Can PSA Kinetics Improve the Yield of PSMA PET/CT in Biochemical Recurrence after Prostatectomy?

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Mounish Nuthalapati, Tanmay Patravale, Nazareth Solomon, Arun Ramdas Menon, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9064970/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction & Objectives Biochemical recurrence (BCR) after radical prostatectomy (RP) occurs in approximately 20–40%. PSMA PET/CT is the preferred imaging modality for detecting recurrence; however, detection rates decline sharply when PSA is < 1 ng/mL, leading to more negative scans, added costs and radiation exposure. PSA kinetics, which reflect tumour aggressiveness, have been correlated with PET positivity in mixed cohorts, but their role in post-prostatectomy BCR exclusively remains unclear. Our study aimed to evaluate the association between PSA kinetics and PSMA PET/CT positivity in post-RP BCR and to define clinically relevant kinetic cut-offs to improve imaging yield. Materials & Methods A retrospective analysis of post-RP patients (2013–2024) who developed BCR and underwent 68Ga-PSMA PET/CT was performed. Patients with prior therapy, PSA persistence, inadequate follow-up, or non-PSMA imaging were excluded. Institutional Ethics Committee approval was obtained prior to data collection. Baseline, pathological, and PSA kinetic parameters were compared between PET-positive and PET-negative cohorts. Logistic regression was used to assess correlation between PSA kinetics and PET positivity, and ROC analysis identified optimal cut-offs. Results A total of 973 men underwent RP during the study period. After applying the inclusion and exclusion criteria, 64 patients were included in final analysis. The median age was 67 years. 19 patients (29.7%) had positive scans, while 45 (70.3%) had negative scans. Baseline and pathological characteristics were comparable between the two groups. Median PSA at the time of imaging was 0.58 ng/mL. PSA kinetics differed significantly between groups. PET-positive patients had higher PSA velocity (1.50 ± 2.20 vs 0.39 ± 0.42 ng/mL/year, p = 0.02) and shorter doubling time (4.40 ± 4.03 vs 8.68 ± 7.91 months, p = 0.009). On univariate analysis, PSA velocity (PSAV) (OR 3.31, 95% CI 1.14–9.58, p = 0.027), PSA doubling time (PSADT) (OR 0.86, 95% CI 0.75–1.00, p = 0.050), and PSA at imaging (OR 10.68, 95% CI 1.23–93.11, p = 0.032) were significant predictors of PET positivity. On ROC analysis, PSA-DT and PSAV showed good discriminatory power (AUC 0.71 and 0.69, respectively) with optimal cut-offs of 3.8 months and 0.5 ng/mL/year respectively. Conclusion Patients with PSA-DT 0.5 ng/mL/year are more likely to have positive scans. Integration of PSA kinetics into imaging decisions can improve the yield. However, prospective studies with large sample size are needed for validation. Prostate cancer biochemical recurrence PSMA PET/CT PSA kinetics PSA doubling time radical prostatectomy Figures Figure 1 Introduction Biochemical recurrence (BCR) occurs in approximately 20–40% of men following radical prostatectomy (RP)( 1 – 3 ). Accurate localization of recurrent disease is crucial for guiding timely and appropriate salvage treatment. PSMA PET/CT has become the preferred imaging modality for detecting recurrent prostate cancer ( 4 , 5 ). However, the diagnostic yield of PSMA PET/CT varies substantially according to the absolute prostate-specific antigen (PSA) level at the time of imaging ( 6 , 7 ). When PSA levels are < 0.5 ng/mL, the proportion of positive scans remains low (28–58%), resulting in increased cost, unnecessary radiation exposure, and no change in management. This variability highlights the need for better tools to determine which patients are most likely to benefit from PSMA PET/CT during BCR post-RP. PSA kinetics are established indicators of tumor burden and biological aggressiveness ( 8 , 9 ). Although several studies have evaluated PSMA PET in BCR, most have involved heterogeneous cohorts that combine patients treated with RP and radiotherapy ( 10 – 13 ). PSA kinetics differ significantly between post-surgical and post-radiation settings, potentially confounding the association between PSA kinetics and PSMA PET positivity. To address this gap, we focused exclusively on men with BCR following radical prostatectomy. The primary aim was to evaluate the association between PSA kinetics and PSMA PET positivity in men with BCR after RP. The secondary aim was to determine clinically relevant PSA kinetic cut-offs that improve the diagnostic yield of PSMA PET/CT and optimize patient selection. Materials and Methods We conducted a retrospective cohort study of men who underwent radical prostatectomy at Amrita Institute of Medical Sciences, Kochi, Kerala between 2013 and 2024 and subsequently developed BCR. BCR was defined as a PSA > 0.2 ng/mL on at least two consecutive measurements ( 11 ). Patients were eligible if they underwent a PSMA PET/CT scan as part of their BCR evaluation with adequate PSA follow-up. Patients were excluded if they had received neoadjuvant therapy, adjuvant radiotherapy prior to the onset of BCR, had incomplete follow-up data, lacked PSMA PET/CT imaging, or demonstrated PSA persistence. Institutional ethics committee approval was obtained prior to study initiation. Clinical, pathological, and follow-up details were retrieved from electronic records. Baseline variables included age, preoperative PSA, family history, clinical T-stage, PSA density and PSMA avidity. Pathological features assessed were Gleason Grade Group, extracapsular extension, seminal vesicle invasion, margin status, nodal involvement, and adverse histological patterns. Follow-up information included serial PSA measurements and PSMA PET findings. Based on PSMA PET/CT findings, patients were categorized into two groups: PSMA PET–positive, indicating identifiable recurrent disease, and PSMA PET–negative, with no detectable lesions. PSA kinetics were derived from serial post-operative PSA values: time to first rise (from date of surgery to confirmed ≥ 0.1 ng/mL), PSA velocity (slope of log-transformed PSA rise of last 3 PSA values before imaging atleast 3 months apart each, calculated via MSKCC tool), PSA doubling time (PSA-DT, via MSKCC), and PSA closest to imaging . PSMA PET/CT scans were performed using 68Ga-PSMA-PET as per institutional protocols, with uptake categorized as positive (local, nodal, or distant) or negative. Statistical Analysis All analyses were performed using SPSS Statistics version 29.0 (IBM Corp., Armonk, NY, USA). Baseline