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Frontiers in Medicine 2023The progression of early stage non-small cell lung cancer (NSCLC) is closely related to epidermal growth factor receptor (EGFR) mutation status. The purpose of this...
Distinguishing EGFR mutant subtypes in stage IA non-small cell lung cancer using the presence status of ground glass opacity and final histologic classification: a systematic review and meta-analysis.
BACKGROUND
The progression of early stage non-small cell lung cancer (NSCLC) is closely related to epidermal growth factor receptor (EGFR) mutation status. The purpose of this study was to systematically investigate the relationship between EGFR mutation status and demographic, imaging, and ultimately pathologic features in patients with NSCLC.
METHODS
A complete literature search was conducted using the PubMed, Web of Science, EMBASE, and Cochrane Library databases to discover articles published by May 15, 2023 that were eligible. The relationship between EGFR mutation status and specific demographic, imaging, and ultimately pathologic features in patients with NSCLC was evaluated using pooled odds ratios (ORs) and their 95% confidence intervals (CIs). The standardized mean difference (SMD) with 95% CIs was the appropriate statistic to summarize standard deviations (SDs) means for continuous variables.
RESULTS
A total of 9 studies with 1789 patients were included in this analysis. The final findings suggested that patients with a greater age, female gender, and non-smoking status would have a relatively higher incidence of EGFR mutations. Additionally, the risk of EGFR mutations increased with larger tumor diameter, tumor imaging presentation of mixed ground glass opacity (mGGO), and tumor pathological findings of minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IAC). Significantly, malignancies presenting as MIA are more likely to contain L858R point mutations (OR = 1.80; 95% CI: 1.04-3.13; = 0.04) rather than exon 19 deletions (OR = 1.81; 95% CI: 0.95-3.44; = 0.07).
CONCLUSION
This meta-analysis showed that imaging parameters and histological classifications of pulmonary nodules may be able to predict stage IA NSCLC genetic changes.
PubMed: 38126071
DOI: 10.3389/fmed.2023.1268846 -
Cancer Research and Treatment Apr 2024Radial probe endobronchial ultrasound (RP-EBUS) accurately locates peripheral lung lesions (PLLs) during transbronchial biopsy (TBB). We performed an updated... (Meta-Analysis)
Meta-Analysis
Development of the Korean Association for Lung Cancer Clinical Practice Guidelines: Recommendations on Radial Probe Endobronchial Ultrasound for Diagnosing Lung Cancer - An Updated Meta-Analysis.
PURPOSE
Radial probe endobronchial ultrasound (RP-EBUS) accurately locates peripheral lung lesions (PLLs) during transbronchial biopsy (TBB). We performed an updated meta-analysis of the diagnostic yield of TBB for PLLs using RP-EBUS to generate recommendations for the development of the Korean Association of Lung Cancer guidelines.
MATERIALS AND METHODS
We systematically searched MEDLINE and EMBASE (from January 2013 to December 2022), and performed a meta-analysis using R software. The diagnostic yield was evaluated by dividing the number of successful diagnoses by the total lesion number. Subgroup analysis was performed to identify related factors.
RESULTS
Forty-one studies with a total of 13,133 PLLs were included. The pooled diagnostic yield of RP-EBUS was 0.72 (95% confidence interval [CI], 0.70 to 0.75). Significant heterogeneity was observed among studies (χ2=292.38, p < 0.01, I2=86.4%). In a subgroup analysis, there was a significant difference in diagnostic yield based on RP-EBUS findings (within, adjacent to, invisible), with a risk ratio of 1.45 (95% CI, 1.23 to 1.72) between within and adjacent to, 4.20 (95% CI, 1.89 to 9.32) between within and invisible, and 2.59 (95% CI, 1.32 to 5.01) between adjacent to and invisible. There was a significant difference in diagnostic yield based on lesion size, histologic diagnosis, computed tomography (CT) bronchus sign, lesion character, and location from the hilum. The overall complication rate of TBB with RP-EBUS was 6.8% (bleeding, 4.5%; pneumothorax, 1.4%).
CONCLUSION
Our study showed that TBB with RP-EBUS is an accurate diagnostic tool for PLLs with good safety profiles, especially for PLLs with within orientation on RP-EBUS or positive CT bronchus sign.
