The Future of Lung Cancer Screening: Current Challenges and Research Priorities

A blood test measuring DNA methylation of BCAT1 and IKZF1 for detection of lung adenocarcinoma

BACKGROUND

Colorectal (CRC) and lung adenocarcinoma share many genetic and pathological similarities. A circulating tumor DNA (ctDNA) test for CRC may also be useful for detection of lung adenocarcinoma. This study determined if a methylated BCAT1/IKZF1 ctDNA test for CRC can be used for detection of lung adenocarcinoma.

PATIENTS AND METHODS

Circulating cell free DNA (ccfDNA) was extracted from plasma collected prospectively from healthy controls, patients in remission from CRC, patients with lung adenocarcinoma, and patients with isolated metastatic CRC lung lesions. Plasma ccfDNA was bisulfite converted and assessed for methylated BCAT1/IKZF1 by quantitative real-time PCR. Comparisons between the different patient groups for a positive ctDNA test (BCAT1 and/or IKZF1) and ctDNA levels (% of total ccfDNA), as well as any associations with clinicopathological and demographic features, were assessed.

RESULTS

Methylated BCAT1/IKZF1 ctDNA was detected in 18/39 (46.2 %) patients with lung adenocarcinoma, which was significantly (p < 0.001) higher compared to healthy controls (49/606; 8.1 %) and patients in remission from CRC (22/171, 12.9 %). Patients with stage III/IV lung adenocarcinoma had higher BCAT1/IKZF1 ctDNA positivity compared to stage I/II cases (68.2 % vs 17.7 %, p < 0.01), where a significantly higher proportion tested positive for methylated IKZF1 ctDNA alone (54.6 % vs 5.9 %, p < 0.001). There was no difference in BCAT1/IKZF1 ctDNA test positivity between patients with stage IV primary lung adenocarcinoma (n = 17) compared to lung-metastasising CRC cases (n = 17; 70.6 % v 64.3 %).

CONCLUSION

A ctDNA test measuring methylated BCAT1/IKZF1 can sensitively detect lung adenocarcinoma and may be a promising aid for detection of advanced disease.

CLINICAL TRIAL REGISTRATIONS

Australian and New Zealand Clinical Trials Registry, www.anzctr.org.au, ACTRN12616001138471, ACTRN12611000318987.

Nontraumatic intraoperative pulmonary nodule localization with laser guide stamping in a hybrid operating room

Lung nodule localization using conventional image-guided video-assisted thoracoscopic surgery involves lung puncture, which increases the risk of needle-related complications. We aimed to evaluate the feasibility and safety of a single-stage non-invasive laser-guided stamping localization technique followed by resection under general anesthesia in a hybrid operating room. We retrospectively reviewed consecutive patients who underwent thoracoscopic surgery for small pulmonary nodules using laser-guided dye-stamping localization methods in a hybrid operating room between June 2023 and October 2023. During the study period, 18 patients with 20 lesions underwent single-stage intraoperative image-guided stamping video-assisted thoracoscopic surgery in the hybrid operating room. The median size of the nodules was 7.4 mm (interquartile range [IQR] 5.7-9.8 mm), and median distance from the pleural surface was 9.8 mm (IQR 7.7-14.6 mm). The median localization time was 26 min (IQR 23-34 min), whereas median operation time was 69 min (IQR 62-87 min). The total median operating room time was 146 min (IQR 136-157 min). Twelve patients underwent less than two cone-beam computed tomography scans, while 6 underwent more than two scans. The total median dose area product, including cone-beam computed tomography scans, was 5731.4 uGym2. No localization-related complications were observed, and the postoperative length of stay was 1 day (IQR 1-2 days). The single-stage image-guided pleural stamping technique for localizing small pulmonary nodules in a hybrid operating room is feasible and safe. Future research with larger cohorts is required to further explore the benefits of this workflow.

Investigating socioeconomic disparities in lung cancer diagnosis, treatment and mortality: an Italian cohort study

BACKGROUND

Lung cancer is one of the most lethal cancers worldwide and patient clinical outcomes seem influenced by their socioeconomic position (SEP). Since little has been investigated on this topic in the Italian context, our aim was to investigate the role of SEP in the care pathway of lung cancer patients in terms of diagnosis, treatment and mortality.

