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<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
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<issn pub-type="epub">2234-943X</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2026.1656688</article-id>
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<article-categories>
<subj-group subj-group-type="heading">
<subject>Systematic Review</subject>
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<title-group>
<article-title>Prostate-specific antigen velocity as a predictor of survival outcomes in patients with prostate cancer: a meta-analysis</article-title>
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<name><surname>Cui</surname><given-names>Feilun</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<name><surname>Man</surname><given-names>Changfeng</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
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<name><surname>Fan</surname><given-names>Yu</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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<aff id="aff1"><label>1</label><institution>Department of Urology, The Fourth Affiliated Hospital of Jiangsu University</institution>, <city>Zhenjiang</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Urology, Affiliated Taizhou Second People&#x2019;s Hospital of Yangzhou University</institution>, <city>Taizhou</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>Department of Medical Laboratory Science, Liaoning University of Traditional Chinese Medicine</institution>, <city>Shenyang</city>, <state>Liaoning</state>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff4"><label>4</label><institution>Cancer Institute, The Affiliated People&#x2019;s Hospital, Jiangsu University</institution>, <city>Zhenjiang</city>,&#xa0;<country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Yu Fan, <email xlink:href="mailto:jszjfanyu@163.com">jszjfanyu@163.com</email>; Changfeng Man, <email xlink:href="mailto:changfengman@njmu.edu.cn">changfengman@njmu.edu.cn</email></corresp>
<fn fn-type="equal" id="fn003">
<label>&#x2020;</label>
<p>These authors have contributed equally to this work</p></fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-10">
<day>10</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>16</volume>
<elocation-id>1656688</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>06</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>26</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>16</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Cui, Zhang, Liu, Zhou, Man and Fan.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Cui, Zhang, Liu, Zhou, Man and Fan</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-10">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. 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.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Prostate-specific antigen velocity (PSAV) has emerged as a promising biomarker for predicting survival outcomes in prostate cancer patients.</p>
</sec>
<sec>
<title>Objectives</title>
<p>To assess the association between PSAV and both all-cause mortality and prostate cancer-specific mortality (PCSM) in men diagnosed with prostate cancer by conducting a meta-analysis.</p>
</sec>
<sec>
<title>Methods</title>
<p>A comprehensive search of electronic medical databases, including PubMed, Web of Science, and Embase, was conducted to identify relevant studies published up to March 1, 2025. Studies reporting adjusted hazard ratios (HR) with 95% confidence intervals (CI) for survival outcomes in prostate cancer patients, based on categorical analyses of PSAV, were included. Pooled HRs with 95% CI was calculated using random-effects models to account for clinical heterogeneity across studies.</p>
</sec>
<sec>
<title>Result</title>
<p>Eleven studies involving 3,713 prostate cancer patients were identified and analyzed. The meta-analysis revealed that elevated PSAV was associated with a higher risk of both all-cause mortality (HR 1.96; 95% CI 1.33&#x2013;2.88) and PCSM (HR 5.38; 95% CI 2.76&#x2013;10.51). In stratified analyses, the pooled HR for all-cause mortality was 1.91 (95% CI 1.43&#x2013;2.55) among patients with localized prostate cancer, compared to 1.26 (95% CI 0.41&#x2013;3.84) in those with metastatic disease.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>Elevated PSAV is a significant predictor of all-cause mortality and PCSM in prostate cancer patients. Measuring PSAV has the potential to improve the prediction of survival outcomes in this population. However, further research is needed to standardize PSAV measurement and validate its predictive value across diverse patient groups. Systematic review registration.</p>
