Lung Cancer Management in Low and Middle-Income Countries

The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations

BACKGROUND

Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibility and cost-effectiveness analysis of a community-based program that used a mobile low-dose computed tomography (LDCT) scan unit and discuss the operational challenges faced during its implementation.

METHODS

This study was conducted in rural areas in Fujian Province, China from July 2022 to August 2022. Individuals aged 40 years and above who had not previously undergone LDCT and who were socioeconomically marginalized were included. Participants received a LDCT program from a multidisciplinary research team. Physicians analyzed the images with the assistance of artificial intelligence "InferRead CT Lung Research" and completed structured reports on their impressions. The primary evaluation indicators for mobile LDCT screening effectiveness were the lung cancer detection rate and diagnosis rate, while the main evaluation indicators for cost-effective analysis were the cost-effective ratio and early detection cost index.

RESULTS

A total of 10,159 individuals participated in this study. The detection rates of suspected lung cancer cases and confirmed cases were 1.06% (n = 108) and 0.7% (n = 71), respectively. The cost of lung cancer screening (LCS) was ¥1,203,504 (US$188,847.71), the average cost per screening was ¥118.47 (US$18.65), and the cost effective ratios for the detection of suspected lung cancer and confirmed lung cancer were ¥11,143.56 (US$1,753.29) and ¥16,950.76 (US$2,669.94), respectively. The early detection cost indices for suspected lung cancer were 0.09 and 0.13 for confirmed lung cancer, respectively.

CONCLUSION

This LDCT with artificial intelligence model for LCS holds economic promise for reducing health disparities in underserved areas and promote larger populations in similar low-income country.

Artificial intelligence in precision medicine for lung cancer: A bibliometric analysis

Background

The increasing body of evidence has been stimulating the application of artificial intelligence (AI) in precision medicine research for lung cancer. This trend necessitates a comprehensive overview of the growing number of publications to facilitate researchers' understanding of this field.

Method

The bibliometric data for the current analysis was extracted from the Web of Science Core Collection database, CiteSpace, VOSviewer ,and an online website were applied to the analysis.

Results

After the data were filtered, this search yielded 4062 manuscripts. And 92.27% of the papers were published from 2014 onwards. The main contributing countries were China, the United States, India, Japan, and Korea. These publications were mainly published in the following scientific disciplines, including Radiology Nuclear Medicine, Medical Imaging, Oncology, and Computer Science Notably, Li Weimin and Aerts Hugo J. W. L. stand out as leading authorities in this domain. In the keyword co-occurrence and co-citation cluster analysis of the publication, the knowledge base was divided into four clusters that are more easily understood, including screening, diagnosis, treatment, and prognosis.

Conclusion

This bibliometric study reveals deep learning frameworks and AI-based radiomics are receiving attention. High-quality and standardized data have the potential to revolutionize lung cancer screening and diagnosis in the era of precision medicine. However, the importance of high-quality clinical datasets, the development of new and combined AI models, and their consistent assessment for advancing research on AI applications in lung cancer are highlighted before current research can be effectively applied in clinical practice.

Tumor-Activated Neutrophils Promote Lung Cancer Progression through the IL-8/PD-L1 Pathway

BACKGROUND

Lung cancer remains a major global health threat due to its complex microenvironment, particularly the role of neutrophils, which are crucial for tumor development and immune evasion mechanisms. This study aimed to delve into the impact of lung cancer cell-conditioned media on neutrophil functions and their potential implications for lung cancer progression.

METHODS

Employing in vitro experimental models, this study has analyzed the effects of lung cancer cell-conditioned media on neutrophil IL-8 and IFN-γ secretion, apoptosis, PD-L1 expression, and T-cell proliferation by using techniques, such as ELISA, flow cytometry, immunofluorescence, and CFSE proliferation assay. The roles of IL-8/PD-L1 in regulating neutrophil functions were further explored using inhibitors for IL-8 and PD-L1.

