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Frontiers in Oncology 2022Breast cancer (BC) screening can be performed in a screening program (BCSP) or in opportunistic screening. The existing reviews on the determinants of non-participation...
BACKGROUND
Breast cancer (BC) screening can be performed in a screening program (BCSP) or in opportunistic screening. The existing reviews on the determinants of non-participation depend on self-reported data which may be biased. Furthermore, no distinction was made between the probably different determinants of both screening strategies.
OBJECTIVE
To find the determinants of non-participation in BCSP by means of a meta-analysis.
METHODS
PubMed, Embase, and Web of Science were searched for observational studies which quantified factors associated with non-participation in BCSP in a general population. Studies on opportunistic screening and studies using self-reported data were excluded. A random-effect model was used to calculate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Potential sources of heterogeneity were explored by stratification of the results.
RESULTS
Twenty-nine studies with in a total of 20,361,756 women were included. Low income (OR: 1.20, 95% CI: 1.10-1.30), low education (OR: 1.18, 95% CI: 1.05-1.32), living far from an assigned screening unit (OR: 1.15, 95% CI: 1.07-1.24), being immigrant (OR: 2.64, 95% CI: 2.48-2.82), and having a male family doctor (OR: 1.43, 95% CI: 1.20-1.61) was associated with higher non-participation in screening. Reminders sent to non-attenders and estimations of ORs (adjusted or not) partly explained substantial heterogeneity.
CONCLUSION
In this meta-analysis excluding studies on the non-participation in opportunistic screening, or with self-reported data on non-participation, the well-known determinants for non-participation are still significant, but less strong. This analysis only supports the relevance of meta-analysis of studies with registered non-participation in a BCSP.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO, CRD42020154016.
PubMed: 35311110
DOI: 10.3389/fonc.2022.817222 -
Disease Markers 2022This study is aimed at determining the best nonacid nucleic blood tumor marker panels in terms of sensitivity, specificity, and accuracy in order to detect breast cancer... (Meta-Analysis)
Meta-Analysis
This study is aimed at determining the best nonacid nucleic blood tumor marker panels in terms of sensitivity, specificity, and accuracy in order to detect breast cancer in early stages (I, II, and III) among eligible women for breast cancer screening. PubMed, Web of Science, Embase, Scopus, and Cochrane were systematically reviewed to assess nonacid nucleic blood tumor marker panels' diagnostic value in women, both healthy and patient (before any anticancer treatment), for detecting breast cancer. A network meta-analysis was carried out using a Bayesian network meta-analysis to estimate combined odd ratio (OR) and 95% CI credible interval for presenting the results. Rankograms plot was drawn to rank the diagnostic value of different panels. Of the 2358 titles initially identified, 9 studies and 8 panels were included in the network meta-analysis. Panels A (MMP-9/TIMP-1) and K (TF1+TF2+TF3) had the highest sensitivity in early stages, as panel A with OR = 11.61 and 95% CI (1.49-102.5) demonstrated a better function than mammography. Panels H (CA 15.3 + IL-18) and A (MMP-9/TIMP-1) had the highest specificity in early stages, but no significant difference with mammography. Panels A (MMP-9/TIMP-1) and H (CA 15.3 + IL-18) had the highest accuracy in early stages, as they significantly exhibited a higher function than mammography with OR = 6.87 and 95% CI (2.07-31.35) as well as OR = 3.44 and 95% CI (1.15-11.07), respectively. Panel A including MMP-9/TIMP-1 in early stages demonstrated a higher diagnostic value for breast cancer than the rest of the panels.
Topics: Bayes Theorem; Biomarkers, Tumor; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Network Meta-Analysis
PubMed: 35222743
DOI: 10.1155/2022/4119345 -
BMC Cancer Feb 2022The aim of this systematic review was to evaluate the evidence and clinical outcomes of screening interventions and implementation trials in sub-Saharan Africa (SSA) and...
BACKGROUND
The aim of this systematic review was to evaluate the evidence and clinical outcomes of screening interventions and implementation trials in sub-Saharan Africa (SSA) and also appraise some ethical issues related to screening in the region through quantitative and qualitative narrative synthesis of the literature.
METHODS
We searched Pubmed, OvidMEDLINE, Embase, and Web of Science to identify studies published on breast cancer screening interventions and outcomes in SSA. Descriptive statistics were used to summarize the frequency and proportions of extracted variables, and narrative syntheses was used to evaluate the clinical outcomes of the different screening modalities. The mixed methods appraisal tool was used to assess the quality of studies included in the review.