</sec>
</abstract>
<kwd-group>
<kwd>all-cause mortality</kwd>
<kwd>meta-analysis</kwd>
<kwd>prostate cancer</kwd>
<kwd>prostate cancer&#x2013;specific mortality</kwd>
<kwd>prostate-specific antigen velocity</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This work is supported by 1) Jiangsu 333 Talent Fund (BRA2020016); and 2) Zhenjiang Key Research and Development Fund (SH2024002).</funding-statement>
</funding-group>
<counts>
<fig-count count="3"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="28"/>
<page-count count="8"/>
<word-count count="3273"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Genitourinary Oncology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Prostate cancer is one of the most frequently diagnosed malignancies in 2022, accounting for 7.3% of all cancers globally (<xref ref-type="bibr" rid="B1">1</xref>). This condition continues to pose an increasing burden in both China and the United States (<xref ref-type="bibr" rid="B2">2</xref>). The 5-year survival rate for metastatic prostate cancer is approximately 30% (<xref ref-type="bibr" rid="B3">3</xref>). Traditionally, the combination of prostate-specific antigen (PSA) levels, Gleason score, and cancer stage has been utilized for the risk classification of prostate cancer (<xref ref-type="bibr" rid="B4">4</xref>). However, accurately predicting disease progression and survival outcomes remains a significant clinical challenge, underscoring the urgent need to enhance the risk stratification of prostate cancer.</p>
<p>PSA has long been a cornerstone in the diagnosis and management of prostate cancer. However, its utility is limited by variability in individual patient contexts and the influence of non-cancerous conditions, such as benign prostatic hyperplasia (<xref ref-type="bibr" rid="B5">5</xref>). PSA kinetics refers to the changes in PSA levels over time and is used as a dynamic marker to assess prostate cancer risk, treatment response, and disease progression. Prostate-specific antigen velocity (PSAV), PSA doubling time (time required for PSA levels to double), and PSA decline rate (rate of PSA reduction) are the three core kinetic parameters. PSAV is the rate of change in serum PSA level over time, expressed in nanograms per milliliter per year (<xref ref-type="bibr" rid="B6">6</xref>). Several studies have suggested that rapid increases in PSA levels were associated with biochemical recurrence or progression (<xref ref-type="bibr" rid="B7">7</xref>&#x2013;<xref ref-type="bibr" rid="B9">9</xref>), metastasis (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B11">11</xref>), and poorer survival outcomes (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B12">12</xref>). However, the results have been inconsistent (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>), partly due to variations in study design, patient populations, and PSAV thresholds.</p>
<p>A comprehensive synthesis of the available evidence is therefore necessary to clarify the prognostic value of PSAV in patients diagnosed with prostate cancer. This meta-analysis aims to thoroughly evaluate the association between PSAV and both all-cause mortality and prostate cancer-specific mortality (PCSM) within this patient population.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="s2_1">
<title>Literature search</title>
<p>The reporting of this study adhered to the Meta-analysis of Observational Studies in Epidemiology (<xref ref-type="bibr" rid="B15">15</xref>) and the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines (<xref ref-type="bibr" rid="B16">16</xref>). A comprehensive search was conducted across multiple electronic databases, including PubMed, Embase, and Web of Science, up to March 1, 2025, to identify relevant studies. The search strategy utilized a combination of the following keywords without language restrictions: (&#x201c;prostate cancer&#x201d; OR &#x201c;prostate carcinoma&#x201d;) AND &#x201c;prostate-specific antigen velocity &#x201c; AND (&#x201c;death&#x201d; OR &#x201c;mortality&#x201d; OR &#x201c;survival&#x201d;). The detailed search strategy is provided in <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Text S1</bold></xref>. Additionally, the reference lists of retrieved studies and relevant reviews were manually screened to identify any potentially eligible studies for inclusion.</p>
</sec>
<sec id="s2_2">
<title>Study selection</title>
