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European Radiology Experimental Jun 2022In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced... (Review)
Review
In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients' risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these "big data" in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer.
Topics: Artificial Intelligence; Humans; Image Processing, Computer-Assisted; Male; Multimodal Imaging; Prostatic Neoplasms; Quality of Life
PubMed: 35701671
DOI: 10.1186/s41747-022-00282-0 -
Journal of Medical Internet Research Apr 2021Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance.
OBJECTIVE
This study assesses the source of heterogeneity and the performance of machine learning applied to radiomic, genomic, and clinical biomarkers for the diagnosis of prostate cancer. One research focus of this study was on clearly identifying problems and issues related to the implementation of machine learning in clinical studies.
METHODS
Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, 816 titles were identified from the PubMed, Scopus, and OvidSP databases. Studies that used machine learning to detect prostate cancer and provided performance measures were included in our analysis. The quality of the eligible studies was assessed using the QUADAS-2 (quality assessment of diagnostic accuracy studies-version 2) tool. The hierarchical multivariate model was applied to the pooled data in a meta-analysis. To investigate the heterogeneity among studies, I statistics were performed along with visual evaluation of coupled forest plots. Due to the internal heterogeneity among machine learning algorithms, subgroup analysis was carried out to investigate the diagnostic capability of machine learning systems in clinical practice.
RESULTS
In the final analysis, 37 studies were included, of which 29 entered the meta-analysis pooling. The analysis of machine learning methods to detect prostate cancer reveals the limited usage of the methods and the lack of standards that hinder the implementation of machine learning in clinical applications.
CONCLUSIONS
The performance of machine learning for diagnosis of prostate cancer was considered satisfactory for several studies investigating the multiparametric magnetic resonance imaging and urine biomarkers; however, given the limitations indicated in our study, further studies are warranted to extend the potential use of machine learning to clinical settings. Recommendations on the use of machine learning techniques were also provided to help researchers to design robust studies to facilitate evidence generation from the use of radiomic and genomic biomarkers.
Topics: Algorithms; Genomics; Humans; Machine Learning; Male; Prostatic Neoplasms
PubMed: 33792552
DOI: 10.2196/22394 -
Pharmacological Research Mar 2022Antidiabetic medications (ADMs) may modify prostate cancer (PCa) risk in patients with diabetes mellitus (DM). Accordingly, the current study assessed the possible... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Antidiabetic medications (ADMs) may modify prostate cancer (PCa) risk in patients with diabetes mellitus (DM). Accordingly, the current study assessed the possible associations between ADMs and the risk of PCa in diabetics.
METHODS
A systematic literature search (PubMed, Embase and Cochrane Library) identified studies evaluating the associations between ADMs and incidence of PCa. A meta-analysis followed PRISMA was performed using odds ratio (OR) with 95% confidence interval (CI) as effect measures.
RESULTS
In total of 47 studies involving 3094,152 patients with diabetes were included. Results of meta-analysis of the observational studies suggested no significant association between metformin, thiazolidinediones, sulfonylureas, insulin or dipeptidyl peptidase-4 inhibitors administration and the risk of PCa (All p-values > 0.05). Separate analysis of randomized controlled trials (RCTs) revealed a significant reduction in PCa risk with thiazolidinediones (OR = 0.55, p = 0.04) or glucagon-like peptide-1 receptor agonists (GLP-1RA) administration (OR = 0.53, p = 0.006), whereas no significant association was found in SGLT2 inhibitors (p = 0.3).
CONCLUSION
Thiazolidinediones or GLP-1RA administration may have benefits in PCa based on RCTs, however, further research is needed to confirm these findings.
