Cumulative incidence of false-positive test results in lung cancer screening: a randomized trial

New Perspectives on Lung Cancer Screening and Artificial Intelligence

Lung cancer is the leading cause of cancer-related death worldwide, with 1.8 million deaths annually. Early detection is vital for improving patient outcomes; however, survival rates remain low due to late-stage diagnoses. Accumulating data supports the idea that screening methods are useful for improving early diagnosis in high-risk patients. However, several barriers limit the application of lung cancer screening in real-world settings. The widespread diffusion of artificial intelligence (AI), radiomics, and machine learning has dramatically changed the current diagnostic landscape. This review explores the potential of AI and biomarker-driven methods, particularly liquid biopsy, in enhancing early lung cancer detection. We report the findings of major randomized controlled trials, cohort studies, and research on AI algorithms that use multi-modal imaging (e.g., CT and PET scans) and liquid biopsy to identify early molecular alterations. AI algorithms enhance diagnostic accuracy by automating image analysis and reducing inter-reader variability. Biomarker-driven methods identify molecular alterations in patients before imaging signs of cancer are evident. Both AI and liquid biopsy show the potential to improve sensitivity and specificity, enabling the detection of early-stage cancers that traditional methods, like low-dose CT (LDCT) scans, might miss. Integrating AI and biomarker-driven methods offers significant promise for transforming lung cancer screening. These technologies could enable earlier, more accurate detection, ultimately improving survival outcomes. AI-driven lung cancer screening can achieve over 90% sensitivity, compared to 70-80% with traditional methods, and can reduce false positives by up to 30%. AI also boosts specificity to 85-90%, with faster processing times (a few minutes vs. 30-60 min for radiologists). However, challenges remain in standardizing these approaches and integrating them into clinical practice. Ongoing research is essential to fully realize their clinical benefits and enhance timely interventions.

MXene-based SERS spectroscopic analysis of exosomes for lung cancer differential diagnosis with deep learning

Lung cancer with heterogeneity has a high mortality rate due to its late-stage detection and chemotherapy resistance. Liquid biopsy that discriminates tumor-related biomarkers in body fluids has emerged as an attractive technique for early-stage and accurate diagnosis. Exosomes, carrying membrane and cytosolic information from original tumor cells, impart themselves endogeneity and heterogeneity, which offer extensive and unique advantages in the field of liquid biopsy for cancer differential diagnosis. Herein, we demonstrate a Gramian angular summation field and MobileNet V2 (GASF-MobileNet)-assisted surface-enhanced Raman spectroscopy (SERS) technique for analyzing exosomes, aimed at precise diagnosis of lung cancer. Specifically, a composite substrate was synthesized for SERS detection of exosomes based on Ti3C2Tx Mxene and the array of gold-silver core-shell nanocubes (MGS), that combines sensitivity and signal stability. The employment of MXene facilitates the non-selective capture and enrichment of exosomes. To overcome the issue of potentially overlooking spatial features in spectral data analysis, 1-D spectra were first transformed into 2-D images through GASF. By using transformed images as the input data, a deep learning model based on the MobileNet V2 framework extracted spectral features from higher dimensions, which identified different non-small cell lung cancer (NSCLC) cell lines with an overall accuracy of 95.23%. Moreover, the area under the curve (AUC) for each category exceeded 0.95, demonstrating the great potential of integrating label-free SERS with deep learning for precise lung cancer differential diagnosis. This approach allows routine cancer management, and meanwhile, its non-specific analysis of SERS signatures is anticipated to be expanded to other cancers.

Development and validation of a tumor marker-based model for the prediction of lung cancer: an analysis of a multicenter retrospective study in Shanghai, China

Background

The incidence and mortality rates of cancer are the highest globally. Developing novel methodologies that precisely, safely, and economically differentiate between benign and malignant lung conditions holds immense clinical importance. This research seeks to construct a predictive model utilizing a combination of diverse biomarkers to effectively discriminate between benign and malignant lung diseases.

Methods

This retrospective study included patients admitted to the two general hospitals in Shanghai from 2014 to 2015. This study was developed using five tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), cytokeratin fragment 21-1 (CA211), squamous cell carcinoma antigen (SCC), and neuron specific enolase (NSE). The entire sample was divided into two groups according to the hospital: 1033 cases were included in the development cohort and 300 cases in the validation cohort. Logistic regression analysis was used for univariate analysis to explore individual correlations between each selected clinical variable and lung cancer diagnostic outcome. Diagnostic prediction models were constructed and validated based on independent prognostic factors identified using multifactorial analysis. A nomogram was created using these tumor markers (age and sex were additionally included) and validated using the concordance index and calibration curves. Clinical prediction models were evaluated using decision curve analysis.

Results

Fully adjusted multivariate analysis showed that the risk of lung cancer was 2.38 times higher in men than in women. CEA positivity was associated with an 13.41-fold increased risk in lung cancer. The area under the curve (AUC) values for the development cohort and validation cohort models were 0.907 and 0.954, respectively. In the established nomogram, the AUC for the receiver operating characteristic curve was 0.907 (95% CI, 0.889-0.925). The validation model confirmed the strong discriminative power of the nomogram (AUC = 0.954). The described calibration curves demonstrated good fit predictions and observation probabilities. In addition, decision curve analysis concluded that the newly established nomogram has important implications for clinical decision making.

Conclusions

Combined prediction models based on CEA, CA199, CA211, SCC, and NSE biomarkers could significantly the differentiation between benign and malignant lung diseases, thus facilitating better clinical decision making.

New Perspectives on Risk Assessment and Anticoagulation in Elective Spine Surgery Patients: The Impact of Ultra-Minimally Invasive Endoscopic Surgery Techniques on Patients with Cardiac Disease

The advent of ultra-minimally invasive endoscopic spine surgery, characterized by significantly reduced surgery times, minimal blood loss, and minimal tissue trauma, has precipitated a paradigm shift in the preoperative management of patients with cardiac disease undergoing elective spine procedures. This perspective article explores how these advancements have influenced the requirements for preoperative cardiac workups and the protocols surrounding the cessation of anticoagulation and antiplatelet therapies. Traditionally, extensive cardiac evaluations and the need to stop anticoagulation and antiplatelet agents have posed challenges, increasing the risk of cardiac events and delaying surgical interventions. However, the reduced invasiveness of endoscopic spine surgery presents a safer profile for patients with cardiac comorbidities, potentially minimizing the necessity for rigorous cardiac clearance and allowing for more flexible anticoagulation management. This perspective article synthesizes current research and clinical practices to provide a comprehensive overview of these evolving protocols. It also discusses the implications of these changes for patient safety, surgical outcomes, and overall healthcare efficiency. Finally, the article suggests directions for future research, emphasizing the need for updated guidelines that reflect the reduced perioperative risk associated with these innovative surgical techniques. This discussion is pivotal for primary care physicians, surgeons, cardiologists, and the broader medical community in optimizing care for this high-risk patient population.

Development and validation of a TAAbs and TAAs based non-invasive model for diagnosing lung cancer

Background

Single Tumor-associated autoantibodies (TAAbs) and tumor-associated antigens (TAAs) have been found to have lower diagnostic efficacy in lung cancer. Our objective is to develop and validate a lung cancer prediction model that utilizes TAAbs and TAAs and to enhance the accuracy of lung cancer detection.

Methods

1830 subjects were randomly divided into training and validation sets at a 7:3 ratio for this study. Lasso regression analysis was used to remove collinear variables, whereas univariate logistic regression analysis was employed to identify potential independent risk factors for lung cancer. A diagnostic model was constructed using multivariate logistic analysis. The results were presented as a nomogram and assessed for various performance measures, including area under the curve, calibration curve, and decision curve analysis.

Results

The diagnostic model was developed using gender, age, GAGE7, MAGE-A1, CA125, and CEA as variables. The training set had an AUC of 0.787, while the validation set had an AUC of 0.750. The calibration curves of the training and validation sets showed a strong agreement between anticipated and observed values. The nomogram performed better than any individual variable in both the training and validation sets in terms of net benefits for lung cancer detection, according to DCA analysis.

Conclusions

This study proposes a diagnostic model for lung cancer that uses TAAbs and TAAs and incorporates individual characteristics. This model can be easily applied to personalized diagnosis.

An analysis of the influencing factors of false negative autoantibodies in patients with non-small cell lung cancer

Objectives

To analyze the clinical significance of seven autoantibodies (P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGE, and CAGE) in patients with non-small cell lung cancer (NSCLC) and the factors that influence false-negative results.

