ReviewNature cancer2020
The challenges of implementing low-dose computed tomography for lung cancer screening in low- and middle-income countries.
Review in Nature cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 52 citations in OpenAlex.
- Availability of Cancer Screening Across HIV Treatment Sites in the IeDEA Consortium.International journal of cancer · 2026Article
- Lung Cancer Screening-Eligible Population From 2000 to 2050 in Argentina: A Simulation Study Brief Report.JTO clinical and research reports · 2026Article
- Trends in lung cancer incidence and mortality and the potential for overdiagnosis associated with computed tomography screening across 21 countries on six continents.Journal of thoracic disease · 2026Article
- Multidisciplinary Team Care for Early-Stage Lung Cancer in Low- and Middle-Income Countries and Emerging Economies: Current Position and Call for Action.Thoracic cancer · 2026Review
- Benefits and harms of lung cancer screening strategies in Argentina: a modeling study.Lancet regional health. Americas · 2026Article
- Understanding LUng Cancer risk factors and their Impact Assessment (LUCIA): protocol for multicentre observational cohort study.BMJ open · 2026Article
- DeepFAN, a transformer-based model for human-artificial intelligence collaborative assessment of incidental pulmonary nodules in CT scans: a multireader, multicase trial.Nature cancer · 2026Article
- Evaluation of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Incidental Pulmonary Nodules: The CREATE Study.Mayo Clinic proceedings. Digital health · 2026Article
- Reducing bulky medical images via shape-texture decoupled deep neural networks.Nature communications · 2026Article
- Lessons Learned From International Lung Cancer Screening Trials; People at Risk Deserve Screening for Early Detection.Respirology (Carlton, Vic.) · 2025Review
- Multi-cohort analysis identifies a blood-based immune transcriptomic signature for early lung cancer detection.NPJ precision oncology · 2025Article
- A Systematic Review of AI Performance in Lung Cancer Detection on CT Thorax.Healthcare (Basel, Switzerland) · 2025Review
- The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations.BMC cancer · 2025Article
- How will lung cancer screening and lung nodule management change the diagnostic and surgical lung cancer landscape?European respiratory review : an official journal of the European Respiratory Society · 2024Review
- Multitask connected U-Net: automatic lung cancer segmentation from CT images using PET knowledge guidance.Frontiers in artificial intelligence · 2024Article
- Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2024Review
- microRNAs in exhaled breath condensate for diagnosis of lung cancer in a resource-limited setting: a concise review.Breathe (Sheffield, England) · 2023Review
- From pre-COPD to COPD: a Simple, Low cost and easy to IMplement (SLIM) risk calculator.The European respiratory journal · 2023Article
- Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models.Sensors (Basel, Switzerland) · 2023Article
- Early detection and stratification of lung cancer aided by a cost-effective assay targeting circulating tumor DNA (ctDNA) methylation.Respiratory research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer accounts for an alarming human and economic burden in low- and middle-income countries (LMICs). Recent landmark trials from high-income countries (HICs) by demonstrating that low-dose computed tomography (LDCT) screening effectively reduces lung cancer mortality have engendered enthusiasm for this approach. Here we examine the effectiveness and affordability of LDCT screening from the viewpoint of LMICs. We consider resource-restricted perspectives and discuss implementation challenges and strategies to enhance the feasibility and cost-effectiveness of LDCT screening in LMICs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.