Diagnosis Of Prostate Cancer In Patients Research Articles

The Value of Elastography in the Detection of Prostate Cancer – Clinical Experience

The aim of this study was to evaluate the efficacy of real-time shear wave elastography (SWE) in prostate cancer diagnosis in patients with elevated prostate-specific antigen values and abnormal results on digital rectal examination. This study included 74 patients (mean age 68.3 years) with suspected prostate cancer – prostate-specific antigen>4 ng/mL and abnormal digital rectal examination. All patients scheduled for transrectal ultrasound biopsy of the prostate underwent standard transrectal ultrasonography and SWE. The reported sensitivity and specificity of SWE in the various studies varied widely, from 43–96% and 33–96%, respectively. This study showed that patients with elevated levels of prostate-specific antigen, abnormal digital rectal examination, and negative SWE may not require a biopsy which could significantly reduce the number of biopsies performed.

Disparities in diabetes-related outcomes in prostate cancer patients - role of social determinants of health and race

Abstract Background Prostate cancer (PC) patients on androgen deprivation therapy (ADT) with diabetes mellitus (DM) are at increased risk of cardiovascular events (CVE) and all-cause mortality (ACM), with metformin use linked to lower ACM. Purpose To analyze the impact of low socioeconomic status (SES), low educational levels, and Non-Hispanic Black (NHB) race on the relationship between DM, and its treatments, and CVE, cardiovascular mortality (CVm), prostate cancer-specific mortality (PCsm), and ACM within 2 years of PC diagnosis in patients ± ADT. Methods We utilized SEER-Medicare (national database for individuals 65 or older covered under US federal health insurance program merged with multiple state cancer registries with ~50% US cancers covered) to study a cohort of PC patients diagnosed from 2009 to 2017, identifying PC cases with ICD-10 - C61 and DM via the Medicare chronic condition file. CVE included Afib, AMI, peripheral artery disease, ischemic stroke, and heart failure. Two patient cohorts were analyzed: those enrolled in Medicare Parts A and B with PC (cohort 1), and those exclusively on ADT (± diabetic medications) and enrolled in Medicare Part D (cohort 2). Outcomes were evaluated using Fine-Gray and Cox models, with further analysis by subgroups: NHB, SES, and education. Results We analyzed 74,052 PC patients, with 6,682 having comprehensive Part D data. Of these, 35% in cohort 1 and 16% in cohort 2 had DM, with median ages of 73 and 72, respectively. Diabetes was more prevalent among NHB men than Non-Hispanic White (NHW), 49% vs 33% in cohort 1 and 25% vs 15% in cohort 2. In cohort 1, 9% and 8.5% of overall and DM individuals were on ADT. Risk factor details are in Table 1, and CVE, CVm, PCsm, and ACM are included in Table 2, showing higher risks of various cardiovascular outcomes for DM patients, particularly for those with low-education levels. In cohort 1, we demonstrated a higher risk of all outcomes across all subgroups with DM (p<0.001). No significant interaction with race was present except in those with lower education levels, where NHW men with lower education showed an increased risk of CVE (sHR 1.15, 95%CI 1.10-1.21, P<0.001). In cohort 2, compared to metformin, the use of all other DM medications was associated with higher ACM. Additionally, those on other DM medications with lower education levels had higher CVE rates. Non-DM individuals with low SES had lower CVE rates, while NHB non-DM individuals had higher PCsm. Conclusion Our study highlights disparities in PC patients with DM in relation to cardiovascular and ACM, with NHB men and those with lower SES and educational status having worse outcomes. Metformin use in patients with low education levels was associated with reduced ACM and CVE risk, indicating its potential protective effect. These findings emphasize the need for further research on the disparities in PC and effects of diabetes medications across different subpopulations.

Prostate cancer biomarkers: from early diagnosis to precision treatment.