<p>Eligible studies met the following criteria:1) population: patients diagnosed with prostate cancer; 2) Exposure: PSAV reported through categorical analysis; 3) Comparison: patients with higher versus lower PSAV levels; 4)Outcome measures: all-cause mortality and PCSM; 5) Study design: retrospective or prospective cohort studies; and 6) Reporting hazard ratios (HR) for the association between PSA velocity and survival outcomes, adjusted for at least age or baseline PSA, along with corresponding 95% confidence intervals (CI). For multiple studies with overlapping participant populations, only the article with the most comprehensive data was included. Exclusion criteria were as follows: 1) Reporting relative risk based on continuous analysis of PSAV; 2) Providing unadjusted relative risk; 3) Lacking relative risk data; and 4) Reviews or conference abstract. Two reviewers independently conducted the literature search, screened titles and abstracts, and retrieved full-text articles to assess eligibility. Any disagreements were resolved through consensus or by consulting the corresponding author.</p>
</sec>
<sec id="s2_3">
<title>Data extraction and quality assessment</title>
<p>Two independent reviewers extracted data from the eligible studies using a pre-designed data extraction form. The extracted data included the first author&#x2019;s name, publication year, geographical region, study design, prostate cancer subtypes, sample size, age distribution, treatment modalities, threshold for elevated PSAV, follow-up duration, multivariable-adjusted HR with corresponding 95% CIs for survival outcomes, and the covariates adjusted for in the multivariable analysis. The quality of the included studies was assessed using the Newcastle - Ottawa Scale (NOS) for cohort studies (<xref ref-type="bibr" rid="B17">17</xref>). Studies with an NOS score of 7 or higher were classified as high-quality, while those with scores between 4 and 6 were considered moderate quality. Any discrepancies in data extraction or quality assessment were resolved through consensus or by consulting the corresponding author.</p>
</sec>
<sec id="s2_4">
<title>Data analysis</title>
<p>The combined adjusted hazard ratio (HR) and 95% confidence interval (CI) were used to evaluate the association between elevated PSAV and both all-cause mortality and prostate cancer-specific mortality (PCSM). Heterogeneity across studies was assessed using the I&#xb2; statistic, with an I&#xb2; value greater than 50% indicating substantial heterogeneity. Due to evident clinical heterogeneity among the studies, a random-effects model was selected for all pooled analyses, regardless of heterogeneity levels. Pre-specified subgroup analyses were conducted based on patient age (&#x2265; 65 years or &lt;65 years), sample size (&#x2265; 300 or &lt;300), cancer subtype (metastatic prostate cancer or localized prostate cancer), and follow-up duration (&#x2265; 5 years or &lt;5 years). Sensitivity analyses were performed to assess the robustness of the results by sequentially excluding individual studies. Publication bias was evaluated using Begg&#x2019;s test (<xref ref-type="bibr" rid="B18">18</xref>) and Egger&#x2019;s test (<xref ref-type="bibr" rid="B19">19</xref>). All statistical analyses were performed using Stata 12.0 software.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Search results</title>
<p>A comprehensive search of electronic databases, supplemented by a manual search, initially identified 799 publications from the databases and 1 additional article. After removing duplicates, 432 articles remained for further screening. Following a review of titles and abstracts, 394 articles were excluded. The remaining 38 articles were retrieved for a full-text eligibility assessment. After applying predefined inclusion and exclusion criteria, 28 articles were excluded, leaving 10 studies (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B12">12</xref>&#x2013;<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B20">20</xref>&#x2013;<xref ref-type="bibr" rid="B24">24</xref>) for final analysis (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Flow chart of studies selection process.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-16-1656688-g001.tif">
<alt-text content-type="machine-generated">Flowchart illustrating the selection of studies for a meta-analysis. Starting with 799 articles from databases and one additional article by manual search, duplicates reduced the number to 432. After screening, 394 articles were excluded based on titles or abstracts. Thirty-eight full-text articles were assessed for eligibility, with 28 exclusions due to reasons such as overlapping participants, non-interest outcomes, or insufficient data. Ten studies were ultimately included in the meta-analysis.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_2">
<title>Study characteristics</title>