Topics: Diabetes Mellitus, Type 2; Dipeptidyl-Peptidase IV Inhibitors; Humans; Hypoglycemic Agents; Male; Prostatic Neoplasms; Thiazolidinediones
PubMed: 35074527
DOI: 10.1016/j.phrs.2022.106094 -
Andrologia Nov 2020Irreversible electroporation is a treatment option used for focal therapy. In this systematic review, we summarise data on irreversible electroporation outcomes in... (Review)
Review
Irreversible electroporation is a treatment option used for focal therapy. In this systematic review, we summarise data on irreversible electroporation outcomes in patients with localised prostate cancer. We performed a literature search in 3 databases and included articles with own data on irreversible electroporation results in patients with localised prostate cancer. Primary outcome was procedure efficacy measured as the absence of cancer in the treatment area on the follow-up biopsy. Secondary outcomes were the absence of prostate cancer recurrence in the treatment area on MRI, out-of-field recurrence, complications and functional outcomes (erectile function and micturition). In-field recurrence rate was 0%-39% and out-field 6.4%-24%. In all studies, PSA level decreased: twice lower than baseline after 4 weeks and by 76% after 2 years. Most of the authors noted sexual and urinary toxicity during the first half year after surgery. However, functional outcomes recovered to baseline after 6 months with mild decrease in sexual function. Complication rates after irreversible electroporation were 0%-1% of Clavien-Dindo III and 5%-20% of Clavien-Dindo I-II. Irreversible electroporation has promise oncological outcomes, rate of post-operative complications and minimal-to-no effects on erectile and urinary function. However, medium and long-term data on cancer-specific and recurrence-free survival are still lacking.
Topics: Ablation Techniques; Electroporation; Humans; Male; Neoplasm Recurrence, Local; Prostatic Neoplasms; Treatment Outcome
PubMed: 32786087
DOI: 10.1111/and.13789 -
Medicine Apr 2020The Prostate Cancer Prevention Trial has shown a protective effect of finasteride on prostate cancer, but it also showed that finasteride can increase the risk of... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The Prostate Cancer Prevention Trial has shown a protective effect of finasteride on prostate cancer, but it also showed that finasteride can increase the risk of high-grade prostate cancer. Several studies have investigated the relationship between finasteride and prostate cancer, but these studies have shown inconsistent results.
ETHICS
The protocol was approved by the institutional review board of each study center. Written informed consent will be obtained from all patients before registration, in accordance with the Declaration of Helsinki.
METHODS
We performed a systematic literature review and meta-analysis to assess the association between finasteride and prostate cancer. Systematic literature searches were conducted using PubMed, EMBASE, Science Direct/Elsevier, MEDLINE, CNKI, and the Cochrane Library up to October 2018 to identify studies that involved the relationship between finasteride and prostate cancer. Meta-analysis was performed using Review Manager and Stata software. Combined ORs were identified with 95% confidence intervals (95% CI) in a random or fixed effects model.
RESULTS
Eight studies were identified, including 54,335 cases of patients that used finasteride and 9197 patients who served as placebo controls. Our results illustrate that there is a significant correlation between finasteride use and prostate cancer with combined ORs of 0.70 [0.51, 0.96]. A significant correlation between finasteride use and high-grade prostate cancer was also observed with combined ORs of 2.10 [1.85, 2.38].
CONCLUSIONS
This study confirms that finasteride significantly reduced the risk of prostate cancer; however, the malignant degree of prostate cancer was increased. Studies with larger sample sizes are needed to better clarify the correlation between finasteride use and prostate cancer.
Topics: 5-alpha Reductase Inhibitors; Finasteride; Humans; Male; Prostatic Neoplasms
PubMed: 32282699
DOI: 10.1097/MD.0000000000019486 -
Prostate Cancer and Prostatic Diseases Mar 2021Although previous studies have shown a decreased incidence of prostate cancer in men with HIV/AIDS, the consensus has not been reached. Our aim is to conduct a... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Although previous studies have shown a decreased incidence of prostate cancer in men with HIV/AIDS, the consensus has not been reached. Our aim is to conduct a systematic review and meta-analysis to assess the risk of prostate cancer among people with HIV/AIDS.
METHODS
We systematically searched PubMed, Web of Science, Embase, and Cochrane Library until March 2020. Cohort studies were included if they compared the prostate cancer risk between people with HIV/AIDS and uninfected controls or the general population. The summary standardized incidence ratio (SIR) and 95% confidence interval (CI) were calculated using a random-effects model.
RESULTS
A total of 27 studies were included for analysis, with more than 2780 males with HIV/AIDS developing prostate cancer. The results showed that HIV infection was associated with a decreased risk of prostate cancer incidence (SIR, 0.76; 95% CI, 0.64-0.91; P = 0.003), with significant heterogeneity (P < 0.001; I = 91.6%). A range of sensitivity analyzes did not significantly change the results.