Methods

Seven autoantibodies were measured in the serum of 502 patients with non-small cell lung cancer (NSCLC) using ELISA, and their correlations with age, sex, smoking history, pathological type, clinical stage, and PD-L1 gene expression were analyzed. The clinicopathological data of the false-negative and positive groups for the seven autoantibodies were compared to determine the influencing factors.

Results

P53 antibody expression level was correlated with lobulation sign, PGP9.5 antibody expression level with sex and vascular convergence; SOX2 antibody expression level with pathological type, clinical stage, and enlarged lymph nodes; and MAGE antibody expression level with the pathological type (P<0.05). False-negative autoantibodies are prone to occur in lung cancer patients with ground-glass nodules, no enlarged lymph nodes, no vascular convergence, and PD-L1 gene expression <1% (P <0.05).

Conclusion

Detection of seven autoantibodies was clinically significant in patients with NSCLC. However, poor sensitivity should be considered in clinical diagnoses to prevent missed diagnoses.

Historical Perspective on Lung Cancer Screening

Lung cancer represents a large burden on society with a staggering incidence and mortality rate that has steadily increased until recently. The impetus to design an effective screening program for the deadliest cancer in the United States and worldwide began in 1950. It has taken more than 50 years of numerous clinical trials and continued persistence to arrive at the development of modern-day screening program. As the program continues to grow, it is important for clinicians to understand its evolution, track outcomes, and continually assess the impact and bias of screening on the medical, social, and economic systems.

Utilization of Diagnostic Procedures After Lung Cancer Screening in the National Lung Screening Trial

OBJECTIVE

To examine utilization patterns of diagnostic procedures after lung cancer screening among participants enrolled in the National Lung Screening Trial.

METHODS

Using a sample of National Lung Screening Trial participants with abstracted medical records, we assessed utilization of imaging, invasive, and surgical procedures after lung cancer screening. Missing data were imputed using multiple imputation by chained equations. For each procedure type, we examined utilization within a year after the screening or until the next screen, whichever came first, across arms (low-dose CT [LDCT] versus chest X-ray [CXR]) and by screening results. We also explored factors associated with having these procedures using multivariable negative binomial regressions.

RESULTS

After baseline screening, our sample had 176.5 and 46.7 procedures per 100 person-years for those with a false-positive and negative result, respectively. Invasive and surgical procedures were relatively infrequent. Among those who screened positive, follow-up imaging and invasive procedures were 25% and 34% less frequent in those screened with LDCT, compared with CXR. Postscreening utilization of invasive and surgical procedures was 37% and 34% lower at the first incidence screen compared with baseline. Participants with positive results at baseline were six times more likely to undergo additional imaging than those with normal findings.

DISCUSSION

Use of imaging and invasive procedures to evaluate abnormal findings varied by screening modality, with a lower rate for LDCT than CXR. Invasive and surgical workup were less prevalent after subsequent screening examinations compared with baseline screening. Utilization was associated with older age but not gender, race or ethnicity, insurance status, or income.

High risk lung nodule: A multidisciplinary approach to diagnosis and management

Pulmonary nodules are often discovered incidentally during CT scans performed for other reasons. While the vast majority of nodules are benign, a small percentage may represent early-stage lung cancer with the potential for curative treatments. With the growing use of CT for both clinical purposes and lung cancer screening, the number of pulmonary nodules detected is expected to increase substantially. Despite well-established guidelines, many nodules do not receive proper evaluation due to a variety of factors, including inadequate coordination of care and financial and social barriers. To address this quality gap, novel approaches such as multidisciplinary nodule clinics and multidisciplinary boards may be necessary. As pulmonary nodules may indicate early-stage lung cancer, it is crucial to adopt a risk-stratified approach to identify potential lung cancers at an early stage, while minimizing the risk of harm and expense associated with over investigation of low-risk nodules. This article, authored by multiple specialists involved in nodule management, delves into the diagnostic approach to lung nodules. It covers the process of determining whether a patient requires tissue sampling or continued surveillance. Additionally, the article provides an in-depth examination of the various biopsy and therapeutic options available for malignant lung nodules. The article also emphasizes the significance of early detection in reducing lung cancer mortality, especially among high-risk populations. Furthermore, it addresses the creation of a comprehensive lung nodule program, which involves smoking cessation, lung cancer screening, and systematic evaluation and follow-up of both incidental and screen-detected nodules.

Accuracy of baseline low-dose computed tomography lung cancer screening: a systematic review and meta-analysis

BACKGROUND

Screening using low-dose computed tomography (LDCT) is a more effective approach and has the potential to detect lung cancer more accurately. We aimed to conduct a meta-analysis to estimate the accuracy of population-based screening studies primarily assessing baseline LDCT screening for lung cancer.

METHODS

MEDLINE, Excerpta Medica Database, and Web of Science were searched for articles published up to April 10, 2022. According to the inclusion and exclusion criteria, the data of true positives, false-positives, false negatives, and true negatives in the screening test were extracted. Quality Assessment of Diagnostic Accuracy Studies-2 was used to evaluate the quality of the literature. A bivariate random effects model was used to estimate pooled sensitivity and specificity. The area under the curve (AUC) was calculated by using hierarchical summary receiver-operating characteristics analysis. Heterogeneity between studies was measured using the Higgins I2 statistic, and publication bias was evaluated using a Deeks' funnel plot and linear regression test.

RESULTS

A total of 49 studies with 157,762 individuals were identified for the final qualitative synthesis; most of them were from Europe and America (38 studies), ten were from Asia, and one was from Oceania. The recruitment period was 1992 to 2018, and most of the subjects were 40 to 75 years old. The analysis showed that the AUC of lung cancer screening by LDCT was 0.98 (95% CI: 0.96-0.99), and the overall sensitivity and specificity were 0.97 (95% CI: 0.94-0.98) and 0.87 (95% CI: 0.82-0.91), respectively. The funnel plot and test results showed that there was no significant publication bias among the included studies.

CONCLUSIONS

Baseline LDCT has high sensitivity and specificity as a screening technique for lung cancer. However, long-term follow-up of the whole study population (including those with a negative baseline screening result) should be performed to enhance the accuracy of LDCT screening.

Estimating the lifetime risk of a false positive screening test result

False positive results in screening tests have potentially severe psychological, medical, and financial consequences for the recipient. However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that an individual who adheres to the U.S. Preventive Services Task Force (USPSTF) screening guidelines will receive at least one false positive in a lifetime. To do so, we assembled a data set of 116 studies cited by the USPSTF that report the number of true positives, false negatives, true negatives, and false positives for the primary screening procedure for one of five cancers or six sexually transmitted diseases. We use these data to estimate the probability that an individual in one of 14 demographic subpopulations will receive at least one false positive for one of these eleven diseases in a lifetime. We specify a suitable statistical model to account for the hierarchical structure of the data, and we use the parametric bootstrap to quantify the uncertainty surrounding our estimates. The estimated probability of receiving at least one false positive in a lifetime is 85.5% (±0.9%) and 38.9% (±3.6%) for baseline groups of women and men, respectively. It is higher for subpopulations recommended to screen more frequently than the baseline, including more vulnerable groups such as pregnant women and men who have sex with men. Since screening technology is imperfect, false positives remain inevitable. The high lifetime risk of a false positive reveals the importance of educating patients about this phenomenon.

Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality

BACKGROUND

Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT).  OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening.

SEARCH METHODS

We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021.  SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes.  DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity.  MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years.  None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence).  Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence).  False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour.  AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.

