Low-dose computed tomography (LDCT) versus other cancer screenings in early diagnosis of lung cancer: A meta-analysis

Combined measurement of circulating tumor cell counts and serum tumor marker levels enhances the screening efficiency for malignant versus benign pulmonary nodules

BACKGROUND

The high false-positive rate for pulmonary nodules (PNs) from using low-dose computed tomography (LDCT) screening can lead to overuse of invasive procedures, overtreatment, and patient anxiety. Therefore, it is very important to develop new diagnostic methods.

METHODS

A negative enrichment-fluorescence in situ hybridization (NE-FISH) approach was used to detect circulating tumor cells (CTCs) in patients with PNs. We evaluated whether or not the combination of CTC counts with serum tumor marker levels (CEA, CA 125, CYFRA 21-1, SCC) could improve the diagnostic ability for distinguishing patients with malignant pulmonary nodules (MPNs) from those with benign pulmonary nodules (BPNs). Moreover, the potential clinical application of this combination for the diagnosis of solitary pulmonary nodules (SPNs) with a diameter ≤2 cm was also investigated.

RESULTS

The combination of CTC counts and tumor marker levels had a sensitivity of 80.12% and the area under the receiver operating characteristics curve (AUC_ROC ) of 0.853 (95% confidence interval [CI]: 0.800-0.897, p < 0.001) for the differential diagnosis of PNs. For early cancer stages, the sensitivity was 75.38% (AUC_ROC  = 0.780, 95% CI: 0.713-0.838, p < 0.001). In addition, for SPNs within 2 cm the combination of CTC counts and tumor marker levels was still the most valuable diagnostic tool with a sensitivity of 78.95% and AUC_ROC of 0.888.

CONCLUSION

The combination of CTC counts and serum tumor marker levels is helpful for improving the diagnosis of PNs, especially in the early stages of cancer and for SPNs within 2 cm.

Expression of Serum sLOX-1 in Patients with Non-Small-Cell Lung Cancer and Its Correlation with Lipid Metabolism

Objective

The aim of this study was to investigate the expression level of soluble LOX-1 (sLOX-1) in the serum of non-small-cell lung cancer (NSCLC) patients and its correlation with lipid metabolism.

Methods

99 inpatients with NSCLC and 81 healthy controls were enrolled in this study. The levels of serum sLOX-1 were compared between the two groups, and the correlation of sLOX-1 with clinicopathological characteristics, blood lipid indices, and carcinoembryonic antigen was analyzed.

Results

Compared with the healthy controls, sLOX-1, low-density lipoprotein, triglyceride, and carcinoembryonic antigen in the patients with NSCLC were significantly higher (p < 0.05), while the expression level of high-density lipoprotein was lower (p < 0.05). The expression level of sLOX-1 in the serum of patients with healthy controls was positively correlated with low-density lipoprotein (r = 0.72, p < 0.05). The levels of sLOX-1 and low-density lipoprotein in the serum of patients with NSCLC were closely related to the lymph node metastasis, distant metastasis, and TNM stage (p < 0.05). Compared with a single index, when the sLOX-1 was combined with the CEA, its specificity increased significantly to 97.5% (AUC = 0.995, p < 0.01, 95% CI: 0.989–1.000).

Conclusion

sLOX-1 and low-density lipoprotein were overexpressed in the serum of patients with NSCLC, positively correlated, and closely related to the TNM stage and metastasis. This result suggested that lipid metabolic disorders may promote the progression of NSCLC through sLOX-1, which could be a potential serological marker with diagnostic value for NSCLC.

Diagnostic Value of Artificial Intelligence Based on CT Image in Benign and Malignant Pulmonary Nodules

Objective

To evaluate the diagnostic value of artificial intelligence-assisted CT imaging in benign and malignant pulmonary nodules.