Prostate cancer (PCa) is the second most prevalent cancer in men. In 2020, approximately 1,414,259 new cases were reported that accounted for 3,75,324 deaths (Sung et al. in CA 71:209-249, 2021). PCa is often asymptomatic at early stages; hence, routine screening and monitoring based on reliable biomarkers is crucial for early detection and assessment of cancer progression. Early diagnosis of disease is key step in reducing PCa-induced mortality. Biomarkers such as PSA have played vital role in reducing recent PCa deaths. Recent research has identified many other biomarkers and also refined PSA-based tests for non-invasive diagnosis of PCa in patients. Despite progress in screening methods, an important issue that influences treatment is heterogeneity of the cancer in different individuals, necessitating personalized treatment. Currently, focus is to identify biomarkers that can accurately diagnose PCa at early stage, indicate the stage of the disease, metastatic nature and chances of survival based on individual patient profile (Fig.1). Fig.1 Graphical abstract.

Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3.

For patients with PI-RADS v2.1 ≥ 3, prostate biopsy is strongly recommended. Due to the unsatisfactory positive rate of biopsy, improvements in clinically significant prostate cancer (csPCa) risk assessments are required. To develop and validate machine learning (ML) models based on clinical and imaging parameters for csPCa detection in patients with PI-RADS v2.1 ≥ 3. Retrospective. One thousand eighty-three patients with PI-RADS v2.1 ≥ 3, randomly split into training (70%, N = 759) and validation (30%, N = 324) datasets, and 147 patients enrolled prospectively for testing. 3.0 T scanners/T2-weighted fast spin echo sequence and DWI with diffusion-weighted single-shot gradient echo planar imaging sequence. The factors evaluated for csPCa detection were age, prostate specific antigen, prostate volume, and the diameter and location of the index lesion, PI-RADSv2.1. Five ML models for csPCa detection were developed: logistic regression (LR), extreme gradient boosting, random forest (RF), decision tree, and support vector machines. The csPCa was defined as Gleason grade ≥2. Univariable and multivariable LR analyses to identify parameters associated with csPCa. Area under the receiver operating characteristic curve (AUC), Brier score, and DeLong test were used to assess and compare the csPCa diagnostic performance with the LR model. The significance level was defined as 0.05. The RF model exhibited the highest AUC (0.880-0.904) and lowest Brier score (0.125-0.133) among the ML models in the validation and testing cohorts, however, there was no difference when compared to the LR model (P = 0.453 and 0.548). The sensitivity and negative predictive values in the validation and testing cohorts were 93.8%-97.6% and 82.7%-95.1%, respectively, at a threshold of 0.450 (99% sensitivity of the RF model). The RF model might help for assessing the risk of csPCa and preventing overdiagnosis and unnecessary biopsy for men with PI-RADSv2.1 ≥ 3. 3 TECHNICAL EFFICACY: Stage 2.

First-in-human study of PSMA-targeting agent, [18F]AlF-P16-093: dosimetry and initial evaluation in prostate cancer patients.

This is a first-in-human study to evaluate the radiation dosimetry of a new prostate-specific membrane antigen (PSMA)-targeted radiopharmaceutical, [18F]AlF-P16-093, and also initial investigation of its ability to detect PSMA-positive tumors using PET scans in a cohort of prostate cancer (PCa) patients. The [18F]AlF-P16-093 was automatically synthesized with a GE TRACERlab. A total of 23 patients with histopathologically proven PCa were prospectively enrolled. Dosimetry and biodistribution study investigations were carried out on a subset of six (6) PCa patients, involving multiple time-point scanning. The mean absorbed doses were estimated with PMOD and OLINDA software. [18F]AlF-P16-093 was successfully synthesized, and radiochemical purity was > 95%, and average labeling yield was 36.5 ± 8.3% (decay correction, n = 12). The highest tracer uptake was observed in the kidneys, spleen, and liver, contributing to an effective dose of 16.8 ± 1.3 μSv/MBq, which was ~ 30% lower than that of [68Ga]Ga-P16-093. All subjects tolerated the PET examination well, and no reportable side-effects were observed. The PSMA-positive tumors displayed rapid uptake, and they were all detectable within 10 min, and no additional lesions were observed in the following multi-time points scanning. Each patient had at least one detectable tumor lesion, and a total of 356 tumor lesions were observed, including intraprostatic, lymph node metastases, bone metastases, and other soft tissue metastases. We report herein a streamlined method for high yield synthesis of [18F]AlF-P16-093. Preliminary study in PCa patients has demonstrated its safety and acceptable radiation dosimetry. The initial diagnostic study indicated that [18F]AlF-P16-093 PET/CT is efficacious and potentially useful for a widespread application in the diagnosis of PCa patients.

