Objectives: To evaluate the impact of antibiotic treatment on total prostate specific antigen (PSA) levels and free/total (f/t) PSA ratio and the relevance of these changes to prostate biopsy results.

Methods: We retrospectively evaluated 1,062 patients with elevated age-adjusted serum PSA levels who underwent prostate biopsy between 2004 and 2016. A total of 303 cases with followup PSA levels and f/t PSA ratio before and after antibiotherapy were included into this study. There were 214 patients with persistent elevated serum PSA levels after antibiotic treatment followed by prostate biopsy (treatment group) and 89 patients who had prostate biopsy after a mean followup of 1 month without antibiotherapy (control group). The groups were compared with regard to both 5% and 10% cut off changes in serum PSA levels and f/t PSA ratios.

Results: Antibiotic treatment had no impact on the relation between serum PSA levels and biopsy results at both cut off values. On the other hand, f/t PSA ratio changes at both cut off values with relevance to antibiotic treatment were found to be related with histopathologic results. While increase in f/t PSA ratio was more related with benign biopsies, decrease in f/t PSA ratio was more related with cancer (for 5% cut off value p= 0.014, p= 0.004; for 10% cut off value p= 0.026, p= 0.014).

Conclusion: Changes at f/t PSA ratio rather than total PSA only, particularly in antibiotic treated cases appear to be more useful in decision making for biopsy.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445968PMC
http://dx.doi.org/10.31557/APJCP.2020.21.4.1051DOI Listing

Publication Analysis

Top Keywords

psa ratio
28
f/t psa
28
psa levels
24
prostate biopsy
20
serum psa
20
psa
17
antibiotic treatment
16
ratio changes
8
elevated serum
8
levels f/t
8

Similar Publications

Background: To examine the feasibility and safety of the SENSEI drop-in gamma probe for robot-assisted, prostate-specific membrane antigen (PSMA)-radioguided salvage surgery (RGS) in lymph node or local oligorecurrent prostate cancer (PCa), detected via PSMA positron emission tomography/computed tomography (PET/CT).

Methods: The first thirteen patients with pelvic oligorecurrent PCa who underwent [Tc]Tc-PSMA-I&S RGS using the SENSEI drop-in gamma probe at the Martini-Klinik (February-June 2024) were retrospectively analyzed. Radioactivity measurements in counts per second (CPS) as absolute values or ratios (CPS of tumor specimens/mean CPS from the patients' benign tissues) were correlated with preoperative imaging and pathological findings (benign/malignant, lesion size).

View Article and Find Full Text PDF

Background: The Prostatype score (P-score) is a prognostic biomarker that integrates a three-gene (IGFBP3, F3, and VGLL3) signature derived from prostate biopsy samples, with key clinical parameters, including prostate-specific antigen (PSA) levels, Gleason grade, and tumor stage at diagnosis. The test has demonstrated superior predictive accuracy for prostate cancer outcomes compared with traditional risk categorization systems such as D'Amico. Notably, it reclassifies a higher proportion of patients into the low-risk category, making them eligible for active surveillance.

View Article and Find Full Text PDF

Purpose To validate a deep learning (DL) model for predicting the risk of prostate cancer (PCa) progression based on MRI and clinical parameters and compare it with established models. Materials and Methods This retrospective study included 1607 MRI scans of 1143 male patients (median age, 64 years; IQR, 59-68 years) undergoing MRI for suspicion of clinically significant PCa (csPCa) (International Society of Urological Pathology grade > 1) between January 2012 and May 2022 who were negative for csPCa at baseline MRI. A DL model was developed using baseline MRI and clinical parameters (age, prostate-specific antigen [PSA] level, PSA density, and prostate volume) to predict the time to PCa progression (defined as csPCa diagnosis at follow-up).

View Article and Find Full Text PDF

Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator.

Sci Rep

January 2025

Department of Urology, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital, Wuhu, 241001, Anhui, People's Republic of China.

To create a diagnostic tool before biopsy for patients with prostate-specific antigen (PSA) levels < 20 ng/ml to minimize prostate biopsy-related discomfort and risks. Data from 655 patients who underwent transperineal prostate biopsy at the First Affiliated Hospital of Wannan Medical College from July 2021 to January 2023 were collected and analyzed. After applying the Synthetic Minority Over-sampling TEchnique class balancing on the training set, multiple machine learning models were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) feature selection to identify the significant variables.

View Article and Find Full Text PDF

Biologics in the treatment of active Psoriatic arthritis in China: a network meta-analysis and cost-effectiveness analysis.

Expert Rev Pharmacoecon Outcomes Res

January 2025

Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.

Background: Biologics are recommended for use in patients with psoriatic arthritis (PsA) after the failure of conventional systemic disease-modifying anti-rheumatic drugs (csDMARDs). However, compared to csDMARDs, biologics are significantly more expensive. The aim of this study was to evaluate the cost-effectiveness of biologic treatments for active PsA patients who have failed treatment with csDMARDs, from the perspective of the Chinese healthcare system.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!