Investigation of GSTP1 and epigenetic regulators expression pattern in a population of Iranian patients with prostate cancer

2020 ◽  
Vol 28 (4) ◽  
pp. 327-334
Author(s):  
Mahan Mohammadi ◽  
Shiva Irani ◽  
Iman Salahshourifar ◽  
Jalil Hosseini ◽  
Afshin Moradi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Efficiency ◽  
Rna Extraction ◽  
P Value ◽  
Prostate Hyperplasia ◽  
Expression Of Genes ◽  
Elevated Expression ◽  
Epigenetic Regulators ◽  
The Impact ◽  
Iranian Patients

BACKGROUND AND AIM: Prostate cancer is the leading cause of death in many countries. It is important to diagnose the disease in the early stages. Current methods detect the disease with low specificity. Examining the expression of genes responsible for disease and their epigenetic regulators are good tools in this regard. MATERIAL AND METHODS: In this prospective case-control study, 40 Iranian patients with cancer, 40 Iranian patients with prostate hyperplasia, and 40 control samples were examined. After blood sampling from each individual, RNA extraction and cDNA synthesis, GSTP1, HDAC, DNMT3A, and DNMT3B expressions were measured in three understudy groups using specific primers and Real-Time PCR method. RESULTS: A reverse correlation was identified between loss of GSTP1 expression and overexpression of HDAC, DNMT3A, and DNMT3B (P value < 0.0001) with a beneficial pattern of cancer development with high efficiency. The significant decrease of GSTP1 expression in patients in comparison to the healthy controls and the elevated expression levels of the studied epigenetic regulators in PCA and BPH samples indicate the impact of the regulators on GSTP1 expression activity. CONCLUSION: This study showed that the measurement of combined GSTP1 and its epigenetic regulators’ expression could be used as suitable genetic markers for the detection and separation of healthy individuals from prostatic patient groups in the Iranian population. However, a similar study in a larger population of case and control could help us to distinguish between normal, benign, and malignant conditions.

Gene profiling in transurethral resection samples of patients with hormone-refractory prostate cancer (HRPC)

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 4641-4641
Author(s):  
O. Stoss ◽  
P. Albers ◽  
M. Werther ◽  
D. Zielinsky ◽  
N. Jost ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Transurethral Resection ◽  
Molecular Mechanisms ◽  
Cell Signalling ◽  
Rna Extraction ◽  
Gene Profiling ◽  
P Value ◽  
Jnk Pathway ◽  
Tissue Samples ◽  
Ablation Therapy

4641 Background: Patients with metastatic carcinoma of the prostate (CaP) develop after a mean of 15 months resistance to hormone ablation therapy. However, the underlying molecular mechanisms are still unknown. Our goal was to identify the transcriptional changes that are characteristic for the transition to hormone resistant prostate cancer (HRPC) using oligonucleotide microarrays. Here, we report the attempt to profile fresh frozen tissue obtained by palliative transurethral resection (TUR) in patients with HRPC and concomittant urinary obstruction. Methods: Indications for palliative TUR were locally progressive tumors with obstruction and voiding problems. HRPC was defined according to the criteria of Scher et al. 1995. Samples of 8 HRPC patients were compared to tissues from 8 hormone-sensitive CaP patients including biological and technical replicates. All tissue samples had been pathologically evaluated. Only macrodissected prostate samples with at least 70% tumor content were used for RNA extraction. RNA quality was controlled using the Bioanalyzer Nanochip (Agilent Technologies, Palo Alto). Expression analysis was performed on Affymetrix oligonucleotide arrays. Results: We identified 323 genes being significantly deregulated (corrected p-value <0.05, false discovery rate <0.05). These genes were mapped to cellular pathways using the KEGG annotation and the most significantly deregulated pathways were identified. Deregulation of metabolic pathways included fatty acid metabolism as well as oxidative phosphorylation and ATP synthesis. Cell cycle control seems to be further suppressed by the downregulation of JNK-pathway via MEKK4 and JUND, the downregulation of p21 (CDKN1A) and the induction of Cylcin D1. We also present evidence for a significant downregulation of actin cyctoskeleton components. Deregulated genes likely to be specific for the transition from prostate carcinoma to HRPC will be presented. Conclusions: Gene expression profiling has been successfully standardised using fresh TUR material of HRPC patients. Deregulated genes have been mapped to specific signal transduction pathways. On this platform, clinical trials in patients with HRPC using specific inhibitors of cell signalling are being developed. [Table: see text]