CONCLUSIONS
Our study shows that people with HIV/AIDS have a lower incidence of prostate cancer compared with the general population. However, significant heterogeneity exists among the included studies. Further prospective studies with better designs are needed to elucidate the association between HIV infection and prostate cancer.
Topics: Acquired Immunodeficiency Syndrome; Global Health; HIV; HIV Infections; Humans; Incidence; Male; Prostatic Neoplasms; Risk Factors
PubMed: 32801354
DOI: 10.1038/s41391-020-00268-2 -
African Journal of Reproductive Health Dec 2020Male genital schistosomiasis (MGS) may result in eggs lodged in the prostate causing persistent inflammation that may play a major role in prostate carcinogenesis.... (Review)
Review
Male genital schistosomiasis (MGS) may result in eggs lodged in the prostate causing persistent inflammation that may play a major role in prostate carcinogenesis. Globally, prostate cancer (PCa) is one of the most common cancers and the global distribution of PCa overlaps with that of schistosomiasis infections, suggesting a probable causal relationship. Objectives of this review were to assess evidence of co-existence of schistosomiasis and PCa and possible causal association between the two diseases. Relevant literature published between 1950 and 2019 yielded 20 publications on schistosomiasis and PCa co-existence. Schistosoma (S.) haematobium and S. mansoni were associated with MGS manifestation and mostly prostate adenocarcinoma diagnosis. Effects of prostatic MGS infection progressed over time with high Schistosoma egg burden thought to contribute to the development of PCa. Causal association and mechanistic pathways of MGS on PCa development and the role of Schistosoma eggs on the development of PCa remains unestablished.
Topics: Adenocarcinoma; Animals; Humans; Male; Prostatic Neoplasms; Schistosoma haematobium; Schistosomiasis
PubMed: 34077083
DOI: 10.29063/ajrh2020/v24i4.19 -
Bioscience Reports Jan 2022Elevated levels of miR-21 expression are associated with many cancers, suggesting it may be a promising clinical biomarker. In prostate cancer (PCa), however, there is... (Meta-Analysis)
Meta-Analysis
Elevated levels of miR-21 expression are associated with many cancers, suggesting it may be a promising clinical biomarker. In prostate cancer (PCa), however, there is still no consensus about the usefulness of miR-21 as an indicator of disease progression. This systematic review and meta-analysis was conducted to investigate the value of miR-21 expression as a prognostic measurement in PCa patients. Medline (Ovid), EMBASE, Web of Science, Scopus and Cochrane Library databases were systematically searched for relevant publications between 2010 to 2021. Studies exploring the relationship between miR-21 expression, PCa prognosis and clinicopathological factors were selected for review. Those reporting hazard ratio (HR) and 95% confidence intervals (CIs) were subject to meta-analyses. Fixed-effect models were employed to calculated pooled HRs and 95% CIs. Risk of bias in each study was assessed using QUIPS tool. Certainty of evidence in each meta-analysis was assessed using GRADE guidelines. A total of 64 studies were included in the systematic review. Of these, 11 were eligible for inclusion in meta-analysis. Meta-analyses revealed that high miR-21 expression was associated with poor prognosis: HR = 1.58 (95% CI = 1.19-2.09) for biochemical recurrence, MODERATE certainty; HR = 1.46 (95% CI = 1.06-2.01) for death, VERY LOW certainty; and HR = 1.26 (95% CI = 0.70-2.27) for disease progression, VERY LOW certainty. Qualitative summary revealed elevated miR-21 expression was significantly positively associated with PCa stage, Gleason score and risk groups. This systematic review and meta-analysis suggests that elevated levels of miR-21 are associated with poor prognosis in PCa patients. miR-21 expression may therefore be a useful prognostic biomarker in this disease.