METHODS

This observational retrospective cohort study included patients discharged in the Lazio Region with a lung cancer diagnosis between 2014 and 2017. In the main analysis, educational level was used as SEP measure. Multivariate models, adjusted for demographic and clinical variables, were applied to evaluate the association between SEP and study outcomes, stratified for metastatic (M) and non-metastatic (NM) cancer. We defined a diagnosis as 'delayed' when patients received their initial cancer diagnosis after an emergency department admission. Access to advanced lung cancer treatments (high-cost, novel and innovative treatments) and mortality were investigated within the 24-month period post-diagnosis. Moreover, two additional indicators of SEP were examined in the sensitivity analysis: one focusing on area deprivation and the other on income-based exemption.

RESULTS

A total of 13,251 patients were identified (37.3% with metastasis). The majority were males (> 60%) and over half were older than 70 years. The distribution of SEP levels among patients was as follow: 31% low, 29% medium-low, 32% medium-high and 7% high. As SEP increased, the risks of receiving a delayed diagnosis ((high vs low: M: OR = 0.29 (0.23-0.38), NM: OR = 0.20 (0.16-0.25)) and of mortality ((high vs low M: OR = 0.77 (0.68-0.88) and NM: 0.61 (0.54-0.69)) decreased. Access to advanced lung cancer treatments increased in accordance with SEP only in the M cohort (high vs low: M: OR = 1.57 (1.18-2.09)). The primary findings were corroborated by sensitivity analysis.

CONCLUSIONS

Our study highlighted the need of public health preventive and educational programs in Italy, a country where the care pathway of lung cancer patients, especially in terms of diagnosis and mortality, appears to be negatively affected by SEP level.

Digital Interventions to Support Lung Cancer Screening: A Systematic Review

INTRODUCTION

Lung cancer remains a leading cause of cancer-related deaths globally. Lung cancer screening (LCS) with low-dose computed tomography (LDCT) can reduce lung cancer mortality, but its adoption in the U.S. has been limited. Digital interventions have the potential to improve uptake of LCS. This systematic review aims to summarize the evidence for the effectiveness of digital interventions in promoting LCS.

METHODS

A systematic search of three electronic databases (PubMed, Embase, and Medline) was conducted to identify studies published between January 2014 and May 2023. Studies were reviewed and abstracted between February 2023 and July 2023. Outcomes related to knowledge, decision-making and screening were measured. Study quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools.

RESULTS

Of 1,979 screened articles, 30 studies were included in this review. Digital interventions evaluated included decision aids (n=20), electronic health record (EHR)-based interventions (n=7), social media campaigns and mobile applications (n=3). Decision aids were the most commonly studied digital interventions, with most studies showing improved knowledge (13/13) and reduced decisional conflict (7/9) but most did not show a substantial change in screening use. Fewer studies tested clinician-facing or multi-level interventions.

DISCUSSION

Digital interventions, particularly decision aids, have shown promise in improving knowledge and the quality of decision-making around LCS. However, few interventions have been shown to substantially alter screening behavior and few clinician-facing or multi-level interventions have been rigorously tested. Further research is needed to develop effective tools for engaging patients in LCS, to compare the efficacy of different interventions, and evaluate implementation strategies in diverse healthcare settings.

Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities

Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.

Assessing, updating and utilising primary care smoking records for lung cancer screening

BACKGROUND

Lung cancer screening with low-dose computed tomography for high-risk populations is being implemented in the UK. However, inclusive identification and invitation of the high-risk population is a major challenge for equitable lung screening implementation. Primary care electronic health records (EHRs) can be used to identify lung screening-eligible individuals based on age and smoking history, but the quality of EHR smoking data is limited. This study piloted a novel strategy for ascertaining smoking status in primary care and tested EHR search combinations to identify those potentially eligible for lung cancer screening.

METHODS

Seven primary care General Practices in South Wales, UK were included. Practice-level data on missing tobacco codes in EHRs were obtained. To update patient EHRs with no tobacco code, we developed and tested an algorithm that sent a text message request to patients via their GP practice to update their smoking status. The patient's response automatically updated their EHR with the relevant tobacco code. Four search strategies using different combinations of tobacco codes for the age range 55-74+ 364 were tested to estimate the likely impact on the potential lung screening-eligible population in Wales. Search strategies included: BROAD (wide range of ever smoking codes); VOLUME (wide range of ever-smoking codes excluding "trivial" former smoking); FOCUSED (cigarette-related tobacco codes only), and RECENT (current smoking within the last 20 years).

