Evidence mapPaperPMID 39955522Full record

ArticleNutrition journal2025

Predictive effects of advanced lung cancer inflammation index and serum vitamin D on mortality in patients with asthma.

Ting Li, Qi Wang, Yuhan Li, Wenyong Zhang, Manyu Chen, Bihua Deng, Lin Liang, Weixian Lin, Yuying Lin, Ying Meng

Abstract read
In one paragraph

Article in Nutrition journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ting Li *Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Qi Wang *Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Yuhan LiThe Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510515, China.
Wenyong ZhangDepartment of Emergency Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Manyu ChenDepartment of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Bihua DengDepartment of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Lin LiangDepartment of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Weixian LinDepartment of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Yuying LinDepartment of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China.
Ying MengDepartment of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou North Road, Guangzhou, 510515, China. nfyymengy@163.com.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2014A030313269National College Students Innovation and Entrepreneurship Training Program 202312121006National Natural Science Foundation of China 82270089Southern Medical University Nanfang Hospital Education Research 22NJ-YB03
6 · The paper itself

Abstract

backgroundChanges in systemic inflammation, nutritional status and serum vitamin D level are important characteristics of asthma. However, role and importance of nutritional inflammatory indicators or serum vitamin D concentrations in predicting the prognosis of asthma remain unclear. The advanced lung cancer inflammation index (ALI), based on body mass index (BMI), serum albumin and neutrophil-lymphocyte ratio (NLR), is a comprehensive index to assess systemic inflammation and nutrition. This study aimed to evaluate their independent and combined predictive value of mortality in asthma patients.

methodsThis study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Cox regression analysis was used to assess the independent or joint effect of ALI and serum vitamin D on mortality risks of asthma. Receiver operator characteristic curve analysis was used to compare the prognostic ability of ALI with its component factors, including NLR, albumin, neutrophil, lymphocyte and BMI.

resultsA total of 2870 eligible asthma patients were included. After adjustment, higher ALI correlated significantly with reduced all-cause and respiratory disease mortality (adjusted hazard ratio [aHR] = 0.64 and 0.34; P < 0.05). Meanwhile, vitamin D deficiency correlated significantly with increased all-cause and respiratory disease mortality (aHR = 2.06 and 2.73; P < 0.05). The area under the curve of ALI in predicting 1-year, 5-year or 10-year all-cause mortality surpassed that of its five component indices. Joint analyses showed that individuals with higher levels of ALI and vitamin D had the lowest risks of all-cause and respiratory disease mortality (aHR = 0.31 and 0.17; P < 0.05).

conclusionsALI and serum vitamin D are robust independent and combined predictors of mortality in asthma patients. ALI offers superior predictive capability over its components, and sufficient vitamin D levels are beneficial for survival outcomes. The synergistic effect of high ALI and adequate vitamin D highlights the benefit of integrating both metrics into clinical practice for enhanced prognostic accuracy.

Indexed as

AsthmaInflammationLung NeoplasmsVitamin DAdultAgedBody Mass IndexFemaleHumansLymphocytesMaleMiddle AgedNeutrophilsNutritional StatusNutrition SurveysPredictive Value of TestsSerum AlbuminVitamin DAsthmaInflammation, Nutrition, Advanced lung cancer inflammation indexMortalityNHANESVitamin D

Identifiers

PMID39955522
PMCPMC11829343

What Socratic holds

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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.