RESULTS

Lung cancer cell lines were found to secrete higher levels of IL-8 compared to normal lung epithelial cells. The conditioned media from lung cancer cells significantly reduced apoptosis in neutrophils, increased PD-L1 expression, and suppressed T-cell proliferation and IFN-γ secretion. These effects were partially reversed in the presence of IL-8 inhibitors in Tumor Tissue Culture Supernatants (TTCS), while being further enhanced by IL-8. Both apoptosis and PD-L1 expression in neutrophils demonstrated dose-dependency to TTCS. Additionally, CFSE proliferation assay results further confirmed the inhibitory effect of lung cancer cell-conditioned media on T-- cell proliferation.

CONCLUSION

This study has revealed lung cancer cell-conditioned media to modulate neutrophil functions through regulating factors, such as IL-8, thereby affecting immune regulation and tumor progression in the lung cancer microenvironment.

Socioeconomic inequality in cervical cancer screening uptake among women in sub-Saharan Africa: a decomposition analysis of Demographic and Health Survey data

OBJECTIVE

To examine socioeconomic inequalities in the use of cervical cancer screening among women in sub-Saharan Africa.

DESIGN

Secondary data from the Demographic and Health Survey data in sub-Saharan Africa.

SETTING

Sub-Saharan Africa.

PARTICIPANTS

Women aged 15-64 years.

OUTCOME MEASURES

Socioeconomic inequalities in cervical cancer screening uptake and the pooled prevalence of cervical cancer screening.

RESULTS

The pooled prevalence of cervical cancer screening among women in sub-Saharan African countries was 10.51% (95% CI: 7.54% to 13.48%). Cervical cancer screening uptake showed a significant pro-rich distribution of wealth-related inequalities, with a weighted Erreygers normalised concentration index of 0.084 and an SE of 0.003 (p value <0.0001). This finding suggests that disparities in cervical cancer screening uptake among women are related to wealth. Decomposition analysis revealed that the wealth index, educational status, place of residence and media exposure were the most important factors contributing to this pro-rich socioeconomic inequality in cervical cancer screening.

CONCLUSION

This study emphasises the importance of addressing modifiable factors such as improving educational opportunities, increasing media exposure accessibility in households and improving the country's economy to reduce wealth disparities and improve cervical cancer screening uptake among women.

Global burden of lung cancer in 2022 and projections to 2050: Incidence and mortality estimates from GLOBOCAN

BACKGROUND

Lung cancer continues to pose a serious global public health challenge. Timely evidence on the global epidemiological profile of the disease is crucial to facilitate the implementation to lung cancer control efforts. This study provides updated global estimates for lung cancer incidence and mortality in 2022, along with projections for new cases and deaths up to 2050.

METHODS

In the population-based study, we extracted data about lung cancer new cases and deaths from GLOBOCAN 2022 database across 185 countries or territories. We analyzed age-standardized rates by sex, country, region, and human development index (HDI). Projected new cases and deaths for 2050 were estimated using global demographic projections.

RESULTS

In 2022, lung cancer stood as the most frequently diagnosed cancer and the primary cause of cancer-related deaths on a global scale with approximately 2.48 million new cases and 1.8 million deaths, respectively. The incidence and mortality rates of lung cancer exhibited disparities in sex and world regions. Furthermore, incidence and mortality rates increasing as HDI increased. If the incidence and mortality rates remain stable as in 2022, the burden of lung cancer is projected to increase to 4·62 million new cases and 3·55 million deaths by 2050.

CONCLUSIONS

Lung cancer is the predominant form of cancer and the foremost contributor to cancer-related mortality in 2022 with notable geographical, sex, and socioeconomic disparities.

Fine needle aspiration biopsy in low- and middle-income countries

Fine needle aspiration biopsy (FNAB) in low- and middle-income countries (LMIC), can provide minimally invasive, cost-effective tissue diagnosis with rapid assessment and specimen triage, which is advantageous in these resource-limited settings. Nevertheless, challenges such as equipment shortages, reagents, and lack of trained personnel exist. This article discusses the effectiveness of FNAB for diagnosis of malignant and inflammatory conditions across various organs, such as lymph nodes, breast, soft tissue, and thyroid and advocates for increased training opportunities and collaboration with academic centers to enhance diagnostic accuracy and access to pathology services.

