The challenges of implementing low-dose computed tomography for lung cancer screening in low- and middle-income countries

Global Burden of Lung Cancer Attributable to Household Fine Particulate Matter Pollution in 204 Countries and Territories, 1990 to 2019

INTRODUCTION

Household particulate matter (PM) air pollution is substantially associated with lung cancer. Nevertheless, the global burden of lung cancer attributable to household PM2.5 is still uncertain.

METHODS

In this study, data from the Global Burden and Disease Study 2019 are used to thoroughly assess the burden of lung cancer associated with household PM2.5.

RESULTS

The number of deaths and disability-adjusted life-years (DALYs) attributable to household PM2.5 was found to be 0.08 million and 1.94 million, respectively in 2019. Nevertheless, the burden of lung cancer attributable to household PM2.5 decreased from 1990 to 2019. At the sociodemographic index (SDI) district level, the middle SDI region had the most number of lung cancer deaths and DALYs attributable to household PM2.5. Moreover, the burden of lung cancer was mainly distributed in low-SDI regions, such as Sub-Saharan Africa. Conversely, in high-SDI regions, the age-standardized mortality rate and age-standardized DALY rate of lung cancer attributable to household PM2.5 exhibit the most rapid declines. The burden of lung cancer attributable to household PM2.5 is heavier for men than for women. The sex difference is more obvious in the elderly.

CONCLUSIONS

The prevalence of lung cancer attributable to household PM2.5 has exhibited a declining trend from 1990 to 2019 owing to a concurrent decline in household PM2.5 exposure.

Perspective on Management of Low-Dose Computed Tomography Findings on Low-Dose Computed Tomography Examinations for Lung Cancer Screening. From the International Association for the Study of Lung Cancer Early Detection and Screening Committee

Lung cancer screening using low-dose computed tomography (LDCT) carefully implemented has been found to reduce deaths from lung cancer. Optimal management starts with selection of eligibility criteria, counseling of screenees, smoking cessation, selection of the regimen of screening which specifies the imaging protocol, and workup of LDCT findings. Coordination of clinical, radiologic, and interventional teams and ultimately treatment of diagnosed lung cancers under screening determine the benefit of LDCT screening. Ethical considerations of who should be eligible for LDCT screening programs are important to provide the benefit to as many people at risk of lung cancer as possible. Unanticipated diseases identified on LDCT may offer important benefits through early detection of leading global causes of death, such as cardiovascular diseases and chronic obstructive pulmonary disease, as the latter may result from conditions such as emphysema and bronchiectasis, which can be identified early on LDCT. This report identifies the key components of the regimen of LDCT screening for lung cancer which include the need for a management system to provide data for continuous updating of the regimen and provides quality assurance assessment of actual screenings. Multidisciplinary clinical management is needed to maximize the benefit of early detection, diagnosis, and treatment of lung cancer. Different regimens have been evolving throughout the world as the resources and needs may be different, for countries with limited resources. Sharing of results, further knowledge, and incorporation of technologic advances will continue to accelerate worldwide improvements in the diagnostic and treatment approaches.

Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging

Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.

Telemedicine-Enhanced Lung Cancer Screening Using Mobile Computed Tomography Unit with Remote Artificial Intelligence Assistance in Underserved Communities: Initial Results of a Population Cohort Study in Western China

