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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: [email protected] 17
TEL: +08613901595401 18
19
Qianwei Xing 20
Department of Urology, The Affiliated Hospital of Nantong University, Nantong, 226001, China. 21
E-mail: [email protected] 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
136
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
190
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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
7 / 24
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
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control study. World J Urol 34(3), 425-430. doi: 10.1007/s00345-015-1625-1.
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prostate cancer: a population-based case-control study in Montreal, Canada. BJU Int 114(6b), E90-
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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