Role of preoperative magnetic resonance imaging on the surgical outcomes of radical prostatectomy: Does preoperative tumor recognition reduce the positive surgical margin in a specific location? Experience from a Thailand prostate cancer specialized center

ObjectiveMultiparametric magnetic resonance imaging (MRI) has become the standard of care for the diagnosis of prostate cancer patients. This study aimed to evaluate the influence of preoperative MRI on the positive surgical margin (PSM) rates. MethodsWe retrospectively reviewed 1070 prostate cancer patients treated with radical prostatectomy (RP) at Siriraj Hospital between January 2013 and September 2019. PSM rates were compared between those with and without preoperative MRI. PSM locations were analyzed. ResultsIn total, 322 (30.1%) patients underwent MRI before RP. PSM most frequently occurred at the apex (33.2%), followed by posterior (13.5%), bladder neck (12.7%), anterior (10.7%), posterolateral (9.9%), and lateral (2.3%) positions. In preoperative MRI, PSM was significantly lowered at the posterior surface (9.0% vs. 15.4%, p=0.01) and in the subgroup of urologists with less than 100 RP experiences (32% vs. 51%, odds ratio=0.51, p<0.05). Blood loss was also significantly decreased when a preoperative image was obtained (200 mL vs. 250 mL, p=0.02). Multivariate analysis revealed that only preoperative MRI status was associated with overall PSM and PSM at the prostatic apex. Neither the surgical approach, the neurovascular bundle sparing technique, nor the perioperative blood loss was associated with PSM. ConclusionMRI is associated with less overall PSM, PSM at apex, and blood loss during RP. Additionally, preoperative MRI has shown promise in lowering the PSM rate among urologists who are in the early stages of performing RP.

Prostate Imaging Reporting and Data System score (PI-RADS) and Glutathione S-transferase P1 methylation status (GST-P1) in the diagnosis of prostate cancer patients with borderline PSA values

Objectives. The objective of this study was to evaluate the potential use of Prostate Imaging – Reporting and Data System version 2 (PI-RADS) in combination with Glutathione S-transferase P1 (GST-P1) expression for an improved diagnosis of prostate cancer, in patients with inconclusive values of prostate-specific antigen (PSA). Materials and Methods. The study was conducted on 80 patients for whom PSA values were evaluated and were found to be inconclusive (4-10 ng/ml). These patients underwent imagistic evaluation (PI-RADS), followed by transurethral prostate biopsy, with the evaluation of GST-P1 expression and histopathological examination (for diagnosis confirmation). Results. By combining the results of PI-RADS and GST-P1 the capacity of the tests to correctly identify healthy subjects, with an area under curve of 0,832 (95% CI 0.732–0.907), with a sensitivity of 73,25% and a specificity of 77,78%. Conclusions. PI-RADS lesions and GST-P1 methylation testing when PSA levels are in a “grey zone”, provide a better specificity and sensitivity by comparison through single testing. Testing patients with inconclusive PSA levels allows for a more accurate diagnosis and less over-diagnosis by non-invasive procedures, such as repeated biopsies.

Implication of circulating microRNA-21 as a potential non-invasive diagnostic predictor of prostate cancer patients

