Abstract
Introduction:
Correlation between zonal origin of clinically localized prostate cancer (PC) and biochemical recurrence (BCR) after treatment is still controversial.
Methods:
We performed a meta-analysis of published articles to investigate the prognostic value of zonal origin in clinically localized PC. Literature was searched from Medline, Embase, Scopus, and Web of Science, from inception to Nov 1st, 2022. The risk of BCR was compared between PC originating from transition zone with peripheral zone. Relative risk (RR) was pooled in a random-effects model. Subgroup analysis and meta-regression were conducted to assess the source of heterogeneity.
Results:
16 cohorts and 19,365 patients were included. PC originating from transition zone was associated with a lower risk of BCR (RR, 0.79, 95%CI; 0.69-0.92, I2, 76.8%). The association was consistent in studies with median follow-up time ≥60 months (RR, 0.65; 95%CI, 0.48 to 0.88, I2 56.8%), studies with NOS score ≥8 (RR, 0.70; 95%CI, 0.62 to 0.80, I2 32.4%), and studies using multivariate regression model (RR, 0.57; 95%CI, 0.48 to 0.69, I2 23%).
Discussion:
This meta-analysis supported that transition zone origin was an independent prognostic factor of a better biochemical result in clinically localized prostate cancer after treatment.
Systematic review registration:
10.37766/inplasy2023.11.0100, identifier INPLASY2023110100.
1 Introduction
Prostate cancer (PC) is the second most common cancer in men and the sixth most common cause of cancer death worldwide in 2020, causing >350,000 death in men (). In most men, prostate cancer is diagnosed while the disease is confined within the prostate (), which is termed localized prostate cancer. Initial treatment of clinically localized PC includes radical prostatectomy (RP), radiotherapy (RT), hormonal therapy, and deferred treatments such as active surveillance and watchful waiting (–). However, after RP or RT with curative intent, up to 27–53% of these patients experience biochemical recurrence (BCR) (). BCR is considered as an early event indicating disease progression and is related to a higher risk of metastasis and disease-specific mortality. To estimate the risks of BCR, D’Amico classification system was developed and verified. Now the derivatives of D’Amico system are widely used in clinical practice (–). However, the best stratification and optimal treatment remain controversial ().
The human prostate was histologically divided into transition zone (TZ), peripheral zone (PZ), central zone (CZ), and anterior fibromuscular stroma (AFMS) by McNeal (). Approximately 25%, 70%, and 5% of prostate cancer originate respectively from TZ, PZ, and CZ (). Heterogeneity has been found between prostate cancers with different zonal origins. Compared with PZ tumors, most TZ tumors are usually diagnosed with larger volume and higher prostatic specific antigen (PSA) levels, but with earlier T stage and lower Gleason scores, indicating that TZ tumors might have better biological behavior. Some studies suggested that zonal origin in TZ was associated with a lower risk of BCR (, ). Conversely, other studies found no significant differences in 5-year biochemical relapse-free survival between TZ tumors and PZ tumors (). Information about CZ tumors is limited due to scarcity (). Therefore, the prognostic role of zonal origin in prostate cancer is still controversial.
Considering that most of the previous studies are retrospective single-institutional, we aim to conduct a meta-analysis of all eligible published studies to quantify the prognostic value of zonal origin in prostate cancer.
2 Methods
2.1 Search strategy
We conducted this meta-analysis according to the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines and Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines (, ). The Medline, Embase, Scopus, Web of Science, and Cochrane databases were searched from inception to November 1st, 2022 for human studies investigating the association between zonal origin and BCR in prostate cancer. The main search terms included: (zone or zonal) and (prostate or prostatic) and (cancer carcinoma) and (recurrence or failure or relapse). The reference lists of retrieved articles were also checked for relevant articles.
2.2 Eligibility criteria
Inclusion criteria for selecting the studies were as follows: (i) The diagnosis of prostate cancer was pathologically confirmed; (ii) Zonal origin was defined as the zone which contains most part of the index tumor with the highest Gleason score; (iii) Correlation of zonal origin with BCR was reported. Exclusion criteria were the following: (i) Abstracts, letters, case reports, reviews, or nonclinical studies; (ii) Studies were not written in English; (iii) Studies with insufficient data for estimating relative risk (RR), odds ratio (OR), hazard ratio (HR), or 95% confidence interval (CI); (iv) Studies with duplicate data. Initial screening of the title and abstract, full-text assessment, and subsequent data extraction were independently performed by two authors (SJJ and LYW). Disagreements were discussed and resolved by consensus with a third reviewer (ZL).