<p>The key characteristics of the included studies are summarized in <xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>. These studies, published between 2004 and 2022, were all retrospective in design and conducted across multiple countries, including the United State (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B24">24</xref>), Canada (<xref ref-type="bibr" rid="B13">13</xref>), Spain (<xref ref-type="bibr" rid="B22">22</xref>), Australia (<xref ref-type="bibr" rid="B23">23</xref>), and China (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B21">21</xref>). The sample sizes ranged from 91 to 1,095, encompassing a total of 3,713 patients. The mean/median age of the patients ranged from 60 to 71.2 years old. PSAV cutoff values were reported in either ng/mL/month or ng/mL/year, with significant heterogeneity in the cutoff values across studies. The follow-up ranged between 1.25 and 6.9 years. According to the NOS criteria, two studies (<xref ref-type="bibr" rid="B12">12</xref>) were deemed moderate quality, while the remaining studies were rated as high-quality (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S1</bold></xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Characteristics of the included studies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Author/year</th>
<th valign="top" align="left">Design</th>
<th valign="top" align="left">Region</th>
<th valign="top" align="left">Patients</th>
<th valign="top" align="left">Age&#xa0;(years)</th>
<th valign="top" align="left">Treatment modalities</th>
<th valign="top" align="left">Cutoff&#xa0;value&#xa0;of PSAV</th>
<th valign="top" align="left">Follow-up (years)</th>
<th valign="top" align="left">Outcomes HR (95% CI)</th>
<th valign="top" align="left">Covariates adjusted</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">D&#x2019;Amico 2004 (<xref ref-type="bibr" rid="B8">8</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Localized PC 1,095</td>
<td valign="top" align="left">Median 65.4</td>
<td valign="top" align="left">RP</td>
<td valign="top" align="left">PSAV &gt;2 ng/mL/year</td>
<td valign="top" align="left">5.1</td>
<td valign="top" align="left">PCSM<break/>9.8 (2.8-34.3)<break/>ACM<break/>1.9 (1.2-3.2)</td>
<td valign="top" align="left">Age at diagnosis, tumor stage at diagnosis, Gleason score, PSA level</td>
</tr>
<tr>
<td valign="top" align="left">D&#x2019;Amico 2005 (<xref ref-type="bibr" rid="B9">9</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Localized PC 358</td>
<td valign="top" align="left">Median 71.2</td>
<td valign="top" align="left">Radiotherapy</td>
<td valign="top" align="left">PSAV &gt;2 ng/mL/year</td>
<td valign="top" align="left">4.0</td>
<td valign="top" align="left">PCSM<break/>12.0(3.0-54.0)<break/>ACM<break/>2.1(1.3-3.6)</td>
<td valign="top" align="left">Age at diagnosis, clinical tumor category, Gleason score, PSA level</td>
</tr>
<tr>
<td valign="top" align="left">Rozhansky&#xa0;2006&#xa0;(<xref ref-type="bibr" rid="B12">12</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">HRMPC 213</td>
<td valign="top" align="left">NP</td>
<td valign="top" align="left">Chemotherapy</td>
<td valign="top" align="left">PSAV &gt; 0.0 ng/mL/month</td>
<td valign="top" align="left">1.25</td>
<td valign="top" align="left">ACM<break/>1.84 (1.31-2.58)</td>
<td valign="top" align="left">LDH, Hb, ECOG PS, PSA</td>
</tr>
<tr>
<td valign="top" align="left">Daskivich 2007 (<xref ref-type="bibr" rid="B20">20</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">PC 91</td>
<td valign="top" align="left">Median 60</td>
<td valign="top" align="left">Chemotherapy</td>
<td valign="top" align="left">PSAV &gt;10 ng/mL/year</td>
<td valign="top" align="left">2.8</td>
<td valign="top" align="left">ACM<break/>2.8 (1.5-5.3)</td>
<td valign="top" align="left">PSADT, PSA nadir during ADT of &gt;0.2 ng/mL, Hb, treatment</td>
</tr>
<tr>
<td valign="top" align="left">Palma 2008 (<xref ref-type="bibr" rid="B13">13</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">Canada</td>
<td valign="top" align="left">Intermediate- high risk PC 277</td>
<td valign="top" align="left">Median 70</td>
<td valign="top" align="left">ADT, Radiotherapy</td>
<td valign="top" align="left">PSAV &gt; 3 ng/mL/month</td>
<td valign="top" align="left">6.8</td>
<td valign="top" align="left">PCSM<break/>2.75(1.27-5.95)<break/>ACM<break/>1.70(0.99-2.92)</td>
<td valign="top" align="left">Age, Gleason score</td>
</tr>
<tr>
<td valign="top" align="left">Ma 2009 (<xref ref-type="bibr" rid="B21">21</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">mPC 250</td>
<td valign="top" align="left">Median 70</td>
<td valign="top" align="left">ADT</td>
