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Correlation between Prostatitis, Benign Prostatic Hyperplasia 1

and Prostate Cancer: A systematic review and Meta-analysis 2

Lei Zhang1,*, Yi Wang1,*, Zhiqiang Qin2,*, Xian Gao3, Qianwei Xing4★, Ran Li1, Wei Wang1, 3

Ninghong Song1, Wei Zhang1,★ 4 5 1Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 6

210009, China. 7 2Department of Urology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, 8

China. 9 3Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 10

210009, China. 11 4Department of Urology, The Affiliated Hospital of Nantong University, Nantong, 226001, China. 12

★Co-corresponding authors: 13

Wei Zhang 14

Department of Urology, The First Affiliated Hospital of Nanjing Medical University, No. 300 15

Guangzhou Road, Nanjing, 210029, China. 16

E-mail: 15250961196@163.com 17

TEL: +08613901595401 18

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Qianwei Xing 20

Department of Urology, The Affiliated Hospital of Nantong University, Nantong, 226001, China. 21

E-mail: xingqianwei@ntu.edu.cn 22

TEL: +08615240552009 23

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Abstract 32

Background: No consensus has been reached on the definite associations among prostatitis, 33

benign prostatic hyperplasia (BPH) and prostate cancer (PCa). Hence, this meta-analysis was 34

conducted to explore their triadic relation by summarizing epidemiological evidence. 35

Methods: Systematical and comprehensive retrieval of online databases PubMed, PMC, 36

EMBASE and Web of Science was performed to acquire eligible studies, up to April 1st, 2019. 37

Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to clarify their 38

correlations. 39

Results: A total of 42 studies were enrolled in the quality assessment and 35 were finally included 40

in the meta-analyses. Among them, 27 studies were included to describe the association between 41

prostatitis and PCa (OR=1.72, 95% CI=1.44-2.06, I2=90.1%, P<0.001). 21 studies presented 42

significant evidence about the relation between BPH and PCa (OR=2.16, 95% CI=1.75-2.88, 43

I²=97.1%, P<0.001). Due to the huge heterogeneity among studies, those with obvious outliers 44

were excluded based on the Galbraith plots. Ultimately, 17 studies were screened out to assess the 45

association between prostatitis and PCa (OR=1.59, 95% CI=1.48-1.70, I²=29.4%, P=0.123). 46

Meanwhile, 8 studies were retained to evaluate the association between BPH and PCa (OR=3.10, 47

95% CI=2.87-3.35, I²=8.4%, P=0.365). As for the relation between prostatitis and BPH, a 48

case-control study and a cohort study both supported that prostatitis could enhance the risk of 49

BPH. 50

Conclusions: Significant correlations were revealed among prostatitis, BPH and PCa. Prostatitis 51

or BPH could lead to escalating risks of PCa. Meanwhile, people with a history of prostatitis 52

might be more vulnerable to BPH. 53

Keywords: Prostatitis; Benign prostatic hyperplasia; Prostate cancer; Meta-analysis; 54

Epidemiological 55

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Introduction 66

Prostate cancer (PCa) is the most prevalent malignancy in the male population, with 164,690 67

newly estimated cases and 29,430 newly estimated deaths in the United States, 2018 [1]. PCa 68

mainly occurs in elderly men, and nearly two thirds of cases are diagnosed at the age of 65 or over 69

[2]. Up to now, several factors have been verified associated with the carcinogenesis of PCa, 70

including aging, family history and race [3-5]. Furthermore, the altered androgen metabolism also 71

plays a pivotal role [6]. However, the definite etiological mechanism remains unclear. With the 72

assistance of epidemiological studies, a large number of potential risk factors for PCa, such as 73

work environment, obesity, smoking, alcohol consumption and sexual activity, have been 74

identified in the past decades [7-11]. Unexpectedly, prostatitis and benign prostatic hyperplasia 75

(BPH) were listed among these risk factors, though controversies existed [12, 13]. 76

Prostatitis and BPH are two common benign diseases of the prostate gland. Prostatitis affects 77

men of all ages, especially the middle age group. Both of them have high incidence ranging from 78

3 to 16% in Europe, North America and Asia [14-16]. Moreover, more than 50% of the surgical 79

prostate specimens were found to be associated with histological inflammation [17]. Pathogenesis 80

of prostatitis includes pathogens infection like bacteria and mycoplasma, urine reflux, 81

autoimmunity, neuro muscular mechanisms and so on [18-20]. However, BPH predominantly 82

occurs in elderly men, and 70% of the patients are 70 years old or over [21]. Aging and androgen 83

are established factors leading to the occurrence of BPH [22]. Furthermore, metabolic syndrome, 84

genetics and lifestyle may also have something to do with BPH [23, 24]. As for the correlation 85

between prostatitis and BPH, Adorini et al. suggested a significant role of inflammation in the 86

occurrence and progression in BPH [25]. What’s more, Jennifer et al. found an increased risk of 87

BPH in those men with a history of prostatitis [26]. However, it has yet to be further determined. 88

As a clinician, we are often enquired of by the anxious patients with prostatitis or BPH, 89

‘Whether or not our disease would develop into PCa?’. Facing these questions, we often told them 90

that prostatitis, BPH and PCa had nothing to do with each other, due to the absence of definite 91

evidence. However, accumulating epidemiological studies have revealed the significant 92

associations among prostatitis, BPH and PCa risk. Nevertheless, controversies still exist, and no 93

consensus has been achieved on this topic till now. Hence, we comprehensively searched online 94

databases and conducted this meta-analysis to clarify their correlations. 95

96

Materials and methods 97

Literature search strategy 98

We comprehensively retrieved relevant studies about the relations among prostatitis, BPH 99

and PCa from online databases PubMed, PMC, EMBASE and Web of Science, published before 100

April 1st, 2019, 2018. Following keywords combined with the Medical Subject Headings (MeSH) 101

items were utilized: “Prostatitis” or “Prostatitides” or “Chronic Pelvic Pain Syndrome” or 102