characteristics were summarized using descriptive statistics, with continuous variables expressed as mean ± standard deviation or median (interquartile range), and categorical variables as counts and percentages. Group comparisons between PSMA PET–positive and negative cohorts employed chi-square or Fisher’s exact tests for categorical variables, and t-test or Mann–Whitney U tests for continuous variables. Associations between PSA kinetics and PSMA PET positivity were assessed using univariate and multivariate logistic regression. Receiver operating characteristic (ROC) curves with Youden index defined optimal cut-offs. A p-value < 0.05 was considered statistically significant. Results Of the 973 men who underwent radical prostatectomy during the study period, 64 fulfilled the study criteria and were included in the final analysis. Nineteen patients (29.6%) had positive PSMA PET findings, while 45 (70.3%) had negative scans. The median age of the cohort was 68 years, the median time to BCR was 24 months (IQR 15–36), and the median absolute PSA at imaging was 0.30 ng/mL (IQR 0.19–0.46). Among those with positive scans, regional lymph node recurrence was the most common site (10 patients, 52.6%), followed by distant metastatic disease (8 patients, 42.1%), and isolated prostate bed recurrence in 1 patient (5.3%). In the PSMA PET–negative group, the majority of patients (38/45; 84.4%) proceeded to salvage therapy based on clinical and pathological risk assessment, whereas 7 patients (15.6%) were managed with observation alone. Baseline clinicopathologic variables were comparable between the PSMA PET–positive and –negative groups ( Table 1 ) . Preoperative PSA levels were similar (median 18.4 vs. 19.0 ng/mL; p = 0.91), and there were no significant differences in pathological T stage or Gleason Grade Group distribution (p = 0.53). High-grade disease (Grade Groups 4–5) was present in 42% of PET-positive and 46% of PET-negative patients. Rates of extracapsular extension, seminal vesicle invasion, lymph node involvement, and aggressive histologic patterns were also similar across groups. Margin positivity was more frequent among PET-negative patients (33% vs. 8%), although this did not reach statistical significance (p = 0.22). Overall, conventional pathological features did not distinguish men with positive from those with negative PSMA PET scans. Table 1 Baseline Characteristics of BCR Patients Stratified by PSMA PET Status Variable Total no. of patients = n= 64 PSMA PET Positive (19 patients) PSMA PET Negative (45 patients) p-value Age (mean ± SD/ median (IQR) 68.63 ± 5.15 / 69.00 (66.50–71.00) 66.78 ± 5.76 / 67.00 (63.00–71.00) 0.173 Positive Family history of Malignancy 1 (1.6%) 4 (6.2%) Initial PSA (mean ± SD/ median (IQR) 20.41 ± 10.53 / 18.40 (12.47–26.40) 23.84 ± 18.11 / 19.00 (10.99–30.10) 0.906 PSMA Avidity (mean ± SD/ median (IQR) 13.78 ± 9.61 / 8.70 (6.90–19.10) 17.71 ± 14.34 / 12.00 (7.40–24.20) 0.360 PSADensity (mean ± SD/ median (IQR) 0.54 ± 0.48 / 0.32 (0.26–0.69) 0.61 ± 0.52 / 0.38 (0.29–0.68) 0.479 cT 0.703 2a 1 (1.6%) 5 (7.8%) 2b 7 (10.9%) 11 (17.2%) 2c 5 (7.8%) 18 (28.1%) 3a 1 (1.6%) 2 (3.1%) 3b 5 (7.8%) 9 (14.1%) Pathological data pT 2 4 (6.2%) 12 (18.8%) 0.77 3a 9 (14.1%) 17 (26.6%) 3b 6 (9.4%) 16 (25.0%) Node positivity 1 (1.6%) 6 (9.4%) 0.61 Final Gleason grade group 0.53 1 0 (0.0%) 1 (1.6%) 2 2 (3.1%) 6 (9.4%) 3 9 (14.1%) 17 (26.6%) 4 2 (3.1%) 12 (18.8%) 5 6 (9.4%) 9 (14.1%) Ductal component present 1 1 1.00 Cibriform pattern present 4 (6.2%) 6 (9.4%) 0.69 Pattern 5 present 2 (3.1%) 6 (9.4%) 1.00 Margins positivity 5 (7.8%) 21 (32.8%) 0.22 EPE positivity 13 (20.3%) 32 (50.0%) 1.00 PSA Kinetics (mean ± SD/ median (IQR) Time to first PSA rise post surgery (in months) 15.82 ± 11.14 / 18.00 (5.50–20.00) 16.15 ± 13.83 / 11.00 (7.00-23.29) 0.930 PSA velocity 1.50 ± 2.20 / 0.58 (0.22–1.64) 0.39 ± 0.42 / 0.27 (0.12–0.47) 0.020 Time to BCR (in months) 22.01 ± 11.98 / 20.59 (12.80-29.28) 25.56 ± 19.99 / 18.49 (11.25–33.98) 0.974 PSA DT before imaging 4.40 ± 4.03 / 3.23 (2.15–4.90) 8.68 ± 7.91 / 5.80 (3.28–11.08) 0.009 Absolute PSA before imaging 0.51 ± 0.48 / 0.41 (0.20–0.54) 0.28 ± 0.19 / 0.24 (0.18–0.30) 0.070 Significant differences were observed in PSA kinetics ( Table 1 ) . Patients with PSMA PET–positive scans had a higher PSA velocity (median 0.58 vs. 0.27 ng/mL/year; p = 0.020) and a shorter PSA doubling time (median 3.23 vs. 5.80 months; p = 0.009). Absolute PSA at imaging showed a trend toward higher values in the PET-positive group (0.41 vs. 0.24 ng/mL) but was not statistically significant (p = 0.070). Time from surgery to first PSA rise and time to BCR did not differ between groups (p = 0.93). On univariate logistic regression analysis, PSA velocity (OR 3.31; 95% CI 1.14–9.58; p = 0.027), PSA doubling time (OR 0.86; 95% CI 0.75–1.00; p = 0.050), and absolute PSA at imaging (OR 10.68; 95% CI 1.23–93.11; p = 0.032) were significantly associated with PET positivity ( Table 2 ) . Neither preoperative PSA, interval to first PSA rise nor the time to BCR predicted PET positivity. In multivariate analysis, none of the kinetic parameters remained independently significant, likely due to collinearity; however, effect estimates remained directionally consistent, supporting the association between rapid PSA progression and PSMA PET positivity. Table 2 Logistic Regression of PSA Kinetics Predicting PSMA PET Positivity Univariate analysis Multivariate analysis Variable OR 95% CI p-value OR 95% CI p-value Initial PSA 0.99 0.95–1.02 0.446 Time to first PSA rise post surgery 1.00 0.96–1.04 0.927 PSA velocity 3.31 1.14–9.58 0.027 2.04 0.53–7.87 0.303 PSA DT before imaging 0.86 0.75-1.00 0.050 0.92 0.79–1.06 0.230 Absolute PSA before PET Imaging 10.68 1.23–93.11 0.032 2.03 0.07–57.31 0.678 Receiver operating characteristic (ROC) analysis demonstrated that PSA doubling time had the highest discriminative performance (AUC 0.713), followed by PSA velocity (AUC 0.695) and absolute PSA (AUC 0.644) ( Table 3 , Fig. 1 ). The optimal PSA-DT threshold was 3.8 months (sensitivity 72%, specificity 68%). Broader PSA-DT cut-offs increased sensitivity (≤ 6 months: 80–85%; ≤9 months: >90%) but substantially reduced specificity, reducing clinical utility. The optimal PSA velocity cut-off was 0.54 ng/mL/year (sensitivity 59%, specificity 84%), and the optimal absolute PSA cut-off was 0.38 ng/mL (sensitivity 58%, specificity 87%). Table 3 ROC Analysis of PSA Kinetics Predicting PSMA PET Positivity Variable AUC Optimal Cutoff Sensitivity Specificity PSA Velocity 0.695 0.54 0.59 0.84 Absolute PSA 0.644 0.38 0.58 0.87 PSA