<td valign="top" align="left">PSAV &gt; 9.1 ng/mL/year</td>
<td valign="top" align="left">2.0</td>
<td valign="top" align="left">ACM<break/>2.92 (1.13-7.55)</td>
<td valign="top" align="left">Age, PSA, Gleason score, M1c stage, PSADT</td>
</tr>
<tr>
<td valign="top" align="left">Rodr&#xed;guez-Alonso 2010 (<xref ref-type="bibr" rid="B22">22</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">Spain</td>
<td valign="top" align="left">PC 265</td>
<td valign="top" align="left">64.6 &#xb1; 5.5</td>
<td valign="top" align="left">RP</td>
<td valign="top" align="left">PSAV &gt;3 ng/mL/year</td>
<td valign="top" align="left">4.3</td>
<td valign="top" align="left">ACM<break/>22.8 (4.71-90.5)</td>
<td valign="top" align="left">Age, PSA, combined Gleason of specimen, surgical margins, extracapsular disease</td>
</tr>
<tr>
<td valign="top" align="left">Shi 2013 (<xref ref-type="bibr" rid="B23">23</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">Australia</td>
<td valign="top" align="left">Localized PC 848</td>
<td valign="top" align="left">69.6 &#xb1; 7.3</td>
<td valign="top" align="left">ADT, Radiotherapy</td>
<td valign="top" align="left">PSAV &gt;0.2 ng/mL/year</td>
<td valign="top" align="left">5.5</td>
<td valign="top" align="left">PCSM<break/>5.15(1.99-13.30)<break/>ACM<break/>1.74 (1.04-2.90)</td>
<td valign="top" align="left">Age, Gleason score, PSA at diagnosis, adjuvant/neoadjuvant ADT use within 2 years</td>
</tr>
<tr>
<td valign="top" align="left">Suzman 2015 (<xref ref-type="bibr" rid="B24">24</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">BRPC 196</td>
<td valign="top" align="left">Median 63</td>
<td valign="top" align="left">Non-hormonal agents</td>
<td valign="top" align="left">PSAV &gt; 0.59 ng/mL/month</td>
<td valign="top" align="left">6.9</td>
<td valign="top" align="left">ACM<break/>2.33 (1.28-4.35)</td>
<td valign="top" align="left">Age, Gleason score, pre-metastatic use of ADT</td>
</tr>
<tr>
<td valign="top" align="left">Wang 2022 (<xref ref-type="bibr" rid="B14">14</xref>)</td>
<td valign="top" align="left">R</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">mCRPC 120</td>
<td valign="top" align="left">NP</td>
<td valign="top" align="left">Abiraterone</td>
<td valign="top" align="left">PSAV &gt;0.77 ng/mL/month</td>
<td valign="top" align="left">NP</td>
<td valign="top" align="left">ACM<break/>0.41 (0.23-0.73)</td>
<td valign="top" align="left">Baseline PSA at abiraterone use, lowest PSA, painkiller, ALP</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>HR, hazard ratio; CI, confidence interval; NP, not provided; R, retrospective; mCRPC, metastatic castration-resistant prostate cancer; HRMPC, hormone-refractory metastatic prostate carcinoma; BRPC, biochemically-recurrent prostate cancer; PC, prostate cancer; PSA, prostate-specific antigen; PSAV, prostate-specific antigen velocity; PSADT, prostate-specific antigen doubling time; ECOG, Eastern Cooperative Oncology Group; PS, performance status; BCF, biochemical failure ADT, androgen-deprivation therapy; Hb, hemoglobin; AKP, alkaline phosphatase; ALP, alkaline phosphatase; LDH, lactate dehydrogenase; BMI, body mass index; OS, overall survival; RP, radical prostatectomy.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<title>All-cause mortality</title>
<p>All included studies examined the association between PSAV and all-cause mortality. The overall findings demonstrated that elevated PSAV was associated with a higher risk of all-cause mortality (HR 1.96; 95% CI 1.33&#x2013;2.88; <xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>), although significant heterogeneity was observed across studies (<italic>I</italic><sup>2</sup> = 77.8%, <italic>p</italic> &lt; 0.001). No publication bias was detected, as indicated by Egger&#x2019;s test (<italic>p</italic> = 0.278) and Begg&#x2019;s test (<italic>p</italic> = 0.107). A leave-one-out sensitivity analysis confirmed the credibility of the pooled risk estimate. In subgroup analyses (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>), the pooled HR for all-cause mortality was 1.91 (95% CI 1.43&#x2013;2.55) among patients with localized prostate cancer, compared to 1.26 (95% CI 0.41&#x2013;3.84) in those with metastatic disease. Additionally, the association between elevated PSAV and all-cause mortality was stronger in studies with follow-up durations of less than 5 years (HR 2.76; 95% CI 1.69&#x2013;4.52) and in studies where the median/mean patient age was &#x2264;65 years (HR 4.10; 95% CI 1.61&#x2013;10.44).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Pooled adjusted hazard ratios with 95% confidence intervals of all-cause mortality for higher versus reference lower prostate-specific antigen velocity.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-16-1656688-g002.tif">