“Chronic Bacterial Prostatitis” or “Acute Bacterial Prostatitis” or “Asymptomatic Inflammatory 103

Prostatitis”, “Benign Prostatic Hyperplasia” or “BPH” or “Prostatic Hyperplasia” or “Prostatic 104

Hypertrophy”, “Prostate Cancer” or “Prostate Neoplasm” or “prostate tumor” or “PCa”. 105

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Furthermore, potentially eligible studies were meticulously identified by checking the reference 106

lists from relevant review studies. 107

Inclusion and exclusion criteria 108

Included studies must meet the following criteria: (1) Used a case-control or cohort study 109

design; (2) Evaluated the epidemiological association among prostatitis, BPH and PCa. (3) 110

Presented concrete numbers of exposures and non-exposures in both case and control groups to 111

calculate the pooled odds ratios (ORs) and 95% confidence intervals (CIs); (4) Enrolled patients 112

with PCa were confirmed by histopathological examination. In addition, exclusive criteria were as 113

follows: (1) Not case-control or cohort studies; (2): Cross-sectional studies; (3) Duplicated studies 114

or invalid data; (4) Studies not related to prostatitis, BPH and PCa. 115

Data Extraction and Quality Assessment 116

All available data from the included studies were extracted independently by two reviewers 117

(L.Z and Y.W) and summarized together. A third reviewer (ZQ.Q) would join in the discussion if 118

any divergence arose and then reached a consensus. Finally, the extracted data were recorded in a 119

standardized format including following items: first author’s name, publication year, age of 120

subjects, country, ethnicity, source of controls, study design, data source, the number of cases and 121

controls, and the number of exposures. In addition, the quality of included studies was assessed 122

with the Newcastle–Ottawa Scale (NOS). If the final score > 6, it was regarded as high-quality and 123

then included in the subsequent meta-analyses. 124

Statistical Analysis 125

Pooled ORs with 95% CIs were respectively calculated to evaluate the associations between 126

prostatitis and PCa, BPH and PCa, prostatitis and BPH. Heterogeneity was tested by Cochrane Q 127

test and Higgins I2 statistic. If the heterogeneity was acceptable (I2<50% or P>0.10), the fixed 128

effect model (a Mantel-Haenszel method) was adopted. Contrarily, the random effect model (a 129

DerSimonian-Laird method) would be applied if heterogeneity was significant (I2>50% or 130

P<0.10). Subgroup analyses were performed by ethnicity, study design, source of control (SOC), 131

and sample size. Furthermore, the stability and reliability of the results was examined by sensitive 132

analyses. The publication bias was assessed by Begg’s funnel plots and Egger’s linear regression 133

test. A significant bias would be considered if the P<0.05. All data were processed by Stata 134

software 12.0 (StataCorp LP, College Station, TX). 135

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Results 137

Studies characteristics 138

Based on the above-mentioned inclusion and exclusion criteria, a total of 42 studies (S1-S42, 139

Table S1) were included in the quality assessment. Results of the quality assessment were shown 140

in Table S2. Ultimately, 35 high-quality studies with NOS scores > 6 were selected for further 141

meta-analyses, while 7 studies (S36-S42) were eliminated. Among them, 27 studies described the 142

relation between prostatitis and PCa, 21 eligible studies focused on the association between BPH 143

and PCa, and 2 studies depicted the relation of prostatitis and BPH. Figure 1 presented the 144

specific details of searching literature and screening steps. The main characteristics of all included 145

studies were separately listed in Table 1, 2 and 3. 146

Association between prostatitis and PCa 147

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Pooled ORs and 95% CIs were calculated to assess the association between prostatitis and 148

PCa. As shown in Figure 2, the overall analysis revealed a significant association between 149

prostatitis and PCa (OR=1.72, 95% CI=1.44-2.06). However, a huge heterogeneity was detected in 150

the results (I²=90.1%, P<0.001). Subsequent subgroup analyses failed to decrease the 151

heterogeneity. Moreover, meta-regression analysis revealed the country and ethnicity might 152

explain a certain proportion of the heterogeneity (Table S3). However, the heterogeneity remained 153

remarkable when stratified by ethnicity. 154

Given these, we performed Galbraith radial plot to spot the outliers as the potential sources of 155

heterogeneity (Figure 3). After eliminating partly of the studies according to the Galbraith plot, 17 156

residual studies were re-analyzed. New results remained significant (OR=1.59, 95% 157

CI=1.48-1.70), and the overall heterogeneity was successfully decreased (I²=29.4%, P=0.123). 158

What’s more, subgroup analyses including ethnicity, study design and sample size showed 159

significant results, which further validated this association (Figure 4). 160

Association between BPH and PCa. 161

The overall analysis revealed a conspicuous association between BPH and PCa (OR=2.16, 95% 162

CI=1.75-2.68). However, the great heterogeneity (I²=97.1%, P<0.001) also appeared and could not 163

be reduced by subgroup analyses (Figure 5). What’s more, meta-regression analyses suggested 164

that no relevant covariates which could be summarized based on the between-study generality and 165

individuality, could explain even part of the heterogeneity (Table S3). 166

Likewise, we excluded studies with distinct heterogeneity based on Galbraith plot in 167

combination with results of Begg’s funnel plot and sensitive analysis (Figure 6). Ultimately, 168

post-elimination results of overall analysis (OR=3.10, 95% CI=2.87-3.35, I²=8.4%, P=0.365) and 169

subgroup analyses maintained positive, which illustrated the significant association between BPH 170

and PCa (Figure 7). 171

Association between prostatitis and BPH 172

A case-control studies and a cohort studies described the epidemiological relation of 173

prostatitis with BPH. Significant results were obtained in the overall analysis (OR=2.95, 95% 174

CI=1.94-4.47, I²=44.1%, P=0.181) (Figure 8). In addition, both the case-control study (OR=4.93, 175

