scholarly journals Predictive models for diagnosing prostate cancer using the PI-RADSv2 classification and the PSA density

2021 ◽  
Vol 33 ◽  
pp. S231
Author(s):  
M.A. Rodríguez Cabello ◽  
J.L. Sanz Miguelañez ◽  
D. Vazquez Alva ◽  
A. Moraga Sanz ◽  
C. Aulló González ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Predictive Models ◽  
Psa Density

scholarly journals Is PSA density of the peripheral zone as a useful predictor for prostate cancer in patients with gray zone PSA levels?

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jaegeun Lee ◽  
Seung Woo Yang ◽  
Long Jin ◽  
Chung Lyul Lee ◽  
Ji Yong Lee ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Diagnosis ◽  
Prostate Biopsy ◽  
Peripheral Zone ◽  
Transitional Zone ◽  
Gray Zone ◽  
Prostate Cancer Diagnosis ◽  
Psa Density ◽  
Diagnosis Group ◽  
Predictive Rate

Abstract Background Serum prostate-specific antigen (PSA) is widely used in screening tests for prostate cancer. As the low specificity of PSA results in unnecessary and invasive prostate biopsies, we evaluated the clinical significance of various PSAs and PSA density (PSAD) related to peripheral zones in patients with gray zone PSA level (4–10 ng/mL). Methods A total of 1300 patients underwent transrectal ultrasonography-guided prostate biopsy from 2014 to 2019. Among them, 545 patients in the gray zone were divided into the prostate cancer diagnosis group and the non-prostate cancer diagnosis group, and PSA, relative extra transitional zone PSA (RETzPSA), estimated post holmium laser enucleation of the prostate PSA (EPHPSA), PSAD, peripheral zone PSA density (PZPSAD) and extra-transitional zone density (ETzD) were compared and analyzed using receiver-operating characteristics (ROC) analysis after 1:1 matching using propensity score. Results Area under the ROC curve values of PSA, EPHPSA, RETzPSA, PSA density, ETzD, and PZPSAD were 0.553 (95% CI: 0.495–0.610), 0.611 (95% CI: 0.554–0.666), 0.673 (95% CI: 0.617–0.725), 0.745 (95% CI: 0.693–0.793), 0.731 (95% CI: 0.677–0.780) and 0.677 (95% CI: 0.611–0.719), respectively. PSAD had 67.11% sensitivity, 71.71% specificity, and 70.34% positive predictive rate at 0.18 ng/mL/cc. ETzD had 69.08% sensitivity, 64.47% specificity, and 66.04% positive predictive rate at 0.04 ng/mL/cc. When the cut-off value of PSAD was increased to 0.18 ng/mL/cc, the best results were obtained with an odds ratio of 5.171 (95% CI: 3.171–8.432), followed by ETzD with 4.054 (95% CI: 2.513–6.540). Conclusions These results suggested that volume-adjusted parameters (ETzD and PSAD) might be more sensitive and accurate than various PSA in gray zone patients who required prostate biopsy to reduce unnecessary biopsy.

scholarly journals Performance of prostate health index and PSA density in a diverse biopsy‐naïve cohort with mpMRI for detecting significant prostate cancer

BJUI Compass ◽  
2021 ◽  
Author(s):  
Samuel Carbunaru ◽  
James Stinson ◽  
Rilwan Babajide ◽  
Courtney M. P. Hollowell ◽  
Ximing Yang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Health Index ◽  
Psa Density ◽  
Prostate Health Index ◽  
Prostate Health

32 Age adjusted PSA density cut off values. A costless way to reduce both underdiagnosis/overdiagnosis of prostate cancer and unnecessary biopses of the prostate

2015 ◽  
Vol 14 (8) ◽  
pp. e1365
Author(s):  
K.V. Mytilekas ◽  
K. Xouplidis ◽  
I. Apostolidis ◽  
X. Tontikidis ◽  
N. Kalinderis ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Psa Density