<alt-text content-type="machine-generated">Forest plot of various studies analyzing hazard ratios (HR) with 95 percent confidence intervals. Each study's HR is plotted with a black square and a horizontal line indicating the confidence interval. Weights are provided, with the overall HR as 1.96 and a confidence interval of 1.33 to 2.88, with I-squared at 77.8 percent. Studies range from D'Amico 2004 to Wang 2022, showing variability in hazard ratios and study weights. A diamond indicates the overall estimate.</alt-text>
</graphic></fig>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Subgroup analysis on all-cause mortality.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Subgroups</th>
<th valign="middle" align="center">No. of studies</th>
<th valign="middle" align="center">Pooled adjusted HR</th>
<th valign="middle" align="center">95%CI</th>
<th valign="middle" align="center">Heterogeneity between studies</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Sample sizes</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;&#x2265; 300</td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">1.91</td>
<td valign="middle" align="center">1.43-2.55</td>
<td valign="middle" align="left"><italic>p</italic> = 0.878; <italic>I</italic><sup>2</sup> = 0.0%</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;&lt; 300</td>
<td valign="middle" align="center">7</td>
<td valign="middle" align="center">2.10</td>
<td valign="middle" align="center">1.14-3.84</td>
<td valign="middle" align="left"><italic>p</italic> &lt; 0.001; <italic>I</italic><sup>2</sup> = 85.0%</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Cancer subtypes</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Localized PC</td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">1.91</td>
<td valign="middle" align="center">1.43-2.55</td>
<td valign="middle" align="left"><italic>p</italic> = 0.878; <italic>I</italic><sup>2</sup> = 0.0%</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Metastatic PC</td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">1.26</td>
<td valign="middle" align="center">0.41-3.84</td>
<td valign="middle" align="left"><italic>p</italic> &lt; 0.001; <italic>I</italic><sup>2</sup> = 91.0%</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Age at baseline</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;&#x2265; 65 years</td>
<td valign="middle" align="center">5</td>
<td valign="middle" align="center">1.92</td>
<td valign="middle" align="center">1.50-2.46</td>
<td valign="middle" align="left"><italic>p</italic> = 0.877; <italic>I</italic><sup>2</sup> = 0.0%</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;&lt; 65 years</td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">4.10</td>
<td valign="middle" align="center">1.61-10.44</td>
<td valign="middle" align="left"><italic>p</italic> = 0.019; <italic>I</italic><sup>2</sup> = 74.8%</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Follow-up duration</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;&#x2265; 5 years</td>
<td valign="middle" align="center">4</td>
<td valign="middle" align="center">1.88</td>
<td valign="middle" align="center">1.44-2.45</td>
<td valign="middle" align="left"><italic>p</italic> = 0.874; <italic>I</italic><sup>2</sup> = 0.0%</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;&lt; 5 years</td>
<td valign="middle" align="center">5</td>
<td valign="middle" align="center">2.76</td>
<td valign="middle" align="center">1.69-4.52</td>
<td valign="middle" align="center"><italic>p</italic> = 0.021; <italic>I</italic><sup>2</sup> = 65.5%</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>HR, hazard ratio; CI, confidence intervals; PC, prostate cancer.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_4">
<title>Prostate cancer-specific mortality</title>
<p>A total of 4 studies (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B23">23</xref>) investigated the association between PSAV and PCSM. The overall findings revealed that elevated PSAV was associated with a significantly higher risk of PCSM (HR 5.38; 95% CI 2.76&#x2013;10.51; <xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3</bold></xref>), despite notable heterogeneity across studies (<italic>I</italic><sup>2</sup> = 37.6%, <italic>p</italic> = 0.186). A leave-one-out sensitivity analysis confirmed the robustness of the pooled risk estimate.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Pooled adjusted hazard ratios with 95% confidence intervals of prostate cancer-specific mortality for higher versus lower prostate-specific antigen velocity.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-16-1656688-g003.tif">