Development and validation of a prediction model for malignant pulmonary nodules: A cohort study

This study is to develop and validate a preoperative prediction model for malignancy of solitary pulmonary nodules. Data from 409 patients who underwent solitary pulmonary nodule resection at the First Affiliated Hospital of Nanjing Medical University, China between June 2018 and December 2020 were retrospectively collected. Then, the patients were nonrandomly split into a training cohort and a validation cohort. Clinical features, imaging parameters and laboratory data were then collected. Logistic regression analysis was used to develop a prediction model to identify variables significantly associated with malignant pulmonary nodules (MPNs) that were then included in the nomogram. We evaluated the discrimination and calibration ability of the nomogram by concordance index and calibration plot, respectively. MPNs were confirmed in 215 (52.6%) patients by a pathological examination. Multivariate logistic regression analysis identified 6 risk factors independently associated with MPN: gender (female, odds ratio [OR] = 2.487; 95% confidence interval [CI]: 1.313-4.711; P = .005), location of nodule (upper lobe of lung, OR = 1.126; 95%CI: 1.054-1.204; P < .001), density of nodule (pure ground glass, OR = 4.899; 95%CI: 2.572-9.716; P < .001; part-solid nodules, OR = 6.096; 95%CI: 3.153-14.186; P < .001), nodule size (OR = 1.193; 95%CI: 1.107-1.290; P < .001), GAGE7 (OR = 1.954; 95%CI: 1.054-3.624; P = .033), and GBU4-5 (OR = 2.576; 95%CI: 1.380-4.806; P = .003). The concordance index was 0.86 (95%CI: 0.83-0.91) and 0.88 (95%CI: 0.84-0.94) in the training and validation cohorts, respectively. The calibration curves showed good agreement between the predicted risk by the nomogram and real outcomes. We have developed and validated a preoperative prediction model for MPNs. The model could aid physicians in clinical treatment decision making.

Biological correlates before esophageal cancer screening and after diagnosis

Almost 50% of the world's esophageal cancer (EC) cases occur in China, and the impact of cancer screening has long been a controversial topic. The study was designed to evaluate the biological correlates of EC screening and subsequent diagnosis in China. Based on the national cohort of esophageal cancer program, a prospective multicenter study in high-risk regions was conducted from 2017 to 2019. 61 participants received twice esophageal endoscopy screening and pathological biopsy successively (with a mean follow-up of 14.03 months). Box-Cox-power transformation and two-way repeated measures ANOVA were used to evaluate hormone cortisol and immunoglobulin (IgA, IgG, IgM) levels in plasma, reflecting their stress, immune function, and biological correlates before screening and after knowing the diagnosis. The median of cortisol, IgA, IgG, and IgM in pre-screening was 15.46 ug/dL, 1.86 g/L, 12.14 g/L, and 0.91 g/L, corresponding value at post-diagnosis was 15.30 ug/dL, 2.00 g/L, 12.79 g/L, and 0.94 g/L, respectively. No significant differences in biological indicators were found between normal and esophagitis and low-grade intraepithelial neoplasia before screening and after diagnosis. After normality transformation, cortisol, IgA, IgG and IgM levels were (0.25 ± 0.04) U/mL, (0.72 ± 0.13) (g/L), (2.44 ± 0.22) (g/L) and (0.98 ± 0.25) (g/L) before screening, (0.25 ± 0.05) U/mL, (0.70 ± 0.13) (g/L), (2.48 ± 0.21) (g/L) and (1.00 ± 0.25) (g/L) after diagnosis, respectively. Repeated Measures ANOVA showed that the main effects were significant on IgA levels between pre-screening and post-diagnosis (P = 0.019). No interaction effects on biological levels between pre-post screening and esophageal pathology, anxiety states (all P > 0.05). Little biological correlates were found both before screening and after diagnosis. Cortisol and IgA dropped less significantly, while IgM and IgA were increased slightly after diagnosis. Further multi-round longitudinal studies are needed to validate these results.

Lung Nodule Detectability of Artificial Intelligence-assisted CT Image Reading in Lung Cancer Screening

BACKGROUND

Artificial intelligence (AI)-based automatic lung nodule detection system improves the detection rate of nodules. It is important to evaluate the clinical value of AI system by comparing AI-assisted nodule detection with actu-al radiology reports.

OBJECTIVE

To compare the detection rate of lung nodules between the actual radiology reports and AI-assisted reading in lung cancer CT screening.

METHODS

Participants in chest CT screening from November to December 2019 were retrospectively included. In the real-world radiologist observation, 14 residents and 15 radiologists participated to finalize radiology reports. In AI-assisted reading, one resident and one radiologist reevaluated all subjects with the assistance of an AI system to lo-cate and measure the detected lung nodules. A reading panel determined the type and number of detected lung nodules between these two methods.

RESULTS

In 860 participants (57±7 years), the reading panel confirmed 250 patients with >1 solid nodule, while radiolo-gists observed 131, lower than 247 by AI-assisted reading (p<0.001). The panel confirmed 111 patients with >1 non-solid nodule, whereas radiologist observation identified 28, lower than 110 by AI-assisted reading (p<0.001). The accuracy and sensitivity of radiologist observation for solid nodules were 86.2% and 52.4%, lower than 99.1% and 98.8% by AI-assisted reading, respectively. These metrics were 90.4% and 25.2% for non-solid nodules, lower than 98.8% and 99.1% by AI-assisted reading, respectively.

CONCLUSION

Comparing with the actual radiology reports, AI-assisted reading greatly improves the accuracy and sensi-tivity of nodule detection in chest CT, which benefits lung nodule detection, especially for non-solid nodules.

Diagnostic value of conventional tumor markers in young patients with pulmonary nodules

Background

Lung cancer is one of the most common malignancies, and there is a trend of increasing incidence in young patients. The preoperative diagnosis of pulmonary nodules is mainly based on the combination of imaging and tumor markers. There is no relevant report on the diagnostic value of tumor markers in young pulmonary nodules. Our study was designed to explore the value of five tumor markers in young patients with pulmonary nodules.

Methods

We reviewed the medical records of 390 young patients (age ≤45 years) with pulmonary nodules treated at two separate centers from January 1, 2015, to January 1, 2021. Malignant pulmonary nodules were confirmed in 318 patients, and the other 72 patients were diagnosed with benign pulmonary nodules. The gold standard for diagnosis of pulmonary nodules was surgical biopsy. The conventional serum biomarkers included cytokeratin 19 (CYFRA21‐1), pro‐gastrin‐releasing‐peptide (ProGRP), carcinoembryonic antigen (CEA), neuron‐specific enolase (NSE), and squamous cell carcinoma‐associated antigen (SCCA). The diagnostic values of five tumor markers were analyzed by receiver operating characteristic (ROC) curves.

Results

There were no significant differences in the expression of five tumor markers between the groups (p > 0.05). Single tumor marker (CYFRA21‐1, ProGRP, CEA, NSE, and SCCA) showed a limited value in the diagnosis of malignant pulmonary nodules, with the AUC of 0.506, 0.503 0.532, 0.548, and 0.562, respectively. The AUC of the combined examination was only 0.502~0.596, which did not improve the diagnostic value.

Conclusions

Five conventional tumor markers had a limited diagnostic value in young patients with pulmonary nodules.

[Lung cancer screening with low dose computed tomography : a systematic review]

INTRODUCTION

Bronchial cancer, often diagnosed at a late stage, is the leading cause of cancer death. As early detection could potentially lead to curative treatment, several studies have evaluated low-dose chest CT (LDCT) as a screening method. The main objective of this work is to determine the impact of LDCT screening on overall mortality of a smoking population.

METHODS

Systematic review of randomised controlled screening trials comparing LDCT with no screening or chest x-ray.

RESULTS

Thirteen randomised controlled trials were identified, seven of which reported mortality results. NSLT showed a significant reduction of 6.7% in overall mortality and 20% in lung cancer mortality after 6.5 years of follow-up. NELSON showed a significant reduction in lung cancer mortality of 24% at 10 years among men. LUSI and MILD showed a reduction in lung cancer mortality of 69% at 8 years among women and 39% at 10 years, respectively.

CONCLUSION

Screening for bronchial cancer is a complex issue. Clarification is needed regarding the selection of individuals, the definition of a positive result and the attitude towards a suspicious nodule.

Should sublobar resection be offered for screening-detected lung nodules?

The increasing use of low-dose CT for screening for lung cancer will inevitably identify many small, asymptomatic lung nodules and ground-glass opacities (GGOs). Current guidelines for the management of screening-detected lesions tend to advise a conservative approach based on serial imaging and intervention only if ‘suspicious’ features emerge. However, more recent developments in thoracic surgery and in the understanding of the screening-detected lesions themselves prompt some pertinent questions over this conservatism. Is CT surveillance sufficiently reliable to exclude malignancy? Is it really necessary to hold back on operative biopsy and resection given modern surgical safety and efficacy? Is the option for early surgical therapy a viable one—especially with the availability of sublobar resection today? Modern data suggests that the risk of inaction for some screening-detected lesions may be higher than expected, whereas the potential harm of surgical intervention may be substantially reduced by sublobar resection and the latest minimally invasive surgical techniques. A more pro-active approach towards offering surgery for screening-detected lesions should now be considered.

Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

IMPORTANCE

Lung cancer is the leading cause of cancer-related death in the US.

OBJECTIVE

To review the evidence on screening for lung cancer with low-dose computed tomography (LDCT) to inform the US Preventive Services Task Force (USPSTF).

DATA SOURCES

MEDLINE, Cochrane Library, and trial registries through May 2019; references; experts; and literature surveillance through November 20, 2020.

STUDY SELECTION

English-language studies of screening with LDCT, accuracy of LDCT, risk prediction models, or treatment for early-stage lung cancer.

DATA EXTRACTION AND SYNTHESIS

Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings. Data were not pooled because of heterogeneity of populations and screening protocols.

MAIN OUTCOMES AND MEASURES

Lung cancer incidence, lung cancer mortality, all-cause mortality, test accuracy, and harms.

RESULTS

This review included 223 publications. Seven randomized clinical trials (RCTs) (N = 86 486) evaluated lung cancer screening with LDCT; the National Lung Screening Trial (NLST, N = 53 454) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON, N = 15 792) were the largest RCTs. Participants were more likely to benefit than the US screening-eligible population (eg, based on life expectancy). The NLST found a reduction in lung cancer mortality (incidence rate ratio [IRR], 0.85 [95% CI, 0.75-0.96]; number needed to screen [NNS] to prevent 1 lung cancer death, 323 over 6.5 years of follow-up) with 3 rounds of annual LDCT screening compared with chest radiograph for high-risk current and former smokers aged 55 to 74 years. NELSON found a reduction in lung cancer mortality (IRR, 0.75 [95% CI, 0.61-0.90]; NNS to prevent 1 lung cancer death of 130 over 10 years of follow-up) with 4 rounds of LDCT screening with increasing intervals compared with no screening for high-risk current and former smokers aged 50 to 74 years. Harms of screening included radiation-induced cancer, false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, and increases in distress. For every 1000 persons screened in the NLST, false-positive results led to 17 invasive procedures (number needed to harm, 59) and fewer than 1 person having a major complication. Overdiagnosis estimates varied greatly (0%-67% chance that a lung cancer was overdiagnosed). Incidental findings were common, and estimates varied widely (4.4%-40.7% of persons screened).

CONCLUSIONS AND RELEVANCE

Screening high-risk persons with LDCT can reduce lung cancer mortality but also causes false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, increases in distress, and, rarely, radiation-induced cancers. Most studies reviewed did not use current nodule evaluation protocols, which might reduce false-positive results and invasive procedures for false-positive results.

Lung cancers and pulmonary nodules detected by computed tomography scan: a population-level analysis of screening cohorts

Background

An increasing number and proportion of younger lung cancer patients have been observed worldwide, raising concerns on the optimal age to begin screening. This study aimed to investigate the association between age and findings in initial CT scans.

Methods

We searched for low-dose CT screening cohorts from electronic databases. Single-arm syntheses weighted by sample size were performed to calculate the detection rates of pulmonary nodules, lung cancers (all stages and stage I), and the proportion of stage I diseases in lung cancers. In addition, we included patients who underwent chest CT in our center as a supplementary cohort. The correlation between the detection rates and age was evaluated by the Pearson Correlation Coefficient.

Results

A total of 37 studies involving 163,442 participants were included. We found the detection rates of pulmonary nodules and lung cancers increased with age. However, the proportion of stage I diseases in lung cancers declined with increased starting age and was significantly higher in the 40-year group than in other groups (40 vs. 45, 50, 55, P<0.001). In addition, the ratio of early-stage lung cancer to the number of nodules declined with age. Similarly, in our center, the detection rates of nodules (R²=0.86, P≤0.001), all lung cancer (R²=0.99, P≤0.001) and stage I diseases (R²=0.87, P=0.001) increased with age, while the proportion of stage I diseases consistently declined with age (R²=0.97, P≤0.001).

Conclusions

Starting lung cancer screening at an earlier age is associated with a higher probability of identifying a curable disease, urging future research to determine the optimal starting age.

Pulmonary nodule radiological diagnostic algorithm in lung cancer screening

Publications of the final results of the two largest randomized lung cancer screening (LCS) trials in the United States and Europe confirmed the reduction in the mortality rate associated with the use of screening with low-dose computed tomography (LDCT). Results of these trials led to widespread acceptance of LCS in properly defined high-risk populations, and its implementation in the clinical practice. Many countries started preparation for national LCS and refreshed still open debate about lung nodule management. Detection of lung cancer in the early stage with a reduction of lung cancer mortality requires dedicated programs with optimized protocols, including a specified pulmonary nodule diagnostic algorithm. The screening protocol should be clear with a precise nodule diameter or volume threshold, based on which a positive screen result is defined. The application of risk-prediction models and the introduction of the semiautomated assessment of detected nodules improves screening accuracy and should be applied in LCS protocols as verified tools to aid radiological diagnosis. In this review, we have summarized recent data about the radiological protocols from the most important LCS programs and pulmonary diagnostic algorithms. These protocols should be taken into consideration in the ongoing and planned LCS programs.

Prognosis of metastasis based on age and serum analytes after follow-up of non-metastatic lung cancer patients

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Lower age of non-metastatic patients developed metastasis during follow-up.

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Higher levels of IL-8 and MMP-9 were observed in these patients.

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IL-8 and age together improved metastasis prognostic ability.

At the diagnostic stage, metastasis detection is around 75% in the lung cancer patients. Major clinical challenge faced by medical oncologists is the unpredictable metastasis development in non-metastatic patients. The literature regarding the biomarkers/factors prognosticating metastasis in non-metastatic patients during follow-up is very limited. In this pilot study, the levels of serum biomarkers (IL-8, VEGF, MMP-2, MMP-9) were measured at diagnosis stage of non-metastatic lung cancer patients and these observations were evaluated for metastasis development after follow-up of median 29.2 months. After follow-up, ∼40% of these patients developed metastasis. The average age of non-metastatic patients which later developed metastasis, was found to be lower than the patients continued to be non-metastatic. These patients also showed higher levels of IL-8 and MMP-9 than the patients which did not develop metastasis. Analysis of Receiver Operating Characteristic Curves, Youden's Index and positive likelihood ratio values showed better diagnostic ability for IL-8 and MMP-9, which improved when both markers used together. Moreover, patients with age ≤60 years showed higher prognostic ability of metastasis development, which was significantly enhanced when patient age was analysed with IL-8. These results suggest potential of serum analytes (IL-8, MMP-9) and/or patient age in prognosticating the metastasis development in non-metastatic patients.

Development and clinical application of deep learning model for lung nodules screening on CT images

Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who evaluate a large LDCT screening images face enormous challenges, including mechanical repetition and boring work, the easy omission of small nodules, lack of consistent criteria, etc. It requires an efficient method for helping radiologists improve nodule detection accuracy with efficiency and cost-effectiveness. Many novel deep neural network-based systems have demonstrated the potential for use in the proposed technique to detect lung nodules. However, the effectiveness of clinical practice has not been fully recognized or proven. Therefore, the aim of this study to develop and assess a deep learning (DL) algorithm in identifying pulmonary nodules (PNs) on LDCT and investigate the prevalence of the PNs in China. Radiologists and algorithm performance were assessed using the FROC score, ROC-AUC, and average time consumption. Agreement between the reference standard and the DL algorithm in detecting positive nodules was assessed per-study by Bland-Altman analysis. The Lung Nodule Analysis (LUNA) public database was used as the external test. The prevalence of NCPNs was investigated as well as other detailed information regarding the number of pulmonary nodules, their location, and characteristics, as interpreted by two radiologists.