Impact of the USPSTF recommendations on prostate cancer stage migration and de-novo metastatic prostate cancer.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 166-166 ◽  
Author(s):  
Yu-Wei Chen ◽  
Ruby Gupta ◽  
Moshe Chaim Ornstein ◽  
Brian I. Rini ◽  
Timothy D. Gilligan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Metastatic Disease ◽  
De Novo ◽  
Task Force ◽  
Specific Antigen ◽  
P Value ◽  
Stage Migration ◽  
Nodal Disease ◽  
Psa Screening ◽  
The Impact

166 Background: The US Preventive Services Task Force (USPSTF) recommended against prostate specific antigen (PSA) screening for men aged≥75 in 2008 and all men in 2012 in an effort to reduce overdiagnosis and overtreatment of men with prostate cancer (PCa). This recommendation may delay diagnosis of clinically significant PCa. Methods: The Surveillance, Epidemiology and End Results Program (SEER) was used to identify men diagnosed with PCa between 2004-2015. PCa stage was categorized as localized (N0M0), nodal (N1M0) and metastatic (NxM1). Trend analysis was stratified on age group (PSA screening eligible was defined as age 55-69 according to the 2018 updated USPSTF recommendation). Multivariable logistic regression was used to identify predictors for nodal and metastatic disease. Results: Between 2004-2015, there were 603,323 men with PCa identified. Metastatic disease accounted for 2.8% of PCa in 2004-2008, 3.7% in 2009-2012, and 6.1% in 2013-2015. In men eligible for PCa screening, metastatic disease increased from 1.9% in 2004-2008, to 2.6% in 2009-2012, to 4.2% in 2013-2015; nodal disease increased from 1.4% to 1.6% to 2.6%, respectively (both p-value for trend< 0.0001). This stage migration was also observed in non-screening eligible groups (age >70 and <55). Compared with PCa diagnosed in 2009-2012, PCa diagnosed in 2013-2015 had higher odds of metastatic disease (AOR: 1.70, p-value<0.0001) or nodal disease (AOR: 1.71, p-value<0.0001). Conclusions: Men diagnosed with PCa in 2013-2015 were more likely to have metastatic or nodal disease, suggesting PCa stage migration since PSA screening was recommended to be discontinued in 2012. Although the impact of PSA screening on PCa mortality remains debatable, the reduced quality of life with advanced Pca should not be overlooked. Future population studies are warranted to investigate the influence of the updated 2018 USPSTF recommendation. [Table: see text]

scholarly journals Small RNAs as biomarkers to differentiate benign and malign prostate diseases: An alternative for transrectal punch biopsy of the prostate?

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247930
Author(s):  
Lukas Markert ◽  
Jonas Holdmann ◽  
Claudia Klinger ◽  
Michael Kaufmann ◽  
Karin Schork ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Machine Learning ◽  
Small Rnas ◽  
Punch Biopsy ◽  
Machine Learning Algorithms ◽  
P Value ◽  
Prostate Hyperplasia ◽  
Prostate Diseases ◽  
Exosomal Mirna ◽  
Benign Prostate

Prostate cancer (PCa) is the most common cancer and the third most frequent cause of male cancer death in Germany. MicroRNAs (miRNA) appear to be involved in the development and progression of PCa. A diagnostic differentiation from benign prostate hyperplasia (BPH) is often only possible through transrectal punch biopsy. This procedure is described as painful and carries risks. It was investigated whether urinary miRNAs can be used as biomarkers to differentiate the prostate diseases above. Therefore urine samples from urological patients with BPH (25) or PCa (28) were analysed using Next-Generation Sequencing to detect the expression profile of total and exosomal miRNA/piRNA. 79 miRNAs and 5 piwi-interacting RNAs (piRNAs) were significantly differentially expressed (adjusted p-value < 0.05 and log2-Fc > 1 or < -1). Of these, 6 miRNAs and 2 piRNAs could be statistically validated (AUC on test cohort > = 0.7). In addition, machine-learning algorithms were used to identify a panel of 22 additional miRNAs, whose interaction makes it possible to differentiate the groups as well. There are promising individual candidates for potential use as biomarkers in prostate cancer. The innovative approach of applying machine learning methods to this kind of data could lead to further small RNAs coming into scientific focus, which have so far been neglected.

