Predictors of Prostate Cancer at Fusion Biopsy: The Role of Positive Family History, Hypertension, Diabetes, and Body Mass Index.


Journal

Current oncology (Toronto, Ont.)
ISSN: 1718-7729
Titre abrégé: Curr Oncol
Pays: Switzerland
ID NLM: 9502503

Informations de publication

Date de publication:
12 05 2023
Historique:
received: 25 03 2023
revised: 09 05 2023
accepted: 10 05 2023
medline: 29 5 2023
pubmed: 26 5 2023
entrez: 26 5 2023
Statut: epublish

Résumé

PSA density and an elevated PI-RADS score are among the strongest predictors of prostate cancer (PCa) in a fusion biopsy. Positive family history, hypertension, diabetes, and obesity have also been associated with the risk of developing PCa. We aim to identify predictors of the prostate cancer detection rate (CDR) in a series of patients undergoing a fusion biopsy. We retrospectively evaluated 736 consecutive patients who underwent an elastic fusion biopsy from 2020 to 2022. Targeted biopsies (2-4 cores per MRI target) were followed by systematic mapping (10-12 cores). Clinically significant PCa (csPCa) was defined as ISUP score ≥ 2. Uni- and multi-variable logistic regression analyses were performed to identify predictors of CDR among age, body mass index (BMI), hypertension, diabetes, positive family history, PSA, a positive digital rectal examination (DRE), PSA density ≥ 0.15, previous negative biopsy status, PI-RADS score, and size of MRI lesion. The median patients' age was 71 years, and median PSA was 6.6 ng/mL. A total of 20% of patients had a positive digital rectal examination. Suspicious lesions in mpMRI were scored as 3, 4, and 5 in 14.9%, 55.0%, and 17.5% of cases, respectively. The CDR was 63.2% for all cancers and 58.7% for csPCa. Only age (OR 1.04, In a series of patients selected for a fusion biopsy, positive family history, hypertension, diabetes, or BMI are not predictors of PCa detection. PSA-density and PI-RADS score are confirmed to be strong predictors of the CDR.

Sections du résumé

BACKGROUND
PSA density and an elevated PI-RADS score are among the strongest predictors of prostate cancer (PCa) in a fusion biopsy. Positive family history, hypertension, diabetes, and obesity have also been associated with the risk of developing PCa. We aim to identify predictors of the prostate cancer detection rate (CDR) in a series of patients undergoing a fusion biopsy.
METHODS
We retrospectively evaluated 736 consecutive patients who underwent an elastic fusion biopsy from 2020 to 2022. Targeted biopsies (2-4 cores per MRI target) were followed by systematic mapping (10-12 cores). Clinically significant PCa (csPCa) was defined as ISUP score ≥ 2. Uni- and multi-variable logistic regression analyses were performed to identify predictors of CDR among age, body mass index (BMI), hypertension, diabetes, positive family history, PSA, a positive digital rectal examination (DRE), PSA density ≥ 0.15, previous negative biopsy status, PI-RADS score, and size of MRI lesion.
RESULTS
The median patients' age was 71 years, and median PSA was 6.6 ng/mL. A total of 20% of patients had a positive digital rectal examination. Suspicious lesions in mpMRI were scored as 3, 4, and 5 in 14.9%, 55.0%, and 17.5% of cases, respectively. The CDR was 63.2% for all cancers and 58.7% for csPCa. Only age (OR 1.04,
CONCLUSIONS
In a series of patients selected for a fusion biopsy, positive family history, hypertension, diabetes, or BMI are not predictors of PCa detection. PSA-density and PI-RADS score are confirmed to be strong predictors of the CDR.

Identifiants

pubmed: 37232832
pii: curroncol30050374
doi: 10.3390/curroncol30050374
pmc: PMC10217714
doi:

Substances chimiques

Prostate-Specific Antigen EC 3.4.21.77

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4957-4965

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Auteurs

Marco Oderda (M)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Alessandro Dematteis (A)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Giorgio Calleris (G)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Adriana Conti (A)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Daniele D'Agate (D)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Marco Falcone (M)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Alessandro Marquis (A)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Gabriele Montefusco (G)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Giancarlo Marra (G)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

Paolo Gontero (P)

Division of Urology, Department of Surgical Sciences, Molinette Hospital, University of Turin, 10126 Turin, Italy.

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Classifications MeSH