[Clinical-radiological-pathological Characteristics of 297 Cases of Surgical Pathology Confirmed Benign Pulmonary Lesions in Which Malignancy Could Not Be Excluded in Preoperative Assessment: A Retrospective Cohort Analysis in a Single Chinese Hospital]

背景与目的

随着癌症早筛意识的提高，低剂量计算机断层扫描(low-dose computed tomography, LDCT)用于肺癌筛查在中国广泛开展。尽管有部分胸部LDCT筛查所见的肺部病灶是肿瘤病灶，但大多数的肺部结节是良性病变。如何有效的对肺部病灶进行术前鉴别，如何降低部分可避免手术的良性疾病的手术切除比例，是需要关注的问题。

方法

本研究纳入2017年1月1日-2018年12月31日期间北京协和医院诊治的，术前考虑肺部恶性病变不能除外，经手术病理确认为良性病变的患者，回顾性分析患者临床信息。

结果

297例患者纳入本研究，占我院肺部病灶行肺部手术治疗患者的9.8%。197例(66.3%)患者因体检行LDCT筛查发现肺部病灶。肺部病变胸部CT影像学评估情况，可评估的323个病灶，平均长径为(17.9±12.1)mm，直径≥8 mm的占91.0%，实性最多见(212/323, 65.6%)，此类肺部病灶可有毛刺征(71/323, 22.0%)、分叶征(94/323, 29.1%)、胸膜牵拉征(81/323, 25.1%)、血管集束征(130/323, 40.2%)、空泡征(23/323, 7.1%)等，提示恶性病变的影像学特征。292例(98.3%)行电视辅助胸腔镜手术(video-assisted thoracoscopic surgery, VATS)，232例(78.1%)患者行肺楔形切除术，13例(4.4%)行肺段切除术，51例(17.2%)患者行肺叶切除术。4例(1.3%)患者出现手术并发症。术后病理类型前3位的是感染性疾病98例(33.0%)、炎性结节96例(32.3%)和错构瘤64例(21.5%)。

结论

因术前不能排除恶性而行手术切除的肺部良性病灶，影像学表现以实性病灶多见，但多具有提示恶性的影像学特征。VATS可作为一种明确病原病理的重要活检方式。此类病灶病理结果以感染性疾病和炎性结节最为常见，错构瘤第三。

Identification and validation of novel DNA methylation markers for early diagnosis of lung adenocarcinoma

Lung cancer has the highest mortality of all cancers worldwide. Epigenetic alterations have emerged as potential biomarkers for early diagnosis of various cancer tissue types. To identify methylation markers for early diagnosis of lung adenocarcinoma, we aimed to integrate genome‐wide DNA methylation and gene expression data from The Cancer Genome Atlas. To this end, we first examined the global DNA methylation pattern of lung adenocarcinoma and investigated the relationship between DNA methylation subtypes and clinical features. We then extracted differentially methylated and expressed genes, and adopted feature selection techniques to determine the final methylation markers. The performance of the markers in predicting lung adenocarcinoma was evaluated on three independent datasets from Gene Expression Omnibus. Protein levels of marker genes were validated by immunohistochemistry, and their biological function was further verified in vivo. We identified three novel methylation markers in lung adenocarcinoma including cg08032924, cg14823851, and cg19161124, mapping to CMTM2, TBX4, and DPP6, respectively. Validating these results on three independent datasets indicated that the three markers can achieve extremely high sensitivity and specificity in distinguishing lung adenocarcinoma from normal samples. Immunohistochemistry quantification results confirmed that markers are weakly expressed in human lung adenocarcinoma, and CMTM2 decreased tumor growth of mouse Lewis lung carcinoma in vivo. Overall, our study identified three novel methylation markers in lung adenocarcinoma which may contribute toward an improved diagnosis potentially leading to a better outcome for patients with lung adenocarcinoma.

Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer

BACKGROUND

This study was designed to detect patients with early NSCLC with tentatively using the stem signatures associated autoantibodies (AAbs), and to evaluate its latent values in the early diagnosis and precise prognosis prediction.

METHODS

The serum concentrations of selective antibodies were quantitated by enzyme-linked immunosorbent assay (ELISA), and a total of 458 cases were enrolled (training set = 401; validation set = 57). TCGA databases were used to analyze the distinct expressions and prognostic values of related genes. The optimal cut-off values were 11.60 U/ml for P53, 4.90 U/ml for MAGEA1, 3.85 U/ml for SOX2, and 7.05U/ml for PGP9.5.

RESULTS

We found that the stem signatures associated antibodies of MAGEA1, PGP9.5, SOX2, and TP53 exhibited high expressions in NSCLC, negatively correlating with the overall survival (OS) (P < 0.05). In the test groups, the diagnosis sensitivity of P53, PGP9.5, SOX2, and MAGEA1 reached to 21.5%, 39.0%, 50.3%, and 35.0%, respectively, and the specificity reached to 98.7%, 99.4%, 92.2%, and 97.4%. The four candidates' panel gave a sensitivity of 71.8% with a specificity of 89%. In the validation group, the detection of the four antibodies in early diagnosis of NSCLC also exhibited high specificity and sensitivity, further consolidating their potential application.

CONCLUSIONS

The detection regarding stem signatures associated antibodies could be used as effective tools in early NSCLC diagnosis, but not for localized screening of cancers, and their abnormal expression was in accordance with poorer survival.

Psychosocial consequences of false positives in the Danish Lung Cancer CT Screening Trial: a nested matched cohort study

OBJECTIVES

Lung cancer CT screening can reduce lung cancer mortality, but high false-positive rates may cause adverse psychosocial consequences. The aim was to analyse the psychosocial consequences of false-positive lung cancer CT screening using the lung cancer screening-specific questionnaire, Consequences of Screening in Lung Cancer (COS-LC).

DESIGN AND SETTING

This study was a matched cohort study, nested in the randomised Danish Lung Cancer Screening Trial (DLCST).

PARTICIPANTS

Our study included all 130 participants in the DLCST with positive CT results in screening rounds 2-5, who had completed the COS-LC questionnaire. Participants were split into a true-positive and a false-positive group and were then matched 1:2 with a control group (n=248) on sex, age (±3 years) and the time of screening for the positive CT groups or clinic visit for the control group. The true positives and false positives were also matched 1:2 with participants with negative CT screening results (n=252).

PRIMARY OUTCOMES

Primary outcomes were psychosocial consequences measured at five time points.

RESULTS

False positives experienced significantly more negative psychosocial consequences in seven outcomes at 1 week and in three outcomes at 1 month compared with the control group and the true-negative group (mean ∆ score >0 and p<0.001). True positives experienced significantly more negative psychosocial consequences in one outcome at 1 week (mean ∆ score 2.86 (95% CI 1.01 to 4.70), p=0.0024) and in five outcomes at 1 month (mean ∆ score >0 and p<0.004) compared with the true-negative group and the control group. No long-term psychosocial consequences were identified either in false positives or true positives.

CONCLUSIONS

Receiving a false-positive result in lung cancer screening was associated with negative short-term psychosocial consequences. These findings contribute to the evidence on harms of screening and should be taken into account when considering implementation of lung cancer screening programmes.

TRIAL REGISTRATION NUMBER

NCT00496977.

The diagnostic value of a seven-autoantibody panel and a nomogram with a scoring table for predicting the risk of non-small-cell lung cancer

The early detection of non-small-cell lung cancer (NSCLC) remains a common concern. The aim of our study was to validate the diagnostic value of a seven-autoantibody (7-AAB) panel compared with radiological diagnosis for NSCLC. We constructed a nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC. We prospectively enrolled 268 patients who presented with radiological lesions and underwent both the 7-AAB panel test and pathological diagnosis by surgical resection. A comparison between the 7-AAB panel and radiological diagnosis was performed. A nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC were constructed and internally validated. The 7-AAB panel test had a specificity of 90.2% and a positive predictive value (PPV) of 92.7%, which were significantly higher than those of the radiological diagnosis. The 7-AAB panel also showed a preferable sensitivity in patients with early-stage disease. Seven factors, including the 7-AAB panel results, were integrated into the nomogram. For more convenient application, we formulated a scoring table based on the nomogram. The area under the receiver operating characteristic curve was 0.840 and 0.860 in the training group and validation group, respectively, which was higher than that using the 7-AAB panel or radiological diagnosis alone. This study reveals that our 7-AAB panel has clinical value in the diagnosis of NSCLC. The utility of our nomogram and the scoring table indicated that they have the potential to assist clinicians in avoiding unnecessary treatment or needless follow-up.

Projected Reductions in Absolute Cancer-Related Deaths from Diagnosing Cancers Before Metastasis, 2006-2015

BACKGROUND

New technologies are being developed for early detection of multiple types of cancer simultaneously. To quantify the potential benefit, we estimated reductions in absolute cancer-related deaths that could occur if cancers diagnosed after metastasis (stage IV) were instead diagnosed at earlier stages.

METHODS

We obtained stage-specific incidence and survival data from the Surveillance, Epidemiology, and End Results Program for 17 cancer types for all persons diagnosed ages 50 to 79 years in 18 geographic regions between 2006 and 2015. For a hypothetical cohort of 100,000 persons, we estimated cancer-related deaths under assumptions that cancers diagnosed at stage IV were diagnosed at earlier stages.