95% CI=2.13-11.41) and the cohort study (OR=2.56, 95% CI=1.59-4.10) supported that prostatitis 176

could enhance the risk of BPH. 177

Sensitivity analysis 178

Sensitivity analyses were performed to evaluate the stability of results and reflect the impact 179

of the individual study to overall results by deleting each study once a time. Our results indicated 180

that no single study significantly influenced the pooled ORs and 95% CIs. Sensitivity analyses of 181

the relation between prostatitis or BPH and PCa were respectively presented in Figure 3A, 3B, 6A, 182

6B. 183

Publication bias 184

The Begg’s funnel plot and Egger’s test were performed to assess the publication bias. In the 185

pooled analysis of prostatitis and PCa, Egger’s P value was 0.17 and Begg’s P value was 0.09 186

after dealing with the heterogeneity (Figure 3E). In the pooled analysis of BPH and PCa, Egger’s 187

P value was 0.763 and Begg’s P value was 0.902 after elimination. (Figure 6E). Therefore, the 188

original studies included in the present meta-analysis have no obvious publication bias. 189

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Discussion 191

Clinically, urologic physicians always asked by some anxious patients whether prostatitis or 192

BPH will develop into PCa or increase the risk of PCa. However, there are no explicit answers on 193

these questions to date. Herein, we carefully searched available literature to seek for explanations. 194

Although no convincingly pathological evidence, a large number of epidemiological studies have 195

revealed the close associations between prostatitis, BPH and PCa [27-29]. However, no consensus 196

has been reached. Hence, this meta-analysis was conducted to further clarify their triadic 197

relationships by comprehensively summarizing the epidemiological studies. 198

As indicated in the results, prostatitis and BPH were both associated with escalating risks of 199

PCa. Moreover, people with a history of prostatitis might be more vulnerable to BPH. All the 200

results of subgroup analyses were positive. However, huge heterogeneity was existed among 201

enrolled studies. Meta-regression results suggested only the country and ethnicity could o explain 202

small parts of the heterogeneity. After careful analysis of all available data, the potential sources of 203

the heterogeneity were displayed below. First, due to the extreme correlations of these three 204

diseases with age, the different distribution of participants’ age was regarded as a vital source of 205

the heterogeneity. On the other hand, prostatitis could be divided into four categories: acute 206

bacterial prostatitis, chronic bacterial prostatitis, Chronic Prostatitis/Chronic Pelvic Pain 207

Syndrome (CP/CPPS) and asymptomatic inflammatory prostatitis, according to the National 208

Institutes of Health (NIH) [30]. Among included studies, no specific classification of prostatitis 209

was identified, which might lead to inhomogeneity. On the other hand, the years of prostatitis or 210

BPH history before getting PCa also affect the results to a great extent, while a good deal of 211

studies had not paid attention to it. Rothman et al. found a highest relative risk for prostate cancer 212

in men who had prostatitis diagnosed within 12 months of their prostate cancer reference data [31]. 213

Moreover, pathological types of PCa were also rarely mention in these studies. Furthermore, 214

methodological heterogeneity and other various factors such as ways of getting data from 215

participants, bias of participants’ memories of medical history and differences of interviewers’ 216

emphasis all inevitably contributed to the source of the heterogeneity. 217

Galbraith plot as one way of displaying several estimates of the same quantity having 218

different standard errors, was also used to spot the outlier as the possibly major source of 219

between-study heterogeneity [32, 33]. Thus, Galbraith plot associated with funnel plot and 220

sensitive analysis was applied to filter those papers with higher heterogeneity and tried to pool 221

analysis with those of approximately homogeneous papers. After carefully screening by the 222

Galbraith plot and considering results from sensitive analyses as well as Begg’s funnel plots 223

together, 17 studies (I2=29.4%, P=0.123) with low heterogeneity were ultimately re-analyzed to 224

display the relationship of prostatitis and PCa, and 8 studies were to re-analyzed the association 225

between BPH and PCa (I2=8.4%, P=0.365). Finally, the results of overall and subgroup analyses 226

remained significant. As for studies about prostatitis and BPH, although large heterogeneity 227

existed as well, pooled OR with 95% CI of each independent study was all above 1, indicating that 228

prostatitis could enhance the risk of BPH anyway. 229

Notably, the outcomes of us remained consistent before and after adjustment for 230

heterogeneity and meanwhile positive results were obtained in both the overall and subgroup 231

analyses, indicating the stability and reliability of our results. With the increasing recognition of 232

the early-diagnosis and early-treatment of PCa, it had caught more and more attention in the recent 233

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years [34]. Although several factors had been verified associated with the carcinogenesis of PCa 234

involving aging, family history, race and altered androgen metabolism, its definite pathogenesis 235

remained unclear [3-5]. While the views “prostatitis could lead to higher PCa risk” or “BPH could 236

increase the PCa susceptibility” had not been acknowledged, a massive number of 237

epidemiological studies had been carried to explore whether prostatitis and BPH were risk factors 238

of PCa. The latest cohort study with 2500 participants suggested that higher proportion in men 239

with prostatitis were diagnosed with PCa after 15 years later [35]. Besides, a cohort study 240

conducted in Denmark with more than a hundred thousand participants from 1980 through 2006 241

also demonstrated that the incidence rate was higher in the BPH cohort [28]. According to above 242

results, the associations between prostatitis or BPH and PCa were almost conclusive. 243

Some potential hypotheses had been put forward in the decades, regarding the correlations 244

between prostatitis, BPH and PCa. Inflammation was seen as highly correlated with several types 245

of cancers including colon, stomach, liver and bladder [36-39]. Chronic Inflammatory stimulating 246

could induce various chemokines and cytokines generation that provided a favorable 247

microenvironment for tumor growth and tumor progression by facilitating angiogenesis and 248

increasing the production of reactive oxygen species (ROS), which can lead to oxidative DNA 249

damage and reduced DNA repair [40]. Chronic inflammatory lesions could be commonly detected 250

in PCa patients when carrying out prostate biopsy [41]. Jiang et al. conducted a meta-analysis of 251