RESULTS

Tobacco codes were not recorded for 3.3% of patients (n = 724/21,956). Of those with no tobacco code and a validated mobile telephone number (n = 333), 55% (n = 183) responded via text message with their smoking status. Of the 183 patients who responded, 43.2% (n = 79) had a history of smoking and were potentially eligible for lung cancer screening. Applying the BROAD search strategy was projected to result in an additional 148,522 patients eligible to receive an invitation for lung cancer screening when compared to the RECENT strategy.

CONCLUSION

An automated text message system could be used to improve the completeness of primary care EHR smoking data in preparation for rolling out a national lung cancer screening programme. Varying the search strategy for tobacco codes may have profound implications for the size of the population eligible for lung-screening invitation.

ERS International Congress 2022: highlights from the Thoracic Oncology Assembly

Thoracic malignancies are associated with a substantial public health burden. Lung cancer is the leading cause of cancer-related mortality worldwide, with significant impact on patients' quality of life. Following 2 years of virtual European Respiratory Society (ERS) Congresses due to the COVID-19 pandemic, the 2022 hybrid ERS Congress in Barcelona, Spain allowed peers from all over the world to meet again and present their work. Thoracic oncology experts presented best practices and latest developments in lung cancer screening, lung cancer diagnosis and management. Early lung cancer diagnosis, subsequent pros and cons of aggressive management, identification and management of systemic treatments' side-effects, and the application of artificial intelligence and biomarkers across all aspects of the thoracic oncology pathway were among the areas that triggered specific interest and will be summarised here.

ATR-FTIR Spectroscopy with Chemometrics for Analysis of Saliva Samples Obtained in a Lung-Cancer-Screening Programme: Application of Swabs as a Paradigm for High Throughput in a Clinical Setting

There is an increasing need for inexpensive and rapid screening tests in point-of-care clinical oncology settings. Herein, we develop a swab "dip" test in saliva obtained from consenting patients participating in a lung-cancer-screening programme being undertaken in North West England. In a pilot study, a total of 211 saliva samples (n = 170 benign, 41 designated cancer-positive) were randomly taken during the course of this prospective lung-cancer-screening programme. The samples (sterile Copan blue rayon swabs dipped in saliva) were analysed using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. An exploratory analysis using principal component analysis (PCA,) with or without linear discriminant analysis (LDA), was then undertaken. Three pairwise comparisons were undertaken including: (1) benign vs. cancer following swab analysis; (2) benign vs. cancer following swab analysis with the subtraction of dry swab spectra; and (3) benign vs. cancer following swab analysis with the subtraction of wet swab spectra. Consistent and remarkably similar patterns of clustering for the benign control vs. cancer categories, irrespective of whether the swab plus saliva sample was analysed or whether there was a subtraction of wet or dry swab spectra, was observed. In each case, MANOVA demonstrated that this segregation of categories is highly significant. A k-NN (using three nearest neighbours) machine-learning algorithm also showed that the specificity (90%) and sensitivity (75%) are consistent for each pairwise comparison. In detailed analyses, the swab as a substrate did not alter the level of spectral discrimination between benign control vs. cancer saliva samples. These results demonstrate a novel swab "dip" test using saliva as a biofluid that is highly applicable to be rolled out into a larger lung-cancer-screening programme.

National lung cancer screening program feasibility study in Estonia

OBJECTIVES

The main aim of the lung cancer screening (LCS) feasibility study was to investigate the plausibility of and bottlenecks to systematic enrolment in family physician practices by evaluating all their patients.

METHODS

In 3 family physician practices, for each individual born in 1947-1966 (target age group 55-74 years), information on ever smoking was gathered by a family physician/nurse. All current and ex-smokers were invited to an 'LCS visit'. In parallel, 2 inclusion criteria were used: (1) current smoker (≥20 pack-years) or ex-smoker (quit <15 years ago and smoking history ≥20 pack-years) and (2) PLCOm2012noRace risk score >1.5. All individuals with elevated lung cancer risk were assigned low-dose computed tomography.