Introduction: Lung cancer is a leading cause of cancer deaths globally. Despite favorable recommendations, low-dose computed tomography (LDCT) lung screening adoption remains low in China. Barriers such as limited infrastructure, costs, distance, and personnel shortages restrict screening access in disadvantaged regions. We initiated a telemedicine-enabled lung cancer screening (LCS) program in a medical consortium to serve people at risk in underserved communities. The objective of this study was to describe the implementation and initial results of the program. Methods: From 2020 to 2021, individuals aged 40-80 years were invited to take LCS by mobile computed tomography (CT) units in three underserved areas in Western China. Numerous CT scans were remotely reported by radiologists aided by artificial intelligence (AI) diagnostic systems. Abnormal cases were tracked through an integrated hospital network for follow-up. A retrospective cohort study documented participant demographics, health history, LDCT results, and outcomes. Descriptive analysis was conducted to report baseline characteristics and first-year follow-up results. Results: Of the 28,728 individuals registered in the program, 19,517 (67.94%) participated in the screening. The study identified 2.68% of participants with high-risk pulmonary nodules and diagnosed 0.55% with lung cancer after a 1-year follow-up. The majority of high-risk participants received timely treatment in hospitals. Conclusions: This study demonstrated mobile CT units with remote AI assistance improved access to LCS in underserved areas, with high participation and early detection rates. Our implementation supports the feasibility of deploying telemedicine-enabled LCS to increase access to a large scale of basic radiology and diagnostic services in resource-limited settings. Clinical Trial Registration Number: ChiCTR1900024623.

microRNAs in exhaled breath condensate for diagnosis of lung cancer in a resource-limited setting: a concise review

Lung cancer is one of the common cancers globally with high mortality and poor prognosis. Most cases of lung cancer are diagnosed at an advanced stage due to limited diagnostic resources. Screening modalities, such as sputum cytology and annual chest radiographs, have not proved sensitive enough to impact mortality. In recent years, annual low-dose computed tomography has emerged as a potential screening tool for early lung cancer detection, but it may not be a feasible option for developing countries. In this context, exhaled breath condensate (EBC) analysis has been evaluated recently as a noninvasive tool for lung cancer diagnosis. The breath biomarkers also have the advantage of differentiating various types and stages of lung cancer. Recent studies have focused more on microRNAs (miRNAs) as they play a key role in tumourigenesis by regulating the cell cycle, metastasis and angiogenesis. In this review, we have consolidated the current published literature suggesting the utility of miRNAs in EBC for the detection of lung cancer.

Lung Cancer Screening in Asia: An Expert Consensus Report

INTRODUCTION

The incidence and mortality of lung cancer are highest in Asia compared with Europe and USA, with the incidence and mortality rates being 34.4 and 28.1 per 100,000 respectively in East Asia. Diagnosing lung cancer at early stages makes the disease amenable to curative treatment and reduces mortality. In some areas in Asia, limited availability of robust diagnostic tools and treatment modalities, along with variations in specific health care investment and policies, make it necessary to have a more specific approach for screening, early detection, diagnosis, and treatment of patients with lung cancer in Asia compared with the West.

METHOD

A group of 19 advisors across different specialties from 11 Asian countries, met on a virtual Steering Committee meeting, to discuss and recommend the most affordable and accessible lung cancer screening modalities and their implementation, for the Asian population.

RESULTS

Significant risk factors identified for lung cancer in smokers in Asia include age 50 to 75 years and smoking history of more than or equal to 20 pack-years. Family history is the most common risk factor for nonsmokers. Low-dose computed tomography screening is recommended once a year for patients with screening-detected abnormality and persistent exposure to risk factors. However, for high-risk heavy smokers and nonsmokers with risk factors, reassessment scans are recommended at an initial interval of 6 to 12 months with subsequent lengthening of reassessment intervals, and it should be stopped in patients more than 80 years of age or are unable or unwilling to undergo curative treatment.

CONCLUSIONS

Asian countries face several challenges in implementing low-dose computed tomography screening, such as economic limitations, lack of efforts for early detection, and lack of specific government programs. Various strategies are suggested to overcome these challenges in Asia.

From pre-COPD to COPD: a Simple, Low cost and easy to IMplement (SLIM) risk calculator

BACKGROUND

The lifetime risk of developing clinical COPD among smokers ranges from 13% to 22%. Identifying at-risk individuals who will develop overt disease in a reasonable timeframe may allow for early intervention. We hypothesised that readily available clinical and physiological variables could help identify ever-smokers at higher risk of developing chronic airflow limitation (CAL).