20 case-control studies and found a significant positive relationship between prostatitis and PCa 252

[12]. Herein, we included larger numbers of studies and demonstrated a likewise significant 253

relationship of prostatitis with PCa. However, which type of prostatitis was more inclined to 254

associate with a higher risk of PCa remained to be determined. 255

As for BPH and PCa, strong arguments that BPH and PCa were unrelated, have been 256

insisted in most urological surgeons on account of differences in the histologic and anatomic 257

location of these 2 conditions that BPH mostly occurs in transitional zone of prostate while PCa 258

often happen in peripheral zone [42]. Besides, BPH was primarily characterized by hyperplasia of 259

stromal, whereas PCa predominantly involves in the epithelium [42]. Nonetheless, parallel 260

features existed in the two diseases like hormone-dependent growth, response to 261

androgen-deprivation treatments and relation with old age [43]. Whether or not BPH could affect 262

tumorigenesis via reacting to epithelium-stromal, it remained undetermined [44]. On the other 263

hand, plenty of studies investigated the epidemiological relationship between BPH and PCa, and 264

found a positive effect of BPH on PCa risk [28, 45]. Accordingly, we pooled all the results of 265

available case-control or cohort studies to further shed light on their relationship and the results 266

showed significant relation. However, those patients with a history of BPH were more likely to 267

consult urologic physicians and perform a regular examination. As a result, increased the detection 268

rate of PCa was found and this might lead to detection bias compared with healthy controls. 269

Our results suggested that prostatitis and BPH could increase the risk of PCa. Then, what’s 270

the connection between prostatitis and BPH? Nunzio et al. found common inflammatory infiltrates 271

in BPH lesions and those cytokines and growth factors released by inflammatory cells could 272

stimulate the stroma and epithelial cells to hyperproliferation [46]. Taoka et al. reported that 273

asymptomatic histological inflammation could induce repeated damage, repair, and regeneration 274

of the prostate tissue, causing prostatic hyperplasia and leading to morphological changes of 275

stromal tissue, which could increase urination resistance and result in symptomatic BPH [47]. 276

Nevertheless, whether prostatitis could lead to BPH has not been widely approved by urological 277

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specialists. Hence, we searched for eligible epidemiological studies to illuminate the potential 278

relationship. A large number of cross-sectional studies have suggested that prostatitis and BPH are 279

closely related with each other [48-50]. A total of 1 case-control study and 1 cohort study were 280

included in meta-analysis meeting the inclusion criteria. It was found that the BPH cases were 281

more likely exposed to a prostatitis history than non-BPH controls [51]. Furthermore, Sauver and 282

his colleague conducted a 14-years follow-up cohort study and demonstrated the longitudinal 283

association between prostatitis and development of BPH [26]. 284

There were mainly four advantages in this article. On the one hand, this study was the first 285

time to explore the associations between prostatitis, BPH and PCa at the same time from an 286

epidemiological perspective and significant results were acquired. On the other hand, our study 287

was performed with the extremely strict inclusion criteria which eliminating the cross-section 288

studies in some surveys. Moreover, we performed strict quality evaluation by excluding 289

low-quality studies (NOS<7) while the previous reviews did not focus on the quality evaluation. 290

What’s more, we preformed in-depth statistical analysis and careful comparison of multiple 291

heterogeneous studies and tried our best to discussed the source of heterogeneity. However, the 292

previous studies of meta-analysis describing similar topic did not detailly explain the source of the 293

heterogeneity and deal with it. Herein, we firstly applied the approach of Galbraith plot to exclude 294

the outlier-studies and compared the results pre and post-elimination. Thus, the integrated results 295

are bound to elevated the reliability of our conclusions. 296

To a certain degree, several limitations of this paper should be considered: Firstly, the results 297

were based on unadjusted estimates without modifying the influences of some other covariates 298

like age and race; Secondly, the heterogeneity among enrolled studies was so huge that we have to 299

eliminate some studies with higher heterogeneity and we could not present more detailed 300

subgroup after analyzing the possible source of heterogeneity; Thirdly, prostatitis, BPH and PCa 301

were all multifactorial diseases that other factors like age, environment, lifestyle and inheritance 302

should also be taken into account as a whole. Fourthly, most included studies were case-control 303

study which were less reliable than cohort studies. Thus, more high-quality cohort studies were 304

required to shed light on the association between prostatitis, BPH and PCa. Last but not least, this 305

paper illustrated their triadic relationships only from the epidemiological perspective and could 306

not clarify whether or not progressive associations existed among prostatitis, BPH and PCa, as 307

hepatitis, liver cirrhosis and hepatocellular carcinoma did. 308

309

Acknowledgement 310

This work has been supported by the National Natural Science Funding of China (No. 311

81370781, 81670608, 81600514, 81400758). 312

313

Author Contributions Statement 314

QW.X, W.Z: Protocol/project development; 315

ZQ.Q, NH.S, R.L: Data collection or management; 316

W.W, XH.M: Data analysis; 317

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L.Z, Y.W, X.G: Manuscript writing/editing. 318

319

Conflict of interest 320

The authors declare no conflict of interest. 321

Data Availability 322

All data generated or analysed during this study are included in this published article (and its 323

Supplementary Information files). 324

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445

Supporting information 446

Table 1: Main characteristics of studies included in the meta-analysis to explore the association 447

between prostatitis and prostate cancer. 448

Table 2: Main characteristics of studies included in the meta-analysis to explore the association 449

between BPH and prostate cancer. 450

Table 3: Main characteristics of studies included in the meta-analysis to explore the association 451

between prostatitis and BPH. 452

453

Figure legends 454

Figure 1: Flow diagrams of the literature selection process. (A) Prostatitis and PCa; (B) BPH and 455

PCa; (C) Prostatitis and BPH. 456

Figure 2: Forest plots of association between prostatitis and PCa by analyzing all enrolled studies. 457

(A) Overall analysis; (B) The subgroup analyses of ethnicity; (C) study design; (D) sample size. 458