RESULTS

Among the total 7035 individuals in the 3 family physician practices, the LCS target age group comprised 1208 individuals, including 649 (46.3-57.1%) males and 559 (42.9-53.7%) females. Of the 1208 applicable age group individuals, 395 (all current or ex-smokers) were invited to the 'LCS visit'. According to either 1 or both the LCS inclusion criteria, 206 individuals were referred to low-dose computed tomography, and 201 (97.6% of those referred) ended up taking it. The estimated participation rate in LCS, based on data from our feasibility study, would have been 87.4%.

CONCLUSIONS

In LCS, systematic enrolment of individuals by family physicians results in high uptake, and thus, effectiveness of the LCS in the setting of a well-functioning family physician system like in Estonia. Also, the feasibility study provided excellent input to the currently ongoing regional LCS pilot study in Estonia.

A Quick Reference Guide for Incidental Findings on Lung Cancer Screening CT Examinations

PURPOSE

The US Preventive Services Task Force has recommended lung cancer screening (LCS) with low-dose CT (LDCT) in high-risk individuals since 2013. Because LDCT encompasses the lower neck, chest, and upper abdomen, many incidental findings (IFs) are detected. The authors created a quick reference guide to describe common IFs in LCS to assist LCS program navigators and ordering providers in managing the care continuum in LCS.

METHODS

The ACR IF white papers were reviewed for findings on LDCT that were age appropriate for LCS. A draft guide was created on the basis of recommendations in the IF white papers, the medical literature, and input from subspecialty content experts. The draft was piloted with LCS program navigators recruited through contacts by the ACR LCS Steering Committee. The navigators completed a survey on overall usefulness, clarity, adequacy of content, and user experience with the guide.

RESULTS

Seven anatomic regions including 15 discrete organs with 45 management recommendations were identified as relevant to the age of individuals eligible for LCS. The draft was piloted by 49 LCS program navigators from 32 facilities. The guide was rated as useful and clear by 95% of users. No unexpected or adverse experiences were reported in using the guide. On the basis of feedback, relevant sections were reviewed and edited.

CONCLUSIONS

The ACR Lung Cancer Screening CT Incidental Findings Quick Reference Guide outlines the common IFs in LCS and can serve as an easy-to-use resource for ordering providers and LCS program navigators to help guide management.

Possible Bias in Supervised Deep Learning Algorithms for CT Lung Nodule Detection and Classification

Simple Summary

Artificial Intelligence (AI) algorithms can assist clinicians in their daily tasks by automatically detecting and/or classifying nodules in chest CT scans. Bias of such algorithms is one of the reasons why implementation of them in clinical practice is still not widely adopted. There is no published review on the bias that these algorithms may contain. This review aims to present different types of bias in such algorithms and present possible ways to mitigate them. Only then it would be possible to ensure that these algorithms work as intended under many different clinical settings.

Abstract

Artificial Intelligence (AI) algorithms for automatic lung nodule detection and classification can assist radiologists in their daily routine of chest CT evaluation. Even though many AI algorithms for these tasks have already been developed, their implementation in the clinical workflow is still largely lacking. Apart from the significant number of false-positive findings, one of the reasons for that is the bias that these algorithms may contain. In this review, different types of biases that may exist in chest CT AI nodule detection and classification algorithms are listed and discussed. Examples from the literature in which each type of bias occurs are presented, along with ways to mitigate these biases. Different types of biases can occur in chest CT AI algorithms for lung nodule detection and classification. Mitigation of them can be very difficult, if not impossible to achieve completely.

EMM-LC Fusion: Enhanced Multimodal Fusion for Lung Cancer Classification

Lung cancer (LC) is the most common cause of cancer-related deaths in the UK due to delayed diagnosis. The existing literature establishes a variety of factors which contribute to this, including the misjudgement of anatomical structure by doctors and radiologists. This study set out to develop a solution which utilises multiple modalities in order to detect the presence of LC. A review of the existing literature established failings within methods to exploit rich intermediate feature representations, such that it can capture complex multimodal associations between heterogenous data sources. The methodological approach involved the development of a novel machine learning (ML) model to facilitate quantitative analysis. The proposed solution, named EMM-LC Fusion, extracts intermediate features from a pre-trained modified AlignedXception model and concatenates these with linearly inflated features of Clinical Data Elements (CDE). The implementation was evaluated and compared against existing literature using F1 score, average precision (AP), and area under curve (AUC) as metrics. The findings presented in this study show a statistically significant improvement (p < 0.05) upon the previous fusion method, with an increase in F-Score from 0.402 to 0.508. The significance of this establishes that the extraction of intermediate features produces a fertile environment for the detection of intermodal relationships for the task of LC classification. This research also provides an architecture to facilitate the future implementation of alternative biomarkers for lung cancer, one of the acknowledged limitations of this study.