Household income unequally affects genetic susceptibility to pulmonary diseases: evidence from bidirectional Mendelian randomization study

Objectives

Previous observational studies have reported a close association between socioeconomic status and pulmonary disease-related morbidity. However, the inherent causal effects remain unclear. Therefore, this bidirectional Mendelian randomization (MR) study aimed to identify the causal relationship between household income and genetic susceptibility to pulmonary diseases.

Methods

An MR study was conducted on a large cohort of European individuals, using publicly available genome-wide association study datasets using a random-effects inverse-variance weighting model as the main standard. Simultaneously, MR-Egger regression, weighted median, and maximum likelihood estimation were applied as supplements. Sensitivity analysis, comprising a heterogeneity test and horizontal pleiotropy test, was performed using the Cochran's Q, MR-Egger intercept, and MR-PRESSO tests to ensure the reliability of the conclusion.

Results

A higher household income tended to lower the risk of genetic susceptibility to chronic obstructive pulmonary disease (COPD, OR: 0.497, 95% CI = 0.337-0.733, p < 0.001), asthma (OR: 0.687, 95% CI = 0.540-0.876, p = 0.002), and lung cancer (OR: 0.569, 95% CI = 0.433-0.748, p < 0.001), and further indicated potential causality with pneumonia (OR: 0.817; 95% CI = 0.686-0.972, p = 0.022). No association was evident with COVID-19 (OR: 0.934, 95% CI = 0.764-1.142, p = 0.507), tuberculosis (OR: 0.597, 95% CI = 0.512-1.189, p = 0.120), or bronchiectasis (OR: 0.680, 95% CI = 0.311-1.489, p = 0.400). Reverse MR analysis suggested no reverse causal relationship between pulmonary disease and household income status, while sensitivity analysis verified the reliability of the results.

Conclusion

The results revealed that the population with a higher household income tended to have a lower risk of genetic susceptibility to COPD, asthma, and lung cancer.

Providing Diagnostic Pathology Services in Low and Middle-Income Countries

Diagnostic pathology services in low and middle-income countries are often hindered by lack of expertise, equipment, and reagents. However, there are also educational, cultural, and political decisions, which must be addressed in order to provide these services successfully. In this review, we describe some of the infrastructure barriers that must be overcome and provide 3 examples of implementing molecular testing in Rwanda and Honduras despite initial lack of resources.

Epidemiological Analysis of Global and Regional Lung Cancer Mortality: Based on 30-Year Data Analysis of Global Burden Disease Database

The objective of this study was to understand dynamic global and regional lung cancer fatality trends and provide a foundation for effective global lung cancer prevention and treatment strategies. Data from 1990 to 2019 were collected from the Global Burden Disease (GBD) database and statistical analysis was conducted using Excel 2010. Standardization was based on the GBD's world population structure, and the Average Annual Percentage Change (AAPC) was calculated using Joinpoint 4.8.0.1 software. Bayesian age-period-cohort analysis (BAPC) predicted global lung cancer mortality from 2020 to 2030. In 2019, worldwide lung cancer deaths reached 2,042,600, a 91.75% increase from 1990 (1,065,100). The standardized age-specific death rate in 2019 was 25.18 per 100,000. Males had a rate of 37.38 while females had 14.99. Men saw a decreasing trend while women experienced an increase. High- and medium-high-SDI regions had declining rates (-0.3 and -0.8 AAPCs) whereas middle-, low-, and low-middle-SDI regions had increased mortality rates (AAPC = 0.1, AAPC = 0.37, AAPC = 0.13). Several regions, including Oceania, South Asia, East Asia, Western Sub-Saharan Africa, Southeast Asia, and Eastern Sub-Saharan Africa, witnessed rising global lung cancer mortality rates (p < 0.01). The global standardized mortality rate for lung cancer is expected to decrease from 2020 to 2030, but predictions indicate increasing female mortality and decreasing male mortality. Despite overall declines, rising female mortality remains a concern. Effective measures are essential to reduce mortality rates and improve patients' quality of life in the global fight against lung cancer.