2.3 Data extraction and quality evaluation
The following items were extracted from each included study: authors, year of publication, country, the proportion of different ethnic groups, study design, number of cases, treatment, follow-up time, the definition of zonal origin, the definition of BCR, and confounding factors which were balanced or adjusted. RR, HR, or OR were directly extracted from literature, or indirectly estimated from Kaplan-Meier curves according to the methods illustrated by Parmer et al, together with the 95% CI (). If results of both univariate and multivariate Cox regression analysis were reported, we chose the multivariate model for a more accurate estimate. We used RR to represent various effect estimates. A RR <1 indicated a better prognosis for prostate cancer originating in transition zone. To evaluate the methodological quality and grade the evidence of included studies, the Newcastle–Ottawa Scale (NOS) (range 1–9 scores) was used (). NOS scores of ≥8 were defined as high-quality studies.
2.4 Statistical analysis
We pooled RRs and 95% CIs using random-effects models and fixed-effects models according to the heterogeneity evaluated by Cochran’s Q test and Higgins I-squared statistic (). An I2 > 50% was considered as significant heterogeneity and a random-effects model (DerSimonian–Laird method) was used. Otherwise, the fixed-effects model (Mantel–Haenszel method) was adopted (). A subgroup analysis was performed based on variables including major ethnic group, sample size, median follow-up time, regression model type (univariate or multivariate), RR source (direct extraction or indirect estimate), NOS total score, the definition of BCR, the definition of TZ origin (on MRI or pathological sections), pre-treatment PSA level, the ratio of Gleason grade group ≥2, and the ratio of T stage ≥T3. Sensitivity analysis was conducted by omitting one study at a time, generating the pooled estimates, and comparing them with the original estimates. Funnel plots, Begg’s test, and Egger’s test were performed to assess publication bias (, ). All analysis was performed using STATA/SE 12.0 (STATA, College Station, TX). Statistical significance was defined as two-tailed alpha <0.05.
3 Results
3.1 Study selection and characteristics
As shown in Figure 1, the literature search initially identified 1684 papers. 36 studies were included in the full-text assessment. Finally, 14 studies, published from 2000 to 2022, were enrolled in the final mete-analysis (, –). Among these, 13 were cohort studies and 1 was case-control. Studies were conducted in France (n=1), Germany (n=1), Brazil (n=1), USA (n=5), Korea (n=2), Japan (n=3), and Australis (n=1). Since Kim and Teloken’s studies both contained two distinct cohorts, there were 16 cohorts in the meta-analysis. Their detailed characteristics are listed in Table 1; Table S1.