Doubling Time 0.713 3.80 0.72 0.68 Discussion Accurate localization of recurrence during biochemical relapse is critical for guiding post-prostatectomy management ( 14 , 15 ). When PSMA PET/CT identifies locoregional disease, patients are typically directed toward prostate-bed salvage radiotherapy, with pelvic nodal irradiation considered when nodal involvement is detected. In contrast, detection of distant metastases generally shifts management toward systemic or metastasis-directed therapies. Thus, determining whether recurrence is local, nodal, or metastatic has direct therapeutic and prognostic relevance. When PSMA PET/CT is negative, however, treatment decisions must rely on clinical and pathological risk stratification with many PET-negative men with rising PSA remain candidates for salvage radiotherapy. Identifying patients likely to have negative scans may therefore reduce unnecessary imaging. PSMA PET positivity in our post-RP BCR cohort was driven primarily by PSA kinetics rather than absolute PSA or pathological variables. PET-positive men exhibited accelerated biochemical progression, reflected by higher PSAV and shorter PSA-DT. These kinetic parameters demonstrated moderate predictive accuracy on ROC analysis, with PSA-DT < 3.8 months providing the strongest discrimination. In contrast, pathological features showed no association with PET detectability, underscoring that biochemical kinetics outperform static histopathology in predicting PSMA PET detectability at low PSA levels. Haidar et al.( 12 ) prospectively imaged 52 biochemically recurrent prostate cancer patients (42 post-RP, 10 post-RT) with 68Ga-PSMA PET/CT: overall positivity was 65.4%. Short PSA doubling time strongly predicted positivity – 32/45 (71.1%) of men with PSAdt ≤ 10 months had positive scans versus 2/7 (28.6%) with longer PSADT (p = 0.006) – and multivariate analysis confirmed PSA at scan (OR 2.54 per ng/mL, p = 0.02) and PSADT as independent predictors. García-Zoghby et al.( 10 ) studied 275 post-treatment patients (mixed RP/RT) with 18F-DCFPyL PET/CT and found 165/275 (60%) positive scans. In their model, higher PSA and faster PSA velocity independently predicted PET positivity, and both measures correlated with larger whole-body tumor burden. ROC analysis yielded optimal cut-offs of ≈ 1.15 ng/mL for PSA and ≈ 0.065 ng/mL/month for PSA velocity, which best discriminated positive vs negative scans. Mestre et al.( 11 ) similarly noted markedly higher PSMA PET detection rates in patients with brisk PSA kinetics. In summary, these heterogeneous cohorts consistently link rapid PSA kinetics to higher PSMA PET/CT positivity. However, because the thresholds and associations were derived in mixed-treatment populations, their applicability to a pure post-prostatectomy setting is limited. EAU high-risk BCR is defined by PSA-DT ≤ 12 months, but this threshold is designed for clinical management ( 4 ). Our ROC-derived PSA-DT cutoff of < 4 months offers threshold for imaging selection. These findings do not replace guideline stratification but rather complement it, suggesting that among EAU high-risk patients, those with rapid PSA kinetics may benefit from PSMA PET-CT. Reducing imaging in patients unlikely to benefit, avoids unnecessary radiation, decreases the psychological burden associated with repeated testing, and prevents the cascade of additional evaluations triggered by incidental or equivocal PET findings. Healthcare systems also can allocate resources more effectively while preserving the high diagnostic value of PSMA-based imaging. The major strength of our study is the use of a homogeneous post-prostatectomy cohort, avoiding confounding from prior radiotherapy, neoadjuvant therapy, or PSA persistence. The uniform imaging protocol, consistent PSA measurements, and practically applicable PSA-DT and PSA velocity thresholds improves the robustness of the study. The study is limited by its retrospective design and modest sample size, which may reduce statistical power and introduce selection bias. In addition, the single-centre setting may limit generalisability. Larger prospective studies are needed to confirm these findings and validate the proposed PSA-kinetic thresholds. Conclusion Patients with PSA-DT 0.5 ng/mL/year are more likely to have positive scans. Integration of PSA kinetics into imaging decisions can improve the yield. However, prospective studies with large sample size are needed for validation. Abbreviations PSA: Prostate-specific antigen PSMA: Prostate-specific membrane antigen PET/CT: Positron emission tomography/computed tomography BCR: Biochemical recurrence RP: Radical prostatectomy PSA-DT: PSA doubling time PSAV: PSA velocity ROC: Receiver operating characteristic AUC: Area under the curve Declarations Ethics approval and consent to participate This retrospective study was approved by the Institutional Ethics Committee of Amrita Institute of Medical Sciences, Kochi, Kerala, India. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Due to the retrospective nature of the study and use of anonymized patient data, the requirement for informed consent was waived by the Institutional Ethics Committee. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are available from the corresponding Competing interests The authors declare that they have no competing interests. Funding No external funding was received for this study. Authors' contributions G.K.P. conceptualized and supervised the study. M.N. performed data collection, statistical analysis, and drafted the manuscript. T.P. assisted with data acquisition and data interpretation. N.S.T. contributed to data collection and manuscript revision. A.R.M. contributed to study supervision and critical revision of the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors acknowledge Ms. Devika Saju for her assistance with statistical analysis. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9064970","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607138540,"identity":"181ff90e-8eba-4554-8421-b7925138a244","order_by":0,"name":"Mounish Nuthalapati","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mounish","middleName":"","lastName":"Nuthalapati","suffix":""},{"id":607138541,"identity":"a38defe5-36e6-4571-bfd2-77a511a55704","order_by":1,"name":"Tanmay Patravale","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tanmay","middleName":"","lastName":"Patravale","suffix":""},{"id":607138542,"identity":"9a02f356-893a-4cfa-8a86-7bbc233caef8","order_by":2,"name":"Nazareth Solomon","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Nazareth","middleName":"","lastName":"Solomon","suffix":""},{"id":607138543,"identity":"8136dace-8046-48eb-9e5b-1fccdb239cba","order_by":3,"name":"Arun Ramdas Menon","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Arun","middleName":"Ramdas","lastName":"Menon","suffix":""},{"id":607138544,"identity":"72c4992a-1af9-4bf2-b94b-a039c87d00da","order_by":4,"name":"Ginil Kumar Pooleri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYDCCAyBkYCEHZj8gQYuEMZidQKwWIJBIbABRRGnhu3384uGCAon0+WGHHwJtsZPTbSCgRfJcTsHhGQYSuRtvpxkAtSQbmx0goMXgDE/CYR6QltkJIC0HErcRqyXdcHb6B2K1sB8AaUmQl84h0hbJMzwMIC2GG6RzCg4kGBDhF74z7I8/8/yxkZefnb75w4cKOzmCWhgYeAwgLgSrNCCoHATYH4Ap+QaiVI+CUTAKRsFIBABtVUcdzFO+qwAAAABJRU5ErkJggg==","orcid":"","institution":"Amrita Institute of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Ginil","middleName":"Kumar","lastName":"Pooleri","suffix":""}],"badges":[],"createdAt":"2026-03-08 14:40:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9064970/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9064970/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106401546,"identity":"635def72-9143-4caa-a027-bb700d7626e7","added_by":"auto","created_at":"2026-04-08 09:06:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":123231,"visible":true,"origin":"","legend":"\u003cp\u003eCombined ROC curves of PSA kinetics for predicting PSMA PET positivity in men with biochemical recurrence after radical prostatectomy. Receiver operating characteristic (ROC) curves are shown for PSA velocity (AUC = 0.69), absolute PSA value at the time of imaging (AUC = 0.64), and PSA doubling time (PSA-DT, inverted; AUC = 0.71). The optimal cut-off values identified by the Youden index were 0.54 ng/mL/year for PSA velocity, 0.38 ng/mL for absolute PSA, and 3.8 months for PSA-DT. Shorter PSA-DT and higher PSA velocity were associated with increased likelihood of PSMA PET positivity.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9064970/v1/e7f4b7c7006c6b962b527448.jpg"},{"id":106405307,"identity":"2d360e07-1205-451e-bcf6-433edcff00d0","added_by":"auto","created_at":"2026-04-08 09:24:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":843551,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9064970/v1/1778ee59-b282-41c1-96c5-fe20d16f71f2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can PSA Kinetics Improve the Yield of PSMA PET/CT in Biochemical Recurrence after Prostatectomy?","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBiochemical recurrence (BCR) occurs in approximately 20\u0026ndash;40% of men following radical prostatectomy (RP)(\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Accurate localization of recurrent disease is crucial for guiding timely and appropriate salvage treatment. PSMA PET/CT has become the preferred imaging modality for detecting recurrent prostate cancer (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the diagnostic yield of PSMA PET/CT varies substantially according to the absolute prostate-specific antigen (PSA) level at the time of imaging (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). When PSA levels are \u0026lt;\u0026thinsp;0.5 ng/mL, the proportion of positive scans remains low (28\u0026ndash;58%), resulting in increased cost, unnecessary radiation exposure, and no change in management. This variability highlights the need for better tools to determine which patients are most likely to benefit from PSMA PET/CT during BCR post-RP.\u003c/p\u003e \u003cp\u003ePSA kinetics are established indicators of tumor burden and biological aggressiveness (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Although several studies have evaluated PSMA PET in BCR, most have involved heterogeneous cohorts that combine patients treated with RP and radiotherapy (\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). PSA kinetics differ significantly between post-surgical and post-radiation settings, potentially confounding the association between PSA kinetics and PSMA PET positivity.\u003c/p\u003e \u003cp\u003eTo address this gap, we focused exclusively on men with BCR following radical prostatectomy. The primary aim was to evaluate the association between PSA kinetics and PSMA PET positivity in men with BCR after RP. The secondary aim was to determine clinically relevant PSA kinetic cut-offs that improve the diagnostic yield of PSMA PET/CT and optimize patient selection.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eWe conducted a retrospective cohort study of men who underwent radical prostatectomy at Amrita Institute of Medical Sciences, Kochi, Kerala between 2013 and 2024 and subsequently developed BCR. BCR was defined as a PSA\u0026thinsp;\u0026gt;\u0026thinsp;0.2 ng/mL on at least two consecutive measurements (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Patients were eligible if they underwent a PSMA PET/CT scan as part of their BCR evaluation with adequate PSA follow-up. Patients were excluded if they had received neoadjuvant therapy, adjuvant radiotherapy prior to the onset of BCR, had incomplete follow-up data, lacked PSMA PET/CT imaging, or demonstrated PSA persistence. Institutional ethics committee approval was obtained prior to study initiation.\u003c/p\u003e \u003cp\u003eClinical, pathological, and follow-up details were retrieved from electronic records. Baseline variables included age, preoperative PSA, family history, clinical T-stage, PSA density and PSMA avidity. Pathological features assessed were Gleason Grade Group, extracapsular extension, seminal vesicle invasion, margin status, nodal involvement, and adverse histological patterns. Follow-up information included serial PSA measurements and PSMA PET findings. Based on PSMA PET/CT findings, patients were categorized into two groups: PSMA PET\u0026ndash;positive, indicating identifiable recurrent disease, and PSMA PET\u0026ndash;negative, with no detectable lesions.\u003c/p\u003e \u003cp\u003ePSA kinetics were derived from serial post-operative PSA values: \u003cem\u003etime to first rise\u003c/em\u003e (from date of surgery to confirmed\u0026thinsp;\u0026ge;\u0026thinsp;0.1 ng/mL), \u003cem\u003ePSA velocity\u003c/em\u003e (slope of log-transformed PSA rise of last 3 PSA values before imaging atleast 3 months apart each, calculated via MSKCC tool), \u003cem\u003ePSA doubling time\u003c/em\u003e (PSA-DT, via MSKCC), and \u003cem\u003ePSA closest to imaging\u003c/em\u003e.\u003c/p\u003e \u003cp\u003ePSMA PET/CT scans were performed using 68Ga-PSMA-PET as per institutional protocols, with uptake categorized as positive (local, nodal, or distant) or negative.