METHODS

Among 2273 Lovelace Smokers' Cohort (LSC) participants, we included 677 (mean age 54 years) with normal spirometry at baseline and a minimum of three spirometries, each 1 year apart. Repeated spirometric measurements were used to determine incident CAL. Using logistic regression, demographics, anthropometrics, smoking history, modified Medical Research Council dyspnoea scale, St George's Respiratory Questionnaire, comorbidities and spirometry, we related variables obtained at baseline to incident CAL as defined by the Global Initiative for Chronic Obstructive Lung Disease and lower limit of normal criteria. The predictive model derived from the LSC was validated in subjects from the COPDGene study.

RESULTS

Over 6.3 years, the incidence of CAL was 26 cases per 1000 person-years. The strongest independent predictors were forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) <0.75, having smoked ≥30 pack-years, body mass index (BMI) ≤25 kg·m2 and symptoms of chronic bronchitis. Having all four predictors increased the risk of developing CAL over 6 years to 85% (area under the receiver operating characteristic curve (AUC ROC) 0.84, 95% CI 0.81-0.89). The prediction model showed similar results when applied to subjects in the COPDGene study with a follow-up period of 10 years (AUC ROC 0.77, 95% CI 0.72-0.81).

CONCLUSION

In middle-aged ever-smokers, a simple predictive model with FEV1/FVC, smoking history, BMI and chronic bronchitis helps identify subjects at high risk of developing CAL.

Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models

Screening programs for early lung cancer diagnosis are uncommon, primarily due to the challenge of reaching at-risk patients located in rural areas far from medical facilities. To overcome this obstacle, a comprehensive approach is needed that combines mobility, low cost, speed, accuracy, and privacy. One potential solution lies in combining the chest X-ray imaging mode with federated deep learning, ensuring that no single data source can bias the model adversely. This study presents a pre-processing pipeline designed to debias chest X-ray images, thereby enhancing internal classification and external generalization. The pipeline employs a pruning mechanism to train a deep learning model for nodule detection, utilizing the most informative images from a publicly available lung nodule X-ray dataset. Histogram equalization is used to remove systematic differences in image brightness and contrast. Model training is then performed using combinations of lung field segmentation, close cropping, and rib/bone suppression. The resulting deep learning models, generated through this pre-processing pipeline, demonstrate successful generalization on an independent lung nodule dataset. By eliminating confounding variables in chest X-ray images and suppressing signal noise from the bone structures, the proposed deep learning lung nodule detection algorithm achieves an external generalization accuracy of 89%. This approach paves the way for the development of a low-cost and accessible deep learning-based clinical system for lung cancer screening.

Early detection and stratification of lung cancer aided by a cost-effective assay targeting circulating tumor DNA (ctDNA) methylation

BACKGROUND

Detection of lung cancer at earlier stage can greatly improve patient survival. We aim to develop, validate, and implement a cost-effective ctDNA-methylation-based plasma test to aid lung cancer early detection.

METHODS

Case-control studies were designed to select the most relevant markers to lung cancer. Patients with lung cancer or benign lung disease and healthy individuals were recruited from different clinical centers. A multi-locus qPCR assay, LunaCAM, was developed for lung cancer alertness by ctDNA methylation. Two LunaCAM models were built for screening (-S) or diagnostic aid (-D) to favor sensitivity or specificity, respectively. The performance of the models was validated for different intended uses in clinics.