Topics: Biomarkers, Tumor; Humans; Male; MicroRNAs; Neoplasm Grading; Neoplasm Staging; Predictive Value of Tests; Progression-Free Survival; Prostatic Neoplasms; Risk Assessment; Risk Factors; Up-Regulation
PubMed: 34931228
DOI: 10.1042/BSR20211972 -
Prostate Cancer and Prostatic Diseases Dec 2023Artificial intelligence (AI) is a promising tool in pathology, including cancer diagnosis, subtyping, grading, and prognostic prediction. (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Artificial intelligence (AI) is a promising tool in pathology, including cancer diagnosis, subtyping, grading, and prognostic prediction.
METHODS
The aim of the study is to assess AI application in prostate cancer (PCa) histology. We carried out a systematic literature search in 3 databases. Primary outcome was AI accuracy in differentiating between PCa and benign hyperplasia. Secondary outcomes were AI accuracy in determining Gleason grade and agreement among AI and pathologists.
RESULTS
Our final sample consists of 24 studies conducted from 2007 to 2021. They aggregate data from roughly 8000 cases of prostate biopsy and 458 cases of radical prostatectomy (RP). Sensitivity for PCa diagnostic exceeded 90% and ranged from 87% to 100%, and specificity varied from 68% to 99%. Overall accuracy ranged from 83.7% to 98.3% with AUC reaching 0.99. The meta-analysis using the Mantel-Haenszel method showed pooled sensitivity of 0.96 with I = 80.7% and pooled specificity of 0.95 with I = 86.1%. Pooled positive likehood ratio was 15.3 with I = 87.3% and negative - was 0.04 with I = 78.6%. SROC (symmetric receiver operating characteristics) curve represents AUC = 0.99. For grading the accuracy of AI was lower: sensitivity for Gleason grading ranged from 77% to 87%, and specificity from 82% to 90%.
CONCLUSIONS
The accuracy of AI for PCa identification and grading is comparable to expert pathologists. This is a promising approach which has several possible clinical applications resulting in expedite and optimize pathology reports. AI introduction into common practice may be limited by difficult and time-consuming convolutional neural network training and tuning.
Topics: Male; Humans; Prostate; Prostatic Neoplasms; Artificial Intelligence; Prostatectomy; Prognosis; Neoplasm Grading
PubMed: 37185992
DOI: 10.1038/s41391-023-00673-3 -
Nutrition, Metabolism, and... Jul 2023Data on the association between nut consumption and prostate cancer risk are conflicting. Therefore, this systematic review and dose-response meta-analysis aimed to... (Meta-Analysis)
Meta-Analysis
AIMS
Data on the association between nut consumption and prostate cancer risk are conflicting. Therefore, this systematic review and dose-response meta-analysis aimed to summarize available findings from observational studies on the associations of nut intake with risk of total, advanced, non-advanced, and fatal prostate cancers.
DATA SYNTHESIS
We searched the online databases of PubMed, Scopus, and Web of Science as well as Google Scholar using appropriate keywords to identify eligible articles up to September 2022. In total, 11 articles with a total sample size of 287,786 participants and 32,213 cases of prostate cancer were included in the current systematic review and meta-analysis. By comparing the highest and lowest intake of total nuts, pooled relative risks (RRs) and 95% confidence intervals (95% CIs) for total, advanced, non-advanced, and fatal prostate cancers were 0.94 (95% CI: 0.85-1.04, P = 0.22), 1.10 (95% CI: 0.98-1.24, P = 0.12), 0.97 (95% CI: 0.85-1.11, P = 0.69), 0.97 (95% CI: 0.79-1.18, P = 0.73), respectively, which indicated non-significant inverse associations for total, non-advanced, and fatal prostate cancers and a non-significant positive association for advanced prostate cancer. In the dose-response analyses, we found no evidence of a linear or non-linear association between total nut intake and prostate cancer risk. Data on other types of nuts, including walnut, tree nuts, peanut, and peanut butter, were not sufficient for performing a meta-analysis.
CONCLUSION
We found no significant association between nut intake and risk of total, advanced, non-advanced, and fatal prostate cancer. Further studies are required to confirm our findings.
PROSPERO REGISTRATION CODE
CRD42022347094.
ETHICAL APPROVAL
Not required.
Topics: Male; Humans; Adult; Nuts; Diet; Juglans; Prostatic Neoplasms; Risk; Observational Studies as Topic
PubMed: 37160404
DOI: 10.1016/j.numecd.2023.04.004