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll analyses were performed using SPSS Statistics version 29.0 (IBM Corp., Armonk, NY, USA). Baseline characteristics were summarized using descriptive statistics, with continuous variables expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range), and categorical variables as counts and percentages. Group comparisons between PSMA PET\u0026ndash;positive and negative cohorts employed chi-square or Fisher\u0026rsquo;s exact tests for categorical variables, and t-test or Mann\u0026ndash;Whitney U tests for continuous variables. Associations between PSA kinetics and PSMA PET positivity were assessed using univariate and multivariate logistic regression. Receiver operating characteristic (ROC) curves with Youden index defined optimal cut-offs. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 973 men who underwent radical prostatectomy during the study period, 64 fulfilled the study criteria and were included in the final analysis. Nineteen patients (29.6%) had positive PSMA PET findings, while 45 (70.3%) had negative scans. The median age of the cohort was 68 years, the median time to BCR was 24 months (IQR 15\u0026ndash;36), and the median absolute PSA at imaging was 0.30 ng/mL (IQR 0.19\u0026ndash;0.46). Among those with positive scans, regional lymph node recurrence was the most common site (10 patients, 52.6%), followed by distant metastatic disease (8 patients, 42.1%), and isolated prostate bed recurrence in 1 patient (5.3%). In the PSMA PET\u0026ndash;negative group, the majority of patients (38/45; 84.4%) proceeded to salvage therapy based on clinical and pathological risk assessment, whereas 7 patients (15.6%) were managed with observation alone.\u003c/p\u003e \u003cp\u003eBaseline clinicopathologic variables were comparable between the PSMA PET\u0026ndash;positive and \u0026ndash;negative groups \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Preoperative PSA levels were similar (median 18.4 vs. 19.0 ng/mL; p\u0026thinsp;=\u0026thinsp;0.91), and there were no significant differences in pathological T stage or Gleason Grade Group distribution (p\u0026thinsp;=\u0026thinsp;0.53). High-grade disease (Grade Groups 4\u0026ndash;5) was present in 42% of PET-positive and 46% of PET-negative patients. Rates of extracapsular extension, seminal vesicle invasion, lymph node involvement, and aggressive histologic patterns were also similar across groups. Margin positivity was more frequent among PET-negative patients (33% vs. 8%), although this did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.22). Overall, conventional pathological features did not distinguish men with positive from those with negative PSMA PET scans.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of BCR Patients Stratified by PSMA PET Status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003cp\u003eTotal no. of patients\u0026thinsp;=\u0026thinsp;n= 64\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePSMA PET Positive (19 patients)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSMA PET Negative (45 patients)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.63\u0026thinsp;\u0026plusmn;\u0026thinsp;5.15 /\u003c/p\u003e \u003cp\u003e69.00 (66.50\u0026ndash;71.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.78\u0026thinsp;\u0026plusmn;\u0026thinsp;5.76 /\u003c/p\u003e \u003cp\u003e67.00 (63.00\u0026ndash;71.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive Family history of Malignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial PSA\u003c/p\u003e \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.41\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53 / 18.40 (12.47\u0026ndash;26.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.84\u0026thinsp;\u0026plusmn;\u0026thinsp;18.11 / 19.00 (10.99\u0026ndash;30.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSMA Avidity\u003c/p\u003e \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.78\u0026thinsp;\u0026plusmn;\u0026thinsp;9.61 / 8.70 (6.90\u0026ndash;19.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.71\u0026thinsp;\u0026plusmn;\u0026thinsp;14.34 / 12.00 (7.40\u0026ndash;24.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSADensity\u003c/p\u003e \u003cp\u003e(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48 / 0.32 (0.26\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52 / 0.38 (0.29\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (28.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePathological data\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (26.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNode positivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinal Gleason grade group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (26.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuctal component present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCibriform pattern present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePattern 5 present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMargins positivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (32.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEPE positivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSA Kinetics\u003c/b\u003e (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to first PSA rise post surgery (in months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.82\u0026thinsp;\u0026plusmn;\u0026thinsp;11.14 / 18.00 (5.50\u0026ndash;20.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.15\u0026thinsp;\u0026plusmn;\u0026thinsp;13.83 / 11.00 (7.00-23.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA velocity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20 / 0.58 (0.22\u0026ndash;1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 / 0.27 (0.12\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to BCR (in months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.01\u0026thinsp;\u0026plusmn;\u0026thinsp;11.98 / 20.59 (12.80-29.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.56\u0026thinsp;\u0026plusmn;\u0026thinsp;19.99 / 18.49 (11.25\u0026ndash;33.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA DT before imaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.40\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03 / 3.23 (2.15\u0026ndash;4.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.91 / 5.80 (3.28\u0026ndash;11.