Topics: Humans; Lung Neoplasms; Bronchoscopy; Retrospective Studies; Biopsy; Republic of Korea; Lung
PubMed: 38037321
DOI: 10.4143/crt.2023.749 -
Medicine Nov 2023Lung cancer is the leading cause of death worldwide, and its diagnosis remains a significant challenge. Identifying effective methods to differentiate benign from... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Lung cancer is the leading cause of death worldwide, and its diagnosis remains a significant challenge. Identifying effective methods to differentiate benign from malignant lung nodules is of paramount importance. This meta-analysis aimed to evaluate the clinical utility of circulating microRNAs (miRNAs) for the differential diagnosis of benign and malignant lung nodules.
METHODS
This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A comprehensive search was conducted across 4 electronic databases, without any temporal restrictions. The inclusion and exclusion criteria were strictly applied to assess the clinical applications of circulating miRNAs. A robust and transparent quality assessment was performed using the quality assessment of diagnostic accuracy studies-2 tool, and rigorous statistical analyses were conducted to synthesize the various diagnostic measures.
RESULTS
In the meta-analysis of 11 studies, quality assessment of diagnostic accuracy studies-2 assessment revealed < 5% high-risk methodologies, ensuring robustness. Sensitivity and Specificity were consolidated at 0.83 (95% confidence interval [CI]: 0.72-0.90) and 0.81 (95% CI: 0.73-0.88), respectively. The positive likelihood ratio and negative likelihood ratio were 4.45 (95% CI: 3.03-6.54) and 0.21 (95% CI: 0.12-0.35), respectively. The diagnostic odds ratio was 21.31 (95% CI: 10.25-44.30) and area under the receiver operating characteristic curve was 0.89 (95% CI: 0.86-0.91). Subgroup analysis highlighted significant variations in diagnostic accuracy by ethnicity and miRNA source, with non-Asian populations and serum-based tests showing higher diagnostic accuracy.
CONCLUSION
This meta-analysis demonstrated that circulating miRNAs hold substantial diagnostic value in distinguishing between benign and malignant lung nodules.
Topics: Humans; MicroRNAs; Sensitivity and Specificity; ROC Curve; Circulating MicroRNA; Lung
PubMed: 37986348
DOI: 10.1097/MD.0000000000035857 -
Life (Basel, Switzerland) Sep 2023For several years, computer technology has been utilized to diagnose lung nodules. When compared to traditional machine learning methods for image processing,... (Review)
Review
OBJECTIVE
For several years, computer technology has been utilized to diagnose lung nodules. When compared to traditional machine learning methods for image processing, deep-learning methods can improve the accuracy of lung nodule diagnosis by avoiding the laborious pre-processing step of the picture (extraction of fake features, etc.). Our goal is to investigate how well deep-learning approaches classify lung nodule malignancy.
METHOD
We evaluated the performance of deep-learning methods on lung nodule malignancy classification via a systematic literature search. We conducted searches for appropriate articles in the PubMed and ISI Web of Science databases and chose those that employed deep learning to classify or predict lung nodule malignancy for our investigation. The figures were plotted, and the data were extracted using SAS version 9.4 and Microsoft Excel 2010, respectively.
RESULTS
Sixteen studies that met the criteria were included in this study. The articles classified or predicted pulmonary nodule malignancy using classification and summarization, using convolutional neural network (CNN), autoencoder (AE), and deep belief network (DBN). The AUC of deep-learning models is typically greater than 90% in articles. It demonstrated that deep learning performed well in the diagnosis and forecasting of lung nodules.
CONCLUSION
It is a thorough analysis of the most recent advancements in lung nodule deep-learning technologies. The advancement of image processing techniques, traditional machine learning techniques, deep-learning techniques, and other techniques have all been applied to the technology for pulmonary nodule diagnosis. Although the deep-learning model has demonstrated distinct advantages in the detection of pulmonary nodules, it also carries significant drawbacks that warrant additional research.