Figure 1
Table 1
| Studies | Year | Country | Cohort size | Treatment | Follow-up (months) | Definition of TZ tumors | Ratio of TZ tumors | Definition of BCR (PSA messured as ng/ml) | RRs a | Counfounders balanced or adjusted b | NOS score |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Asuncion ( | 2022 | France | 230 | RT | 104.4 | MRI | 11.1 | nadir + 2 | RR(U,I) | N | 7 |
| Billis ( | 2017 | Brazil | 345 | RP | 45.9 | PS | 31.9 | 0.2 | HR(U,D) | 12568 | 8 |
| Chun ( | 2007 | Germany | 1262 | RP | 45.1 | PS | 9.1 | 0.1 | RR(U,I) | 7 | 7 |
| Falzarano ( | 2020 | USA | 485 | RP | 14.1 | PS | 27.2 | 0.2 | OR(U,I) | 1238 | 9 |
| Iremashvili ( | 2012 | USA | 1441 | RP | 42 | PS | 11 | 0.2 | HR(M,D) | 1235678 | 9 |
| Kim1 ( | 2020 | Korea | 1521 | RP | N | PS | 29.7 | N | HR(U,D) | 1 | 4 |
| Kim2 ( | 2020 | Korea | 2302 | RP | N | PS | 29.7 | N | HR(U,D) | 1 | 4 |
| Lee ( | 2015 | USA | 1354 | RP | 84 | PS | 17 | 0.1 | HR(M,D) | 12345678 | 9 |
| Magheli ( | 2007 | USA | 265 | RP | 81.6 | PS | 19 | 0.2 | RR(U,I) | 134578 | 8 |
| Mygatt ( | 2014 | USA | 1528 | RP | 90 | PS | 10.1 | 0.2 | RR(U,I) | 12 | 8 |
| Sakai ( | 2006 | Japan | 134 | RP | 37 | PS | 20.1 | 0.2 | RR(U,I) | 123678 | 9 |
| Sato ( | 2021 | Japan | 270 | RP | 93.8 | PS | 34.4 | 0.2 | HR(M,D) | 123478 | 9 |
| Shin (32) | 2020 | Korea | 232 | RP | 18 | MRI | 27.6 | 0.2 | HR(M,D) | 345 | 7 |
| Takamatsu ( | 2019 | Japan | 638 | RP | 59 | PS | 46 | 0.2 | HR(M,D) | 123478 | 9 |
| Teloken1 ( | 2017 | Australia | 2677 | RP | 31.8 | PS | 10.2 | 0.2 | HR(M,D) | 134568 | 8 |
| Teloken2 ( | 2017 | Australia | 4374 | RP | 39.8 | PS | 25.1 | 0.2 | HR(U,D) | 67 | 7 |
Characteristics of included studies.
TZ, transition zone; BCR, biochemical recurrence; PSA, prostatic specific antigen; RT, radiation therapy; RP, radical prostatectomy; MRI, magnetic resonance imaging; PS, pathological sections; N, not available.
Type of relative risk and its source: RR, relative risk; OR, odds ratio; HR, hazard ratio; U, univariate analysis; M, multivariate analysis; D, directly extracted from the text; I, indirectly estimated from the text or Kaplan-Meier curve.
Confounders balanced between TZ/PZ group in baseline data and counfounders adjusted in multivariate regression analysis: 1, age; 2, T stage; 3, Gleason score/Gleason grade/ISUP group; 4, PSA level before treatment; 5, extraprostatic expansion; 6, seminal vesicle invasion; 7, lymph node involvement; 8, positive surgical margin.
Among the 16 cohorts, sample sizes ranged from 134 to 4374, with a median of 950. The median/mean age ranged from 58.7 to 68.5. The median follow-up time ranged from 18 months to 104.4 months. The ratio of TZ tumors ranged from 9.1% to 46%, and PZ tumors from 54% to 90.1%. CZ tumors were not separately reported in 14 cohorts. In the other 2 cohorts, CZ tumors were excluded from the prognostic analysis. As a result, we can only compare the prognosis of TZ tumors and PZ tumors. Regarding the reported data on prognostic indicators, the median pre-treatment PSA level ranged from 5.7 to 32.2 ng/ml. The ratio of prostate cancer with Gleason grade ≥2 ranged from 34.8% to 100%. And the ratio of prostate cancer with pathological T stage ≥ T3 ranged from 25.5% to 49.3%. Patients undertook RP in 15 cohorts and RT in 1 cohort. The use of neoadjuvant or adjuvant therapy were summarized in Table S2. Most RP cohorts excluded patients who received neoadjuvant or adjuvant therapy.
3.2 Risk of bias and quality assessment
The methodological quality profile of included studies according to NOS is shown in Table S3. The mean NOS score was 7.625. Only one study showed a high risk of bias because it was conference literature and lacked detailed methodological data (
3.3 Overall analysis
Because the heterogeneity test showed a high level of heterogeneity (I2 = 76.8%, p<0.01) between the studies, a random-effects model was used for the analysis (see Figure 2). A pooled RR of 0.79 (95%CI, 0.69-0.92; p<0.01) showed that clinically localized PC originating from the transition zone were associated with a better outcome in terms of biochemical-free survival.
Figure 2

Forest plot of the association between transition zonal origin and biochemical recurrence. Diamonds represent study-specific relative risks or summary relative risks with 95% CIs. Horizontal lines represent 95% CIs. A RR<1 represents better prognosis of TZ tumors.