BackgroundProstate cancer is a major cause of morbidity and mortality worldwide with an increasing incidence every year leading to enlarged socioeconomic burden and poor quality of life of patients. Current diagnostic approaches are non-specific and have inadequate clinical applicability due to reduced sensitivity and specificity. AimTo evaluate the significance of circulatory microRNA-21 as a non-invasive diagnostic tool for prostate cancer patients with high level of sensitivity and specificity irrespective of the patient's age. MethodsA total of 64 men, including 32 patients with prostate cancer and 32 healthy controls were enrolled in this study. Circulating microRNA was extracted from serum samples using miRNeasy Serum/Plasma Kit (Cat No. 217184, Qiagen). Circulating microRNA-21 was quantified using SYBR Green-based relative quantification assay. The age-wise (<50 years and > 50 years) correlation of microRNA-21 expression with serum Prostate-specific antigen (PSA) levels was performed to determine their possible association. ResultsCirculating microRNA-21 showed significantly upregulated expression in patients compared to control individuals with 71.05% sensitivity and 77.35% specificity (p < 0.0001). Age-wise analysis showed significantly increased expression levels of microRNA-21 in both the younger and older patients (for both p < 0.0001) compared to respective control individuals. The XY analysis showed positive correlation between microRNA-21 expression and PSA levels (r = 0.03012; p = 0.8992). The trend in values of microRNA-21 expression was corresponding to the serum PSA levels. ConclusionCirculating microRNA-21 levels with serum PSA can be used as a non-invasive tool for accurate diagnosis of prostate cancer patients to overcome the constraints of current approaches for timely management.

Construction of a Comprehensive Diagnostic Scoring Model for Prostate Cancer Based on a Novel Six-Gene Panel.

Accumulating evidence indicates that the N6-methyladenosine (m6A) modification plays a critical role in human cancers. Given the current understanding of m6A modification, this process is believed to be dynamically regulated by m6A regulators. Although the discovery of m6A regulators has greatly enhanced our understanding of the mechanism underlying m6A modification in cancers, the function and role of m6A in the context of prostate cancer (PCa) remain unclear. Here, we aimed to establish a comprehensive diagnostic scoring model that can act as a complement to prostate-specific antigen (PSA) screening. To achieve this, we first drew the landscape of m6A regulators and constructed a LASSO-Cox model using three risk genes (METTL14, HNRNP2AB1, and YTHDF2). Particularly, METTL14 expression was found to be significantly related to overall survival, tumor T stage, relapse rate, and tumor microenvironment of PCa patients, showing that it has important prognostic value. Furthermore, for the sake of improving the predictive ability, we presented a comprehensive diagnostic scoring model based on a novel 6-gene panel by combining with genes found in our previous study, and its application potential was further validated by the whole TCGA and ICGC cohorts. Our study provides additional clues and insights regarding the treatment and diagnosis of PCa patients.

Magnetic Resonance Imaging Image Feature Analysis Algorithm under Convolutional Neural Network in the Diagnosis and Risk Stratification of Prostate Cancer.

This work aimed to explore the accuracy of magnetic resonance imaging (MRI) images based on the convolutional neural network (CNN) algorithm in the diagnosis of prostate cancer patients and tumor risk grading. A total of 89 patients with prostate cancer and benign prostatic hyperplasia diagnosed by MRI examination and pathological examination in hospital were selected as the research objects in this study (they passed the exclusion criteria). The MRI images of these patients were collected in two groups and divided into two groups before and after treatment according to whether the CNN algorithm was used to process them. The number of diagnosed diseases and the number of cases of risk level inferred based on the tumor grading were compared to observe which group was closer to the diagnosis of pathological biopsy. Through comparative analysis, compared with the positive rate of pathological diagnosis (44%), the positive rate after the treatment of the CNN algorithm (42%) was more similar to that before the treatment (34%), and the comparison was statistically marked (P < 0.05). In terms of risk stratification, the grading results after treatment (37 cases) were closer to the results of pathological grading (39 cases) than those before treatment (30 cases), and the comparison was statistically obvious (P < 0.05). In addition, it was obvious that the MRT images would be clearer after treatment through the observation of the MRT images before and after treatment. In conclusion, MRI image segmentation algorithm based on CNN was more accurate in the diagnosis and risk stratification of prostate cancer than routine MRI. According to the evaluation of Dice similarity coefficient (DSC) and Hausdorff I distance (HD), the CNN segmentation method used in this study was more perfect than other segmentation methods.

The Role of C-Reactive Protein in Kidney, Bladder, and Prostate Cancers.