RESULTS
Fifteen studies were included, which consisted of 72,572 women in ten countries in SSA. 63% (8/15) of the included publications evaluated Clinical Breast Examination (CBE), 47% (7/15) evaluated mammography and 7% (1/15) evaluated ultrasound screening. The cancer detection rate was < 1/1000 to 3.3/1000 and 3.3/100 to 56/1000 for CBE and mammography screening respectively. There was a lot of heterogeneity in CBE methods, target age for screening and no clear documentation of screening interval. Cost-effective analyses showed that CBE screening linked to comprehensive cancer care is most cost effective. There was limited discussion of the ethics of screening, including the possible harms of screening in the absence of linkage to care. The gap between conducting good screening program and the appropriate follow-up with diagnosis and treatment remains one of the major challenges of screening in SSA.
DISCUSSION
There is insufficient real-world data to support the systematic implementation of national breast cancer screening in SSA. Further research is needed to answer important questions about screening, and national and international partnerships are needed to ensure that appropriate diagnostic and treatment modalities are available to patients who screen positive.
Topics: Adolescent; Adult; Africa South of the Sahara; Breast Neoplasms; Early Detection of Cancer; Ethics, Medical; Female; Health Plan Implementation; Humans; Mammography; Middle Aged; Patient Acceptance of Health Care; Qualitative Research; Young Adult
PubMed: 35197002
DOI: 10.1186/s12885-022-09299-5 -
NPJ Digital Medicine Feb 2022Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we conduct a meta-analysis to assess the diagnostic performance of deep...
Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) algorithms for early breast and cervical cancer identification. Four subgroups are also investigated: cancer type (breast or cervical), validation type (internal or external), imaging modalities (mammography, ultrasound, cytology, or colposcopy), and DL algorithms versus clinicians. Thirty-five studies are deemed eligible for systematic review, 20 of which are meta-analyzed, with a pooled sensitivity of 88% (95% CI 85-90%), specificity of 84% (79-87%), and AUC of 0.92 (0.90-0.94). Acceptable diagnostic performance with analogous DL algorithms was highlighted across all subgroups. Therefore, DL algorithms could be useful for detecting breast and cervical cancer using medical imaging, having equivalent performance to human clinicians. However, this tentative assertion is based on studies with relatively poor designs and reporting, which likely caused bias and overestimated algorithm performance. Evidence-based, standardized guidelines around study methods and reporting are required to improve the quality of DL research.
PubMed: 35169217
DOI: 10.1038/s41746-022-00559-z -
Journal of Osteopathic Medicine Feb 2022Management remains controversial due to the risk of upgrade for malignancy from flat epithelial atypia (FEA). Data about the frequency and malignancy upgrade rates are... (Meta-Analysis)
Meta-Analysis Review
CONTEXT
Management remains controversial due to the risk of upgrade for malignancy from flat epithelial atypia (FEA). Data about the frequency and malignancy upgrade rates are scant. Namely, observational follow-up is advised by many studies in cases of pure FEA on core biopsy and in the absence of an additional surgical excision. For cases of pure FEA, the American College of Surgeons no longer recommends surgical excision but rather recommends observation with clinical and imaging follow-up.
OBJECTIVES
The aim of this study is to perform a systematic review and meta-analysis to calculate the pooled upgrade of pure FEA following core needle biopsies.
METHODS
A search of MEDLINE and Embase databases were conducted in December 2020. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A fixed- or random-effects model was utilized. Heterogeneity among studies was estimated by utilizing the I2 statistic and considered high if the I2 was greater than 50%. The random-effects model with the DerSimonian and Laird method was utilized to calculate the pooled upgrade rate and its 95% confidence interval.
RESULTS
A total of 1924 pure FEA were analyzed among 59 included studies. The overall pooled upgrade rate to malignancy was 8.8%. The pooled upgrade rate for mammography only was 8.9%. The pooled upgrade rate for ultrasound was 14%. The pooled upgrade rate for mammography and ultrasound combined was 8.8%. The pooled upgrade rate for MRI-only cases was 27.3%.
CONCLUSIONS
Although the guidelines for the management of pure FEA are variable, our data support that pure FEA diagnosed at core needle biopsy should undergo surgical excision since the upgrade rate >2%.
