Objective: To evaluate the roles of total prostate specific antigen (tPSA), PSA density (PSAD) and biopsy Gleason score in predicting the pathologic stage of prostate cancer.
Methods: We retrospectively analyzed the clinical data of 124 cases of pathologically confirmed prostate adenocarcinoma, and divided them into Groups A (n=48) and B (n=76) based on the results of bone scanning, CT, MRI, tPSA, PSAD and postoperative biopsy Gleason score, the former with extraprostatic infiltration or distant metastasis, while the latter without. We compared the above parameters between the two groups, screened the main factors that influenced the pathologic staging of prostate cancer by multivariate logistic regression analysis, and appraised the value of each of the parameters in predicting the pathologic stage of prostate cancer with a relative operating characteristic (ROC) curve.
Results: The tPSA level and biopsy Gleason score were significantly higher in Group A than in B (P < 0.05). Multivariate logistic regression analysis showed that only tPSA could predict the pathologic stage of localized prostate cancer. The ROC curve exhibited that the combined use of tPSA and Gleason score had a better predicting value than other parameters (Gleason score + tPSA > tPSA > PSAD + tPSA + Gleason score).
Conclusion: Total PSA remains a valuable predictor of the pathologic stage of prostate cancer, and its combination with Gleason score can further improve the predictive accuracy and contribute much to the treatment and prognosis of the disease.
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Int Urol Nephrol
January 2025
Faculty of Medical Sciences, Pharmacology and Toxicology Department, University of Kragujevac, Kragujevac, Serbia.
Purposes: Intermediate-risk prostate cancer (IR PCa) is the most common risk group for localized prostate cancer. This study aimed to develop a machine learning (ML) model that utilizes biopsy predictors to estimate the probability of IR PCa and assess its performance compared to the traditional clinical model.
Methods: Between January 2017 and December 2022, patients with prostate-specific antigen (PSA) values of ≤ 20 ng/mL underwent transrectal ultrasonography-guided prostate biopsies.
Cancer Immunol Immunother
January 2025
Division of Oncology, Department of Clinical Sciences Lund, and Lund University Cancer Center, Lund University, Lund, Sweden.
Tertiary lymphoid structures (TLS) in the tumor microenvironment are prognostically beneficial in many solid cancer types. Reports on TLS in high-grade serous tubo-ovarian carcinoma (HGSC) are few, and the prognostic impact is unclear. We investigated mature TLS (mTLS), immature TLS (iTLS) and lymphoid aggregates (LA) in primary adnexal tumors (PTs) and synchronous omental/peritoneal metastases (pMets) of HGSC.
View Article and Find Full Text PDFIntroduction: Prostate cancer is incidentally diagnosed in 6%-11% of benign prostatic hyperplasia surgeries.
Case Presentation: A 79-year-old man was diagnosed with benign prostatic hyperplasia. The prostate volume was 54.
Pathologica
October 2024
Pathology Unit, Department of Oncology, ASST Sette Laghi, Varese, Italy.
P53-abnormal endometrial carcinomas are high-grade and aggressive tumors which should be treated with chemo-/radiotherapy. In low-grade endometrioid carcinoma (LGEC), abnormal expression of p53 is an exceptional finding and is typically accompanied by patchy p16 positivity and diffuse hormone receptor expression. Herein, we report a case of LGEC exhibiting both p53 and p16 overexpression, highlighting the diagnostic pitfalls related to such phenotype.
View Article and Find Full Text PDFPathologica
October 2024
Biolab, PoliToBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
Objective: Stain normalization is a technique used to standardize the color appearance of digital whole slide images (WSIs). This study aimed to assess the impact of digital stain normalization on prostate cancer diagnosis by pathologists.
Methods: A multi-institutional board of four pathologists evaluated 407 hematoxylin and eosin (H&E) prostate WSIs before and after stain normalization.
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