C-Reactive Protein (CRP) is associated with diverse outcomes in patients with, or suspected to have, genitourinary malignancies. CRP levels have been shown to be associated with the probability of a prostate cancer diagnosis in patients with elevated PSA, the probability of biochemical recurrence following definitive treatment for localized prostate cancer, and decreased overall survival for patients with advanced disease. In patients with bladder and kidney cancers, CRP levels have been associated with disease progression, stage, and cancer-specific survival. Despite the abundance of correlative studies, the relationship between CRP levels and genitourinary cancer pathogenesis is not clearly understood. Here, we review the evidence for CRP as a biomarker in genitourinary (GU) cancers, with specific focus on potential clinical applications.

Significance of the prostate central gland and total gland volume ratio in the diagnosis of prostate cancer patients in the prostate specific antigen grey zone

ObjectiveTo explore the significance of the prostate central gland to total gland volume ratio (PVc/PV) in the diagnosis of prostate cancer (PCa) in patients with prostate specific antigen (PSA) levels in the grey zone (4–10 ng/ml).MethodsThis retrospective study enrolled patients that had undergone prostate biopsy. The volume of the prostate and the central prostate gland were measured. The differences in PSA, the ratio of free to total PSA (f/tPSA), PSA density (PSAD) and PVc/PV between the PCa and non-PCa groups were compared. Receiver operating characteristic curve analysis for PCa and clinically significant PCa (csPCa) diagnosis were calculated according to PSA (reference), f/tPSA, PSAD and PVc/PV.ResultsThis study enrolled 136 patients. There was no significant difference in PSA and f/tPSA between the PCa and non-PCa groups, while there were significant differences in PSAD and PVc/PV. The area under the curve values of PVc/PV for PCa or csPCa diagnosis were 0.876 and 0.933, respectively; and for PSAD, they were 0.705 and 0.790, respectively. These were significantly different compared with the PSA curve, whereas f/tPSA showed no significant difference from the PSA curve.ConclusionPVc/PV could be a predictor of PCa when PSA is between 4–10 ng/ml.

Preparation of Targeted Nano-Microbubble Contrast Agent and Its Application in the Diagnosis of Prostate Cancer

The objective of this study was to explore the application value of microbubble contrast materials in the diagnosis of prostate cancer. Firstly, ordinary nano-microbubbles and biotinylated nano-microbubbles were prepared by rotary evaporation method and mechanical vibration method. Then, the biotinylated anti-six-transmembrane prostate epithelial antigen-1 (STQWK-1) antibody was connected with the previously prepared nano-microbubbles with the help of biotin-avidin method, so as to generate a nano-microbubble contrast agent targeting prostate PC3 cells. While the contrast agent was characterized based on the immunofluorescence method, a microscope was applied to observe the in vitro targeting performance of targeted nano-microbubbles on PC3 cells. A prostate PC3 cell nude mouse transplanted tumor model was established, so that the contrast-enhanced ultrasound (CEUS) effect of different contrast agents on transplanted tumor was compared, which were applied in CEUS examination of prostate cancer patients. The results showed that the targeted nano-microbubbles could display circular green fluorescence under the microscope, and the blank nano-microbubbles had no display under the microscope. Both ultrasonic microbubbles were circular and evenly distributed. The in vitro targeting experiments indicated that targeted nano-bubbles could accumulate on the surface of prostate cancer PC3 cells, and tumor transplantation model proved that the targeted contrast agent carrying STQWK-1 antibody had a strong development and enhancement effect. In the diagnosis of prostate cancer patients, the sensitivity (83.3% vs. 52%), specificity (66.7% vs. 36.3%), accuracy (75% vs. 47.2%), and other indicators of the diagnosis of targeted nano-bubbles prepared showed marked advantages compared with routine trans-rectal US (TRUS) diagnosis. The contrast agent prepared in this study could be specifically targeted to prostate PC3 cells in vitro, which had the effect of development and enhancement and had a good diagnostic performance in the diagnosis of prostate cancer.

Prostate-specific antigen density during dutasteride treatment for 1year predicts the presence of prostate cancer in benign prostatic hyperplasia after the first negative biopsy (PREDICT study).