Figure 3: Galbraith plot associated with funnel plot and sensitive analysis of the association 459

between prostatitis and PCa. (A) Sensitive analysis before adjustment for heterogeneity; (B) 460

Funnel plot before adjustment for heterogeneity; (C) Galbraith plot before adjustment for 461

heterogeneity; (D) Sensitive analysis after adjustment for heterogeneity; (E) Funnel plot after 462

adjustment for heterogeneity; (F) Galbraith plot after adjustment for heterogeneity; 463

Figure 4: Forest plots of association between prostatitis and PCa after adjustment for 464

heterogeneity based on Galbraith plot associated with funnel plot and sensitive analysis. (A) 465

Overall analysis; (B) The subgroup analyses of ethnicity; (C) study design; (D) sample size. 466

Figure 5: Forest plots of association between BPH and PCa by analyzing all enrolled studies. (A) 467

Overall analysis; (B) The subgroup analyses of ethnicity; (C) study design; (D) sample size. 468

Figure 6: Galbraith plot associated with funnel plot and sensitive analysis of the association 469

between BPH and PCa. (A) Sensitive analysis before adjustment for heterogeneity; (B) Funnel 470

plot before adjustment for heterogeneity; (C) Galbraith plot before adjustment for heterogeneity; 471

(D) Sensitive analysis after adjustment for heterogeneity; (E) Funnel plot after adjustment for 472

heterogeneity; (F) Galbraith plot after adjustment for heterogeneity; 473

Figure 7: Forest plots of association between BPH and PCa after adjustment for heterogeneity 474

based on Galbraith plot associated with funnel plot and sensitive analysis. (A) Overall analysis; (B) 475

The subgroup analyses of ethnicity; (C) study design; (D) sample size. 476

Figure 8: Forest plots of association between prostatitis and BPH. 477

478

479

Supplementary materials 480

Table S1: References of 42 enrolled studies (S1-S42); 481

Table S2: Results of quality assessment; 482

Table S3: Results of meta-regression. 483

484

13 / 24

Table 1: Main characteristics of eligible studies explore the association between prostatitis and 485

prostate cancer; 486

Author Ye

ar

Ag

e

Coun

try

Ethni

city

S

O

C

Design Data

source

No.

cancer

cases

No.

control

s

No.

prostatitis in

cases

No. prostatitis

in controls

*DoatS1 20

17

40-

75

Franc

e

Cauc

asian

PB case-c

ontrol

intervie

w

819 879 84 63

Nair-Sha

llikerS2

20

17

19-

94

Austr

alia

Cauc

asian

PB case-c

ontrol

intervie

w

1181 875 97 25

RybickiS3 20

16

NA US Mixe

d

PB case-c

ontrol

Medical

record

574 574 102 105

*BoehmS

4

20

16

<76 Cana

da

Cauc

asian

PB case-c

ontrol

intervie

w

1884 1965 223 134

*SpenceS

5

20

14

40-

79

Cana

da

Cauc

asian

PB case-c

ontrol

intervie

w

1555 1586 195 115

HungS6 20

13

>50 China Asian PB case-c

ontrol

Medical

record

1184 4376 137 99

HennisS7 20

13

NA Barba

dian

Afric

an

PB case-c

ontrol

intervie

w

963 941 75 23

*Wright

S8

20

12

34-

74

US Cauc

asian

PB case-c

ontrol

intervie

w

1754 1645 217 132

*ChaoS9 20

10

45-

69

US Mixe

d

PB case-c

ontrol

intervie

w

1559 75384 139 4788

Weinma

nnS10

20

10

45–

84

US Mixe

d

PB case-c

ontrol

Medical

record

768 929 119 145

*HuangS

11

20

08

61-

69

US Cauc

asian

PB case-c

ontrol

intervie

w

868 1283 78 89

*Sutcliff

eS12

20

07

40

–75

US Cauc

asian

PB case-c

ontrol

intervie

w

691 691 152 124

SarmaS13 20

06

40-

79

US Afric

an

PB case-c

ontrol

intervie

w

129 706 34 47

*PatelS14 20

05

50-

74

US Mixe

d

PB case-c

ontrol

intervie

w

700 604 86 38

Rothman

S15

20

04

40-

64

US Cauc

asian

PB case-c

ontrol

intervie

w

750 702 660 644

*Roberts

S16

20

04

63-

77

US Cauc

asian

PB case-c

ontrol

Medical

record

409 803 41 50

Lightfoot

S17

20

04

45-

84

Cana

da

Cauc

asian

PB case-c

ontrol

intervie

w

760 1632 30 88

*Rosenbl

attS18

20

01

40-

64

US Cauc

asian

PB case-c

ontrol

intervie

w

753 703 87 57

*ZhuS19 19

99

40-

69

US Cauc

asian

PB case-c

ontrol

intervie

w

159 277 37 41

14 / 24

*LeeS20 19

98

45-

89

China Asian PB case-c

ontrol

intervie

w

133 265 32 16

*ZhuS21 19

96

40-

69

US Cauc

asian

PB case-c

ontrol

intervie

w

175 258 15 22

JohnS22 19

95

<85 US Mixe

d

PB case-c

ontrol

intervie

w

1642 1636 418 177

*HiattS23 19

94

NA US Mixe

d

PB case-c

ontrol

intervie

w

177 177 14 13

*HondaS

24

19

88

<60 US Cauc

asian

PB case-c

ontrol

intervie

w

211 211 39 18

*Vaarala

S25

20

16

20-

80

Finla

nd

Cauc

asian

PB cohort intervie

w

40 1732 13 238

*ChengS

26

20

10

45-

69

US Mixe

d

PB cohort intervie

w

1631 63613 147 4081

SutcliffeS

27

20

06

40

–75

US Cauc

asian

PB cohort intervie

w

2230 33356 421 5311

NA: Not available; SOC: Source of controls; PB: Population-based; HB: Hospital-based; S#: 487