3.4 Subgroup analysis and meta-regression
Given the high heterogeneity showed through the I2 statistic, a subgroup analysis and a meta-regression were performed based on the following variables: major ethnic group (Caucasian or eastern Asian), sample size (<1000 or≥1000), median follow-up time (<60m or ≥60m), regression model type (univariate or multivariate), RR source (directly extraction or indirectly estimate), NOS total score(<8, ≥8), BCR definition (0.1 ng/ml or 0.2 ng/ml), definition of TZ origin (on MRI or pathological sections), PSA level (<10 ng/ml or ≥10 ng/ml), ratio of Gleason grade group ≥2 (<80% or ≥80%), and ratio of T stage ≥T3 (<40% or ≥40%). In the subgroup analysis shown in Table 2, regardless of the grouping variables used, I2 of the subgroups could not drop below 50% at the same time. In the meta-regression shown in Table 3, regression model type (P=0.002) and NOS score (P=0.025) were found to be possible sources of heterogeneity, but the residual I2 was still high than 50% (64.45% for regression model type and 69.79% for NOS score), indicating that they could only explain part of the heterogeneity.
Table 2
| Analysis | N | Reference | Random-effects model | Fixed-effects model | Heterogeneity | |||
|---|---|---|---|---|---|---|---|---|
| RR | 95%CI | RR | 95%CI | I2 | Ph | |||
| Subgroup1:Caucasian | 10 | ( | 0.79 | 0.62-1.00 | 77.8 | <0.001 | ||
| Eastern Asian | 6 | ( | 0.75 | 0.56-1.00 | 76.6 | 0.001 | ||
| Subgroup2: Sample size <1000 | 8 | ( | 0.66 | 0.51-0.85 | 0.69 | 0.59-0.81 | 48.4 | 0.059 |
| Sample size ≥1000 | 8 | ( | 0.89 | 0.75-1.05 | 82 | <0.001 | ||
| Subgroup3: Median follow-up time <60m | 9 | ( | 0.77 | 0.58-1.03 | 78.4 | <0.001 | ||
| Median follow-up time ≥60m | 5 | ( | 0.65 | 0.48-0.88 | 56.8 | 0.055 | ||
| Subgroup4: Univariate | 10 | ( | 0.94 | 0.82-1.09 | 72.6 | <0.001 | ||
| Multivariate | 6 | ( | 0.56 | 0.45-0.70 | 0.57 | 0.48-0.69 | 23 | 0.261 |
| Subgroup5: RR directly extracted | 10 | ( | 0.76 | 0.63-0.92 | 84.9 | <0.001 | ||
| RR indirectly estimated | 6 | ( | 0.82 | 0.69-0.98 | 0.82 | 0.69-0.98 | 0 | 0.584 |
| Subgroup6: NOS score < 8 | 6 | ( | 0.98 | 0.78-1.23 | 84.9 | <0.001 | ||
| NOS score ≥ 8 | 10 | ( | 0.70 | 0.60-0.82 | 0.70 | 062-0.80 | 32.4 | 0.149 |
| Subgroup7: BCR with cut-off of 0.1ng/ml | 2 | ( | 0.68 | 0.50-0.93 | 0.68 | 0.50-0.93 | 0 | 0.351 |
| BCR with cut-off of 0.2ng/ml | 11 | ( | 0.73 | 0.56-0.95 | 82.1 | <0.001 | ||
| Subgroup8: TZ origin defined on MRI | 2 | ( | 0.25 | 0.09-0.73 | 0.25 | 0.09-0.73 | 0 | 0.369 |
| TZ origin defined on pathological section | 14 | ( | 0.81 | 0.71-0.94 | 77.7 | <0.001 | ||
| Subgroup9: median/mean PSA < 10ng/ml | 9 | ( | 0.68 | 0.49-0.94 | 84.4 | <0.001 | ||
| median/mean PSA > 10ng/ml | 6 | ( | 0.91 | 0.83-0.99 | 0.91 | 0.88-0.94 | 14.8 | 0.319 |
| Subgroup10: Ratio of Grg≥2: <80% | 6 | ( | 0.93 | 0.76-1.14 | 15.0 | 0.318 | ||
| Ratio of Grg≥2: ≥80% | 9 | ( | 0.74 | 0.60-0.90 | 0.95 | 0.80-1.13 | 86.2 | <0.001 |
| Subgroup11: Ratio of T stage≥T3: <40% | 3 | ( | 0.78 | 0.58-1.04 | 0.78 | 0.61-1.00 | 28.8 | 0.246 |
| Ratio of T stage≥T3: ≥40% | 3 | ( | 0.69 | 0.37-1.29 | 76.6 | 0.014 | ||
Subgroup analysis of the pooled association of transition zonal origin with biochemical recurrence.