RESULTS

Stage IV cancers represented 18% of all estimated diagnoses but 48% of all estimated cancer-related deaths within 5 years. Assuming all stage IV cancers were diagnosed at stage III, 51 fewer cancer-related deaths would be expected per 100,000, a reduction of 15% of all cancer-related deaths. Assuming one third of metastatic cancers were diagnosed at stage III, one third diagnosed at stage II, and one third diagnosed at stage I, 81 fewer cancer-related deaths would be expected per 100,000, a reduction of 24% of all cancer-related deaths, corresponding to a reduction in all-cause mortality comparable in magnitude to eliminating deaths due to cerebrovascular disease.

CONCLUSIONS

Detection of multiple cancer types earlier than stage IV could reduce at least 15% of cancer-related deaths within 5 years, affecting not only cancer-specific but all-cause mortality.

IMPACT

Detecting cancer before stage IV, including modest shifts to stage III, could offer substantial population benefit.

Sarcoma Surveillance: A Review of Current Evidence and Guidelines

After initial treatment of sarcoma, disease progression may occur in the form of local recurrence, pulmonary metastases, or extrapulmonary metastases. As such, surveillance is an important aspect of management, but no universally accepted practice standards are found. In the absence of strong evidence, and to allow for individualized care, existing guidelines contain flexibility in terms of both the frequency and modality of surveillance. In general, they agree that follow-up should be more intense in the early years after treatment, especially for high-grade sarcomas, and continue for at least 10 years. For local recurrence, data suggest that physical examination is usually sufficient for monitoring; in addition, some guidelines endorse imaging routinely, whereas others only as clinically indicated. For pulmonary metastasis, either radiograph or CT is recommended, with the latter having theoretical advantages but no proven survival benefit to date. Extrapulmonary metastases are rare in most sarcoma types, so the literature only supports extrapulmonary surveillance for certain diagnoses. This topic is complicated by the diversity of sarcomas, the limited evidence, and the indefinite, often conflicting recommendations; therefore, it is critical for providers to understand the existing research and guidelines to determine optimal surveillance strategies for their patients.

Measuring serum human epididymis secretory protein autoantibody as an early biomarker of lung cancer

BACKGROUND

Lung cancer (LC) is one of the most common types of malignant tumors and is the most prominent cause of tumor-related death worldwide. LC is a heterogeneous disease caused by somatic cell mutations and dysregulation in several signaling pathways. Understanding these pathways provides the basis for detecting LC. LC screening and diagnosis in current clinic still rely on computed tomography (CT), but its high false positive rates and cost may prevent it from being a routine screening method. Therefore, the discovery of new non-invasive and more valuable biomarkers may present an improved diagnostic approach for LC, and potentially provide more useful information for the prognosis and treatment of LC in patients. This study investigated the potential of detecting serum autoantibodies produced against human epididymis secretory protein 4 (HE4) for LC diagnosis in high-risk groups.

METHODS

Serum samples from 61 patients with LC were included in this study, and another 53 serum samples from healthy donors or benign lung diseases (BLD) patients were collected as the control group. The samples were analyzed with enzyme-linked immunosorbent assays (ELISA).

RESULTS

ELISA results showed significantly higher levels of serum autoantibodies against HE4 in samples from LC patients compared to the control group (P<0.001). Analysis of HE4 autoantibodies showed a receiver operating characteristic (ROC) curve indicating 67.21% sensitivity, 96.23% specificity, and an area under the curve (AUC) of 0.848. Levels of HE4 autoantibodies can discriminate early-stage LC patients from the control group with a 54.76% sensitivity.

CONCLUSIONS

Detecting serum HE4 autoantibody levels may be a potential biomarker in high-risk groups of LC. We present a new method for the diagnosis of LC in the clinic.

Exploring Novel Technologies in Lung Cancer Diagnosis: Do We Have Room for Improvement?

Lung cancer remains the leading cause of cancer-related death worldwide. Preventive strategies, mainly smoking cessation have a big impact on the reduction of lung cancer-related mortality. Screening with low dose computed tomography (LDCT) has proven to be beneficial in reducing the mortality related to lung cancer mainly based on early detection of cancer and timely initiation of treatment. Despite its beneficial effects, guideline-directed LDCT screening could lead to high false positive results, subjecting patients to harmful radiation, increase cost of healthcare and induce anxiety amongst the patients. Thus, it is imperative to look beyond the prevailing modalities of lung cancer screening and diagnosis to achieve better yield and mitigate the existent drawbacks.

Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology

Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. Early detection of lung cancer is an important opportunity for decreasing mortality. Data support using low-dose computed tomography (LDCT) of the chest to screen select patients who are at high risk for lung cancer. Lung screening is covered under the Affordable Care Act for individuals with high-risk factors. The Centers for Medicare & Medicaid Services (CMS) covers annual screening LDCT for appropriate Medicare beneficiaries at high risk for lung cancer if they also receive counseling and participate in shared decision-making before screening. The complete version of the NCCN Guidelines for Lung Cancer Screening provides recommendations for initial and subsequent LDCT screening and provides more detail about LDCT screening. This manuscript focuses on identifying patients at high risk for lung cancer who are candidates for LDCT of the chest and on evaluating initial screening findings.

False-Positive Results in a Population-Based Colorectal Screening Program: Cumulative Risk from 2000 to 2017 with Biennial Screening

BACKGROUND

The aim of this study was to estimate the cumulative risk of a false-positive (FP) result in a fecal occult blood test (FOBT) through 7 screening rounds and to identify its associated factors in a population-based colorectal cancer screening program.

METHODS

Retrospective cohort study, which included participants ages 50 to 69 years of a colorectal cancer screening program in Catalonia, Spain. During this period, 2 FOBTs were used (guaiac and immunochemical). A discrete-time survival model was performed to identify risk factors of receiving a positive FOBT with no high-risk adenoma or colorectal cancer in the follow-up colonoscopy. We estimated the probability of having at least 1 FP over 7 screening rounds.

RESULTS

During the period of 2000 to 2017, the cumulative FP risk was 16.3% (IC_95%: 14.6%-18.3%), adjusted by age, sex, and type of test. The median number of screens was 2. Participants who began screening at age 50 years had a 7.3% [95% confidence interval (CI), 6.35-8.51] and a 12.4% (95% CI, 11.00-13.94) probability of an FP with 4 screening rounds of guaiac-based test and immunochemical test, respectively. Age, the fecal immunochemical test, first screening, and number of personal screens were factors associated with an FP result among screenees.

CONCLUSIONS

The cumulative risk of an FP in colorectal screening using FOBT seems acceptable as the colonoscopy, with its high accuracy, lengthens the time until additional colorectal screening is required, while complication rates remain low.

IMPACT

It is useful to determine the cumulative FP risk in cancer screening for both advising individuals and for health resources planning.

Recommendations for lung cancer screening in Southern Africa

Lung cancer remains the leading cause of cancer-related deaths in southern Africa. Early trials of chest radiograph-based screening in males at high risk for lung cancer found no mortality benefit of a radiograph alone, or a radiograph plus sputum cytology screening strategy. Large prospective studies, including the National Lung Screening Trial, have shown an all-cause mortality benefit when low-dose computed tomography (LDCT) was used as a screening modality in patients that are at high risk of developing lung cancer. The South African Thoracic Society, based on these findings, and those from several international guidelines, recommend that annual LDCT should be offered to patients between 55-74 years of age who are current or former smokers (having quit within the preceding 15 years), with at least a 30-pack year smoking history and with no history of lung cancer. Patients should be in general good health, fit for surgery, and willing to undergo further investigations if deemed necessary. Given the high local prevalence of tuberculosis (TB) infection and post-TB lung disease, which can radiographically mimic lung cancer, a conservative threshold (nodule size ≥6 mm) should be used to determine whether the baseline LDCT screen is positive (thus nodules <6 mm require no action until the next annual screen). If a non-calcified, solid or partly solid nodule is ≥6 mm, but <10 mm with no malignant features (e.g., distinct spiculated margins), the LDCT should be repeated in 6 months. If a solid nodule or the largest component of a non-solid nodule is ≥10 or ≥6 mm and enlarging or with additional malignant features present, definitive action to exclude lung cancer is warranted. Patients should be screened annually until 15 years have elapsed from date of smoking cessation, they turn 80, become unfit for a curative operation or significant changes are observed.

