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BMJ Open May 2022The aggressive triple-negative breast cancer (TNBC) subtype disproportionately affects women of African ancestry across the diaspora, but its frequency across Africa has... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
The aggressive triple-negative breast cancer (TNBC) subtype disproportionately affects women of African ancestry across the diaspora, but its frequency across Africa has not been widely studied. This study seeks to estimate the frequency of TNBC among African populations.
DESIGN
Systematic review and meta-analysis using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.
DATA SOURCES
PubMed, EMBASE, African Journals Online and Web of Science were searched on 25 April 2021.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES
We included studies that use breast cancer tissue samples from indigenous African women with sample size of eligible participants ≥40 and full receptor status for all three receptors (oestrogen receptor (ER)/progesterone receptor (PR)/human epidermal growth factor receptor 2 (HER2)) reported.
DATA EXTRACTION AND SYNTHESIS
Two independent reviewers extracted data and assessed risk of bias using the modified assessment tool by Hoy (2012) for prevalence studies. A random-effects meta-analysis was performed, and data were pooled using the inverse-variance method and logit transformation. Pooled frequencies were reported with 95% CIs calculated with the Clopper-Pearson method and heterogeneity quantified with I statistic. GRADE assessed the certainty of the evidence.
RESULTS
1808 potentially eligible studies were identified of which 67 were included in the systematic review and 60 were included in the meta- analysis. Pooled TNBC frequency across African countries represented was estimated to be 27.0%; 95% CI: 24.0% to 30.2%, I=94%. Pooled TNBC frequency was highest across West Africa, 45.7% (n=15, 95% CI: 38.8% to 52.8%, I=91%) and lowest in Central Africa, 14.9% (n=1, 95% CI: 8.9 % to 24.1%). Estimates for TNBC were higher for studies that used Allred guidelines for ER/PR status compared with American Society of Clinical Oncology(ASCO)/College of American Pathologists(CAP) guidelines, and for studies that used older versions of ASCO/CAP guidelines for assessing HER2 status. Certainty of evidence was assessed to be very low using GRADE approach.
CONCLUSION
TNBC frequency was variable with the highest frequency reported in West Africa. Greater emphasis should be placed on establishing protocols for assessing receptor status due to the variability among studies.
Topics: Africa; Female; Humans; Population Groups; Prevalence; Receptors, Estrogen; Triple Negative Breast Neoplasms
PubMed: 35623750
DOI: 10.1136/bmjopen-2021-055735 -
International Journal of Transgender... 2021For transgender women, communication and speech characteristics might not be congruent with their gender expressions. This can have a major influence on their... (Review)
Review
For transgender women, communication and speech characteristics might not be congruent with their gender expressions. This can have a major influence on their psychosocial functioning. Higher quality of life scores were observed the more their voice was perceived as feminine. Speech language pathologists may play an important role in this, as the gender affirming hormone treatment for transgender women does not affect the voice. This systematic review aimed to provide speech and language pathologists with the current literature concerning the effects of speech therapy in transgender women in terms of acoustic and perceptual outcomes. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used for reporting this systematic review. The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (using the PubMed interface) and Embase (using the embase.com interface) were used as electronic databases. All individual studies which measured the effects of speech therapy in transgender women were evaluated with a risk of bias assessment tool and levels of evidence. Relevant data were extracted from these studies and a narrative synthesis was performed. 14 studies were identified through the databases and other sources. These studies show positive outcome results concerning pitch elevation, oral resonance, self-perception and listener perception. However, methodological issues contribute to problems with generalization and reproducibility of the studies. There is an urgent need for effectiveness studies using RCT designs, larger sample sizes, multidimensional voice assessments, well-described therapy programs, investigators blinded to study process, and longer-term follow-up data. Speech and language pathologists who work with transgender women may find these results essential for defining therapy goals.
PubMed: 37808532
DOI: 10.1080/26895269.2021.1915224 -
Journal of Medical Internet Research Sep 2023Multimodal treatment-induced dysphagia has serious negative effects on survivors of head and neck cancer. Owing to advances in communication technologies, several... (Review)
Review
BACKGROUND
Multimodal treatment-induced dysphagia has serious negative effects on survivors of head and neck cancer. Owing to advances in communication technologies, several studies have applied telecommunication-based interventions that incorporate swallowing exercises, education, monitoring, feedback, self-management, and communication. It is especially urgent to implement home-based remote rehabilitation in the context of the COVID-19 pandemic. However, the optimal strategy and effectiveness of remote interventions are unclear.
OBJECTIVE
This systematic review aimed to examine the evidence regarding the efficacy of telerehabilitation for reducing physiological and functional impairments related to swallowing and for improving adherence and related influencing factors among head and neck cancer survivors.