PubMed: 37763314
DOI: 10.3390/life13091911 -
Insights Into Imaging Sep 2023Health systems worldwide are implementing lung cancer screening programmes to identify early-stage lung cancer and maximise patient survival. Volumetry is recommended... (Review)
Review
Health systems worldwide are implementing lung cancer screening programmes to identify early-stage lung cancer and maximise patient survival. Volumetry is recommended for follow-up of pulmonary nodules and outperforms other measurement methods. However, volumetry is known to be influenced by multiple factors. The objectives of this systematic review (PROSPERO CRD42022370233) are to summarise the current knowledge regarding factors that influence volumetry tools used in the analysis of pulmonary nodules, assess for significant clinical impact, identify gaps in current knowledge and suggest future research. Five databases (Medline, Scopus, Journals@Ovid, Embase and Emcare) were searched on the 21st of September, 2022, and 137 original research studies were included, explicitly testing the potential impact of influencing factors on the outcome of volumetry tools. The summary of these studies is tabulated, and a narrative review is provided. A subset of studies (n = 16) reporting clinical significance were selected, and their results were combined, if appropriate, using meta-analysis. Factors with clinical significance include the segmentation algorithm, quality of the segmentation, slice thickness, the level of inspiration for solid nodules, and the reconstruction algorithm and kernel in subsolid nodules. Although there is a large body of evidence in this field, it is unclear how to apply the results from these studies in clinical practice as most studies do not test for clinical relevance. The meta-analysis did not improve our understanding due to the small number and heterogeneity of studies testing for clinical significance. CRITICAL RELEVANCE STATEMENT: Many studies have investigated the influencing factors of pulmonary nodule volumetry, but only 11% of these questioned their clinical relevance in their management. The heterogeneity among these studies presents a challenge in consolidating results and clinical application of the evidence. KEY POINTS: • Factors influencing the volumetry of pulmonary nodules have been extensively investigated. • Just 11% of studies test clinical significance (wrongly diagnosing growth). • Nodule size interacts with most other influencing factors (especially for smaller nodules). • Heterogeneity among studies makes comparison and consolidation of results challenging. • Future research should focus on clinical applicability, screening, and updated technology.
PubMed: 37741928
DOI: 10.1186/s13244-023-01480-z -
Journal of Global Health Sep 2023China has a high burden of nontuberculous mycobacterial (NTM) infections. Immunocompromised populations, such as those with human immunodeficiency virus/acquired... (Meta-Analysis)
Meta-Analysis
BACKGROUND
China has a high burden of nontuberculous mycobacterial (NTM) infections. Immunocompromised populations, such as those with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), are at a higher risk of being infected with NTM than immunocompetent individuals. Yet, there is a paucity of information on the clinical features of positive NTM isolates from patients with HIV/AIDS in China. To address this gap, we conducted a systematic review and meta-analysis of existing studies, comparing them against current expert consensus to provide guidance for clinical practice.
METHODS
Two researchers independently searched eight databases (SinoMed, China National Knowledge Infrastructure, Wanfang, VIP, Cochrane Library, PubMed, Embase, and Web of Science) from inception to 26 December 2022 to retrieve published Chinese- and English-language studies reporting clinical features of NTM-positive isolates among patients with HIV/AIDS in China.
RESULTS
We included 28 studies with 1861 patients. The rate of positive NTM isolates detected from men among all patients was 87.3%. NTM species distribution was mainly Mycobacterium avium complex (64.3%), which was predominant in different regions. The five most common clinical symptoms were fever (68.5%), cough or expectoration (67.0%), appetite loss (49.4%), weight loss (45.5%), and superficial lymphadenectasis (41.1%). The prevalence of laboratory tests were as follows: albumin <35 g/L (55.6%), erythrocyte sedimentation rate >20 mm/h (91.4%), anaemia (59.0%), predominantly mild, CD4+ T cell count ≤50 pieces/μL (70.3%), and CD4+ T cell count 51-200 pieces/μL (22.1%). Lesion manifestations in thoracic imaging mainly included bilateral lung involvement (83.8%), showed stripe shadows (60.3%), patchy shadows (42.9%), nodules (40.6%), and bronchiectasis (38.6%). Accompanied signs included thoracic lymph node enlargement (49.5%). Seventy per cent of symptoms improved after treatment.
CONCLUSIONS
Focusing on clinical symptoms, laboratory tests, and thoracic imaging helps with initial screening for NTM infections. Physicians should raise awareness of the diagnosis and treatment of Mycobacterium avium complex, providing guidance for experimental treatment, screening of priority populations for NTM infections, and prophylactic treatment of NTM disease.