Methods

The CT scan screening of pulmonary nodules from November 2018 to November 2020 was retrospectively collected. The diagnosis of pulmonary nodules and surgical treatment were performed. A total of 194 nodules in 152 patients with clear pathological results were observed. All patients underwent CT examination to analyze the consistency of the results of artificial intelligence, physician reading according to imaging features, multidisciplinary team work (MDT) diagnosis, and postoperative pathological results; the diagnostic efficacy of different diagnostic methods for solitary pulmonary nodules and the differences of ROC curve and AUC were analyzed. The accuracy, specificity, sensitivity, positive predictive value, negative predictive value, false negative rate, and false positive rate of different diagnostic methods for pulmonary nodules were calculated, and the ROC curves of different diagnostic methods were plotted.

Results

The accuracy, sensitivity, specificity, and Youden index of artificial intelligence (AI) were 89.69%, 92.98%, 65.22%, and 58.20%; the accuracy, sensitivity, specificity, and Youden index of physician reading were 85.57%, 88.30%, 65.22%, and 53.52%; the accuracy, sensitivity, specificity, and Youden index of MDT were 96.91%, 98.25%, 86.96%, and 85.21%, respectively. The kappa values of artificial intelligence, physician reading, and MDT were 0.541, 0.437, and 0.852, and the AUC was 0.768, 0.791, and 0.926, respectively (P < 0.001). The average detection time of pulmonary nodules in the AI group, manual reading group, and MAT group was (145 ± 97) s, (534 ± 297) s, and (421 ± 128) s (P < 0.001).

Conclusion

Artificial intelligence pulmonary nodule detection system can improve the coincidence rate and accuracy of early diagnosis of lung cancer, shorten the average detection time, and provide more accurate information for clinical decision-making.

Sputum-Based Tumor Fluid Biopsy: Isolation and High-Throughput Single-Cell Analysis of Exfoliated Tumor Cells for Lung Cancer Diagnosis

Timely and effective diagnosis is of great significance for improving the survival rate of lung cancer patients. Although histopathology is the main diagnostic tool among the existing methods for lung cancer diagnosis, it is not suitable for high-risk groups, early lung cancer patients, patients with advanced-stage disease, and other situations wherein tumor tissues cannot be obtained. In view of this, we proposed an innovative lung cancer diagnosis method employing for the first time a microfluidic technology for high-efficiency isolation and high-throughput single-cell analysis of exfoliated tumor cells (ETCs) in sputum. This method fully combines the advantages of traditional sputum cytology and microfluidic technology and realizes the diagnosis of lung cancer by using a small amount of repeatable ETCs instead of the tumor tissue. This method is expected to provide a practical strategy for the non-invasive detection of lung cancer patients and lung cancer screening for high-risk groups.

The cognitive and perceptual processes that affect observer performance in lung cancer detection: a scoping review

INTRODUCTION

Early detection of malignant pulmonary nodules through screening has been shown to reduce lung cancer-related mortality by 20%. However, perceptual and cognitive factors that affect nodule detection are poorly understood. This review examines the cognitive and visual processes of various observers, with a particular focus on radiologists, during lung nodule detection.

METHODS

Four databases (Medline, Embase, Scopus and PubMed) were searched to extract studies on eye-tracking in pulmonary nodule detection. Studies were included if they used eye-tracking to assess the search and detection of lung nodules in computed tomography or 2D radiographic imaging. Data were charted according to identified themes and synthesised using a thematic narrative approach.

RESULTS

The literature search yielded 25 articles and five themes were discovered: 1 - functional visual field and satisfaction of search, 2 - expert search patterns, 3 - error classification through dwell time, 4 - the impact of the viewing environment and 5 - the effect of prevalence expectation on search. Functional visual field reduced to 2.7° in 3D imaging compared to 5° in 2D radiographs. Although greater visual coverage improved nodule detection, incomplete search was not responsible for missed nodules. Most radiological errors during lung nodule detection were decision-making errors (30%-45%). Dwell times associated with false-positive (FP) decisions informed feedback systems to improve diagnosis. Interruptions did not influence diagnostic performance; however, it increased viewing time by 8% and produced a 23.1% search continuation accuracy. Comparative scanning was found to increase the detection of low contrast nodules. Prevalence expectation did not directly affect diagnostic accuracy; however, decision-making time increased by 2.32 seconds with high prevalence expectations.