METHODS
The PubMed, MEDLINE, CINAHL, Embase, and Cochrane Library databases were systematically searched up to July 2023 to identify relevant articles. In total, 2 investigators independently extracted the data and assessed the methodological quality of the included studies using the quality assessment tool of the Joanna Briggs Institute.
RESULTS
A total of 1465 articles were initially identified; ultimately, 13 (0.89%) were included in the systematic review. The quality assessment indicated that the included studies were of moderate to good quality. The results showed that home-based telerehabilitation improved the safety of swallowing and oral feeding, nutritional status, and swallowing-related quality of life; reduced negative emotions; improved swallowing rehabilitation adherence; was rated by participants as highly satisfactory and supportive; and was cost-effective. In addition, this review investigated factors that influenced the efficacy of telerehabilitation, which included striking a balance among swallowing training strategy, intensity, frequency, duration, and individual motor ability; treating side effects of radiotherapy; providing access to medical, motivational, and educational information; providing feedback on training; providing communication and support from speech pathologists, families, and other survivors; and addressing technical problems.
CONCLUSIONS
Home-based telerehabilitation has shown great potential in reducing the safety risks of swallowing and oral feeding, improving quality of life and adherence, and meeting information needs for dysphagia among survivors of head and neck cancer. However, this review highlights limitations in the current literature, and the current research is in its infancy. In addition, owing to the diversity of patient sociodemographic, medical, physiological and functional swallowing, and behavioral factors, we recommend the development of tailored telemedicine interventions to achieve the best rehabilitation effects with the fewest and most precise interventions.
Topics: Humans; Deglutition Disorders; Telerehabilitation; Pandemics; Quality of Life; COVID-19; Neoplasms
PubMed: 37682589
DOI: 10.2196/47324 -
BMC Medical Informatics and Decision... Jul 2023Esophageal cancer (EC) is a significant global health problem, with an estimated 7th highest incidence and 6th highest mortality rate. Timely diagnosis and treatment are...
INTRODUCTION
Esophageal cancer (EC) is a significant global health problem, with an estimated 7th highest incidence and 6th highest mortality rate. Timely diagnosis and treatment are critical for improving patients' outcomes, as over 40% of patients with EC are diagnosed after metastasis. Recent advances in machine learning (ML) techniques, particularly in computer vision, have demonstrated promising applications in medical image processing, assisting clinicians in making more accurate and faster diagnostic decisions. Given the significance of early detection of EC, this systematic review aims to summarize and discuss the current state of research on ML-based methods for the early detection of EC.
METHODS
We conducted a comprehensive systematic search of five databases (PubMed, Scopus, Web of Science, Wiley, and IEEE) using search terms such as "ML", "Deep Learning (DL (", "Neural Networks (NN)", "Esophagus", "EC" and "Early Detection". After applying inclusion and exclusion criteria, 31 articles were retained for full review.
RESULTS
The results of this review highlight the potential of ML-based methods in the early detection of EC. The average accuracy of the reviewed methods in the analysis of endoscopic and computed tomography (CT (images of the esophagus was over 89%, indicating a high impact on early detection of EC. Additionally, the highest percentage of clinical images used in the early detection of EC with the use of ML was related to white light imaging (WLI) images. Among all ML techniques, methods based on convolutional neural networks (CNN) achieved higher accuracy and sensitivity in the early detection of EC compared to other methods.
CONCLUSION
Our findings suggest that ML methods may improve accuracy in the early detection of EC, potentially supporting radiologists, endoscopists, and pathologists in diagnosis and treatment planning. However, the current literature is limited, and more studies are needed to investigate the clinical applications of these methods in early detection of EC. Furthermore, many studies suffer from class imbalance and biases, highlighting the need for validation of detection algorithms across organizations in longitudinal studies.
Topics: Humans; Deep Learning; Early Detection of Cancer; Machine Learning; Neural Networks, Computer; Esophageal Neoplasms
PubMed: 37460991
DOI: 10.1186/s12911-023-02235-y -
Journal of Healthcare Engineering 2022Treatment of speech disorders during childhood is essential. Many technologies can help speech and language pathologists (SLPs) to practice speech skills, one of which... (Review)
Review
INTRODUCTION
Treatment of speech disorders during childhood is essential. Many technologies can help speech and language pathologists (SLPs) to practice speech skills, one of which is digital games. This study aimed to systematically investigate the games developed to treat speech disorders and their challenges in children.
METHODS
A comprehensive search was conducted in four databases, including Medline (through PubMed), Scopus, Web of Science, and IEEE Xplore, to retrieve English articles published by July 14, 2021. The articles in which a digital game was developed to treat speech disorders in children were included in the study. Then, the features of the designed games and their challenges were extracted from the studies.