RESULTS

Profiling DNA methylation on 429 plasma samples including 209 lung cancer, 123 benign diseases and 97 healthy participants identified the top markers that detected lung cancer from benign diseases and healthy with an AUC of 0.85 and 0.95, respectively. The most effective methylation markers were verified individually in 40 tissues and 169 plasma samples to develop LunaCAM assay. Two models corresponding to different intended uses were trained with 513 plasma samples, and validated with an independent collection of 172 plasma samples. In validation, LunaCAM-S model achieved an AUC of 0.90 (95% CI: 0.88-0.94) between lung cancer and healthy individuals, whereas LunaCAM-D model stratified lung cancer from benign pulmonary diseases with an AUC of 0.81 (95% CI: 0.78-0.86). When implemented sequentially in the validation set, LunaCAM-S enables to identify 58 patients of lung cancer (90.6% sensitivity), followed by LunaCAM-D to remove 20 patients with no evidence of cancer (83.3% specificity). LunaCAM-D significantly outperformed the blood test of carcinoembryonic antigen (CEA), and the combined model can further improve the predictive power for lung cancer to an overall AUC of 0.86.

CONCLUSIONS

We developed two different models by ctDNA methylation assay to sensitively detect early-stage lung cancer or specifically classify lung benign diseases. Implemented at different clinical settings, LunaCAM models has a potential to provide a facile and inexpensive avenue for early screening and diagnostic aids for lung cancer.

Lung cancer screening beliefs in Armenia

Introduction

In Armenia, an upper-middle income country, 93% of deaths are from non-communicable diseases and over half of the male population smokes. Armenia has more than double the global lung cancer incidence. Over 80% of lung cancer is diagnosed at stages III or IV. However, there is a significant mortality benefit in detecting early-stage lung cancer via screening with low-dose computed tomography.

Methods

This study employed a rigorously-translated, previously-validated survey based on the Expanded Health Belief Model to understand how Armenian male smokers' beliefs would affect lung cancer screening participation.

Results

Survey responses highlighted key health beliefs that would mediate screening participation. Most respondents felt they were at risk for lung cancer, but over 50% also believed their cancer risk was equivalent to (or less than) non-smokers' risk. Respondents also overwhelmingly agreed a scan could help detect cancer earlier, but fewer agreed early detection could reduce cancer mortality. Important barriers included absence of symptoms and costs of screening and treatment.

Discussion

Overall, the potential to reduce lung cancer-related deaths in Armenia is high, but there are a number of central health beliefs and barriers that would limit screening uptake and effectiveness. Improved health education, careful consideration of socioeconomic screening barriers, and appropriate screening recommendations may be useful in overcoming these beliefs.

Epidemiological and demographic drivers of lung cancer mortality from 1990 to 2019: results from the global burden of disease study 2019

Background

Understanding the effects of demographic drivers on lung cancer mortality trends is critical for lung cancer control. We have examined the drivers of lung cancer mortality at the global, regional, and national levels.

Methods

Data on lung cancer death and mortality were extracted from the Global Burden of Disease (GBD) 2019. Estimated annual percentage change (EAPC) in the age-standardized mortality rate (ASMR) for lung cancer and all-cause mortality were calculated to measure temporal trends in lung cancer from 1990 to 2019. Decomposition analysis was used to analyze the contributions of epidemiological and demographic drivers to lung cancer mortality.

Results

Despite a non-significant decrease in ASMR [EAPC = -0.31, 95% confidence interval (CI): -1.1 to 0.49], the number of deaths from lung cancer increased by 91.8% [95% uncertainty interval (UI): 74.5-109.0%] between 1990 and 2019. This increase was due to the changes in the number of deaths attributable to population aging (59.6%), population growth (56.7%), and non-GBD risks (3.49%) compared with 1990 data. Conversely, the number of lung cancer deaths due to GBD risks decreased by 19.8%, mainly due to tobacco (-12.66%), occupational risks (-3.52%), and air pollution (-3.47%). More lung cancer deaths (1.83%) were observed in most regions, which were due to high fasting plasma glucose levels. The temporal trend of lung cancer ASMR and the patterns of demographic drivers varied by region and gender. Significant associations were observed between the contributions of population growth, GBD risks and non-GBD risks (negative), population aging (positive), and ASMR in 1990, the sociodemographic index (SDI), and the human development index (HDI) in 2019.