Reference. 488

* Adjustment for heterogeneity performed by excluding relevant studies as the outliers spotted by 489

Galbraith plot and the possible major source of heterogeneity. 490 491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

15 / 24

Table 2: Main characteristics of eligible studies explore the association between BPH and prostate 515

cancer; 516

Author Ye

ar

Age Coun

try

Ethni

city

S

O

C

Design Data

source

No.

cancer

cases

No.

control

s

No. BPH

in cases

No. BPH in

controls

*Nair-Sha

llikerS2

20

17

19-

94

Austr

alia

Cauca

sian

PB case-co

ntrol

interview 1181 875 436 124

*HungS6 20

13

>50 China Asian PB case-co

ntrol

Medical

record

1184 4763 1084 1071

*HennisS7 20

13

NA Barba

dian

Africa

n

PB case-co

ntrol

interview 963 941 428 186

ChaoS9 20

10

45-

69

US Mixed PB case-co

ntrol

interview 1559 75384 514 14728

Weinmann

S10

20

10

45–

84

US Mixed PB case-co

ntrol

Medical

record

768 929 284 282

HuangS11 20

08

61-

69

US Cauca

sian

PB case-co

ntrol

interview 868 1283 258 306

*PatelS14 20

05

50-

74

US Mixed PB case-co

ntrol

interview 700 604 246 101

CokerS28 20

04

65–

79

US Mixed PB case-co

ntrol

interview 407 393 159 102

LightfootS1

7

20

04

45-

84

Canad

a

Cauca

sian

PB case-co

ntrol

interview 710 1543 103 315

*Rosenbla

ttS18

20

01

40-

64

US Cauca

sian

PB case-co

ntrol

interview 753 703 253 122

*ZhuS19 19

99

40-

69

US Cauca

sian

PB case-co

ntrol

interview 156 281 77 75

LeeS20 19

98

45-

89

China Asian H

B

case-co

ntrol

interview 133 265 64 36

ZhuS21 19

96

40-

69

US Cauca

sian

PB case-co

ntrol

interview 175 258 30 35

JohnS22 19

95

<85 US Mixed PB case-co

ntrol

interview 1642 1636 539 309

HiattS23 19

94

NA US Mixed PB case-co

ntrol

interview 177 177 68 61

*HondaS24 19

88

<60 US Cauca

sian

PB case-co

ntrol

interview 211 211 56 19

MishinaS29 19

85

45-

89

Janpa

n

Asian PB case-co

ntrol

interview 100 100 28 3

SchenkS30 20

11

≥55 US Cauca

sian

PB cohort interview 1225 2618 394 761

ØrstedS31 20

11

20-

100

Denm

ark

Cauca

sian

PB cohort interview 53171 794616 24486 161489

16 / 24

Greenwald

S32

19

74

<80 US Cauca

sian

H

B

cohort Medical

record

50 1590 24 814

*Armenie

nS33

19

74

NA US Cauca

sian

H

B

cohort Medical

record

45 566 35 271

NA: Not available; SOC: Source of controls; PB: Population-based; HB: Hospital-based; S#: 517

Reference. 518

* Adjustment for heterogeneity performed by excluding relevant studies as the outliers spotted by 519

Galbraith plot and the possible major source of heterogeneity. 520

521

522

Table 3: Main characteristics of eligible studies explore the association between prostatitis and 523

BPH; 524

Auth

or

Ye

ar

Ag

e

Cou

ntry

Ethni

city

SOC Desi

gn

Data

source

No. BPH

cases

No.

control

s

No. prostatitis

in cases

No. prostatitis

in controls

Sauve

rS34

20

08

40-

79

US Cauca

sian

cohort PB Medical

record

1921 527 176 20

NingS

35

20

03

60

+

Chin

a

Asian case-co

ntrol

PB interview 100 100 30 8

NA: Not available; SOC: Source of controls; PB: Population-based; HB: Hospital-based; S#: 525

Reference. 526

527

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

17 / 24

Figure 1 550

551 552

553

554

555

556

557

558

559

560

18 / 24

Figure 2 561

562 563

564

565

566

567

568

569

570

571

572

573

19 / 24

Figure 3 574

575

576

577

578

579

580

581

582

583

584

585

586

587

20 / 24

Figure 4 588

589

590

591

592

593

594

595

596

597

598

599

600

601

21 / 24

Figure 5 602

603 604

605

606

607

608

609

610

611

612

613

614

615

22 / 24

Figure 6 616

617

618

619

620

621

622

623

624

625

626

627

628

23 / 24

Figure 7 629

630 631

632

633

634

635

636

637

638

639

640

641

24 / 24

Figure 8 642

643

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Nonsteroidal anti-inflammatory drugs (NSAIDs) and prostate cancer risk: results from the EPICAP

study. Cancer Med 6(10), 2461-2470. doi: 10.1002/cam4.1186.

S2: Nair-Shalliker, V., Yap, S., Nunez, C., Egger, S., Rodger, J., Patel, M.I., et al. (2017). Adult body

size, sexual history and adolescent sexual development, may predict risk of developing prostate

cancer: Results from the New South Wales Lifestyle and Evaluation of Risk Study (CLEAR). Int J

Cancer 140(3), 565-574. doi: 10.1002/ijc.30471.

S3: Rybicki, B.A., Kryvenko, O.N., Wang, Y., Jankowski, M., Trudeau, S., Chitale, D.A., et al.

(2016). Racial differences in the relationship between clinical prostatitis, presence of inflammation

in benign prostate and subsequent risk of prostate cancer. Prostate Cancer Prostatic Dis 19(2), 145-

150. doi: 10.1038/pcan.2015.54.

S4: Boehm, K., Valdivieso, R., Meskawi, M., Larcher, A., Schiffmann, J., Sun, M., et al. (2016).

Prostatitis, other genitourinary infections and prostate cancer: results from a population-based case-

control study. World J Urol 34(3), 425-430. doi: 10.1007/s00345-015-1625-1.