Role of PSA density in diagnosis of prostate cancer in obese men

2014 ◽  
Vol 46 (12) ◽  
pp. 2251-2254 ◽  
Author(s):  
Peter Ka-Fung Chiu ◽  
Jeremy Yuen-Chun Teoh ◽  
Samson Yun-Sang Chan ◽  
Peggy Sau-Kwan Chu ◽  
Chi-Wai Man ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Psa Density

scholarly journals Integrated predictive model for prostatic cancer using clinical, laboratory and ultrasound data

2016 ◽  
Vol 43 (6) ◽  
pp. 430-437
Author(s):  
GUSTAVO DAVID LUDWIG ◽  
HENRIQUE PERES ROCHA ◽  
LÚCIO JOSÉ BOTELHO ◽  
MAIARA BRUSCO FREITAS
Keyword(s):  
Prostate Cancer ◽  
Predictive Model ◽  
Prostate Biopsy ◽  
Clinical Laboratory ◽  
Prostate Volume ◽  
Specific Antigen ◽  
Digital Rectal Examination ◽  
Roc Curves ◽  
Rectal Examination ◽  
Psa Density

ABSTRACT Objective: to develop a predictive model to estimate the probability of prostate cancer prior to biopsy. Methods: from September 2009 to January 2014, 445 men underwent prostate biopsy in a radiology service. We excluded from the study patients with diseases that could compromise the data analysis, who had undergone prostatic resection or used 5-alpha-reductase inhibitors. Thus, we selected 412 patients. Variables included in the model were age, prostate specific antigen (PSA), digital rectal examination, prostate volume and abnormal sonographic findings. We constructed Receiver Operating Characteristic (ROC) curves and calculated the areas under the curve, as well as the model's Positive Predictive Value (PPV) . Results: of the 412 men, 155 (37.62%) had prostate cancer (PC). The mean age was 63.8 years and the median PSA was 7.22ng/ml. In addition, 21.6% and 20.6% of patients had abnormalities on digital rectal examination and image suggestive of cancer by ultrasound, respectively. The median prostate volume and PSA density were 45.15cm3 and 0.15ng/ml/cm3, respectively. Univariate and multivariate analyses showed that only five studied risk factors are predictors of PC in the study (p<0.05). The PSA density was excluded from the model (p=0.314). The area under the ROC curve for PC prediction was 0.86. The PPV was 48.08% for 95%sensitivity and 52.37% for 90% sensitivity. Conclusion: the results indicate that clinical, laboratory and ultrasound data, besides easily obtained, can better stratify the risk of patients undergoing prostate biopsy.

scholarly journals PSA Density Help to Identify Patients With Elevated PSA Due to Prostate Cancer Rather Than Intraprostatic Inflammation: A Prospective Single Center Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Salvatore M. Bruno ◽  
Ugo G. Falagario ◽  
Nicola d’Altilia ◽  
Marco Recchia ◽  
Vito Mancini ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Biopsy ◽  
Prostate Volume ◽  
Multivariable Analysis ◽  
Binary Logistic Regression Analysis ◽  
Single Center ◽  
Negative Biopsy ◽  
Psa Density ◽  
Clinically Significant ◽  
Prostatic Inflammation

