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Record W4402173496 · doi:10.5812/numonthly-147023

Investigation of the Relationship Between Prostate-Specific Antigen Levels and Prostate Cancer in Patients Attending a Urology Clinic from 2014 to 2023

2024· article· en· W4402173496 on OpenAlexaff
Hamed Mohseni Rad, Ali Hosseinkhani, Emad Hosseinkhani, Mahdieh Aali

Bibliographic record

VenueNephro-Urology Monthly · 2024
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsBrock University
Fundersnot available
KeywordsMedicineUrologyProstate cancerProstate-specific antigenProstateGynecologyInternal medicineOncologyCancer

Abstract

fetched live from OpenAlex

Background: Prostate cancer is the second most common neoplasm and the fifth most aggressive cancer among men worldwide, with approximately 1.4 million new cases diagnosed annually. The incidence and mortality of prostate cancer increase with age, with a mean age at diagnosis of 66 years. Prostate cancer may be asymptomatic in its early stages and often has a latent period. The use of the Prostate-Specific Antigen (PSA) Index in the definitive diagnosis of prostate cancer remains a challenge for many urologists, and further research in this area can help to better understand the precise relationship between PSA levels and prostate cancer. Objectives: The present study aimed to investigate the relationship between PSA levels and prostate cancer in patients attending a urology clinic from 2014 to 2023, with the goal of improving diagnosis, developing effective treatments, and enhancing clinical outcomes. Methods: In this cross-sectional study, 242 patients with prostate cancer who attended a urology surgical clinic over a nine-year period from 2014 to 2023 were included. The patients were divided into two groups—youngest and oldest—based on the duration of their disease diagnosis. Demographic and clinical laboratory data were collected and entered into a checklist. Subsequently, the patients underwent a biopsy, and the results were recorded. Upon completion of the study, the collected data were entered into SPSS software for statistical analysis. Multiple regression analysis was used for correlation tests, while nonparametric tests, such as the Kruskal-Wallis test and the Mann-Whitney U test, were applied for nonparametric data analysis. Results: This study included 242 out of 276 samples for analysis. The ages of the participants ranged from 41 to 90 years, with a mean age of 67 ± 9.42 years. The data indicated that at PSA concentrations of 4 - 10 ng/mL, 5% of the samples were healthy, 15.2% had cancer, 46% had benign prostatic hyperplasia (BPH), and 33% had prostate intraepithelial neoplasia (PIN). At PSA concentrations of 10 - 50 ng/mL, 6% of the samples were healthy, 37% had cancer, 26% had BPH, and 29% had PIN. At PSA concentrations greater than 50 ng/mL, 3% of the samples were healthy, 76% had cancer, 14% had BPH, and 7% had PIN. A chi-square test revealed a significant association between PSA levels and pathological response (P < 0.001). Additionally, an analysis of variance (ANOVA) test showed a significant difference between different age and severity groups (P < 0.001). The free PSA-to-total PSA ratio in this study was 0.18, and the PSA-to-prostate volume ratio was 0.15, both of which were significantly associated with biopsy results (P < 0.01). Conclusions: Overall, the data obtained from this study indicated that plasma PSA levels were directly associated with the likelihood of prostate cancer. Additionally, the results showed that plasma PSA levels were not only directly associated with age but also correlated with the severity of trophic disorders, such as cancer, as indicated by biopsy results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.307
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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