S5: Spence, A.R., Rousseau, M.C., Karakiewicz, P.I., and Parent, M.E. (2014). Circumcision and

prostate cancer: a population-based case-control study in Montreal, Canada. BJU Int 114(6b), E90-

E98. doi: 10.1111/bju.12741.

S6: Hung, S.-C., Lai, S.-W., Tsai, P.-Y., Chen, P.-C., Wu, H.-C., Lin, W.-H., et al. (2013). Synergistic

interaction of benign prostatic hyperplasia and prostatitis on prostate cancer risk. British Journal of

Cancer 108(9), 1778-1783. doi: 10.1038/bjc.2013.184.

S7: Hennis, A.J., Wu, S.Y., Nemesure, B., and Leske, M.C. (2013). Urologic characteristics and

sexual behaviors associated with prostate cancer in an african-Caribbean population in barbados,

west indies. Prostate Cancer 2013, 682750. doi: 10.1155/2013/682750.

S8: Wright, J.L., Lin, D.W., and Stanford, J.L. (2012). Circumcision and the risk of prostate cancer.

Cancer 118(18), 4437-4443. doi: 10.1002/cncr.26653.

S9: Chao, C., Haque, R., Van Den Eeden, S.K., Caan, B.J., Poon, K.Y., and Quinn, V.P. (2010). Red

wine consumption and risk of prostate cancer: the California men's health study. Int J Cancer 126(1),

171-179. doi: 10.1002/ijc.24637.

S10: Weinmann, S., Shapiro, J.A., Rybicki, B.A., Enger, S.M., Van Den Eeden, S.K., Richert-Boe,

K.E., et al. (2010). Medical history, body size, and cigarette smoking in relation to fatal prostate

cancer. Cancer Causes Control 21(1), 117-125. doi: 10.1007/s10552-009-9441-9.

S11: Huang, W.Y., Hayes, R., Pfeiffer, R., Viscidi, R.P., Lee, F.K., Wang, Y.F., et al. (2008). Sexually

transmissible infections and prostate cancer risk. Cancer Epidemiol Biomarkers Prev 17(9), 2374-

2381. doi: 10.1158/1055-9965.EPI-08-0173.

S12: Sutcliffe, S., Giovannucci, E., Gaydos, C.A., Viscidi, R.P., Jenkins, F.J., Zenilman, J.M., et al.

(2007). Plasma antibodies against Chlamydia trachomatis, human papillomavirus, and human

herpesvirus type 8 in relation to prostate cancer: a prospective study. Cancer Epidemiol Biomarkers

Prev 16(8), 1573-1580. doi: 10.1158/1055-9965.EPI-07-0134.

S13: Sarma, A.V., McLaughlin, J.C., Wallner, L.P., Dunn, R.L., Cooney, K.A., Schottenfeld, D., et

al. (2006). Sexual behavior, sexually transmitted diseases and prostatitis: the risk of prostate cancer

in black men. J Urol 176(3), 1108-1113. doi: 10.1016/j.juro.2006.04.075.

S14: Patel, D.A., Bock, C.H., Schwartz, K., Wenzlaff, A.S., Demers, R.Y., and Severson, R.K.

(2005). Sexually transmitted diseases and other urogenital conditions as risk factors for prostate

cancer: a case–control study in Wayne County, Michigan. Cancer Causes & Control 16(3), 263-273.

doi: 10.1007/s10552-004-3486-6.

S15: Rothman, I., Stanford, J.L., Kuniyuki, A., and Berger, R.E. (2004). Self-report of prostatitis

and its risk factors in a random sample of middle-aged men. Urology 64(5), 876-879. doi:

10.1016/j.urology.2004.06.071.

S16: Roberts, R.O., Bergstralh, E.J., Bass, S.E., Lieber, M.M., and Jacobsen, S.J. (2004). Prostatitis

as a risk factor for prostate cancer. Epidemiology 15(1), 93-99. doi:

10.1097/01.ede.0000101022.38330.7c.

S17: Lightfoot, N., Conlon, M., Kreiger, N., Sass-Kortsak, A., Purdham, J., and Darlington, G.

(2004). Medical history, sexual, and maturational factors and prostate cancer risk. Ann Epidemiol

14(9), 655-662. doi: 10.1016/j.annepidem.2003.11.006.

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prostate cancer. Am J Epidemiol 153(12), 1152-1158.

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self-report data and medical records data: results from a case-control study on prostate cancer. Int J

Epidemiol 28(3), 409-417.

S20: Lee, M.M., Wang, R.T., Hsing, A.W., Gu, F.L., Wang, T., and Spitz, M. (1998). Case-control

study of diet and prostate cancer in China. Cancer Causes Control 9(6), 545-552.

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Vasectomy and prostate cancer: a case-control study in a health maintenance organization. Am J

Epidemiol 144(8), 717-722.

S22: John, E.M., Whittemore, A.S., Wu, A.H., Kolonel, L.N., Hislop, T.G., Howe, G.R., et al. (1995).

Vasectomy and prostate cancer: results from a multiethnic case-control study. J Natl Cancer Inst

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S23: Hiatt, R.A., Armstrong, M.A., Klatsky, A.L., and Sidney, S. (1994). Alcohol consumption,

smoking, and other risk factors and prostate cancer in a large health plan cohort in California (United

States). Cancer Causes Control 5(1), 66-72.

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Vasectomy, cigarette smoking, and age at first sexual intercourse as risk factors for prostate cancer

in middle-aged men. Br J Cancer 57(3), 326-331.

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in men with self-reported prostatitis after 15 years of follow-up. Oncol Lett 12(2), 1149-1153. doi:

10.3892/ol.2016.4702.

S26: Cheng, I., Witte, J.S., Jacobsen, S.J., Haque, R., Quinn, V.P., Quesenberry, C.P., et al. (2010).

Prostatitis, sexually transmitted diseases, and prostate cancer: the California Men's Health Study.

PLoS One 5(1), e8736. doi: 10.1371/journal.pone.0008736.

