scholarly journals Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis

2022 ◽  
Vol 11 ◽  
Author(s):  
Yu Fan ◽  
Yelin Mulati ◽  
Lingyun Zhai ◽  
Yuke Chen ◽  
Yu Wang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Bayesian Network ◽  
Publication Bias ◽  
Active Surveillance ◽  
Meta Analysis ◽  
Cancer Center ◽  
Low Grade ◽  
Significant Heterogeneity ◽  
The Absolute

BackgroundSeveral active surveillance (AS) criteria have been established to screen insignificant prostate cancer (insigPCa, defined as organ confined, low grade and small volume tumors confirmed by postoperative pathology). However, their comparative diagnostic performance varies. The aim of this study was to compare the diagnostic accuracy of contemporary AS criteria and validate the absolute diagnostic odds ratio (DOR) of optimal AS criteria.MethodsFirst, we searched Pubmed and performed a Bayesian network meta-analysis (NMA) to compare the diagnostic accuracy of contemporary AS criteria and obtained a relative ranking. Then, we searched Pubmed again to perform another meta-analysis to validate the absolute DOR of the top-ranked AS criteria derived from the NMA with two endpoints: insigPCa and favorable disease (defined as organ confined, low grade tumors). Subgroup and meta-regression analyses were conducted to identify any potential heterogeneity in the results. Publication bias was evaluated.ResultsSeven eligible retrospective studies with 3,336 participants were identified for the NMA. The diagnostic accuracy of AS criteria ranked from best to worst, was as follows: Epstein Criteria (EC), Yonsei criteria, Prostate Cancer Research International: Active Surveillance (PRIAS), University of Miami (UM), University of California-San Francisco (UCSF), Memorial Sloan-Kettering Cancer Center (MSKCC), and University of Toronto (UT). I2 = 50.5%, and sensitivity analysis with different insigPCa definitions supported the robustness of the results. In the subsequent meta-analysis of DOR of EC, insigPCa and favorable disease were identified as endpoints in ten and twenty-two studies, respectively. The pooled DOR for insigPCa and favorable disease were 0.44 (95%CI, 0.31–0.58) and 0.66 (95%CI, 0.61–0.71), respectively. According to a subgroup analysis, the DOR for favorable disease was significantly higher in US institutions than that in other regions. No significant heterogeneity or evidence of publication bias was identified.ConclusionsAmong the seven AS criteria evaluated in this study, EC was optimal for positively identifying insigPCa patients. The pooled diagnostic accuracy of EC was 0.44 for insigPCa and 0.66 when a more liberal endpoint, favorable disease, was used.Systematic Review Registration[https://www.crd.york.ac.uk/prospero/], PROSPERO [CRD42020157048].

Effect of Statins on the Risk of Different Stages of Prostate Cancer: A Meta-Analysis

2021 ◽  
pp. 1-9
Author(s):  
Yun Li ◽  
Xuan Cheng ◽  
Jia-lian Zhu ◽  
Wen-wen Luo ◽  
Huai-rong Xiang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Lower Risk ◽  
Advanced Prostate Cancer ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Low Grade ◽  
High Grade ◽  
The Cochrane Library ◽  
The Relationship ◽  
Comprehensive Literature Search

<b><i>Introduction:</i></b> The aim of this article was to investigate the relationship between statins and the risk of different stages or grades of prostate cancer. <b><i>Methods:</i></b> A comprehensive literature search was performed for articles published until December 18, 2020, on the PubMed, Embase, and the Cochrane Library databases. The pooled relative risk (RR) and 95% confidence interval (CI) were then analyzed using the STATA.16.0 software. <b><i>Results:</i></b> A total of 588,055 patients from 14 studies were included in the analysis. We found that the use of statins expressed a significant correlation with a lower risk of advanced prostate cancer (RR = 0.81, 95% CI: 0.73–0.91; RR = 0.86, 95% CI: 0.75–0.99, respectively). However, no evidence suggested that the use of statins was beneficial for the prevention of localized prostate cancer incidence. Similarly, the pooled results also revealed no association between the use of statins and the risk of high-grade and low-grade prostate cancer. <b><i>Conclusion:</i></b> It has been found that the use of statins is associated with a lower risk of advanced prostate cancer but was not related to the risk of localized, low-grade, or high-grade prostate cancer.