Conclusion

Population aging and population growth increased global lung cancer deaths from 1990 to 2019, despite a decrease in age-specific lung cancer death rates due to GBD risks in most regions. A tailored strategy is needed to reduce the increasing burden of lung cancer due to outpacing demographic drivers of epidemiological change globally and in most regions, taking into account region- or gender-specific risk patterns.

Pre- and post-intervention survey on lung cancer awareness among adults in selected communities in KwaZulu-Natal, South Africa: A quasi-experimental study

Background

Lung cancer remains the number one cause of cancer mortality estimated at 1.8 million deaths. There are limited studies in resource poor countries regarding knowledge, attitudes and practices towards lung cancer.

Objective

This study aimed to assess the effects of a lung cancer awareness intervention in selected communities in KwaZulu- Natal, South Africa.

Materials and Methods

A quasi-experimental study design was conducted in the selected communities in KwaZulu-Natal. A community intervention was administered in the communities after a baseline survey. The intervention effects were assessed a month after implementation.

Results

There were statistical differences in the mean age (p<0.001) and proportion of males and females (p<0.001) at baseline and post-intervention. There were no differences in terms of smoking status (p=0.958), however, there was a reduction in the number of cigarettes smoked per day (p<0.001) and the number of packs smoked per week (p=0.026). The mean knowledge score increased from 41.8% (95% CI 35.7 - 47.9) at baseline to 59.9 (95% CI 53.8 - 66.0) post-intervention (p<0.001). The proportion of participants who were aware that lung cancer can be detected early increased from 46.5% (95% CI 39.1 - 53.9) at baseline to 81.1% (95% CI 71.7 - 87.9) post-intervention (p<0.001). The intervention had a statistically significant effect (aOR 4.370, 95% CI 1.477-12.928) on the level of lung cancer knowledge in the selected communities (p<0.001).

Conclusions

Interventions increasing the recognition of signs and symptoms, focusing on the importance of early detection and health seeking behaviour (including screening), smoking cessation, and addressing the perceived health system barriers are required.

Barriers and facilitators for low-dose computed tomography lung cancer screening in rural populations in the United States: a scoping review protocol

OBJECTIVE

The objective of this scoping review is to identify barriers and facilitators for low-dose computed tomography lung cancer screening uptake and adherence among rural populations in the United States.

INTRODUCTION

Lung cancer is the leading cause of cancer-related death in the United States, and cancer patients from rural areas have poorer outcomes than those from metropolitan areas. Evidence exists that lung cancer screening by low-dose computed tomography significantly increases survival time but is also significantly underutilized.

INCLUSION CRITERIA

Studies completed in the United States with adults who fit United States Preventive Services Task Force guidelines for lung cancer screening and who live in rural areas will be included. Studies published in English since 2013 that report on barriers and facilitators for low-dose computed tomography lung cancer screening uptake and adherence will be included in this review. Quantitative, qualitative, or mixed-methods studies will be included, along with opinion pieces published by government agencies or professional cancer-related organizations.

METHODS

The search strategy will locate published primary studies, reviews, and opinion papers, including those by government and nonprofit agencies focused on cancer. The databases to be searched include MEDLINE, CINAHL Complete, Embase, Web of Science, and Cochrane Library. Gray literature databases and sources of unpublished studies will also be searched. Independent reviewers will be used throughout the search and selection process.

Radiology for Thoracic Conditions in Low- and Middle-Income Countries

With a disproportionately high burden of global morbidity and mortality caused by chronic respiratory diseases (CRDs) in low and middle-income countries (LMICs), access to radiological services is of critical importance for screening, diagnosis, and treatment guidance.

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.

Defining timeliness in care for patients with lung cancer: a scoping review

OBJECTIVES

Early diagnosis and reducing the time taken to achieve each step of lung cancer care is essential. This scoping review aimed to examine time points and intervals used to measure timeliness and to critically assess how they are defined by existing studies of the care seeking pathway for lung cancer.