RESULTS
After reviewing the full texts of 69 articles and assessing them in terms of inclusion and exclusion criteria, 27 articles were included in the systematic review. In these articles, 59.25% of the games had been developed in English language and children with hearing impairments had received much attention from researchers compared to other patients. Also, the Mel-Frequency Cepstral Coefficients (MFCC) algorithm and the PocketSphinx speech recognition engine had been used more than any other speech recognition algorithm and tool. In terms of the games, 48.15% had been designed in a way that children could practice with the help of their parents. The evaluation of games showed a positive effect on children's satisfaction, motivation, and attention during speech therapy exercises. The biggest barriers and challenges mentioned in the studies included sense of frustration, low self-esteem after several failures in playing games, environmental noise, contradiction between games levels and the target group's needs, and problems related to speech recognition.
CONCLUSION
The results of this study showed that the games positively affect children's motivation to continue speech therapy, and they can also be used as the SLPs' aids. Before designing these tools, the obstacles and challenges should be considered, and also, the solutions should be suggested.
Topics: Child; Humans; Motivation; Perception; Speech; Speech Disorders; Speech Therapy
PubMed: 35509705
DOI: 10.1155/2022/4814945 -
Head and Neck Pathology Jun 2021Extranodal extension (ENE) is a very strong prognostic factor in head and neck squamous cell carcinoma. However, significant variance in reported incidence of ENE...
Extranodal extension (ENE) is a very strong prognostic factor in head and neck squamous cell carcinoma. However, significant variance in reported incidence of ENE suggests discordance in perception of ENE among pathologists. This study aims to map the different definitions of histopathological ENE used in the literature. A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. Guided by the research question: "How is histopathological ENE defined?" the databases Medline, Embase, and Cochrane were systematically searched. All retrieved studies were reviewed and qualitatively analyzed. Three categories of existing definitions were formed. The systematic literature search yielded 1786 studies after removal of duplicates. Nine hundred and thirty-four full text articles were assessed for inclusion and 44 unique ENE definitions were identified and categorized 1-3; (1) simple definitions only describing a breach in the capsule (48%), (2) definitions also including a description of the perinodal tissue (43%), and (3) definitions adding a description of a specific reaction in the perinodal structure (9%). No consensus definition of ENE exists, but based on the level of details in the identified definitions, three overall categories of ENE definitions were established.
Topics: Extranodal Extension; Humans; Pathology, Clinical; Squamous Cell Carcinoma of Head and Neck
PubMed: 32918710
DOI: 10.1007/s12105-020-01221-4 -
BMC Oral Health Jan 2024Since AI algorithms can analyze patient data, medical records, and imaging results to suggest treatment plans and predict outcomes, they have the potential to support... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Since AI algorithms can analyze patient data, medical records, and imaging results to suggest treatment plans and predict outcomes, they have the potential to support pathologists and clinicians in the diagnosis and treatment of oral and maxillofacial pathologies, just like every other area of life in which it is being used. The goal of the current study was to examine all of the trends being investigated in the area of oral and maxillofacial pathology where AI has been possibly involved in helping practitioners.
METHODS
We started by defining the important terms in our investigation's subject matter. Following that, relevant databases like PubMed, Scopus, and Web of Science were searched using keywords and synonyms for each concept, such as "machine learning," "diagnosis," "treatment planning," "image analysis," "predictive modelling," and "patient monitoring." For more papers and sources, Google Scholar was also used.
RESULTS
The majority of the 9 studies that were chosen were on how AI can be utilized to diagnose malignant tumors of the oral cavity. AI was especially helpful in creating prediction models that aided pathologists and clinicians in foreseeing the development of oral and maxillofacial pathology in specific patients. Additionally, predictive models accurately identified patients who have a high risk of developing oral cancer as well as the likelihood of the disease returning after treatment.
CONCLUSIONS
In the field of oral and maxillofacial pathology, AI has the potential to enhance diagnostic precision, personalize care, and ultimately improve patient outcomes. The development and application of AI in healthcare, however, necessitates careful consideration of ethical, legal, and regulatory challenges. Additionally, because AI is still a relatively new technology, caution must be taken when applying it to this industry.
Topics: Humans; Algorithms; Artificial Intelligence; Image Processing, Computer-Assisted; Medical Records; Mouth; Face
PubMed: 38263027
DOI: 10.1186/s12903-023-03533-7 -
International Journal of Breast Cancer 2022The frozen section (FS) has been a good technique in surgical management of breast lesions since many years. But complete agreement and cooperation have not been... (Review)
Review
BACKGROUND
The frozen section (FS) has been a good technique in surgical management of breast lesions since many years. But complete agreement and cooperation have not been achieved everywhere among surgeons and pathologists especially in the developing countries. FS undergoes continuous criticism due to various shortcomings but continued to be evaluated especially in developing countries.