S27: Sutcliffe, S., Giovannucci, E., De Marzo, A.M., Leitzmann, M.F., Willett, W.C., and Platz, E.A.

(2006). Gonorrhea, syphilis, clinical prostatitis, and the risk of prostate cancer. Cancer Epidemiol

Biomarkers Prev 15(11), 2160-2166. doi: 10.1158/1055-9965.EPI-05-0913.

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prostate cancer risk among older men: population-based case-control study. Br J Cancer 90(11),

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Table S2: Results of quality assessment;

1: Quality assessment of 34 individual studies on association between prostatitis and prostate cancer.

Case control study SELECTION Comparability Exposure

Is the Case Definition

Adequate?

Representativeness of

the Cases

Selection of

Controls

Definition of Controls Comparability of cases

and controls on the basis

of the design or analysis

Ascertainment of

exposure

Same method of

ascertainment for

cases and controls

Non-

Response rate

Total

Qadire2018 * *

* * * *

6

Doat2017 * * * * * * * * 8

Nair-Shalliker2017 * * * * ** * * * 9

Rybicki2016 * * * * *

* * 7

Boehm2016 * * * * *

* * 7

Spence2014 * * * * ** * *

8

Hung2013 * * * * * * * * 8

Hennis2013 * * * * * * *

7

Wright2012 * * * * * * * * 8

Hosseini2010 * * * * *

*

6

Chao2010 * * * * * * * * 8

Weinmann2010 *

* * * * * * 7

Daniels2009 *

*

* * *

5

Huang2008 * * * * *

* * 7

Sutcliffe2007 * * * * **

*

7

Pelucchi2006 * *

* * *

5

Sarma2006 * * * * * * *

7

Patel2005 * * * * *

* * 7

Rothman2004 * * * * * * *

7

Roberts2004 * * * * ** * *

8

Lightfoot2004 * * * * * * *

7

Ritchie2003 * * * * *

*

6

Rosenblatt2001 * * * * * * *

7

Zhu1999 * * * * *

* * 7

Lee1998 * * * * **

*

7

Zhu1996 * * * * * * *

7

John1995 * * * * * * *

7

Hsing1994 * *

* * * *

6

Hiatt1994 *

* * * * * * 7

Wei1994 *

* * * *

5

Honda1988 * * * * * * *

7

Cohort study SELECTION Comparability Outcome

Representativeness of

the exposed cohort

Selection of the non

exposed cohort

Ascertainment of

exposure

Demonstration that

outcome of interest was

not present at start of

study

Comparability of cohorts

on the basis of the design

or analysis

Assessment of

outcome

Was follow-up long

enough for outcomes

to occur

Adequacy of

follow up of

cohorts

Total

Vaarala2016 * * * * * * * * 8

Cheng2010 * * * * * * *

7

Sutcliffe2006 * * * * ** * * * 9

2: Quality assessment of 25 individual studies on association between BPH and prostate cancer.

Case control study SELECTION Comparability Exposure

Is the Case Definition

Adequate?

Representativeness of

the Cases

Selection of

Controls

Definition of Controls Comparability of cases and

controls on the basis of the

design or analysis

Ascertainment

of exposure

Same method of

ascertainment for

cases and controls

Non-Response

rate

Total

Nair-Shalliker2017 * * * * ** * * * 9

Hung2013 * * * * * * * * 8

Hennis2013 * * * * * * *

7

Chao2010 * * * * * * * * 8

Weinmann2010 *

* * * * * * 7

Daniels2009 *

*

* * *

5

Huang2008 * * * * *

* * 7

Pelucchi2006 * *

* * *

5

Patel2005 * * * * *

* * 7

Coker2004 * * * * ** * *

8

Lightfoot2004 * * * * * * *

7

Rosenblatt2001 * * * * * * *

7

Zhu1999 * * * * *

* * 7

Lee1998 * * * * **

*

7

Zhu1996 * * * * * * *

7

John1995 * * * * * * *

7

Hsing1994 * *

* * * *

6

Hiatt1994 *

* * * * * * 7

Wei1994 *

* * * *

5

Honda1988 * * * * * * *

7

Mishina1985 * * * * * * *

7

Cohort study SELECTION Comparability Outcome

Representativeness of

the exposed cohort

Selection of the non

exposed cohort

Ascertainment

of exposure

Demonstration that

outcome of interest was

not present at start of

study

Comparability of cohorts

on the basis of the design or

analysis

Assessment of

outcome

Was follow-up long

enough for outcomes

to occur

Adequacy of

follow up of

cohorts

Total

Schenk2011 * * * * ** * *

8

Ørsted2011 * * * * ** * * * 9

Greenwald1974 *

* * ** * * * 8

Armenien1974 *

* * ** * * * 8

3: Quality assessment of 4 individual studies on association between prostatitis and BPH.

Case control

study

SELECTION Comparability Exposure

Is the Case Definition

Adequate?

Representativeness of

the Cases

Selection of

Controls

Definition of Controls Comparability of cases and

controls on the basis of the

design or analysis

Ascertainment of

exposure

Same method of

ascertainment for

cases and controls

Non-Response

rate

Total

Ning2003 * * *

* * * * 7

Cohort study SELECTION Comparability Outcome

Representativeness of

the exposed cohort

Selection of the non

exposed cohort

Ascertainment of

exposure

Demonstration that

outcome of interest was not

present at start of study

Comparability of cohorts on

the basis of the design or

analysis

Assessment of

outcome

Was follow-up long

enough for outcomes

to occur

Adequacy of

follow up of

cohorts

Total

Sauver2009 * * * * * *

* 7

Table S3: Results of meta-regression.

Meta Regression Prostatitis and PCa BPH and PCa

Covariate P value

Country 0.041 0.433

Ethnicity 0.003 0.904

Sources of exposure assessment 0.969 0.673

public year 0.79 0.618

Samplesize 0.124 0.44

Design 0.871 0.599

SOC - 0.637