To prospectively evaluate the detection rate of prostate cancer, and to identify the risk factors of prostate cancer detection after a 1-year administration of dutasteride and first negative prostate biopsy. Patients with benign prostatic hyperplasia who presented high prostate-specific antigen levels after the first negative prostate biopsy were administered 0.5mg dutasteride daily for 1year. They underwent a repeat prostate biopsy after 1year. The primary end-point was the detection rate of prostate cancer. The secondary end-point was the ability of prostate-specific antigen kinetics to predict prostate cancer detection. Prostate-specific antigen was measured before the initial prostate biopsy and at 6, 9 and 12months after starting dutasteride. Patients were classified into a prostate cancer and a non-prostate cancer group. Prostate cancer was detected in 15 of 149 participants (10.1%). The total prostate-specific antigen change between the prostate cancer and non-prostate cancer group at 1year was significantly different (P=0.002). Although prostate-specific antigen levels at baseline did not significantly differ between study groups (P=0.102), prostate-specific antigen levels at 6, 9 and 12months were significantly different (P=0.002, P=0.001 and P<0.001, respectively). The mean reduction rate of prostate-specific antigen density between the prostate cancer and non-prostate cancer group at 1year was significantly different (-4.25±76.5% vs -38.0±28.7%, P=0.001). Using a multivariate analysis, a >10% increase of prostate-specific antigen density at 1year post-dutasteride treatment was the only predictive risk factor for prostate cancer after the first negative prostate biopsy (odds ratio 11.238, 95% confidence interval 3.112-40.577, P<0.001). In the present study cohort, >10% increase in prostate-specific antigen density represented the only significant predictive risk factor for prostate cancer diagnosis in patients with elevated prostate-specific antigen after the first negative prostate biopsy.

A preliminary study of micro-RNAs as minimally invasive biomarkers for the diagnosis of prostate cancer patients

BackgroundA prostate cancer diagnosis is based on biopsy sampling that is an invasive, expensive procedure, and doesn’t accurately represent multifocal disease.MethodsTo establish a model using plasma miRs to distinguish Prostate cancer patients from non-cancer controls, we enrolled 600 patients histologically diagnosed as having or not prostate cancer at biopsy. Two hundred ninety patients were eligible for the analysis. Samples were randomly divided into discovery and validation cohorts.ResultsNGS-miR-expression profiling revealed a miRs signature able to distinguish prostate cancer from non-cancer plasma samples. Of 51 miRs selected in the discovery cohort, we successfully validated 5 miRs (4732-3p, 98-5p, let-7a-5p, 26b-5p, and 21-5p) deregulated in prostate cancer samples compared to controls (p ≤ 0.05). Multivariate and ROC analyses show miR-26b-5p as a strong predictor of PCa, with an AUC of 0.89 (CI = 0.83–0.95;p < 0.001). Combining miRs 26b-5p and 98-5p, we developed a model that has the best predictive power in discriminating prostate cancer from non-cancer (AUC = 0.94; CI: 0,835-0,954).To distinguish between low and high-grade prostate cancer, we found that miR-4732-3p levels were significantly higher; instead, miR-26b-5p and miR-98-5p levels were lower in low-grade compared to the high-grade group (p ≤ 0.05).Combining miR-26b-5p and miR-4732-3p we have the highest diagnostic accuracy for high-grade prostate cancer patients, (AUC = 0.80; CI 0,69-0,873).ConclusionsNoninvasive diagnostic tests may reduce the number of unnecessary prostate biopsies.The 2-miRs-diagnostic model (miR-26b-5p and miR-98-5p) and the 2-miRs-grade model (miR-26b-5p and miR-4732-3p) are promising minimally invasive tools in prostate cancer clinical management.