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsolute PSA before imaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48 / 0.41 (0.20\u0026ndash;0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19 / 0.24 (0.18\u0026ndash;0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSignificant differences were observed in PSA kinetics \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Patients with PSMA PET\u0026ndash;positive scans had a higher PSA velocity (median 0.58 vs. 0.27 ng/mL/year; p\u0026thinsp;=\u0026thinsp;0.020) and a shorter PSA doubling time (median 3.23 vs. 5.80 months; p\u0026thinsp;=\u0026thinsp;0.009). Absolute PSA at imaging showed a trend toward higher values in the PET-positive group (0.41 vs. 0.24 ng/mL) but was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.070). Time from surgery to first PSA rise and time to BCR did not differ between groups (p\u0026thinsp;=\u0026thinsp;0.93).\u003c/p\u003e \u003cp\u003eOn univariate logistic regression analysis, PSA velocity (OR 3.31; 95% CI 1.14\u0026ndash;9.58; p\u0026thinsp;=\u0026thinsp;0.027), PSA doubling time (OR 0.86; 95% CI 0.75\u0026ndash;1.00; p\u0026thinsp;=\u0026thinsp;0.050), and absolute PSA at imaging (OR 10.68; 95% CI 1.23\u0026ndash;93.11; p\u0026thinsp;=\u0026thinsp;0.032) were significantly associated with PET positivity \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Neither preoperative PSA, interval to first PSA rise nor the time to BCR predicted PET positivity. In multivariate analysis, none of the kinetic parameters remained independently significant, likely due to collinearity; however, effect estimates remained directionally consistent, supporting the association between rapid PSA progression and PSMA PET positivity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic Regression of PSA Kinetics Predicting PSMA PET Positivity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial PSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to first PSA rise post surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.96\u0026ndash;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA velocity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.14\u0026ndash;9.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.53\u0026ndash;7.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA DT before imaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.050\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsolute PSA before PET Imaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026ndash;93.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u0026ndash;57.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eReceiver operating characteristic (ROC) analysis demonstrated that PSA doubling time had the highest discriminative performance (AUC 0.713), followed by PSA velocity (AUC 0.695) and absolute PSA (AUC 0.644) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e The optimal PSA-DT threshold was 3.8 months (sensitivity 72%, specificity 68%). Broader PSA-DT cut-offs increased sensitivity (\u0026le;\u0026thinsp;6 months: 80\u0026ndash;85%; \u0026le;9 months: \u0026gt;90%) but substantially reduced specificity, reducing clinical utility. The optimal PSA velocity cut-off was 0.54 ng/mL/year (sensitivity 59%, specificity 84%), and the optimal absolute PSA cut-off was 0.38 ng/mL (sensitivity 58%, specificity 87%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC Analysis of PSA Kinetics Predicting PSMA PET Positivity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOptimal Cutoff\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA Velocity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsolute PSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSA Doubling Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccurate localization of recurrence during biochemical relapse is critical for guiding post-prostatectomy management (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). When PSMA PET/CT identifies locoregional disease, patients are typically directed toward prostate-bed salvage radiotherapy, with pelvic nodal irradiation considered when nodal involvement is detected. In contrast, detection of distant metastases generally shifts management toward systemic or metastasis-directed therapies. Thus, determining whether recurrence is local, nodal, or metastatic has direct therapeutic and prognostic relevance. When PSMA PET/CT is negative, however, treatment decisions must rely on clinical and pathological risk stratification with many PET-negative men with rising PSA remain candidates for salvage radiotherapy. Identifying patients likely to have negative scans may therefore reduce unnecessary imaging.\u003c/p\u003e \u003cp\u003ePSMA PET positivity in our post-RP BCR cohort was driven primarily by PSA kinetics rather than absolute PSA or pathological variables. PET-positive men exhibited accelerated biochemical progression, reflected by higher PSAV and shorter PSA-DT. These kinetic parameters demonstrated moderate predictive accuracy on ROC analysis, with PSA-DT\u0026thinsp;\u0026lt;\u0026thinsp;3.8 months providing the strongest discrimination. In contrast, pathological features showed no association with PET detectability, underscoring that biochemical kinetics outperform static histopathology in predicting PSMA PET detectability at low PSA levels.\u003c/p\u003e \u003cp\u003eHaidar et al.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) prospectively imaged 52 biochemically recurrent prostate cancer patients (42 post-RP, 10 post-RT) with 68Ga-PSMA PET/CT: overall positivity was 65.4%. Short PSA doubling time strongly predicted positivity \u0026ndash; 32/45 (71.1%) of men with PSAdt\u0026thinsp;\u0026le;\u0026thinsp;10 months had positive scans versus 2/7 (28.6%) with longer PSADT (p\u0026thinsp;=\u0026thinsp;0.006) \u0026ndash; and multivariate analysis confirmed PSA at scan (OR 2.54 per ng/mL, p\u0026thinsp;=\u0026thinsp;0.02) and PSADT as independent predictors. Garc\u0026iacute;a-Zoghby et al.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) studied 275 post-treatment patients (mixed RP/RT) with 18F-DCFPyL PET/CT and found 165/275 (60%) positive scans. In their model, higher PSA and faster PSA velocity independently predicted PET positivity, and both measures correlated with larger whole-body tumor burden. ROC analysis yielded optimal cut-offs of \u0026asymp;\u0026thinsp;1.15 ng/mL for PSA and \u0026asymp;\u0026thinsp;0.065 ng/mL/month for PSA velocity, which best discriminated positive vs negative scans. Mestre et al.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) similarly noted markedly higher PSMA PET detection rates in patients with brisk PSA kinetics. In summary, these heterogeneous cohorts consistently link rapid PSA kinetics to higher PSMA PET/CT positivity. However, because the thresholds and associations were derived in mixed-treatment populations, their applicability to a pure post-prostatectomy setting is limited.