The impact of intratumoral heterogeneity on prognostic biomarkers in localized prostate cancer.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 46-46
Author(s):  
Harry Brastianos ◽  
Jure Murgic ◽  
Adriana Salcedo ◽  
Melvin Lee Kiang Chua ◽  
Alice Meng ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Biochemical Recurrence ◽  
Cox Proportional Hazards ◽  
Intratumoral Heterogeneity ◽  
Genomic Variation ◽  
P Value ◽  
Genomic Biomarkers ◽  
Multiple Tumor ◽  
The Impact

46 Background: Genomic biomarkers can identify patients that harbour aggressive disease. The utility of these biomarkers is uncertain due to genomic variation between prostate biopsy specimens. To quantify the robustness of genomic biomarkers, we performed spatio-genomic characterization of distinct tumor foci. We scored three validated DNA-based biomarkers of early biochemical recurrence: percentage of genome with a copy number aberration (PGA), a 100-loci biomarker, and an optimized 31- loci biomarker derived from the previous. For each biomarker, we determined their robustness to intratumoral heterogeneity in association with predicting early biochemical recurrence (eBCR; ≤18 months) and long term control (LTC; ≥48 months). Methods: We queried a registry of 1054 patients with high-risk prostate cancer who underwent a radical prostatectomy (RP). We developed a cohort (n = 42) risk matched by clinicopathologic prognostic indices. Half of the patients had eBCR, while the other half had LTC. We profiled multiple tumor foci per patient, analyzing 119 tumor foci. For each focus, CNA profiles were generated, and three biomarker scores were calculated. For each patient and biomarker, we calculated the score of the lowest-score region, the highest-score region, or sampling of all foci and use the mean score. Results: All three biomarkers distinguished LTC from eBCR. PGA scores separated the two groups with an area under the receiver operator curves (AUC) ranging from 0.75-0.80. The 100- and 31-loci signatures, had AUCs ranging from 0.76-0.85 and 0.76-0.80 respectively. Using Cox proportional hazards modeling, we found that PGA was associated with LTC (Hazard ratio (HR) range: 2.56-6.22; p < 0.05. This was replicated for the 100-loci signature (HR range: 3.55-5.23; p < 0.05). The 31-loci detected associations with eBCR independent of how different foci were summarized (log-rank p-value range: 5.1 x 10-4- 5.9 x 10-3). Conclusions: Despite divergence in biomarker scores, all three predicted eBCR. Our study suggests that genomic biomarkers can overcome intratumoral heterogeneity, making discrete samples potentially adequate in patients with high-risk disease to determine the risk of eBCR after radical treatment.

scholarly journals Farming, Reported Pesticide Use, and Prostate Cancer

2012 ◽  
Vol 7 (2) ◽  
pp. 102-109 ◽  
Author(s):  
Camille Ragin ◽  
Brionna Davis-Reyes ◽  
Helina Tadesse ◽  
Dennis Daniels ◽  
Clareann H. Bunker ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Pesticide Exposure ◽  
Meta Analysis ◽  
P Value ◽  
Cancer Type ◽  
Case Control Studies ◽  
Prostate Hyperplasia ◽  
Unpublished Studies ◽  
Pubmed Database ◽  
Increased Risk