Diagnostic Accuracy of 68Ga-PSMA PET/CT for Initial Detection in Patients With Suspected Prostate Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND. Early diagnosis is important in the overall management of prostate cancer (PCa). Gallium-68-labeled prostate-specific membrane antigen (PSMA) PET/CT has an established role in the detection of recurrent disease and staging of patients with intermediate- to high-risk PCa. However, only a small number of studies have evaluated its role in the initial diagnosis of PCa. OBJECTIVE. This systematic review was conducted to evaluate the diagnostic performance of 68Ga-PSMA PET/CT in the initial detection of PCa in patients with clinical or biochemical findings suspicious for PCa. EVIDENCE ACQUISITION. This systematic review followed PRISMA guidelines. Searches in PubMed, Scopus, and Embase were conducted using relevant keywords, and articles published through April 30, 2020, were included. Using histopathology results as the reference standard, the numbers of true- and false-positives and true- and false-negatives were extracted. Pooled estimates of diagnostic test accuracy-including sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and summary ROC (SROC) curve-were generated using bivariate random-effects meta-analysis. EVIDENCE SYNTHESIS. Seven studies comprising 389 patients were included in the systematic review and meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio for the initial diagnosis of PCa using 68Ga-PSMA PET/CT were 0.97 (95% CI, 0.90-0.99), 0.66 (95% CI, 0.52-0.78), 2.86 (95% CI, 1.95-4.20), and 0.05 (95% CI, 0.01-0.15), respectively. The test had high accuracy; the area under the SROC curve was 0.91 (95% CI, 0.88-0.93). CONCLUSION. Gallium-68-labeled PSMA PET/CT had excellent sensitivity and negative likelihood ratio in the initial diagnosis of PCa in patients with clinical or biochemical findings suspicious for PCa. CLINICAL IMPACT. Gallium-68-labeled PSMA PET/CT had high diagnostic accuracy for the initial detection of PCa in patients with clinical or biochemical findings suspicious for PCa and has potential utility as a rule-out test for these patients.

Construction of a Comprehensive Diagnostic Scoring Model for Prostate Cancer Based on Six Gene-Panel

Accumulating evidence indicates that the N6-methyladenosine (m6A) modification plays a critical role in human cancers.Given the current understanding of m6A modification, this process is believed to be dynamically regulated by m6A regulators. Although the discovery of m6A regulators has greatly enhanced our understanding of the mechanism underlying m6A modification in cancers, the function and role of m6A in the context of prostate cancer (PCa) remains unclear.Here, we aimed to establish a comprehensive diagnostic scoring model that can be used to prostate-specific antigen (PSA) screening.To achieve this, we first drew the landscape of m6A regulators and constructed a LASSO-Cox model using 3 risk genes (METTL14, HNRNP2AB1 and YTHDF2). Particularly,METTL14 expression was found to be significantly related to overall survival, tumor T stage and relapse rate, showing that METTL14 has important prognostic value. Furthermore, for the sake of improving the predictive ability, we presented a comprehensive diagnostic scoring model based on 6 gene-panel by combining with genes found in our previous study.In conclusion, our study provides additional clues and insights regarding the treatment and diagnosis of PCa patients. Funding Statement: This work was supported by grants from the National Natural Science Foundation of China (31870928, Project-recepient: Q.L; 81770494, Project-recepient: Q. X.). Declaration of Interests: The authors declare that they have no conflicts of interest.

Impact on quality of life 3\u2009years after diagnosis of prostate cancer patients below 75 at diagnosis: an observational case-control study

BackgroundProstate cancer patients are known to suffer from poor sexual and urinary long-term side-effects following treatment, potentially impacting quality of life. The purpose of our study was to compare health-related quality of life at 3 years between prostate cancer patients and healthy controls according to key life-style characteristics. Secondary objectives were to compare urological dysfunction, sexual function, anxiety and depression.MethodsMulticentric, case-control, observational prospective, open, follow-up study including 819 prostate cancer patients < 75 years old from the EPICAP cohort, newly diagnosed from 1 December 2011 to 31 March 2014 and 879 healthy controls. Participants were excluded if they experienced a relapse. Controls from the same geographical region were age-matched and were excluded if they were diagnosed with prostate cancer. Patients received one of the following treatments: active surveillance (AS), radical prostatectomy (RP), external beam radiotherapy (EBRT), High-intensity Focused Ultrasound (HIFU), chemotherapy (CT), or androgen deprivation therapy (ADT) as appropriate. The primary outcome was the quality of life as evaluated by the QLQ-C30 questionnaire. Scores were analyzed by multivariate analysis to adjust for predefined socio-demographic confounding effects.ResultsIn total, 564 participants were included (mean age 67.9 years): 376 patients and 188 controls. Treatment breakdown was: 258 underwent RP, 90 received EBRT, 52 brachytherapy or HIFU, 15 CT, 26 ADT and 61 AS. There was no difference in median global quality of life between patients and controls (94.87 vs 94.15, p = 0.71). Multivariate analysis showed poorer social functioning in patients (24.3% vs. 16.3%, p = 0.0209), more dyspnea (22% vs. 12.4%, p = 0.0078), and yet less current pain (23% vs 33%, p = 0.0151).ConclusionsGlobal health status score at 3 years after diagnosis was similar between patients and controls, though patients showed a significantly worse social functioning. Prostate cancer diagnosis per se does not seem to impact the quality of life of patients < 75 years at diagnosis. However, the therapeutic option that will be chosen following diagnosis should be carefully discussed with the medical staff in terms of benefit-risk ratios as it could have a long-term impact on urinary or erectile dysfunction.Trial registrationclinicaltrials.gov, NCT02854982. Registered 4 August 2016, retrospectively registered.