<alt-text content-type="machine-generated">Forest plot showing hazard ratios (HR) and 95% confidence intervals (CI) for four studies: D'Amico 2004, D'Amico 2005, Palma 2008, and Shi 2013. Each study is represented by a square and line, indicating HR and CI. Weights vary from 16.22% to 35.34%. The overall effect is marked by a diamond, indicating an HR of 5.38 with a CI of 2.76 to 10.51. I-squared is 37.6% and p-value is 0.186. Weights are from random effects analysis. The plot ranges from 0.0185 to 54 on the x-axis.</alt-text>
</graphic></fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>This meta-analysis evaluated the association between PSAV and survival outcomes in patients with prostate cancer, specifically focusing on all-cause mortality and PCSM. The findings indicate that an increased PSAV is a significant predictor of both all-cause mortality and PCSM. Compared to patients with lower PSAV, those with higher PSAV exhibited a 96% increased risk of all-cause mortality and a 5.38-fold increased risk of PCSM. These results underscore the potential of PSAV as a valuable biomarker for risk stratification and survival prediction in patients with prostate cancer.</p>
<p>Subgroup analyses provided further insights into the relationship between PSAV and survival outcomes. Among patients with localized prostate cancer, the association between increased PSAV and all-cause mortality was robust; however, this association was not statistically significant in patients with metastatic disease. This discrepancy may be attributed to the advanced nature of metastatic prostate cancer, where factors such as tumor burden, treatment resistance, and comorbidities may overshadow the predictive value of PSAV. Additionally, the stronger association between PSAV and all-cause mortality in studies with shorter follow-up durations and younger patient populations suggests that PSAV may be particularly relevant in earlier stages of the disease or among patients with a longer life expectancy, where timely interventions could significantly influence outcomes. The results also demonstrated a significant association between elevated PSAV and PCSM, underscoring the potential of PSAV as a biomarker for aggressive disease and an increased risk of death specifically attributable to prostate cancer. However, the limited number of studies reporting PCSM outcomes emphasizes the need for further research to validate these findings.</p>
<p>The pooled estimate of all-cause mortality should be interpreted in the context of significant heterogeneity. Most notably, the extreme HR reported by Rodr&#xed;guez-Alonso et&#xa0;al., 2010 (<xref ref-type="bibr" rid="B22">22</xref>) is a potential outlier. However, we conducted a sensitivity analysis by excluding this study and confirm that the overall direction and statistical significance of our pooled results remained unchanged (HR 1.73; 955 CI 1.23-2.44), which supports the robustness of our primary findings.</p>
<p>In addition to the categorical analysis of PSAV, elevated PSAV was also a significant predictor of worse survival outcomes when analyzed as a continuous variable. Among 201 men with nonmetastatic castration-resistant prostate cancer, each logarithmic increase in PSAV (ng/mL/year) was associated with a 39% reduction in overall survival (<xref ref-type="bibr" rid="B25">25</xref>). Furthermore, in a cohort of 915 patients with metastatic prostate cancer, each unit increase in PSAV was linked to a 5.23-fold higher risk of death (<xref ref-type="bibr" rid="B26">26</xref>).Additionally, higher PSAV was identified as a significant prognostic biomarker for overall survival in patients with metastatic castration-resistant prostate cancer (adjusted HR 1.008; 95% CI 1.004&#x2013;1.012) (<xref ref-type="bibr" rid="B27">27</xref>) and hormone-refractory prostate cancer (adjusted HR 1.004; 95% CI 1.001&#x2013;1.007) (<xref ref-type="bibr" rid="B28">28</xref>). These findings provide further evidence supporting the role of increased PSAV in predicting overall survival in prostate cancer patients.</p>