Prostate cancer is the leading cancer type diagnosed in American men and is the second leading cancer diagnosed in men worldwide. Although studies have been conducted to investigate the association between prostate cancer and exposure to pesticides and/or farming, the results have been inconsistent. We performed a meta-analysis to summarize the association of farming and prostate cancer. The PubMed database was searched to identify all published case–control studies that evaluated farming as an occupational exposure by questionnaire or interview and prostate cancer. Ten published and two unpublished studies were included in this analysis, yielding 3,978 cases and 7,393 controls. Prostate cancer cases were almost four times more likely to be farmers compared with controls with benign prostate hyperplasia (BPH; meta odds ratio [OR], crude = 3.83, 95% confidence interval [CI] = 1.96-7.48, Q-test p value = .352; two studies); similar results were obtained when non-BPH controls were considered, but with moderate heterogeneity between studies (meta OR crude = 1.38, 95% CI = 1.16-1.64, Q-test p value = .216, I2 = 31% [95% CI = 0-73]; five studies). Reported pesticide exposure was inversely associated with prostate cancer (meta OR crude = 0.68, 95% CI = 0.49-0.96, Q-test p value = .331; four studies), whereas no association with exposure to fertilizers was observed. Our findings confirm that farming is a risk factor for prostate cancer, but this increased risk may not be due to exposure to pesticides.

scholarly journals The effects of aneuploidy on gene expression in a dosage series of maize chromosome arm 1L

2017 ◽  
Author(s):  
◽  
Adam Johnson
Keyword(s):  
Gene Expression ◽  
Chromosome Region ◽  
Rna Extraction ◽  
Leaf Tissue ◽  
Dosage Level ◽  
Expression Of Genes ◽  
Chromosome Arm ◽  
Cascade Effects ◽  
The Impact

Aneuploidy is a class of genetic conditions involving an unbalanced number of chromosomes. The most familiar human aneuploid condition is trisomy 21, called Down syndrome. Aneuploid conditions necessarily involve a change in the dosage of those genes which are located on the varied chromosome. However, the dosage level of a gene does not automatically correspond to the amount of RNA or protein that will be produced in vivo. Based on previously published studies, the impact of chromosome dosage changes on the transcription of single genes may be direct, inverse, or anywhere in between; and genes may be impacted anywhere in the genome, not just on the varied chromosome. Using a maize model system, a dosage series of plants was produced in which sibling plants are identical, except for the copy number of chromosome arm 1L. These plants were grown until 45 days postgermination, at which point leaf tissue was collected for RNA extraction. This dosage series included 5 dosage levels for comparison: diploid, trisomic, tetrasomic, haploid, and disomic haploid. A second dosage series was grown up to day 55, and included diploid, monosomic, and trisomic. Using RNA sequencing, expression levels for all genes were determined. The results were analyzed in aggregate, allowing for a view of effects on the level of the whole transcriptome. Results suggest that dosage of genes on the varied chromosome region has some correlation with expression of those genes, though the change compared to a diploid is often partial. Inverse relationships between chromosome dosage and RNA expression of genes elsewhere in the genome are seen to occur. Both direct and inverse reactions were amplified by increased levels of genomic imbalance. The kinetics of interacting proteins and other cellular components, as described in the gene balance hypothesis, may be the mechanism leading to these responses. Using the same methods of analysis, similar phenomena were observed in aneuploid/euploid comparisons in other organisms. Partial dosage compensation and inverse effects were observed in published datasets from aneuploid yeast and mouse. A set of trisomics in Arabidopsis displayed the same effects, though to a different extent in different trisomies. Using a published database of transcription factors, the responses of genes to dosage changes of their regulators was analyzed. A number of cascade effects were observed, in which inverse relationships of transcription factor dosage and target gene expression occurred sequentially, disrupting normal regulation of several genes in a network by changing the dosage of a single component.

