Lung Cancer in Patients of African Descent: A Transcontinental Review of Epidemiology, Disparities, Outcomes, and Opportunities for Equity in Africa, North America, South America, and the Caribbean
Bibliographic record
Abstract
Lung cancer in people of African descent is characterized by transcontinental disparities driven by epidemiologic heterogeneity, systemic inequities, and unequal access to health care. Globally, lung cancer incidence and mortality rates vary; however, underdiagnosis and late-stage presentation in low- and middle-income countries obscure the true prevalence of lung cancer because of limited cancer registries and diagnostic infrastructure. In Africa, most patients with lung cancer present at an advanced stage, primarily because of health illiteracy, misdiagnosis, delayed referrals, and inadequate treatment infrastructure. Although tobacco smoking remains a dominant risk factor worldwide, African populations are disproportionately exposed to environmental and occupational hazards, which substantially elevate their lung cancer risk. In North America, Black people experience disproportionately poor outcomes, including lower rates of lung cancer screening, early diagnosis, surgical intervention, and higher mortality rates compared with their White counterparts. In the Caribbean and South America, Black people continue to face racial infrastructural constraints, racial inequities, and elevated exposure to environmental and occupational carcinogens. Systemic barriers perpetuate these disparities, including limited access to screening, genomic testing, and guideline-concordant therapies. Achieving equity in lung cancer outcomes requires strategic initiatives, including the expansion of lung cancer registries in Africa, the Caribbean, and South America, to inform evidence-based interventions. Urgent national and international measures focused on prevention and care for populations of African descent, implementing robust tobacco control policies, addressing systemic and racial inequities, and strengthening health care systems to report and manage lung cancer efficiently are essential steps toward reducing disparities. A transcontinental collaborative approach that includes establishing lung cancer research consortia is vital to share best practices in screening protocols, optimize early detection strategies and treatment, and advocate for policy reforms that address the global burden of lung cancer in populations of African descent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".