A longitudinal study of patients undergoing active surveillance for low grade prostate cancer diagnosed at Transperineal Template Prostate Mapping

2019 ◽  
Vol 18 (1) ◽  
pp. e615
Author(s):  
M. Kailavasan ◽  
T.J. Walton ◽  
P. Ravindra ◽  
S. Trecarten ◽  
J. Voss ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Longitudinal Study ◽  
Active Surveillance ◽  
Low Grade

scholarly journals Performance of 18F-DCFPyL PET/CT Imaging in Early Detection of Biochemically Recurrent Prostate Cancer: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiale Sun ◽  
Yuxin Lin ◽  
Xuedong Wei ◽  
Jun Ouyang ◽  
Yuhua Huang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Early Detection ◽  
Publication Bias ◽  
Detection Rate ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Recurrent Prostate Cancer ◽  
Pet Ct ◽  
Statistical Heterogeneity

Background: Prostate-specific membrane antigen (PSMA)-targeted 2-(3-{1-carboxy-5-[(6-[18F] fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid (18F-DCFPyL) positron emission tomography/computed tomography (PET/CT) has shown advantages in primary staging, restaging, and metastasis detection of prostate cancer (PCa). However, little is known about the role of 18F-DCFPyL PET/CT in biochemically recurrent prostate cancer (BRPCa). Hence, we performed a systematic review and meta-analysis to evaluate 18F-DCFPyL PET/CT as first-line imaging modality in early detection of BRPCa.Methods: A comprehensive literature search of PubMed, Web of Science, Embase, and Cochrane Library was conducted until December 2020. The pooled detection rate on a per-person basis and together with 95% confidence interval (CI) was calculated. Furthermore, a prostate-specific antigen (PSA)-stratified performance of detection positivity was obtained to assess the sensitivity of 18F-DCFPyL PET/CT in BRPCa with different PSA levels.Results: A total of nine eligible studies (844 patients) were included in this meta-analysis. The pooled detection rate (DR) of 18F-DCFPyL PET/CT in BRPCa was 81% (95% CI: 76.9–85.1%). The pooled DR was 88.8% for PSA ≥ 0.5 ng/ml (95% CI: 86.2–91.3%) and 47.2% for PSA &lt; 0.5 ng/ml (95% CI: 32.6–61.8%). We also noticed that the regional lymph node was the most common site with local recurrence compared with other sites (45.8%, 95% CI: 42.1–49.6%). Statistical heterogeneity and publication bias were found.Conclusion: The results suggest that 18F-DCFPyL PET/CT has a relatively high detection rate in BRPCa. The results also indicate that imaging with 18F-DCFPyL may exhibit improved sensitivity in BRPCa with increased PSA levels. Considering the publication bias, further large-scale multicenter studies are warranted for validation.

scholarly journals Active Surveillance Strategies for Low-Grade Prostate Cancer: Comparative Benefits and Cost-effectiveness

Radiology ◽  
2021 ◽  
pp. 204321
Author(s):  
Stella K. Kang ◽  
Rahul D. Mali ◽  
Vinay Prabhu ◽  
Bart S. Ferket ◽  
Stacy Loeb
Keyword(s):  
Prostate Cancer ◽  
Cost Effectiveness ◽  
Active Surveillance ◽  
Low Grade

Abstract 14339: Nonalcoholic Fatty Liver Disease and the Risk of Clinical Cardiovascular Events: A Meta-Analysis

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Toufik Mahfood Haddad ◽  
Shadi Hamdeh ◽  
Mahesh Anantha Narayanan ◽  
Arun Kanmanthareddy ◽  
Venkata M Alla
Keyword(s):  
Liver Disease ◽  
Fatty Liver ◽  
Nonalcoholic Fatty Liver Disease ◽  
Publication Bias ◽  
Fatty Liver Disease ◽  
Cardiovascular Events ◽  
Meta Analysis ◽  
Significant Heterogeneity ◽  
Cross Sectional ◽  
Nonalcoholic Fatty Liver

Background: Numerous studies have assessed the association of Nonalcoholic fatty liver disease (NAFLD) withcardiovascular disease (CVD). However, results have been conflicting due to variability in definitionsof NAFLD and ascertainment of CVD, often combining clinical and surrogate endpoints. We therefore systematically reviewed published literature to assess the association between NAFLD and clinical cardiovascular events. Methods: We searched Medline, Cochrane, google scholar, CINAHL, and Web of Sciencedatabasesusing terms “nonalcoholic fatty liver disease”, “cardiovascular disease”, and their combinations to identify studies published through March 2015. Data from selected studies was extracted and meta-analysis was then performed using Random effects model following the PRISMA guidelines. Publication bias and heterogeneity wereassessed. The main outcome measure was Odds ratio (OR) with 95% CI. Clinical CVD was defined as symptomatic coronary artery disease, myocardial infarction, coronary or peripheral intervention, ischemic stroke, and symptomatic peripheral vascular disease. Results: A total of 7 studies with 14634 patients (NAFLD: 4204; controls: 10430) were included in the final analysis. 3 studies were cross- sectional reporting prevalence, while 4 studies were prospective cohort studies reporting incidence. Patients with NAFLD had a significantly higher risk of clinical CVD compared to controls [OR: 3.17; 95% CI: 1.89-5.30, P<0.01) (figure 1A). There was significant heterogeneity (I2=93%). Funnel plot and Begg’s test did not reveal significant publication bias. Separate analyses of the cohort and cross sectional studies and exclusion sensitivity analysis did not alter the findings (figure 1B). Conclusion: NAFLD is associated with a three fold increase in the risk of clinical CVD compared to controls without NAFLD. These results need to be conformed in large prospective studies.