Epigenome-Wide Association Analysis of Differentially Methylated Signals in Blood Samples of Patients with Non-Small-Cell Lung Cancer

Lung cancer is a common form of cancer and the leading cause of cancer-related deaths worldwide. Early diagnosis using noninvasive biomarkers may play an important role in increasing the survival rate of patients with lung cancer. Biomarkers of DNA methylation in blood samples may improve the early diagnosis of lung cancer. Here, we used peripheral blood samples obtained from 150 patients diagnosed with non-small-cell lung cancer (NSCLC) and 150 healthy controls. The latter were selected by frequency matching with the 150 patients with NSCLC, based on age, sex, and smoking status. Genome-wide methylation profiles were obtained using a MethylationEPIC BeadChip Kit, which covers the 850k bp cytosine–phosphate–guanine site. This analysis showed two significant differentially methylated changes (cg12169243 [DPH6] and cg25429010 [IMP3]) associated with NSCLC in current smokers, six changes (cg09245319, cg17183999 [USP7], cg06366994 [CPE], cg24992236 [MEG9], cg22144719, and cg22448179 [epidermal growth factor receptor]) associated with epidermal growth factor receptor mutation in patients with adenocarcinoma, and four changes (cg25021476 [RSL24D1], cg04989085 [FAM113B], cg20905681 [CKAP4], and cg26379694) associated with advanced-stage NSCLC compared with stage I NSCLC. The validation of these DNA methylation changes and further research on the related genes may help develop easily accessible biomarkers for the early diagnosis or prognosis of NSCLC.

Autoantibodies as diagnostic biomarkers for lung cancer: A systematic review

Lung cancer (LC) accounts for the largest number of tumor-related deaths worldwide. As the overall 5-year survival rate of LC is associated with its stages at detection, development of a cost-effective and noninvasive cancer screening method is necessary. We conducted a systematic review to evaluate the diagnostic values of single and panel tumor-associated autoantibodies (TAAbs) in patients with LC. This review included 52 articles with 64 single TAAbs and 19 with 20 panels of TAAbs. Enzyme-linked immunosorbent assays (ELISA) were the most common detection method. The sensitivities of single TAAbs for all stages of LC ranged from 3.1% to 92.9% (mean: 45.2%, median: 37.1%), specificities from 60.6% to 100% (mean: 88.1%, median: 94.9%), and AUCs from 0.416 to 0.990 (mean: 0.764, median: 0.785). The single TAAb with the most significant diagnostic value was the autoantibody against human epididymis secretory protein (HE4) with the maximum sensitivity 91% for NSCLC. The sensitivities of the panel of TAAbs ranged from 30% to 94.8% (mean: 76.7%, median: 82%), specificities from 73% to 100% (mean: 86.8%, median: 89.0%), and AUCs from 0.630 to 0.982 (mean: 0.821, median: 0.820), and the most significant AUC value in a panel (M13 Phage 908, 3148, 1011, 3052, 1000) was 0.982. The single TAAb with the most significant diagnostic calue for early stage LC, was the autoantibody against Wilms tumor protein 1 (WT1) with the maximum sensitivity of 90.3% for NSCLC and its sensitivity and specificity in a panel (T7 Phage 72, 91, 96, 252, 286, 290) were both above 90.0%. Single or TAAbs panels may be useful biomarkers for detecting LC patients at all stages or an early-stage in high-risk populations or health people, but the TAAbs panels showed higher detection performance than single TAAbs. The diagnostic value of the panel of six TAAbs, which is higher than the panel of seven TAAbs, may be used as potential biomarkers for the early detection of LC and can probably be used in combination with low-dose CT in the clinic.

Diagnostic value of multiple tumor-associated autoantibodies in lung cancer

Background

Lung cancer is the leading cause of cancer-related deaths. Survival rate improves significantly with early detection of lung cancer. Effective methods of early detection can reduce lung cancer mortality to a large extent as well as benefit the whole public health. The diagnostic value of one single marker is relatively low. Combined autoantibodies (AABs) can improve the sensitivity significantly rather than rely on one AAB and serve as good reservoir for early detection of lung cancer.

Patients and methods

We designed three parts in our experiment. In training set we measured the expression levels of AABs in 100 non-small-cell lung cancer (NSCLC) patients and 60 healthy controls by using ELISA detection method. A blinded validation was subsequently performed in 254 NSCLC patients, 125 healthy controls, and 71 nodule patients. A prospective expansion set was performed to evaluate the diagnosis value of AABs combined detection.

Results

Both in training set and validation set, the concentrations of SOX2, GAGE 7, MAGE A1, and P53 in NSCLC group increased prominently when compared to the healthy group (P<0.05). The concentration of GBU4-5 in adenocarcinoma group was higher than in the squamous cell carcinoma (SCC) group (P<0.05); the PGP9.5, which was opposite, in SCC group was higher than in the adenocarcinoma group (P<0.05). The positive rate of each AAB did not show any bias with age, gender, smoking history, and tumor location. Most importantly, different choice of biomarkers led to different detection results.

Conclusion

Our study confirmed the diagnostic value of tumor-associated AABs. They may be useful as latent tumor markers to facilitate the detection of early lung cancer.

A Gene Expression Classifier from Whole Blood Distinguishes Benign from Malignant Lung Nodules Detected by Low-Dose CT

Low-dose CT (LDCT) is widely accepted as the preferred method for detecting pulmonary nodules. However, the determination of whether a nodule is benign or malignant involves either repeated scans or invasive procedures that sample the lung tissue. Noninvasive methods to assess these nodules are needed to reduce unnecessary invasive tests. In this study, we have developed a pulmonary nodule classifier (PNC) using RNA from whole blood collected in RNA-stabilizing PAXgene tubes that addresses this need. Samples were prospectively collected from high-risk and incidental subjects with a positive lung CT scan. A total of 821 samples from 5 clinical sites were analyzed. Malignant samples were predominantly stage 1 by pathologic diagnosis and 97% of the benign samples were confirmed by 4 years of follow-up. A panel of diagnostic biomarkers was selected from a subset of the samples assayed on Illumina microarrays that achieved a ROC-AUC of 0.847 on independent validation. The microarray data were then used to design a biomarker panel of 559 gene probes to be validated on the clinically tested NanoString nCounter platform. RNA from 583 patients was used to assess and refine the NanoString PNC (nPNC), which was then validated on 158 independent samples (ROC-AUC = 0.825). The nPNC outperformed three clinical algorithms in discriminating malignant from benign pulmonary nodules ranging from 6-20 mm using just 41 diagnostic biomarkers. Overall, this platform provides an accurate, noninvasive method for the diagnosis of pulmonary nodules in patients with non-small cell lung cancer. SIGNIFICANCE: These findings describe a minimally invasive and clinically practical pulmonary nodule classifier that has good diagnostic ability at distinguishing benign from malignant pulmonary nodules.

Similarities in Blood Mononuclear Cell Membrane Phospholipid Profiles During Malignancy

Phospholipids (PLs), key elements of cellular membranes, are regulated reciprocally with membrane proteins and can act as sensors for alterations in physiological or pathological states of cells including initiation and development of cancer. On the other hand, peripheral blood mononuclear cells (MNCs) play an important role in antitumor immune response by reacting to cancerous modifications in distant organs. In the current study, we tested the hypothesis that tumor initiation and development are reflected in the alteration pattern of the MNC PL component. We analyzed MNC membrane PL fractions in samples from healthy individuals and from patients with diverse types of cancers to reveal possible alterations induced by malignancy. Compared to healthy controls, the cancer samples demonstrated shifts in several membrane PL profiles. In particular, when analyzing cancer data pooled together, there were significantly higher levels in lysophosphatidylcholine, phosphatidylcholine, and phosphatidylethanolamine fractions, and significantly lower quantities in phosphatidylinositol, phosphatidylserine, and phosphatidic acid fractions in cancer samples compared to controls. The levels of sphingomyelins and diphosphatidylglycerols were relatively unaffected. Most of the differences in PLs were sustained during the analysis of individual cancers such as breast cancer and chronic lymphocytic leukemia. Our findings suggest the presence of a common pattern of changes in MNC PLs during malignancy.

Influence of radiologic expertise in detecting lung tumors on chest radiographs

PURPOSE

To analyze the influence of radiologic expertise in detecting lung tumors on chest radiographs.