REGISTRATION
PROSPERO CRD42023388185.
Topics: Humans; Male; Acquired Immunodeficiency Syndrome; China; Nontuberculous Mycobacteria; Mycobacterium Infections, Nontuberculous; HIV Infections
PubMed: 37651639
DOI: 10.7189/jogh.13.04093 -
European Radiology Mar 2024Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its... (Meta-Analysis)
Meta-Analysis
OBJECTIVES
Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its performance across different populations. This systematic review and meta-analysis aimed to evaluate the performance of Lung-RADS (versions 1.0 and 1.1) for detecting lung cancer in different populations.
METHODS
We performed literature searches in PubMed, Web of Science, Cochrane Library, and Embase databases on October 21, 2022, for studies that evaluated the accuracy of Lung-RADS in lung cancer screening. A bivariate random-effects model was used to estimate pooled sensitivity and specificity, and heterogeneity was explored in stratified and meta-regression analyses.
RESULTS
A total of 31 studies with 104,224 participants were included. For version 1.0 (27 studies, 95,413 individuals), pooled sensitivity was 0.96 (95% confidence interval [CI]: 0.90-0.99) and pooled specificity was 0.90 (95% CI: 0.87-0.92). Studies in high-risk populations showed higher sensitivity (0.98 [95% CI: 0.92-0.99] vs. 0.84 [95% CI: 0.50-0.96]) and lower specificity (0.87 [95% CI: 0.85-0.88] vs. 0.95 (95% CI: 0.92-0.97]) than studies in general populations. Non-Asian studies tended toward higher sensitivity (0.97 [95% CI: 0.91-0.99] vs. 0.91 [95% CI: 0.67-0.98]) and lower specificity (0.88 [95% CI: 0.85-0.90] vs. 0.93 [95% CI: 0.88-0.96]) than Asian studies. For version 1.1 (4 studies, 8811 individuals), pooled sensitivity was 0.91 (95% CI: 0.83-0.96) and specificity was 0.81 (95% CI: 0.67-0.90).
CONCLUSION
Among studies using Lung-RADS version 1.0, considerable heterogeneity in sensitivity and specificity was noted, explained by population type (high risk vs. general), population area (Asia vs. non-Asia), and cancer prevalence.
CLINICAL RELEVANCE STATEMENT
Meta-regression of lung cancer screening studies using Lung-RADS version 1.0 showed considerable heterogeneity in sensitivity and specificity, explained by the different target populations, including high-risk versus general populations, Asian versus non-Asian populations, and populations with different lung cancer prevalence.
KEY POINTS
• High-risk population studies showed higher sensitivity and lower specificity compared with studies performed in general populations by using Lung-RADS version 1.0. • In non-Asian studies, the diagnostic performance of Lung-RADS version 1.0 tended to be better than in Asian studies. • There are limited studies on the performance of Lung-RADS version 1.1, and evidence is lacking for Asian populations.
Topics: Humans; Tomography, X-Ray Computed; Lung Neoplasms; Early Detection of Cancer; Lung; Sensitivity and Specificity
PubMed: 37646809
DOI: 10.1007/s00330-023-10049-9 -
Sensors (Basel, Switzerland) Jul 2023Pulmonary tuberculosis (PTB) is a bacterial infection that affects the lung. PTB remains one of the infectious diseases with the highest global mortalities. Chest... (Review)
Review
Pulmonary tuberculosis (PTB) is a bacterial infection that affects the lung. PTB remains one of the infectious diseases with the highest global mortalities. Chest radiography is a technique that is often employed in the diagnosis of PTB. Radiologists identify the severity and stage of PTB by inspecting radiographic features in the patient's chest X-ray (CXR). The most common radiographic features seen on CXRs include cavitation, consolidation, masses, pleural effusion, calcification, and nodules. Identifying these CXR features will help physicians in diagnosing a patient. However, identifying these radiographic features for intricate disorders is challenging, and the accuracy depends on the radiologist's experience and level of expertise. So, researchers have proposed deep learning (DL) techniques to detect and mark areas of tuberculosis infection in CXRs. DL models have been proposed in the literature because of their inherent capacity to detect diseases and segment the manifestation regions from medical images. However, fully supervised semantic segmentation requires several pixel-by-pixel labeled images. The annotation of such a large amount of data by trained physicians has some challenges. First, the annotation requires a significant amount of time. Second, the cost of hiring trained physicians is expensive. In addition, the subjectivity of medical data poses a difficulty in having standardized annotation. As a result, there is increasing interest in weak localization techniques. Therefore, in this review, we identify methods employed in the weakly supervised segmentation and localization of radiographic manifestations of pulmonary tuberculosis from chest X-rays. First, we identify the most commonly used public chest X-ray datasets for tuberculosis identification. Following that, we discuss the approaches for weakly localizing tuberculosis radiographic manifestations in chest X-rays. The weakly supervised localization of PTB can highlight the region of the chest X-ray image that contributed the most to the DL model's classification output and help pinpoint the diseased area. Finally, we discuss the limitations and challenges of weakly supervised techniques in localizing TB manifestations regions in chest X-ray images.