CONCLUSION

Visual and cognitive factors influence pulmonary nodule detection. Insights gained from eye-tracking can inform advancements in lung screening. Further exploration of eye-tracking in lung screening, particularly with low-dose computed tomography (LDCT), will benefit the future of lung cancer screening.

Tumor Differentiation and EGFR Mutation Associated with Disease-Free Survival in Stage IA Lung Adenocarcinoma Patients with Curative Surgery

Background

Nearly 30% of stage IA non-small-cell lung cancer patients eventually die of recurrence or metastasis. This study aimed to predict stage IA lung adenocarcinoma (LADC) patients who underwent radical resection with a high risk of recurrence or metastasis.

Methods

Information on clinicopathological, genetic and therapeutic features and recurrence status was collected in this retrospective and two-center study. A nomogram based on multivariate analysis was established to predict disease-free survival. Further stratification was performed to identify populations with a high risk of relapse.

Results

A total of 1584 patients with pathological stage IA LADC who underwent radical surgery between 2011 and 2015 were enrolled from two medical institutions in this study. The nomogram including tumor differentiation and EGFR mutation had a higher C-index of 0.880 (95% CI 0.833–0.926) compared to 0.598 (95% CI 0.486–0.711) for the AJCC 8th TNM staging system. Furthermore, the C-index for the validation cohort was 0.798 (95% CI 0.738–0.857). In addition, the 3-year cumulative nonrecurrence rate in the high-risk group stratified by this model was 21.8% compared to 98.1% in the low-risk group.

Conclusion

This study proposed a new nomogram including tumor differentiation and EGFR mutation to predict recurrence or metastatic probability in stage IA LADC patients who underwent radical surgery. This nomogram could identify patients in the high-risk group and help guide adjuvant treatment in the future.

9G TestTM Cancer/Lung: A Desirable Companion to LDCT for Lung Cancer Screening

Simple Summary

Lung cancer is the most common cause of cancer-related deaths globally. Patients diagnosed at early-stage (0–I) have a higher survival rate than the metastasized stages (III–IV). Thus, there is great potential to reduce mortality by diagnosing lung cancer at stage 0~I through community screening. LDCT is a promising method, but it has a high false-positive rate. Therefore, a biomarker test that can be used in combination with LDCT for lung cancer screening to reduce false-positive rates is highly awaited. The present study evaluated the applicability of 9G test^TM Cancer/Lung test to detect stage 0~IV lung cancer. 9G test^TM Cancer/Lung test detects stage I, stage II, stage III, and stage IV cancers with the sensitivities of 77.5%, 78.1%, 67.4%, and 33.3%, respectively, at the specificity of 97.3%. These results indicate that the 9G test^TM Cancer/Lung can be used in conjunction with LDCT to screen lung cancer.

Abstract

A complimentary biomarker test that can be used in combination with LDCT for lung cancer screening is highly desirable to improve the diagnostic capacity of LDCT and reduce the false-positive rates. Most importantly, the stage I lung cancer detection rate can be dramatically increased by the simultaneous use of a biomarker test with LDCT. The present study was conducted to evaluate 9G test^TM Cancer/Lung’s sensitivity and specificity in detecting Stage 0~IV lung cancer. The obtained results indicate that the 9G test^TM Cancer/Lung can detect lung cancer with overall sensitivity and specificity of 75.0% (69.1~80.3) and 97.3% (95.0~98.8), respectively. The detection of stage I, stage II, stage III, and stage IV cancers with sensitivities of 77.5%, 78.1%, 67.4%, and 33.3%, respectively, at the specificity of 97.3% have never been reported before. The receiver operating characteristic curve analysis allowed us to determine the population-weighted AUC of 0.93 (95% CI, 0.91–0.95). These results indicate that the 9G test^TM Cancer/Lung can be used in conjunction with LDCT to screen lung cancer. Furthermore, obtained results indicate that the use of 9G test^TM Cancer/Lung with LDCT for lung cancer screening can increase stage I cancer detection, which is crucial to improve the currently low 5-year survival rates.

