, and YJ contributed to the writing of the original draft. LZ contributed to the writing and review and editing. All authors read and approved the final manuscript

Ethics approval and consent to participate

Not applicable.

Consent for publication

I give my consent for information about my relative circle to be published in the World Journal of Surgical Oncology (WJSO-D-18-00097R1, Lijin Zhang). I understand that the information will be published without my relative’s (circle as appropriate) name attached, but that full anonymity cannot be guaranteed. I understand that the text and any pictures or videos published in the article will be freely available on the internet and may be seen by the general public. The pictures, videos, and text may also appear on other websites or in print, may be translated into other languages, or used for commercial purposes. I have been offered the opportunity to read the manuscript.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Departments of Urology, Affiliated Jiang-yin Hospital of the Southeast University Medical College, Jiang-yin, 214400, China

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Copyright

© The Author(s). 2018

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