METHODS

This scoping review was guided by the methodological framework for scoping reviews by Arksey and O'Malley. MEDLINE, EMBASE, CINAHL and PsycINFO electronic databases were searched for articles published between 1999 and 2019. After duplicate removal, all publications went through title and abstract screening followed by full text review and inclusion of articles in the review against the selection criteria. A narrative synthesis describes the time points, intervals and measurement guidelines used by the included articles.

RESULTS

A total of 2113 articles were identified from the initial search. Finally, 68 articles were included for data charting process. Eight time points and 14 intervals were identified as the most common events researched by the articles. Eighteen different lung cancer care guidelines were used to benchmark intervals in the included articles; all were developed in Western countries. The British Thoracic Society guideline was the most frequently used guideline (20%). Western guidelines were used by the studies in Asian countries despite differences in the health system structure.

CONCLUSION

This review identified substantial variations in definitions of some of the intervals used to describe timeliness of care for lung cancer. The differences in healthcare delivery systems of Asian and Western countries, and between high-income countries and low-income-middle-income countries may suggest different sets of time points and intervals need to be developed.

A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil

BACKGROUND

Country-specific evidence is needed to guide decisions regarding whether and how to implement lung cancer screening in different settings. For this study, we estimated the potential numbers of individuals screened and lung cancer deaths prevented in Brazil after applying different strategies to define screening eligibility.

METHODS

We applied the Lung Cancer Death Risk Assessment Tool (LCDRAT) to survey data on current and former smokers (ever-smokers) in 15 Brazilian state capital cities that comprise 18% of the Brazilian population. We evaluated three strategies to define eligibility for screening: (1) pack-years and cessation time (≥30 pack-years and <15 years since cessation); (2) the LCDRAT risk model with a fixed risk threshold; and (3) LCDRAT with age-specific risk thresholds.

FINDINGS

Among 2.3 million Brazilian ever-smokers aged 55-79 years, 21,459 (95%CI 20,532-22,387) lung cancer deaths were predicted over 5 years without screening. Applying the fixed risk-based eligibility definition would prevent more lung cancer deaths than the pack-years definition [2,939 (95%CI 2751-3127) vs. 2,500 (95%CI 2318-2681) lung cancer deaths], and with higher screening efficiency [NNS=177 (95%CI 170-183) vs. 205 (95%CI 194-216)], but would tend to screen older individuals [mean age 67.8 (95%CI 67.5-68.2) vs. 63.4 (95%CI 63.0-63.9) years]. Applying age-specific risk thresholds would allow younger ever-smokers to be screened, although these individuals would be at lower risk. The age-specific thresholds strategy would avert three-fifths (60.1%) of preventable lung cancer deaths [N = 2629 (95%CI 2448-2810)] by screening 21.9% of ever-smokers.

INTERPRETATION

The definition of eligibility impacts the efficiency of lung cancer screening and the mean age of the eligible population. As implementation of lung screening proceeds in different countries, our analytical framework can be used to guide similar analyses in other contexts. Due to limitations of our models, more research would be needed.

Fluorescent paper strip immunoassay with carbon nanodots@silica for determination of human serum amyloid A1