Outcomes of statin use in veterans with prostate cancer: A retrospective single-center experience.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e17612-e17612
Author(s):  
Brian Warnecke ◽  
Juan Garza ◽  
Paromita Datta ◽  
Annie Hung ◽  
Michael Mader ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Primary Endpoint ◽  
San Antonio ◽  
The United States ◽  
Epidemiological Studies ◽  
P Value ◽  
End Points ◽  
Statin Usage ◽  
The Impact ◽  
Statin Use

e17612 Background: Prostate cancer is the most common cancer in men in the United States. Death in prostate cancer patients is often reported to be non-prostate cancer related, attributed to other medical conditions. As prostate cancer is associated with a prolonged survival, care of these patients includes optimizing other co-morbidities, such as cardiovascular disease. There are multiple reports and epidemiological studies of statins decreasing the risk, progression, and overall mortality of prostate cancer. Previously we had gathered data on 300 patients diagnosed with prostate cancer at the VA in San Antonio. The results indicated that using statins has a statistically significant positive effect at delaying death by prostate cancer, with a p-value of 0.018. We have updated our results with the addition of 105 patients. Methods: This is a retrospective observational study with chart review of 405 patients diagnosed with prostate cancer from 1995 to 2010, in a VA Hospital in San Antonio, Texas. Variables included age of diagnosis, statin use, type of statin (1st, 2nd, or 3rd generation), dose of statin (6 levels of dosage were identified), length of statin use, time followed in months (from time of diagnosis to either death or the end of the study period), death, and cause of death. The Cox proportional hazards regression model was used to estimate the hazard function, with age at diagnosis used as a covariate. Primary end point was death by prostate cancer (33 patients) and secondary end points- death by any cancer (71 patients), and death by all causes (205 patients). Results: The hazard ratio for use of statins at least 6 months was 0.56, with 95% confidence limits of 0.41 to 1.13, and a p-value of 0.118, indicating no statistically significant effect of statin usage and delay in death by prostate cancer. Secondary endpoint of death by all causes was significantly affected by statins, while death by any cancer showed no significant effect. The study was unable to conclude if the type of statin, dose of statin or the length of statin use had a significant effect in reaching the different end points. Conclusions: The addition of 105 more patients to this study has changed our previous statistically significant primary endpoint results.Concomitant statin use may not help prevent death from prostate cancer or death from any cancer, but may help prevent death from all causes. This updated primary endpoint data conflicts with multiple prior epidemiological studies and raises questions on the impact of statin usage on men with prostate cancer.

The impact of race and insurance status on survival of prostate cancer patients.

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 233-233
Author(s):  
Trevanne Rose Matthews Hew ◽  
Jason Desmond Hew ◽  
Hardik Satish Chhatrala ◽  
Ian Tfirn ◽  
Meet Kadakia ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
African Americans ◽  
Cancer Patients ◽  
Low Income ◽  
Health Care Access ◽  
P Value ◽  
Insurance Type ◽  
Lower Stage ◽  
Chi Square Analysis ◽  
The Impact

233 Background: While prostate cancer mortality has declined in the in the general population, it remains high in African Americans. The aim of our study is to determine whether race and insurance type affect treatment outcomes in prostate cancer patients at our institution. Methods: A retrospective chart analysis between 2012 and 2017 of 2763 prostate cancer patients was done at our institution. We collected data on age, race, stage, insurance, treatment history, date of diagnosis, Gleason score, date of death. The healthcare insurance information was categorized into Medicare with and without supplement, VA, Medicaid, no insurance/self- pay, City Contract and private. City Contract is the city sponsored health care access for person with low income living in the Duval County. Univariate and multivariate chi square analysis with odd ratio was performed, 95 % confident intervals were evaluated with P value < 0.05. Results: African Americans were 2.93 times more likely to experience death than Caucasians (Odds Ratio, OR, 1.79-4.78, 95 % CI). Both Private and VA insurance were more likely to have a lower stage of prostate cancer compared to City Contract (0.53 times, 0.30-0.93, and 0.411 times, OR 0.23-0.84 95 % CI respectively). African Americans were significantly more likely to have a more advanced cancer stage when compared to Caucasians (1.85 times, 1.49 -2.29 95 % CI). Every insurance type was significantly less likely to undergo surgery compared to City Contract. All except Medicaid, were more likely to undergo radiation compared to City Contract. African Americans are more likely to undergo surgery (2.68 times, 2.01-3.56, 95% CI) and were less likely to have radiation or chemotherapy when compared Caucasians (0.25 times, 0.20-0.31 95% CI). Conclusions: Disparities in race and insurance type can affect the stage at presentation, type of treatment received and survival.[Table: see text]

scholarly journals Phosphodiesterase SMPDL3B Gene Expression as Independent Outcome Prediction Marker in Localized Prostate Cancer