Likely uptake of a future a lung cancer screening programme in Hodgkin lymphoma survivors: a questionnaire study

Background

Many Hodgkin lymphoma (HL) survivors are at increased risk of subsequent malignant neoplasms (SMN), including lung cancer, due to previous treatment for HL. Lung cancer screening (LCS) detects early-stage lung cancers in ever smokers but HL survivors without a heavy smoking history are ineligible for screening. There is a rationale to develop a targeted LCS. The aim of this study was to investigate levels of willingness to undergo LCS in HL survivors, and to identify the psycho-social factors associated with screening hesitancy.

Methods

A postal questionnaire was sent to 281 HL survivors registered in a long-term follow-up database and at increased risk of SMNs. Demographic, lung cancer risk factors, psycho-social and LCS belief variables were measured. Multivariable logistic regression analysis was performed to determine the factors associated with lung cancer screening hesitancy, defined as those who would ‘probably’ or ‘probably not’ participate.

Results

The response rate to the questionnaire was 58% (n = 165). Participants were more likely to be female, older and living in a less deprived area than non-participants. Uptake (at any time) of breast and bowel cancer screening among those previously invited was 99% and 77% respectively. 159 participants were at excess risk of lung cancer. The following results refer to these 159. Around half perceived themselves to be at greater risk of lung cancer than their peers. Only 6% were eligible for lung cancer screening pilots aimed at ever smokers in the UK. 98% indicated they would probably or definitely participate in LCS were it available. Psycho-social variables associated with LCS hesitancy on multivariable analysis were male gender (OR 5.94 CI 1.64–21.44, p < 0.01), living in an area with a high index of multiple deprivation decile (deciles 6–10) (OR 8.22 CI 1.59–42.58, p < 0.05) and lower levels of self-efficacy (OR 1.64 CI 1.30–2.08 p < 0.01).

Conclusion

HL survivors responding to this survey were willing to participate in a future LCS programme but there was some hesitancy. A future LCS trial for HL survivors should consider the factors associated with screening hesitancy in order to minimise barriers to participation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01959-3.

Potential of Inflammatory Protein Signatures for Enhanced Selection of People for Lung Cancer Screening

Randomized trials have demonstrated a substantial reduction in lung cancer (LC) mortality by screening heavy smokers with low-dose computed tomography (LDCT). The aim of this study was to assess if and to what extent blood-based inflammatory protein biomarkers might enhance selection of those at highest risk for LC screening. Ever smoking participants were chosen from 9940 participants, aged 50-75 years, who were followed up with respect to LC incidence for 17 years in a prospective population-based cohort study conducted in Saarland, Germany. Using proximity extension assay, 92 inflammation protein biomarkers were measured in baseline plasma samples of ever smoking participants, including 172 incident LC cases and 285 randomly selected participants free of LC. Smoothly clipped absolute deviation (SCAD) penalized regression with 0.632+ bootstrap for correction of overoptimism was applied to derive an inflammation protein biomarker score (INS) and a combined INS-pack-years score in a training set, and algorithms were further evaluated in an independent validation set. Furthermore, the performances of nine LC risk prediction models individually and in combination with inflammatory plasma protein biomarkers for predicting LC incidence were comparatively evaluated. The combined INS-pack-years score predicted LC incidence with area under the curves (AUCs) of 0.811 and 0.782 in the training and the validation sets, respectively. The addition of inflammatory plasma protein biomarkers to established nine LC risk models increased the AUCs up to 0.121 and 0.070 among ever smoking participants from training and validation sets, respectively. Our results suggest that inflammatory protein biomarkers may have potential to improve the selection of people for LC screening and thereby enhance screening efficiency.