scholarly journals Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Curtis K. Sohn ◽  
Sotirios Bisdas
Keyword(s):  
Machine Learning ◽  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Total Sample ◽  
Low Grade ◽  
Sample Sizes ◽  
Summary Receiver Operating Characteristic ◽  
Pubmed Database ◽  
Sensitivity Specificity

Purpose. This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas. Method. A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained. Result. The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes ( p = 0.05 ), imaging sequence types ( p = 0.02 ), and data sources ( p = 0.01 ), but not for the inclusion of the testing set ( p = 0.19 ), feature extraction number ( p = 0.36 ), and selection of feature number ( p = 0.18 ). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG. Conclusion. This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

18F-NaF-PET/CT for the detection of bone metastasis in prostate cancer: a meta-analysis of diagnostic accuracy studies

2019 ◽  
Vol 33 (5) ◽  
pp. 351-361 ◽  
Author(s):  
Sara Sheikhbahaei ◽  
Krystyna M. Jones ◽  
Rudolf A. Werner ◽  
Roberto A. Salas-Fragomeni ◽  
Charles V. Marcus ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Pet Ct

Overdiagnosis and Overtreatment of Prostate Cancer

2012 ◽  
pp. e35-e39 ◽  
Author(s):  
Ian M. Thompson
Keyword(s):  
Prostate Cancer ◽  
Active Surveillance ◽  
Specific Antigen ◽  
The United States ◽  
Assessment Tools ◽  
Low Grade ◽  
High Grade ◽  
Surveillance Strategy ◽  
Psa Testing ◽  
Prostate Cancer Prevention

Overview: Prostate cancer is a ubiquitous disease, affecting as many as two-thirds of men in their 60s. Through widespread prostate-specific antigen (PSA) testing, increasing rates of prostate biopsy, and increased sampling of the prostate, a larger fraction of low-grade, low-volume tumors have been detected, consistent with tumors often found at autopsy. These tumors have historically been treated in a manner similar to that used for higher-grade tumors but, more recently, it has become evident that with a plan of active surveillance that reserves treatment for only those patients whose tumors show evidence of progression, very high disease-specific survival can be achieved. Unfortunately, the frequency of recommendation of an active surveillance strategy in the United States is low. An alternative strategy to improve prostate cancer detection is through selected biopsy of those men who are at greater risk of harboring high-grade, potentially lethal cancer. This strategy is currently possible through the use of risk assessment tools such as the Prostate Cancer Prevention Trial Risk Calculator ( www.prostate.cancer.risk.calculator.com ) as well as others. These tools can predict with considerable accuracy a man's risk of low-grade and high-grade cancer, allowing informed decision making for the patient with a goal of detection of high-risk disease. Ultimately, other biomarkers including PCA3, TMPRSS2:ERG, and [-2]proPSA will likely aid in discriminating these two types of cancer before biopsy.

scholarly journals Diagnostic accuracy of prostate cancer antigen 3 (PCA3) prior to first prostate biopsy: A systematic review and meta-analysis

2019 ◽  
Vol 14 (5) ◽  
Author(s):  
Sandra Viviana Muñoz Rodríguez ◽  
Herney Andrés García-Perdomo
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Prostate Biopsy ◽  
Reference Lists ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Diagnostic Odds Ratio ◽  
Cancer Antigen ◽  
Prostate Cancer Antigen

Introduction: We aimed to determine the diagnostic accuracy of the prostate cancer antigen 3 (PCA3) test before performing the first biopsy compared with prostate biopsy for the diagnosis of prostate cancer. Methods: A systematic search was performed in MEDLINE, EMBASE, CENTRAL, LILACS, reference lists, specialized journals in urology and cancer, and unpublished literature. The population was adults with suspected prostate cancer, and the intervention was the measurement of PCA3 in urine samples for the diagnosis of prostate cancer. The quality of studies was evaluated with the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. The operative characteristics were determined, and a meta-analysis was performed. Results: Nine studies of diagnostic tests were included based on a cutoff value of 35. The following overall values were obtained: the sensitivity was 0.69 (95% confidence interval [CI] 0.61–0.75); specificity was 0.65 (95% CI 0.553–0.733); the diagnostic odds ratio (DOR) was 4.244 (95% CI 3.487–5.166); and the area under the curve was 0.734 (95% CI 0.674–0.805) with a heterogeneity of 0%. Conclusions: Urinary PCA3 has an acceptable diagnostic accuracy, aids in the study of patients with suspected prostate cancer, and can be used as a guide for directing the performance of the first prostate biopsy and decreasing unnecessary biopsies.

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