Topics: Breast; Breast Neoplasms; Carcinoma, Intraductal, Noninfiltrating; Female; Humans; Mammography
PubMed: 35150124
DOI: 10.1515/jom-2021-0206 -
Frontiers in Oncology 2021mutation carriers are suggested with regular breast cancer surveillance screening strategies using mammography with supplementary MRI as an adjunct tool in Western...
BACKGROUND
mutation carriers are suggested with regular breast cancer surveillance screening strategies using mammography with supplementary MRI as an adjunct tool in Western countries. From a cost-effectiveness perspective, however, the benefits of screening modalities remain controversial among different mutated genes and screening schedules.
METHODS
We searched the MEDLINE/PubMed, Embase, Cochrane Library, Scopus, and Web of Science databases to collect and compare the results of different cost-effectiveness analyses. A simulated model was used to predict the impact of screening strategies in the target group on cost, life-year gained, quality-adjusted life years, and incremental cost-effectiveness ratio (ICER).
RESULTS
Nine cost-effectiveness studies were included. Combined mammography and MRI strategy is cost-effective in mutation carriers for the middle-aged group (age 35 to 54). mutation carriers are less likely to benefit from adjunct MRI screening, which implies that mammography alone would be sufficient from a cost-effectiveness perspective, regardless of dense breast cancer.
CONCLUSIONS
Precision screening strategies among mutation carriers should be conducted according to the acceptable ICER, i.e., a combination of mammography and MRI for mutation carriers and mammography alone for mutation carriers.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO, identifier CRD42020205471.
PubMed: 35083138
DOI: 10.3389/fonc.2021.763161 -
Journal of the American College of... Feb 2022The aim of this study was to describe the current state of science regarding independent external validation of artificial intelligence (AI) technologies for screening...
PURPOSE
The aim of this study was to describe the current state of science regarding independent external validation of artificial intelligence (AI) technologies for screening mammography.
METHODS
A systematic review was performed across five databases (Embase, PubMed, IEEE Explore, Engineer Village, and arXiv) through December 10, 2020. Studies that used screening examinations from real-world settings to externally validate AI algorithms for mammographic cancer detection were included. The main outcome was diagnostic accuracy, defined by area under the receiver operating characteristic curve (AUC). Performance was also compared between radiologists and either stand-alone AI or combined radiologist and AI interpretation. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool.
RESULTS
After data extraction, 13 studies met the inclusion criteria (148,361 total patients). Most studies (77% [n = 10]) evaluated commercially available AI algorithms. Studies included retrospective reader studies (46% [n = 6]), retrospective simulation studies (38% [n = 5]), or both (15% [n = 2]). Across 5 studies comparing stand-alone AI with radiologists, 60% (n = 3) demonstrated improved accuracy with AI (AUC improvement range, 0.02-0.13). All 5 studies comparing combined radiologist and AI interpretation with radiologists alone demonstrated improved accuracy with AI (AUC improvement range, 0.028-0.115). Most studies had risk for bias or applicability concerns for patient selection (69% [n = 9]) and the reference standard (69% [n = 9]). Only two studies obtained ground-truth cancer outcomes through regional cancer registry linkage.
CONCLUSIONS
To date, external validation efforts for AI screening mammographic technologies suggest small potential diagnostic accuracy improvements but have been retrospective in nature and suffer from risk for bias and applicability concerns.
Topics: Algorithms; Artificial Intelligence; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Retrospective Studies
PubMed: 35065909
DOI: 10.1016/j.jacr.2021.11.008 -
Journal of Ambient Intelligence and... 2023Artificial intelligence can assist providers in a variety of patient care and intelligent health systems. Artificial intelligence techniques ranging from machine...