OBJECTIVES
This review was conducted to synthesize information on the use of frozen section in carcinoma breast. . The MEDLINE database for frozen section since its origin and its implication in recent breast surgery techniques was studied. . Sixty-five articles were reviewed with complete analysis on FS in both benign and malignant breast lesions. . The analysis of frozen section was done as a diagnostic tool in breast lesions, margin status in breast conservative surgery in carcinoma breast, and sentinel lymph node and use of immunohistochemistry for sentinel lymph node FS.
RESULTS
It was analysed that the FS gives accurate results in margin status analysis, decreasing rerecurrence.
CONCLUSION
The accuracy of FSA, low recurrence rate, avoidance of reoperation, and good cosmesis are the key points of its use in breast conservative surgery. Its use in sentinel lymph node biopsy (SLNB) is equivocal. However, application of immunohistochemistry on frozen section of SLNB is an evolving trend in today's era.
PubMed: 35655582
DOI: 10.1155/2022/4958580 -
Synovial Sarcoma of the Nerve-Clinical and Pathological Features: Case Series and Systematic Review.Neurosurgery Dec 2019Synovial sarcoma of the nerve is a rare entity with several cases and case series reported in the literature. Despite an improved understanding of the biology, the...
BACKGROUND
Synovial sarcoma of the nerve is a rare entity with several cases and case series reported in the literature. Despite an improved understanding of the biology, the clinical course is difficult to predict.
OBJECTIVE
To compile a series of patients with synovial sarcoma of the peripheral nerve (SSPN) and assess clinical and pathological factors and their contribution to survival and recurrence.
METHODS
Cases from 2 institutions collected in patients undergoing surgical intervention for SSPN. Systematic review including PubMed and Scopus databases were searched for related articles published from 1970 to December 2018. Eligibility criteria: (1) case reports or case series reporting on SSPN, (2) clinical course and/or pathological features of the tumor reported, and (3) articles published in English.
RESULTS
From patients treated at our institutions (13) the average follow-up period was 3.2 yr. Tumor recurrence was seen in 4 cases and death in 3. Systematic review of the literature yielded 44 additional cases with an average follow-up period of 3.6 yr. From pooled data, there were 10 recurrences and 7 deaths (20% and 14%, respectively). Adjuvant treatment used in 62.5% of cases. Immunohistochemical markers used in diagnosis varied widely; the most common are the following: Epithelial membrane antigen (EMA), cytokeratin, vimentin, cluster of differentiation (CD34), and transducin-like enhancer of split 1 (TLE1). Statistical analysis illustrated tumor size and use of chemotherapy to be negative predictors of survival. No other factors, clinically or from pathologist review, were correlated with recurrence or survival.
CONCLUSION
By combining cases from our institution with historical data and performing statistical analysis we show correlation between tumor size and death.
Topics: Biomarkers, Tumor; Humans; Peripheral Nervous System Neoplasms; Sarcoma, Synovial
PubMed: 31435657
DOI: 10.1093/neuros/nyz321 -
Journal of Nephrology Sep 2022Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ allocation and post-transplant graft... (Review)
Review
BACKGROUND
Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ allocation and post-transplant graft biopsy for assessment of rejection or graft damage. The introduction of digital pathology with whole-slide imaging (WSI) in clinical research, trials and practice has catalyzed the application of artificial intelligence (AI) for histopathology, with development of novel machine-learning models for tissue interrogation and discovery. We aimed to review the literature for studies specifically applying AI algorithms to WSI-digitized pre-implantation kidney biopsy.
METHODS
A systematic search was carried out in the electronic databases PubMed-MEDLINE and Embase until 25th September, 2021 with a combination of the key terms "kidney", "biopsy", "transplantation" and "artificial intelligence" and their aliases. Studies dealing with the application of AI algorithms coupled with WSI in pre-implantation kidney biopsies were included. The main theme addressed was detection and quantification of tissue components. Extracted data were: author, year and country of the study, type of biopsy features investigated, number of cases, type of algorithm deployed, main results of the study in terms of diagnostic outcome, and the main limitations of the study.
RESULTS
Of 5761 retrieved articles, 7 met our inclusion criteria. All studies focused largely on AI-based detection and classification of glomerular structures and to a lesser extent on tubular and vascular structures. Performance of AI algorithms was excellent and promising.
CONCLUSION
All studies highlighted the importance of expert pathologist annotation to reliably train models and the need to acknowledge clinical nuances of the pre-implantation setting. Close cooperation between computer scientists and practicing as well as expert renal pathologists is needed, helping to refine the performance of AI-based models for routine pre-implantation kidney biopsy clinical practice.
Topics: Algorithms; Artificial Intelligence; Biopsy; Humans; Intelligence; Kidney
PubMed: 35441256
DOI: 10.1007/s40620-022-01327-8