The association between PSA density, prostate cancer (PCa) and BPH is well established. The aim of the present study was to establish whether PSA density can be used as a reliable parameter to predict csPCa and to determine its optimal cutoff to exclude increased PSA levels due to intraprostatic inflammation. This is a large prospective single-center, observational study evaluating the role of PSA density in the discrimination between intraprostatic inflammation and clinically significant PCa (csPCa). Patients with PSA ≥ 4 ng/ml and/or positive digito-rectal examination (DRE) and scheduled for prostate biopsy were enrolled. Prostatic inflammation (PI) was assessed and graded using the Irani Scores. Multivariable binary logistic regression analysis was used to assess if PSA density was associated with clinically significant PCa (csPCa) rather than prostatic inflammation. A total of 1988 patients met the inclusion criteria. Any PCa and csPCa rates were 47% and 24% respectively. In the group without csPCa, patients with prostatic inflammation had a higher PSA (6.0 vs 5.0 ng/ml; p=0.0003), higher prostate volume (58 vs 52 cc; p&lt;0.0001), were more likely to have a previous negative biopsy (29% vs 21%; p=0.0005) and a negative DRE (70% vs 65%; p=0.023) but no difference in PSA density (0.1 vs 0.11; p=0.2). Conversely in the group with csPCa, patients with prostatic inflammation had a higher prostate volume (43 vs 40 cc; p=0.007) but no difference in the other clinical parameters. At multivariable analysis adjusting for age, biopsy history, DRE and prostate volume, PSA density emerged as a strong predictor of csPCA but was not associated with prostatic inflammation. The optimal cutoffs of PSA density to diagnose csPCa and rule out the presence of prostatic inflammation in patients with an elevated PSA (&gt;4 ng/ml) were 0.10 ng/ml2 in biopsy naïve patients and 0.15 ng/ml2 in patients with a previous negative biopsy. PSA density rather than PSA, should be used to evaluate patients at risk of prostate cancer who may need additional testing or prostate biopsy. This readily available parameter can potentially identify men who do not have PCa but have an elevated PSA secondary to benign conditions.

scholarly journals Usefulness of Prostate-Specific Antigen Density as an Indicator for Recommending Prebiopsy Magnetic Resonance Imaging to Prevent Missed Prostate Cancer Diagnoses

2021 ◽  
Vol 19 (3) ◽  
pp. 155-163
Author(s):  
Jin Hyung Jeon ◽  
Kyo Chul Koo ◽  
Byung Ha Chung ◽  
Kwang Suk Lee
Keyword(s):  
Magnetic Resonance Imaging ◽  
Prostate Cancer ◽  
Magnetic Resonance ◽  
Prostate Specific Antigen ◽  
Specific Antigen ◽  
Resonance Imaging ◽  
Detection Rates ◽  
Psa Density ◽  
Systematic Biopsy ◽  
Target Biopsy

Purpose: To identify the indication for recommending prebiopsy magnetic resonance imaging (MRI) to prevent prostate cancer missed diagnoses in cases without prebiopsy MRI.Materials and Methods: Between January 2017 and September 2020, 585 patients suspected with prostate cancer underwent prostate biopsy after MRI. For patients with visible lesions, MRI-targeted biopsy using an image-based fusion program was performed in addition to the 12- core systematic biopsy. Patients for whom MRI was performed in other institutions (n=4) and patients who underwent target biopsy alone (n=7) were excluded.Results: Of 574 patients (median prostate-specific antigen [PSA] level, 6.88 ng/mL; mean age, 68.2 years), 342 (59.6%) were diagnosed with prostate cancer (visible lesions=312/449 [69.5%]; nonvisible lesions=30/123 [24.0%]). The detection rates of visible lesions stratified using the Prostate Imaging Reporting and Data System score (3 vs. 4 vs. 5) were 30.9% (54 of 175), 61.2% (150 of 245), and 90.1% (127 of 141), respectively. Multivariate analysis showed that PSA density was a significant factor for presence of visible lesions, prostate cancer, and significant prostate cancer diagnosis. Among patients with positive lesions, 27 (8.2%) were diagnosed with prostate cancer concomitant with negative systematic biopsy results. A PSA density of 0.15 ng/mL/cm<sup>3</sup> was identified as the significant cutoff value for predicting positive target biopsy in groups with negative systematic biopsy. Sixty of the negative target lesions (26.1%) were diagnosed using systematic biopsy.Conclusions: To maximize cancer detection rates, both targeted and systematic biopsies should be implemented. PSA density was identified as a useful factor for recommending prebiopsy MRI to patients suspected with prostate cancer.

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