Exosomal miR-21/Let-7a ratio distinguishes non-small cell lung cancer from benign pulmonary diseases

Aim

To assess the exosomal miR‐21/Let‐7a ratio, a noninvasive method, in distinguishing non‐small cell lung cancer (NSCLC) from benign pulmonary diseases.

Methods

The exosomes were extracted from the peripheral blood serum using serum exosomal extraction kit. miR‐21 and Let‐7a levels were evaluated by quantitative reverse transcription polymerase chain reaction.

Results

We found that miR‐21/Let‐7a ratio of NSCLC patients was significantly higher than that of healthy people, patients with pulmonary inflammation diseases, and benign pulmonary nodules, respectively. Receiver‐operating characteristic analysis revealed that as compared with healthy controls, miR‐21/Let‐7a produced the area under the curve (AUC) at 0.8029 in patients with NSCLC, which helped to distinguish NSCLC from healthy controls with 81.33% sensitivity and 69.57% specificity. In addition, the AUC of miR‐21/Let‐7a in NSCLC patients was 0.8196 in comparison to patients with pulmonary inflammation diseases. Meanwhile, the sensitivity and specificity were 56.00% and 100%, respectively. Furthermore, compared with patients with benign pulmonary nodules, the AUC of miR‐21/Let‐7a in NSCLC patients was 0.7539. The sensitivity and specificity were 56.00% and 82.61%, respectively.

Conclusion

In the present study, our findings revealed that exosomal miR‐21/Let‐7a ratio holds considerable promise as a noninvasive biomarker for the diagnosis of NSCLC from benign pulmonary diseases.

A rapid liquid biopsy of lung cancer by separation and detection of exfoliated tumor cells from bronchoalveolar lavage fluid with a dual-layer "PERFECT" filter system

Separation and detection of exfoliated tumor cells (ETCs) from bronchoalveolar lavage fluid (BALF), namely the liquid biopsy of BALF, has been proved to be a valuable tool for the diagnosis of lung cancer. Herein, we established a rapid liquid biopsy of BALF based on a dual-layer PERFECT (precise, efficient, rapid, flexible, easy-to-operate, controllable and thin) filter system for the first time. Methods: The dual-layer PERFECT filter system consists of an upper-layer filter with large micropores (feature size of 49.4 ± 0.5 μm) and a lower-layer filter with small micropores (9.1 ± 0.1 μm). The upper-layer filter contributes to the isolation of cell clusters and removal of mucus from BALF samples, meanwhile the lower-layer one targets for the separation of single ETCs. First, separation of 10000 spiked A549s (cultured lung cancer cells) from 10 mL clinical BALF samples (n=3) were performed to investigate the performance of the proposed system in rare cell separation. Furthermore, separation and detection of ETCs and ETC clusters from clinical BALF samples were performed with this system to test its efficacy and compared with the routine cytocentrifuge. The clinical BALF samples were collected from 33 lung cancer-suspected patients with visible lesions under bronchoscope. The final histopathological results showed that 20 samples were from lung cancer positive patients while the other 13 cases were from lung cancer negative patients. Results: The recovery rate of spiked A549 cells from clinical BALF samples with the developed system (89.8 ± 5.2%) is significantly higher than that with the cytocentrifuge (13.6 ± 7.8%). In the preliminary clinical trial, although 33 clinical BALF samples with volume ranging from 6 mL to 18 mL showed greatly varied turbidity, filtrations could be finished within 3 min for 54.6% of samples (18/33), and 10 min at most for the rest. The dual-layer PERFECT filter system is proved to have a much higher sensitivity (80.0%, 95% CI: 55.7%-93.4%) than the routine cytocentrifuge (45.0%, 95% CI: 23.8%-68.0%), p=0.016 (McNemar test, two-tail). Moreover, the sensitivity of this platform is neither interfered by the variations of turbidity of the BALF samples, nor associated with the types of lung cancer. Conclusions: The easy and rapid processing of BALF samples with varying volume and turbidity, competitive sensitivity and good versatility for different lung cancer types will make the established dual-layer PERFECT filter system a promising approach for the liquid biopsy of BALF. The high-performance BALF-based liquid biopsy will improve the cytopathological identification and diagnosis of lung cancer.