N, number of cohorts; RR, relative risk; CI, confidence interval; BCR, biochemical recurrence; TZ, transition zone; PSA, prostatic specific antigen; Grg, Gleason grade group.
Table 3
| Variables | Univariate analysis | ||
|---|---|---|---|
| Coefficienct | P | 95%CI | |
| Major ethnic group: Eastern Asian v.s. Gaucasion | -0.059 | 0.768 | -0.477to0.360 |
| Sample size: Larger v.s. Smaller | 0.279 | 0.128 | -0.091to0.650 |
| Follow-up time: ≥60m v.s. <60m | -0.239 | 0.250 | -0.672to0.192 |
| Multivariate RR v.s. Univariate RR | -0.528 | 0.002 | -0.820to-0.236 |
| RR was directly extracted v.s. RR was indirectly estimated | -0.134 | 0.509 | -0.559to0.290 |
| Total NOS score: ≥8 v.s. <8 | -0.358 | 0.025 | -0.663to-0.052 |
| Definition of BCR: 0.2ng/ml v.s. others | -0.120 | 0.554 | -0.547to0.306 |
| Definition of TZ origin: MRI v.s. pathological sections | 0.094 | 0.685 | -0.413to0.601 |
| Median/mean PSA level: ≥10ng/ml v.s. <10ng/ml | 0.256 | 0.148 | -0.104to0.616 |
| Ratio of Grg≥2: ≥80% v.s. <80% | -0.202 | 0.344 | -0.645to0.242 |
| Ratio of T stage≥T3: ≥40% v.s. <40% | -0.095 | 0.801 | -1.070to0.881 |
Meta-regression analysis for exploring potential sources of heterogeneity.
CI, confidence interval; BCR, biochemical recurrence; TZ, transition zone; PSA, prostatic specific antigen; Grg, Gleason grade group.
Results of specific subgroup analysis were consistent with the overall analysis, supporting the prognostic value of TZ origin. The pooled RR was 0.79 (95%CI, 0.69 to 0.92) in studies with long follow-up time (median follow-up time ≥60m), in a random-effects model (I2, 76.8%). The pooled RR was 0.70 (95%CI, 0.62 to 0.80) in high-quality studies (NOS≥8), in a fixed-effects model (I2, 32.4%). When we restricted the meta-analysis to studies using a multivariate regression model only, the pooled RR was 0.57 (95%CI, 0.48 to 0.69) in a fixed-effects model (I2, 23%). Another valuable finding of subgroup analysis was that in the higher Gleason grade subgroup (ratio of Grg≥2 was higher than 80%), the pooled RR was 0.74 (95%CI, 0.60 to 0.90), in contrast with 0.93(95%CI, 0.76 to 1.14) in the lower Gleason grade subgroup (ratio of Grg≥2 was lower than 80%), both in random-effects models (see Figure S1).
3.5 Sensitivity and publication bias analysis
The sensitivity analysis (see Figure S2; Table S4) confirmed the stability of the association between zonal origin and BCR because the pooled RR remained stable if a certain cohort was omitted. For example, if we left out the cohort ‘Kim1’ with the highest weight (12.22%), the pooled RR turned out to be 0.75 (95% CI, 0.61 to 0.93), which was even more significant. The funnel plot (see Figure S3), Begg’s test, and Egger’s test did not indicate the existence of obvious bias. Pr>|z| was 0.392 for Begg’s test and P>|t| was 0.128 for Egger’s test.