A fluorescent paper strip immunoassay in conjunction with carbon nanodots@silica (CND@SiO₂) as a label was developed for the quantitative measurements of human serum amyloid A1 (hSAA1) in serum at clinically significant concentrations for lung cancer diagnosis. Monodispersed CND@SiO₂ was prepared by cohydrolysis between silane-crosslinked carbon nanodots and silica precursors via the Ströber method and further attached covalently to anti-hSAA1 (14F8) monoclonal antibody [anti-hSAA1(14F8)] specific to the hSAA1 target. The hSAA1 concentrations were then determined by quantifying the blue fluorescence intensity upon 365 nm excitation of the captured hSAA1 with anti-hSAA1(14F8)-CND@SiO₂ conjugates in the test line on a paper strip where anti-hSAA1 (10G1) monoclonal antibody was physisorbed. The developed fluorescent paper strip with CND@SiO₂ can detect hSAA1 at concentrations ranging from 0.1 to 5 nM (R² = 0.995), with a limit of detection of  0.258 nM in 10 mM phosphate buffer pH 7.4 containing human serum albumin. The performance of  recovery (90.98-109.17%) and repeatability (coefficients of variation < 8.46%) obtained was also acceptable for quantitative determinations. The platform was employed for direct determination of hSAA1 concentrations in undiluted serum samples from lung cancer patients (relative standard deviation (RSD) < 7.46%) and healthy humans (RSD < 3.96%). The results were compared with those obtained using a commercially available enzyme-linked immunosorbent assay alongside liquid chromatography with tandem mass spectrometry measurements.

Early Diagnosis of Lung Cancer in the United Arab Emirates: Challenges and Strategic Recommendations

In the United Arab Emirates (UAE), lung cancer (LC) was the third leading cause of deaths due to cancer in 2017. Around 80% of the patients in the UAE are diagnosed at a late stage, rendering the treatment less effective in improving survival outcomes. Lack of awareness of disease symptomatology, deficient screening initiatives, misdiagnosis, and delayed referral to the specialist are contributing factors for delayed diagnosis. Effective screening at a primary care setting can be crucial for early diagnosis, referral to specialists, and enhancing patient outcomes. It is important to establish screening and referral guidelines through which each suspected case can be identified and provided timely intervention. Although the international screening and referral pathway framework are comprehensive, several regional barriers need to be addressed before they can be adapted at the national level. A group of LC experts from the UAE deliberated on issues like delayed diagnosis of LC and strategic recommendations for overcoming the challenges. The discussion was based on the review of the published evidence, international and regional guidelines for screening and early diagnosis of LC. Herein, we present a guideline, endorsed by the esteemed panel of experts, for aiding early diagnosis and optimizing the management of LC in the UAE.

Duration of intervals in the care seeking pathway for lung cancer in Bangladesh: A journey from symptoms triggering consultation to receipt of treatment

Timeliness in seeking care is critical for lung cancer patients' survival and better prognosis. The care seeking trajectory of patients with lung cancer in Bangladesh has not been explored, despite the differences in health systems and structures compared to high income countries. This study investigated the symptoms triggering healthcare seeking, preferred healthcare providers (including informal healthcare providers such as pharmacy retailers, village doctors, and "traditional healers"), and the duration of intervals in the lung cancer care pathway of patients in Bangladesh. A cross-sectional study was conducted in three tertiary care hospitals in Bangladesh among diagnosed lung cancer patients through face-to-face interview and medical record review. Time intervals from onset of symptom and care seeking events were calculated and compared between those who sought initial care from different providers using Wilcoxon rank sum tests. Among 418 study participants, the majority (90%) of whom were males, with a mean age of 57 ±9.86 years, cough and chest pain were the most common (23%) combination of symptoms triggering healthcare seeking. About two-thirds of the total respondents (60%) went to informal healthcare providers as their first point of contact. Living in rural areas, lower levels of education and lower income were associated with seeking care from such providers. The median duration between onset of symptom to confirmation of diagnosis was 121 days, between confirmation of diagnosis and initiation of treatment was 22 days, and between onset of symptom and initiation of treatment was 151 days. Pre-diagnosis durations were longer for those who had sought initial care from an informal provider (p<0.05). Time to first contact with a health provider was shorter in this study compared to other developed and developing countries but utilizing informal healthcare providers caused delays in diagnosis and initiation of treatment. Encouraging people to seek care from a formal healthcare provider may reduce the overall duration of the care seeking pathway.

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.