<p>The results of this meta-analysis have significant clinical implications. Determining PSAV could potentially enhance the prediction of overall survival in prostate cancer patients, enabling more personalized treatment strategies. The strong association between increased PSAV and PCSM further underscores the importance of PSAV as a prognostic biomarker. This strong correlation indicates that PSAV can effectively predict the risk of death specifically from prostate cancer, which is crucial for determining the intensity of treatment and the necessity for closer surveillance. However, several areas warrant future research: 1) establishing a standardized protocol for PSAV measurement, which specifies core requirements including a minimum of three measurements collected over 18&#x2013;24 months, standardized sampling time points, PSAV calculation via linear regression analysis, and an explicitly defined measurement timeframe, would improve the comparability of future studies and enhance the reliability of PSAV as a biomarker; 2) validating its predictive value across diverse patient populations; 3) exploring the optimal PSAV threshold for identifying high-risk patients; and 4) evaluating the incremental value of PSAV when combined with other prognostic markers and risk stratification tools.</p>
<p>Our meta-analysis has several limitations that warrant consideration. First, all included studies were retrospective in nature, which introduces potential selection bias and recall bias. Second, there was significant heterogeneity across studies regarding patient populations, PSAV measurement techniques or cutoff values, treatment approaches, and follow-up durations, all of which could introduce bias. Third, the methods for calculating PSAV varied among studies. Different intervals between PSA measurements, as well as diverse statistical approaches, can lead to inconsistent results. This lack of standardization in measuring PSAV undermines its reliability as a universal prognostic biomarker. In particular, interpreting PSAV should be done in the context of non-cancerous conditions, as these factors can cause fluctuations in PSA levels, making it challenging to accurately assess the true velocity. Fourth, the results of subgroup analyses were based on a relatively small number of studies, and the interpretation of these findings should be approached with caution. Finally, different units and varying time frames (e.g., ng/mL/year, log[ng/mL]/year, or ng/mL/month) rendered quantitative pooling of continuous PSAV results impossible, which reinforce the need for standardized continuous PSAV reporting guidelines in future research.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<title>Conclusions</title>
<p>This meta-analysis provides robust evidence that elevated PSAV is a significant predictor of both all-cause mortality and PCSM in prostate cancer patients. These findings highlight the potential clinical utility of incorporating PSAV into routine practice to improve risk stratification and enhance the prediction of survival outcomes, particularly in patients with localized diseases. However, further research is needed to standardize PSAV measurement methods and validate its predictive value across diverse patient populations.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Material</bold></xref>. Further inquiries can be directed to the corresponding authors.</p></sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>FC: Validation, Data curation, Funding acquisition, Writing &#x2013; original draft, Resources, Formal analysis, Visualization. YSZ:&#xa0;Visualization, Formal analysis, Validation, Data curation, Resources, Writing &#x2013; review &amp; editing. ZL: Writing &#x2013; review &amp; editing, Formal analysis, Visualization, Data curation, Resources, Validation. YJZ: Writing &#x2013; review &amp; editing, Validation, Investigation, Visualization. CM: Conceptualization, Validation, Writing &#x2013; review &amp; editing, Visualization. YF: Writing &#x2013; review &amp; editing, Project administration, Validation, Conceptualization, Supervision, Visualization.</p></sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If&#xa0;you identify any issues, please contact us.</p></sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>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.</p></sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fonc.2026.1656688/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fonc.2026.1656688/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="DataSheet1.docx" id="SF1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
<supplementary-material xlink:href="Table1.doc" id="SM1" mimetype="application/msword"/></sec>
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<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2886938">Marvin Langston</ext-link>, Stanford University, United States</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/306944">Daniel Taussky</ext-link>, Montreal University, Canada</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2361248">Jorge Adri&#xe1;n Ram&#xed;rez De Arellano S&#xe1;nchez</ext-link>, University of Guadalajara, Mexico</p></fn>
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