Artificial intelligence can assist providers in a variety of patient care and intelligent health systems. Artificial intelligence techniques ranging from machine learning to deep learning are prevalent in healthcare for disease diagnosis, drug discovery, and patient risk identification. Numerous medical data sources are required to perfectly diagnose diseases using artificial intelligence techniques, such as ultrasound, magnetic resonance imaging, mammography, genomics, computed tomography scan, etc. Furthermore, artificial intelligence primarily enhanced the infirmary experience and sped up preparing patients to continue their rehabilitation at home. This article covers the comprehensive survey based on artificial intelligence techniques to diagnose numerous diseases such as Alzheimer, cancer, diabetes, chronic heart disease, tuberculosis, stroke and cerebrovascular, hypertension, skin, and liver disease. We conducted an extensive survey including the used medical imaging dataset and their feature extraction and classification process for predictions. Preferred reporting items for systematic reviews and Meta-Analysis guidelines are used to select the articles published up to October 2020 on the Web of Science, Scopus, Google Scholar, PubMed, Excerpta Medical Database, and Psychology Information for early prediction of distinct kinds of diseases using artificial intelligence-based techniques. Based on the study of different articles on disease diagnosis, the results are also compared using various quality parameters such as prediction rate, accuracy, sensitivity, specificity, the area under curve precision, recall, and F1-score.
PubMed: 35039756
DOI: 10.1007/s12652-021-03612-z -
Physica Medica : PM : An International... Feb 2022Patient shielding during medical X-ray imaging has been increasingly criticized in the last years due to growing evidence that it often provides minimal benefit and may... (Review)
Review
PURPOSE
Patient shielding during medical X-ray imaging has been increasingly criticized in the last years due to growing evidence that it often provides minimal benefit and may even compromise image quality. In Europe, and as also shown in a short assessment in Switzerland, the use of patient shielding is inhomogeneous. The aim of this study was to systematically review recent literature in order to assess benefits and appraise disadvantages related to the routine use of patient shielding.
METHODS
To evaluate benefits and disadvantages related to the application of patient shielding in radiological procedures, a systematic literature review was performed for CT, radiography, mammography and fluoroscopy-guided medical X-ray imaging. In addition, reports from medical physics societies and authorities of different countries were considered in the evaluation.
RESULTS
The literature review revealed 479 papers and reports on the topic, from which 87 qualified for closer analysis. The review considered in- and out-of-plane patient shielding as well as shielding for pregnant and pediatric patients. Dose savings and other dose and non-dose related effects of patient shielding were considered in the evaluation.
CONCLUSIONS
Although patient shielding has been used in radiological practice for many years, its use is no longer undisputed. The evaluation of the systematic literature review of recent studies and reports shows that dose savings are rather minimal while significant dose- and non-dose-related detrimental effects are present. Consequently, the routine usage of patient protection shielding in medical X-ray imaging can be safely discontinued for all modalities and patient groups.
Topics: Child; Female; Fluoroscopy; Humans; Pregnancy; Radiation Dosage; Radiation Protection; Radiography; Radiology; X-Rays
PubMed: 35030383
DOI: 10.1016/j.ejmp.2021.12.016 -
Epidemiology and Health 2022The aim of this study was to provide an overview of published mathematical estimation approaches to quantify the duration of the preclinical detectable phase (PCDP)...
OBJECTIVES
The aim of this study was to provide an overview of published mathematical estimation approaches to quantify the duration of the preclinical detectable phase (PCDP) using data from cancer screening programs.
METHODS
A systematic search of PubMed and Embase was conducted for original studies presenting mathematical approaches using screening data. The studies were categorized by mathematical approach, data source, and assumptions made. Furthermore, estimates of the duration of the PCDP of breast and colorectal cancer were reported per study population.
RESULTS
From 689 publications, 34 estimation methods were included. Five distinct types of mathematical estimation approaches were identified: prevalence-to-incidence ratio (n=8), maximum likelihood estimation (n=16), expectation-maximization algorithm (n=1), regression of observed on expected (n=6) and Bayesian Markov-chain Monte Carlo estimation (n=5). Fourteen studies used data from both screened and unscreened populations, whereas 19 studies included only information from a screened population. Estimates of the duration of the PCDP varied between 2 years and 7 years for breast cancer in the Health Insurance Plan study (annual mammography and clinical breast examinations in women aged 40-64 years) and 2 years and 5 years for colorectal cancer in the Calvados study (a guaiac fecal occult blood test in men and women aged 45-74 years).
CONCLUSIONS
Different types of mathematical approaches lead to different estimates of the PCDP duration. We advise researchers to use the method that matches the data available, and to use multiple methods for estimation when possible, since no method is perfect.
Topics: Bayes Theorem; Breast Neoplasms; Colorectal Neoplasms; Early Detection of Cancer; Female; Humans; Male; Mammography; Mass Screening; Sensitivity and Specificity
PubMed: 34990529
DOI: 10.4178/epih.e2022008