ArticleHuman mutation2026
Disentangling Links Between Lung Cancer and Infectious Pneumonia via Real-World Data and Integrative Genomics.
Article in Human mutation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Disentangling Links Between Lung Cancer and Infectious Pneumonia via Real-World Data and Integrative Genomics.Human mutation · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer (LC) patients frequently develop infectious pneumonia, often leading to suspension of anticancer therapy, yet the impact of LC on pneumonia progression remains unclear. This study employed a multidimensional approach to investigate whether LC constitutes a critical factor contributing to pulmonary infection onset and adverse short-term outcomes. Data from two intensive care unit databases were analyzed to assess the association between LC and pneumonia incidence and prognosis from a real-world perspective, with Mendelian randomization (MR) applied to validate causality. Additionally, post-GWAS analyses were conducted to explore comorbidity interaction patterns and potential shared therapeutic targets. Cross-sectional and cohort analyses identified LC as an independent risk factor for infectious pneumonia development and 28-day mortality, findings corroborated by sensitivity analyses across multiple models and datasets. Meta-analysis of MR results demonstrated causal relationships between genetically predicted LC and both pneumonia risk (OR = 1.103, 95% CI: 1.031-1.181,
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Registered trials
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