The study of multiple diagnosis models of human prostate cancer based on Taylor database by artificial neural networks.

Prostate cancer (PCa) is the most common malignancy seen in men and the second leading cause of cancer-related death in males. The incidence and mortality associated with PCa has been rapidly increasing in China recently. Multiple diagnostic models of human PCa were developed based on Taylor database by combining the artificial neural networks (ANNs) to enhance the ability of PCa diagnosis. Genetic algorithm (GA) is used to select feature genes as numerical encoded parameters that reflect cancer, metastatic, or normal samples. Back propagation (BP) neural network and learning vector quantization (LVQ) neural network were used to build different Cancer/Normal, Primary/Metastatic, and Gleason Grade diagnostic models. The performance of these modeling approaches was evaluated by predictive accuracy (ACC) and area under the receiver operating characteristic curve (AUC). By observing the statistically significant parameters of the three training sets, our Cancer/Normal, Primary/Metastatic, and Gleason Grade models' with ACC and AUC can be drawn (97.33%, 0.9832), (99.17%, 0.9952), and (90.48%, 0.8742), respectively. These results indicated that our diagnostic models of human PCa based on Taylor database combining the feature gene expression profiling data and artificial intelligence algorithms might act as a powerful tool for diagnosing PCa. Gleason Grade diagnostic models were used as novel prognostic diagnosis models for biochemical recurrence-free survival and overall survival, which might be helpful in the prognostic diagnosis of PCa in patients.

Significance of prostate central gland/total gland volume ratio combined with PSA in the diagnosis of prostate cancer patients

Objective: To explore the significance of prostate central gland/total gland volume (PVc/PV) ratio combined with PSA in the diagnosis of PSA 4-20 ng/ml prostate cancer patients. Methods: Data of patients undergoing prostate puncture in Minghang Branch, Zhongshan Hospital from July 2015 to December 2018 were retrospectively analyzed. The anteroposterior, transverse and axial diameters of the prostate and the central prostate gland were measured by magnetic resonance imaging (MRI). The differences of tPSA, f/tPSA, PSAD and PVc/PV between the prostate cancer group and non-prostate cancer group were compared. Receiver operating characteristic (ROC) curves of prostate cancer diagnosis were plotted according to tPSA, f/tPSA, PSAD, PVc/PV alone and PVc/PV combined with tPSA, respectively, and the area under the curve (AUC) was calculated and compared using tPSA as the reference. Results: There was no significant difference in tPSA between the two groups (P>0.05). However, significant differences were observed in f/tPSA, PSAD and PVc/PV between the two groups (P<0.05). The AUC value of PVc/PV combined with tPSA, PVc/PV and PSAD was 0.901 2,0.866 7 and 0.848 1,respectively, which were statistically different from that of tPSA (P<0.05). The AUC value of f/tPSA was 0.716, which was not statistically different from that of tPSA (P>0.05). Conclusion: The PVc/PV ratio combined with tPSA can be used as an important reference index for the diagnosis of prostate cancer in PSA 4-20 ng/ml patients.