\u003c/p\u003e \u003cp\u003eEAU high-risk BCR is defined by PSA-DT\u0026thinsp;\u0026le;\u0026thinsp;12 months, but this threshold is designed for clinical management (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Our ROC-derived PSA-DT cutoff of \u0026lt;\u0026thinsp;4 months offers threshold for imaging selection. These findings do not replace guideline stratification but rather complement it, suggesting that among EAU high-risk patients, those with rapid PSA kinetics may benefit from PSMA PET-CT. Reducing imaging in patients unlikely to benefit, avoids unnecessary radiation, decreases the psychological burden associated with repeated testing, and prevents the cascade of additional evaluations triggered by incidental or equivocal PET findings. Healthcare systems also can allocate resources more effectively while preserving the high diagnostic value of PSMA-based imaging.\u003c/p\u003e \u003cp\u003eThe major strength of our study is the use of a homogeneous post-prostatectomy cohort, avoiding confounding from prior radiotherapy, neoadjuvant therapy, or PSA persistence. The uniform imaging protocol, consistent PSA measurements, and practically applicable PSA-DT and PSA velocity thresholds improves the robustness of the study. The study is limited by its retrospective design and modest sample size, which may reduce statistical power and introduce selection bias. In addition, the single-centre setting may limit generalisability. Larger prospective studies are needed to confirm these findings and validate the proposed PSA-kinetic thresholds.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePatients with PSA-DT\u0026thinsp;\u0026lt;\u0026thinsp;4 months or PSAV\u0026thinsp;\u0026gt;\u0026thinsp;0.5 ng/mL/year are more likely to have positive scans. Integration of PSA kinetics into imaging decisions can improve the yield. However, prospective studies with large sample size are needed for validation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePSA: Prostate-specific antigen\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;PSMA: Prostate-specific membrane antigen\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;PET/CT: Positron emission tomography/computed tomography\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;BCR: Biochemical recurrence\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;RP: Radical prostatectomy\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;PSA-DT: PSA doubling time\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;PSAV: PSA velocity\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;ROC: Receiver operating characteristic\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;AUC: Area under the curve\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was approved by the Institutional Ethics Committee of Amrita Institute of Medical Sciences, Kochi, Kerala, India.\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.\u003c/p\u003e\n\u003cp\u003eDue to the retrospective nature of the study and use of anonymized patient data, the requirement for informed consent was waived by the Institutional Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eG.K.P. conceptualized and supervised the study.\u003cbr\u003e\u0026nbsp;M.N. performed data collection, statistical analysis, and drafted the manuscript.\u003cbr\u003e\u0026nbsp;T.P. assisted with data acquisition and data interpretation.\u003cbr\u003e\u0026nbsp;N.S.T. contributed to data collection and manuscript revision.\u003cbr\u003e\u0026nbsp;A.R.M. contributed to study supervision and critical revision of the manuscript.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge \u003cstrong\u003eMs. Devika Saju\u003c/strong\u003e for her assistance with statistical analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHull GW, Rabbani F, Abbas F, Wheeler TM, Kattan MW, Scardino PT. CANCER CONTROL WITH RADICAL PROSTATECTOMY ALONE IN 1,000 CONSECUTIVE PATIENTS. Journal of Urology. 2002 Feb;167(2 Part 1):528\u0026ndash;34. doi:10.1016/S0022-5347(01)69079-7\u003c/li\u003e\n\u003cli\u003eKupelian P, Katcher J, Levin H, Zippe C, Klein E. Correlation of clinical and pathologic factors with rising prostate-specific antigen profiles after radical prostatectomy alone for clinically localized prostate cancer. Urology. 1996 Aug;48(2):249\u0026ndash;60. doi:10.1016/S0090-4295(96)00167-7\u003c/li\u003e\n\u003cli\u003eStephenson AJ, Scardino PT, Eastham JA, Bianco FJ, Dotan ZA, Fearn PA, et al. Preoperative Nomogram Predicting the 10-Year Probability of Prostate Cancer Recurrence After Radical Prostatectomy. JNCI: Journal of the National Cancer Institute. 2006 May 17;98(10):715\u0026ndash;7. doi:10.1093/jnci/djj190\u003c/li\u003e\n\u003cli\u003eCornford P, van den Bergh RCN, Briers E et al. EAU-EANM-ESTRO-ESUR-ISUP-SIOG Guidelines on Prostate Cancer. Arnhem, The Netherlands: EAU Guidelines Office, 2024. [Internet]. Available from: https://d56bochluxqnz.cloudfront.net/documents/full-guideline/EAU-EANM-ESTRO-ESUR-ISUP-SIOG-Guidelines-on-Prostate-Cancer-2024_2024-04-09-132035_ypmy_2024-04-16-122605_lqpk\u003c/li\u003e\n\u003cli\u003eSpratt DE, Srinivas S, Schaeffer EM et al. NCCN Clinical Practice Guidelines in Oncology for Prostate Cancer Version 1.2025. Pennsylvania: National Comprehensive Cancer Network, 2025. [Internet]. Available from: https://www.nccn.org/professionals/physician_gls/pdf/prost\u003c/li\u003e\n\u003cli\u003eWu Q, Bates A, Guntur P, Shamim SA, Nabi G. Detection Rate of PSMA PET Using Different Ligands in Men with Biochemical Recurrent Prostate Cancer Following Radical Treatment: A Systematic Review and Meta-analysis of Prospective Studies. Academic Radiology. 2024 Feb;31(2):544\u0026ndash;63. doi:10.1016/j.acra.2023.08.044\u003c/li\u003e\n\u003cli\u003eCrocerossa F, Marchioni M, Novara G, Carbonara U, Ferro M, Russo GI, et al. Detection Rate of Prostate Specific Membrane Antigen Tracers for Positron Emission Tomography/Computerized Tomography in Prostate Cancer Biochemical Recurrence: A Systematic Review and Network Meta-Analysis. Journal of Urology. 2021 Feb;205(2):356\u0026ndash;69. doi:10.1097/JU.0000000000001369\u003c/li\u003e\n\u003cli\u003ePound CR, Partin AW, Eisenberger MA, Chan DW, Pearson JD, Walsh PC. Natural history of progression after PSA elevation following radical prostatectomy. JAMA. 1999 May 5;281(17):1591\u0026ndash;7. doi:10.1001/jama.281.17.1591 PubMed PMID: 10235151.