Topics: Humans; X-Rays; Radiography, Thoracic; Tuberculosis, Pulmonary; Radiography; Tuberculosis
PubMed: 37571564
DOI: 10.3390/s23156781 -
Oral Oncology Oct 2023Head and neck squamous cell carcinoma (HNSCC) often presents with synchronous nodules of the lung (sNL), which may be benign nodules, second primary malignancies or... (Review)
Review
Head and neck squamous cell carcinoma (HNSCC) often presents with synchronous nodules of the lung (sNL), which may be benign nodules, second primary malignancies or metastases of HNSCC. We sought to gain an insight into the incidence of sNL and synchronous second primary of the lung (sSPML) in HNSCC patients and current opinions on useful diagnostic and therapeutic approaches. We conducted a systematic search of the PubMed database for articles that reported the simultaneous detection of HNSCC and sNL/sPML, within the timeframe of diagnosis and staging. Only studies involving humans were included, without restrictions for sex, age, ethnicity, or smoking history. All articles were categorised according to the Oxford Centre of Evidence-Based Medicine levels and their data collected. Data from 24 studies were analysed. Amongst HNSCC, the mean overall incidence rate of sNL and sSPML was 11.4% (range: 1.3-27%) and 2.95% (range: 0.4-7.4%), respectively. The possibility of a sNL to be a sSPML cannot be ignored (mean: 35.2%). Studies investigating smoking habits showed that the majority (98-100%) of HNSCC patients with sSPML were previous or active smokers. Detection of human papillomavirus through DNA analysis, p16 immunohistochemistry, and identification of clonal evolution were useful in differentiating metastasis from sSPML. FDG-PET scan was the most reliable method to diagnose sSPML (sensitivity: 95%; specificity: 96%; positive predictive value: 80%). With early sSPML detection and curative treatment, the 5-year overall survival rate is 34-47%. However, the proposed advantage of early detection warrants further evidence-based justification.
Topics: Humans; Squamous Cell Carcinoma of Head and Neck; Neoplasms, Multiple Primary; Head and Neck Neoplasms; Neoplasms, Second Primary; Lung
PubMed: 37506514
DOI: 10.1016/j.oraloncology.2023.106529 -
Journal of Clinical Medicine May 2023To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists, many Artificial Intelligence (AI) algorithms have been developed. Some... (Review)
Review
To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists, many Artificial Intelligence (AI) algorithms have been developed. Some algorithms are currently being implemented in clinical practice, but the question is whether radiologists and patients really benefit from the use of these novel tools. This study aimed to review how AI assistance for lung nodule assessment on CT scans affects the performances of radiologists. We searched for studies that evaluated radiologists' performances in the detection or malignancy prediction of lung nodules with and without AI assistance. Concerning detection, radiologists achieved with AI assistance a higher sensitivity and AUC, while the specificity was slightly lower. Concerning malignancy prediction, radiologists achieved with AI assistance generally a higher sensitivity, specificity and AUC. The radiologists' workflows of using the AI assistance were often only described in limited detail in the papers. As recent studies showed improved performances of radiologists with AI assistance, AI assistance for lung nodule assessment holds great promise. To achieve added value of AI tools for lung nodule assessment in clinical practice, more research is required on the clinical validation of AI tools, impact on follow-up recommendations and ways of using AI tools.
PubMed: 37240643
DOI: 10.3390/jcm12103536