4 Discussion
4.1 Principal findings
In this meta-analysis, pooling all available data to estimate the prognostic value of zonal origin in clinically localized prostate cancer, we found that patients with prostate cancer originating from the transition zone have a lower risk of BCR compared with patients with prostate cancer originating from the peripheral zone (RR, 0.79; 95%CI, 0.69-0.92). The result was robust in sensitivity analysis and no publication bias was observed. This association should be considered cautiously as there was high heterogeneity in the overall analysis (I2, 76.8%). Nevertheless, it was supported by subgroup analysis in high-quality literature with NOS ≥8 (RR, 0.70; 95%CI, 0.62-0.80; I2, 32.4%). To our acknowledgment, this was the first meta-analysis about the prognostic value of zonal origin of clinically localized prostate cancer. Our results suggest that the association of zonal origin with BCR merits consideration.
4.2 Possible mechanisms for principal findings
Previous studies had indicated the difference between prostate cancer originating from different zones. In patients receiving prostatectomy (
Regarding the prognosis after treatment with curative intent, conclusions were not consistent. One explanation for this phenomenon is that most of the previous studies did not control confounding factors such as tumor stage, Gleason grade group, and surgical margin. Augustin (
Molecular biology might help to reveal the fundamental differences between TZ and PZ tumors. Adler (
4.3 Secondary findings
One interesting finding in our meta-analysis was the different prognostic role of TZ origin between the high Gleason grade group and the low Gleason grade group. In Kim’s (
Another point worth discussing is that two of our included studies (
4.4 Limitations
Our study had several limitations. First was the heterogeneity. Though we used subgroup analysis and meta-regression, only the regression model type were identified as possible sources of heterogeneity and they could only explain a limited part of the heterogeneity. Secondly, RRs were indirectly estimated from 6 cohorts, which might introduce errors. However, subgroup analysis showed that the prognostic value was still significant and not changed much when we considered the source of RRs. Thirdly, only one study of radiation therapy and no study of active surveillance were included, because there is a lack of relevant literature. As a result, our result was unsuitable for patients who received radiation therapy or active surveillance. We expect relevant research to fill this gap in the future. Finally, there was a language bias, since our search included only studies written in English. In the future, we plan to focus on the prognostic value of zonal origin specifically in high-grade group prostate cancer, and include high-quality studies to decrease the heterogeneity.
5 Conclusion
In conclusion, our study supports that tumor location is an independent prognostic indicator of BCR after radical prostatectomy and is promising to be included in the postoperative risk stratification system. Prostate tumors originating from the transition zone might be a different clinical entity with a better prognosis. The biological mechanisms behind such correlation remained partially unclear, and thus better designed epidemiological and mechanistic studies were necessary to clarify the underlying mechanism. More radiation therapy cohorts and active surveillance cohorts are also desperately needed to verify the prognostic value of zonal origin in such patients.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.
Author contributions
SJ, LW, and WY were responsible for the conception and design of the review. SJ, LW, and ZL contributed to the data acquisition and interpretation. SJ and ZL were responsible for data analysis. SJ, LW, and ZL contributed to the drafting of the manuscript. WY contributed to data interpretation and revised the paper critically in terms of argument. All authors contributed to the article and approved the submitted version.
Funding
This work was supported by National High Level Hospital Clinical Research Funding of Peking Union Medical College Hospital (grant numbers 2022-PUMCH-A-063, 2022-PUMCH-B-009).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2023.1248222/full#supplementary-material
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Summary
Keywords
prostatic neoplasms, transition zone, peripheral zone, prognosis, biochemical recurrence
Citation
Jin S, Wu L, Liang Z and Yan W (2023) The prognostic value of zonal origin in clinically localized prostate cancer: a systematic review and meta-analysis. Front. Oncol. 13:1248222. doi: 10.3389/fonc.2023.1248222
Received
03 July 2023
Accepted
21 November 2023
Published
08 December 2023
Volume
13 - 2023
Edited by
Sharon R. Pine, University of Colorado, United States
Reviewed by
Yuxuan Song, Peking University People’s Hospital, China
Fahad Quhal, King Fahad Specialist Hospital Dammam, Saudi Arabia
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Copyright
© 2023 Jin, Wu, Liang and Yan.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Weigang Yan, yanweigang@pumch.cn
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