Relevance of lung ultrasound in the diagnostic algorithm of respiratory diseases in a real-life setting: A multicentre prospective study

BACKGROUND AND OBJECTIVE

The aim of this study was to assess the role of lung ultrasound (LUS) in a diagnostic algorithm of respiratory diseases, and to establish the accuracy of LUS compared with chest radiography (CXR).

METHODS

Over a period of 2 years, 509 consecutive patients admitted for respiratory-related symptoms to both emergency and general medicine wards were enrolled and evaluated using LUS and CXR. LUS was conducted by expert operators who were blinded to the medical history and laboratory data. Computed tomography (CT) of the chest was performed in case of discordance between the CXR and LUS, suspected lung cancer and an inconclusive diagnosis. Diagnosis made by CT was considered the gold standard.

RESULTS

The difference in sensitivity and specificity between LUS and CXR as demonstrated by ROC curve analyses (LUS-AUROC: 0.853; specificity: 81.6%; sensitivity: 93.9% vs CXR-AUROC: 0.763; specificity: 57.4%; sensitivity: 96.3%) was significant (P = 0.001). Final diagnosis included 240 cases (47.2%) of pneumonia, 44 patients with cancer (8.6%), 20 patients with chronic obstructive pulmonary disease (COPD, 3.9%), 24 patients with heart failure (4.7%) and others (6.1%). In 108 patients (21.2%) with any lung pathology, a CT scan was performed with a positive diagnosis in 96 cases (88.9%); we found that CXR and LUS detected no abnormality in 24 (25%) and 5 (5.2%) cases, respectively. LUS was concordant with the final diagnosis (P < 0.0001), and in healthy patients, there was a low percentage of false positives (5.9%).

CONCLUSION

The results support the routine use of LUS in the clinical context.

Effects of low-dose computed tomography on lung cancer screening: a systematic review, meta-analysis, and trial sequential analysis

BACKGROUND

The Nelson mortality results were presented in September 2018. Four other randomized control trials (RCTs) were also reported the latest mortality outcomes in 2018 and 2019. We therefore conducted a meta-analysis to update the evidence and investigate the benefits and harms of low-dose computed tomography (LDCT) in lung cancer screening.

METHODS

Detailed electronic database searches were performed to identify reports of RCTs that comparing LDCT to any other type of lung cancer screening. Pooled risk ratios (RRs) were calculated using random effects models.

RESULTS

We identified nine RCTs (n = 97,244 participants). In pooled analyses LDCT reduced lung cancer mortality (RR 0.83, 95% CI 0.76-0.90, I2 = 1%) but had no effect on all-cause mortality (RR 0.95, 95% CI 0.90-1.00). Trial sequential analysis (TSA) confirmed the results of our meta-analysis. Subgroup defined by high quality trials benefitted from LDCT screening in reducing lung cancer mortality (RR 0.82, 95% CI 0.73-0.91, I2 = 7%), whereas no benefit observed in other low quality RCTs. LDCT was associated with detection of a significantly higher number of early stage lung cancers than the control. No significant difference (RR 0.64, 95% CI 0.30-1.33) was found in mortality after invasive procedures between two groups.

CONCLUSIONS

In meta-analysis based on sufficient evidence demonstrated by TSA suggests that LDCT screening is superiority over usual care in lung cancer survival. The benefit of LDCT is expected to be heavily influenced by the risk of lung cancer in the different target group (smoking status, Asian) being screened.

Quantification of CYFRA 21-1 and a CYFRA 21-1–anti-CYFRA 21-1 autoantibody immune complex for detection of early stage lung cancer

Population-based screening of stage 0–I lung cancer is crucial for saving lives. The CIC/CYFRA 21-1 ratio allows the detection of stage I lung cancer with 76.0% sensitivity and 87.5% specificity.