MATERIALS AND METHODS

We retrieved posteroanterior chest radiographs and CT examination obtained from 283 patients with solitary primary malignant lung tumors who underwent surgical resection. There were 176 men and 107 women with a mean age of 67.0±9.1 (SD) years (range: 33-88 years). Thirteen first-year post-graduate (PGY-1) trainees and nine pulmonary specialists (three radiologists, three thoracic surgeons, and three pulmonologists) interpreted the chest radiographs. Detection rates among trainees and specialists were compared using Student t test.

RESULTS

The total numbers of detected tumors ranged from 103 (36.4%) to 136 (48.1%) with a mean of 127.9±9.1 (45.2±3.2%) in the trainee group, and 137 (48.4%) to 182 (64.3%) with a mean of 161.6±13.1 (57.1±4.6%) in the specialist group; the intergroup difference was statistically significant (P<0.001). Significant intergroup detectability differences of >10% were noted for tumors in the peripheral zone with (i) ground glass opacity (GGO) ratio ≥10% and <70% and any size, or (ii) GGO ratio <10% and size ≤2cm; and for tumors hidden by the mediastinum, heart, or diaphragm with (i) GGO ratio ≥10% and <30% and size >3cm, or (ii) GGO ratio <10% and size >2cm.

CONCLUSION

Our study demonstrates significant differences in lung tumor detectability on chest radiographs between PGY-1 trainees and pulmonary specialists according to tumor size, extent of GGO, and tumor location.

Circulating microRNA biomarkers for lung cancer detection in Western populations

Lung cancer (LC) is a leading cause of cancer-related death in the Western world. Patients with LC usually have poor prognosis due to the difficulties in detecting tumors at early stages. Multiple studies have shown that circulating miRNAs might be promising biomarkers for early detection of LC. We aimed to provide an overview of published studies on circulating miRNA markers for early detection of LC and to summarize their diagnostic performance in Western populations. A systematic literature search was performed in PubMed and ISI Web of Knowledge to find relevant studies published up to 11 August 2017. Information on study design, population characteristics, miRNA markers, and diagnostic accuracy (including sensitivity, specificity, and AUC) were independently extracted by two reviewers. Overall, 17 studies evaluating 35 circulating miRNA markers and 19 miRNA panels in serum or plasma were included. The median sensitivity (range) and specificity (range) were, respectively, 78.4% (51.7%-100%) and 78.7% (42.9%-93.5%) for individual miRNAs, and 83.0% (64.0%-100%) and 84.9% (71.0%-100%) for miRNA panels. Most studies incorporated individual miRNA markers as panels (with 2-34 markers), with multiple miRNA-based panels generally outperforming individual markers. Two promising miRNA panels were discovered and verified in prospective cohorts. Of note, both studies exclusively applied miRNA ratios when building up panels. In conclusion, circulating miRNAs may bear potential for noninvasive LC screening, but large studies conducted in screening or longitudinal settings are needed to validate the promising results and optimize the marker panels.

Analysis of risk factors for stage I lung adenocarcinoma using low-dose high-resolution computed tomography

Risk factors for stage I lung adenocarcinoma were analyzed using low-dose high-resolution computed tomography (CT). The patients were divided into case group (stage I lung adenocarcinoma patients) and control group (benign pulmonary nodules patients). All patients were subjected to low-dose high-resolution CT. Multiple linear regression was performed to analyze the CT imaging features of the two groups. Stage I lung adenocarcinoma patients were significantly associated with nodular site (X3, upper left lobe) [95% CI (1.796, 54.695), p=0.008], nodule type (X4) (p<0.001), nodule size (X5) [95% CI (0.614, 0.803), p<0.001], spicule sign (X7) [95% CI (0.029, 0.580), p=0.008], lobulation sign (X8) [95% CI (0.048, 0.673), p=0.011]. The stepwise regression equation is: Logistic (p) =-12.009 + 2.294X3 - 0.327X4 - 0.354X5 - 2.042X7 - 1.713X8. Risk factors of low-dose and high-resolution CT imaging for patients with stage I lung adenocarcinoma are nodular site (upper left lobe), nodule type, nodule size, spicule sign, and lobulation sign.

Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults

Objective

Four commonly used clinical models for predicting the probability of malignancy in pulmonary nodules were compared. While three of the models (Mayo Clinic, Veterans Association [VA], and Brock University) are based on clinical and computed tomography (CT) characteristics, one model (Herder) additionally includes the ¹⁸F-fluorodeoxyglucose (FDG) uptake value among the positron emission tomography (PET) characteristics. This study aimed to compare the predictive power of these four models in the context of a population drawn from a single center in an endemic area for tuberculosis in Korea.

Methods

A retrospective analysis of 242 pathologically confirmed nodules (4–30 mm in diameter) in 242 patients from January 2015 to December 2015 was performed. The area under the receiver operating characteristic curve (AUC) was used to assess the predictive performance with respect to malignancy.

Results

Of 242 nodules, 187 (77.2%) were malignant and 55 (22.8%) were benign, with tuberculosis granuloma being the most common type of benign nodule (23/55). PET was performed for 227 nodules (93.8%). The Mayo, VA, and Brock models showed similar predictive performance for malignant nodules (AUC: 0.6145, 0.6042 and 0.6820, respectively). The performance of the Herder model (AUC: 0.5567) was not significantly different from that of the Mayo (vs. Herder, p = 0.576) or VA models (vs. Herder, p = 0.999), and there were no differences among the three models in determining the probability of malignancy of pulmonary nodules. However, compared with the Brock model, the Herder model showed a significantly lower ability to predict malignancy (adjusted p = 0.0132).

Conclusions

In our study, the Herder model including the ¹⁸FDG uptake value did not perform better than the other models in predicting malignant nodules, suggesting the limited utility of adding PET/CT data to models predicting malignancy in populations within endemic areas for benign inflammatory nodules, such as tuberculosis.

Optimizing Live Kidney Donor Workup: A Decision Analysis Approach

BACKGROUND

Screening potential live kidney donors is an intense process for both candidates and the healthcare system. It is conventionally implemented using a standard generic protocol. Efficiencies in this process could potentially be achieved using personalized protocols that are optimized for a given candidate. Aim: To create personalized protocols (by age, sex, and paired exchange status) and evaluate them relative to the standard generic protocol.

METHODS

Two personalized protocols were created. One sequenced tests according to probability (high to low) of excluding a given candidate. The other sequenced tests according to the expected cost (low to high) per exclusion. Test costs and exclusion probabilities were extracted predominantly from Australian sources. These were integrated into a decision analysis incorporating Markov processes. This estimated the expected financial cost and expected number of tests performed to exclude an ineligible candidate in the standard generic and personalized protocols.

RESULTS

The standard generic protocol consistently ranked poorest in terms of expected costs and expected tests per exclusion across all ages, sexes, and paired exchange status. Compared with the most efficient personalized protocol, the standard generic protocol was on average A$1767.49 more expensive and required 3.53 more tests.

CONCLUSIONS

Personalized protocols enhance the ability of a kidney transplant unit to effectively exclude live kidney donor candidates more quickly and cost effectively compared with the conventional standard generic protocol.

Liquid biopsy for early stage lung cancer

Liquid biopsy, which analyzes biological fluids especially blood specimen to detect and quantify circulating cancer biomarkers, have been rapidly introduced and represents a promising potency in clinical practice of lung cancer diagnosis and prognosis. Unlike conventional tissue biopsy, liquid biopsy is non-invasive, safe, simple in procedure, and is not influenced by manipulators' skills. Notably, some circulating cancer biomarkers are already detectable in disease with low-burden, making liquid biopsy feasible in detecting early stage lung cancer. In this review, we described a landscape of different liquid biopsy methods by highlighting the rationale and advantages, accessing the value of various circulating biomarkers and discussing their possible future development in the detection of early lung cancer.

Presenters or Patients? A Crucial Distinction in Individual Health Assessments

Individual health assessments (IHAs) for asymptomatic individuals provide a challenge to traditional distinctions between patient care and non-medical practice. They may involve undue radiation exposure, lead to false positives, and involve high out-of-pocket costs for recipients. A recent paper (Journal of the American College of Radiology 13(12): 1447-1457.e1, 2016) has criticised the use of IHAs and argued that recipients should be classified as 'presenters', not 'patients', to distinguish it from regular medical care. I critique this classificatory move, on two grounds: one, it is conceptually suspect. Two, it obviates the medical ethics framework for IHAs, potentially exposing recipients of IHAs to lower standards of oversight and protection. Responsible regulation of IHAs will be easier to ethically justify if those seeking IHAs are considered patients and not merely presenters.