\u003c/li\u003e\n\u003cli\u003eD\u0026rsquo;Amico AV, Chen MH, Roehl KA, Catalona WJ. Preoperative PSA velocity and the risk of death from prostate cancer after radical prostatectomy. N Engl J Med. 2004 Jul 8;351(2):125\u0026ndash;35. doi:10.1056/NEJMoa032975 PubMed PMID: 15247353.\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-Zoghby L, Amo-Salas M, Soriano Castrej\u0026oacute;n \u0026Aacute;M, Garc\u0026iacute;a Vicente AM. Whole-body tumour burden on [18F]DCFPyL PET/CT in biochemical recurrence of prostate cancer: association with tumour biology and PSA kinetics. Eur J Nucl Med Mol Imaging. 2024 Jul;51(8):2467\u0026ndash;83. doi:10.1007/s00259-024-06685-y\u003c/li\u003e\n\u003cli\u003ePereira Mestre R, Treglia G, Ferrari M, Pascale M, Mazzara C, Azinwi NC, et al. Correlation between PSA kinetics and detection rate of PSMA-PET in the setting of biochemical recurrent prostate cancer: A systematic review and meta-analysis. JCO. 2019 Mar 1;37(7_suppl):71\u0026ndash;71. doi:10.1200/JCO.2019.37.7_suppl.71\u003c/li\u003e\n\u003cli\u003eHaidar M, Abi-Ghanem AS, Moukaddam H, Jebai ME, Al Zakleet S, Al Rayess S, et al. 68Ga-PSMA PET/CT in early relapsed prostate cancer patients after radical therapy. Sci Rep. 2022 Nov 28;12(1):20500. doi:10.1038/s41598-022-24688-3\u003c/li\u003e\n\u003cli\u003eCeci F, Uprimny C, Nilica B, Geraldo L, Kendler D, Kroiss A, et al. 68Ga-PSMA PET/CT for restaging recurrent prostate cancer: which factors are associated with PET/CT detection rate? Eur J Nucl Med Mol Imaging. 2015 Jul;42(8):1284\u0026ndash;94. doi:10.1007/s00259-015-3078-6\u003c/li\u003e\n\u003cli\u003eSchmidt-Hegemann NS, Stief C, Kim TH, Eze C, Kirste S, Strouthos I, et al. Outcome after PSMA PET/CT based salvage radiotherapy in patients with biochemical recurrence after radical prostatectomy: a bi-institutional retrospective analysis. J Nucl Med. 2019 Feb 1;60(2):227\u0026ndash;33. doi:10.2967/jnumed.118.212563 PubMed PMID: 30002108; PubMed Central PMCID: PMC8833850.\u003c/li\u003e\n\u003cli\u003eCalais J, Czernin J, Cao M, Kishan AU, Hegde JV, Shaverdian N, et al. 68Ga-PSMA-11 PET/CT Mapping of Prostate Cancer Biochemical Recurrence After Radical Prostatectomy in 270 Patients with a PSA Level of Less Than 1.0 ng/mL: Impact on Salvage Radiotherapy Planning. J Nucl Med. 2018 Feb;59(2):230\u0026ndash;7. doi:10.2967/jnumed.117.201749 PubMed PMID: 29123013; PubMed Central PMCID: PMC5807533.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Prostate cancer, biochemical recurrence, PSMA PET/CT, PSA kinetics, PSA doubling time, radical prostatectomy","lastPublishedDoi":"10.21203/rs.3.rs-9064970/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9064970/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction \u0026amp; Objectives\u003c/h2\u003e \u003cp\u003eBiochemical recurrence (BCR) after radical prostatectomy (RP) occurs in approximately 20\u0026ndash;40%. PSMA PET/CT is the preferred imaging modality for detecting recurrence; however, detection rates decline sharply when PSA is \u0026lt;\u0026thinsp;1 ng/mL, leading to more negative scans, added costs and radiation exposure. PSA kinetics, which reflect tumour aggressiveness, have been correlated with PET positivity in mixed cohorts, but their role in post-prostatectomy BCR exclusively remains unclear. Our study aimed to evaluate the association between PSA kinetics and PSMA PET/CT positivity in post-RP BCR and to define clinically relevant kinetic cut-offs to improve imaging yield.\u003c/p\u003e\u003ch2\u003eMaterials \u0026amp; Methods\u003c/h2\u003e \u003cp\u003eA retrospective analysis of post-RP patients (2013\u0026ndash;2024) who developed BCR and underwent 68Ga-PSMA PET/CT was performed. Patients with prior therapy, PSA persistence, inadequate follow-up, or non-PSMA imaging were excluded. Institutional Ethics Committee approval was obtained prior to data collection. Baseline, pathological, and PSA kinetic parameters were compared between PET-positive and PET-negative cohorts. Logistic regression was used to assess correlation between PSA kinetics and PET positivity, and ROC analysis identified optimal cut-offs.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 973 men underwent RP during the study period. After applying the inclusion and exclusion criteria, 64 patients were included in final analysis. The median age was 67 years. 19 patients (29.7%) had positive scans, while 45 (70.3%) had negative scans. Baseline and pathological characteristics were comparable between the two groups. Median PSA at the time of imaging was 0.58 ng/mL. PSA kinetics differed significantly between groups. PET-positive patients had higher PSA velocity (1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20 vs 0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 ng/mL/year, p\u0026thinsp;=\u0026thinsp;0.02) and shorter doubling time (4.40\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03 vs 8.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.91 months, p\u0026thinsp;=\u0026thinsp;0.009). On univariate analysis, PSA velocity (PSAV) (OR 3.31, 95% CI 1.14\u0026ndash;9.58, p\u0026thinsp;=\u0026thinsp;0.027), PSA doubling time (PSADT) (OR 0.86, 95% CI 0.75\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.050), and PSA at imaging (OR 10.68, 95% CI 1.23\u0026ndash;93.11, p\u0026thinsp;=\u0026thinsp;0.032) were significant predictors of PET positivity. On ROC analysis, PSA-DT and PSAV showed good discriminatory power (AUC 0.71 and 0.69, respectively) with optimal cut-offs of 3.8 months and 0.5 ng/mL/year respectively.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePatients with PSA-DT\u0026thinsp;\u0026lt;\u0026thinsp;4 months or PSAV\u0026thinsp;\u0026gt;\u0026thinsp;0.5 ng/mL/year are more likely to have positive scans. Integration of PSA kinetics into imaging decisions can improve the yield. However, prospective studies with large sample size are needed for validation.\u003c/p\u003e","manuscriptTitle":"Can PSA Kinetics Improve the Yield of PSMA PET/CT in Biochemical Recurrence after Prostatectomy?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-19 16:00:44","doi":"10.21203/rs.3.rs-9064970/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"845ad709-e0e2-4167-943d-5b42a2f7aaef","owner":[],"postedDate":"March 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-06T07:11:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-19 16:00:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9064970","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9064970","identity":"rs-9064970","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}