2020 ◽  
Vol 21 (12) ◽  
pp. 4373
Author(s):  
Frank Waldbillig ◽  
Katja Nitschke ◽  
Abdallah Abdelhadi ◽  
Jost von Hardenberg ◽  
Philipp Nuhn ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cell Migration ◽  
Outcome Prediction ◽  
The Cancer Genome Atlas ◽  
Localized Prostate Cancer ◽  
Prostate Hyperplasia ◽  
Long Term Follow Up ◽  
And Migration ◽  
Sirna Knockdown ◽  
The Impact

Current outcome prediction markers for localized prostate cancer (PCa) are insufficient. The impact of the lipid-modifying Sphingomyelin Phosphodiesterase Acid Like 3B (SMPDL3B) in PCa is unknown. Two cohorts of patients with PCa who underwent radical prostatectomy (n = 40, n = 56) and benign prostate hyperplasia (BPH) controls (n = 8, n = 11) were profiled for SMPDL3B expression with qRT-PCR. Publicly available PCa cohorts (Memorial Sloane Kettering Cancer Centre (MSKCC; n = 131, n = 29 controls) and The Cancer Genome Atlas (TCGA; n = 497, n = 53 controls)) served for validation. SMPDL3B’s impact on proliferation and migration was analyzed in PC3 cells by siRNA knockdown. In both cohorts, a Gleason score and T stage independent significant overexpression of SMPDL3B was seen in PCa compared to BPH (p < 0.001 each). A lower expression of SMPDL3B was associated with a shorter overall survival (OS) (p = 0.005) in long term follow-up. A SMPDL3B overexpression in PCa tissue was confirmed in the validation cohorts (p < 0.001 each). In the TCGA patients with low SMPDL3B expression, biochemical recurrence-free survival (p = 0.011) and progression-free interval (p < 0.001) were shorter. Knockdown of SMPDL3B impaired PC3 cell migration but not proliferation (p = 0.0081). In summary, SMPLD3B is highly overexpressed in PCa tissue, is inversely associated with localized PCa prognosis, and impairs PCa cell migration.

scholarly journals Development of Interpretable Predictive Models for BPH and Prostate Cancer

2015 ◽  
Vol 9 ◽  
pp. CMO.S19739 ◽  
Author(s):  
Pablo Bermejo ◽  
Alicia Vivo ◽  
Pedro J. Tárraga ◽  
J. A. Rodríguez-Montes
Keyword(s):  
Prostate Cancer ◽  
Logistic Regression ◽  
Decision Tree ◽  
Predictive Models ◽  
Specific Antigen ◽  
Digital Rectal Examination ◽  
Statistical Dependence ◽  
P Value ◽  
Prostate Hyperplasia ◽  
Logistic Regression Models

Background Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH. Methods An observational study was performed on 150 patients with PSA ≥3 ng/mL and age >50 years. We built a decision tree and a logistic regression model, validated with the leave-one-out methodology, in order to predict PC or BPH, or reject both. Results Statistical dependence with PC and BPH was found for prostate volume ( P-value < 0.001), PSA ( P-value < 0.001), international prostate symptom score (IPSS; P-value < 0.001), digital rectal examination (DRE; P-value < 0.001), age ( P-value < 0.002), antecedents ( P-value < 0.006), and meat consumption ( P-value < 0.08). The two predictive models that were constructed selected a subset of these, namely, volume, PSA, DRE, and IPSS, obtaining an area under the ROC curve (AUC) between 72% and 80% for both PC and BPH prediction. Conclusion PSA and volume together help to build predictive models that accurately distinguish among PC, BPH, and patients without any of these pathologies. Our decision tree and logistic regression models outperform the AUC obtained in the compared studies. Using these models as decision support, the number of unnecessary biopsies might be significantly reduced.

Sign in / Sign up

Export Citation Format

Share Document