Evidence map›Paper›PMID 39507019›Full record

ArticleTranslational lung cancer research2024

Exposure-lag response of surface net solar radiation on lung cancer incidence: a global time-series analysis.

Xuanzhuang Lu, Runchen Wang, Jianfu Li, Shixuan Lyu, Jianrong Zhang, Qixia Wang, Wenhao Chi, Ran Zhong, Chao Chen, Xinjian Wu and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational lung cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Effects of shortZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

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

19 authors.

Xuanzhuang Lu *Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Runchen Wang *Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Jianfu Li *Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Shixuan Lyu *Department of Civil Engineering, University of Bristol, Bristol, UK.
Jianrong Zhang *Centre for Cancer Research & Department of General Practice, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
Qixia Wang *Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Wenhao ChiAcademy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
Ran ZhongDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Chao ChenDepartment of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Xinjian WuDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Ruiyu HuDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Zhixuan YouDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Yuqi MaiFirst Clinical School, Guangzhou Medical University, Guangzhou, China.
Songlin XieNanshan School, Guangzhou Medical University, Guangzhou, China.
Jiayu LinNanshan School, Guangzhou Medical University, Guangzhou, China.
Boyu ZhengNanshan School, Guangzhou Medical University, Guangzhou, China.
Qiu ZhongNanshan School, Guangzhou Medical University, Guangzhou, China.
Jianxing HeDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Wenhua LiangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recently, the impact of solar radiation (RAD) on diseases worldwide has garnered growing attention. However, the association between RAD and lung cancer remains largely unknow and no consensus has been reached. The aim of this study was to investigate the lag exposure-response of RAD on lung cancer and provide robust scientific evidence for updating prevention and treatment strategies of lung cancer. Methods: Data of RAD were obtained from Google Earth Engine, which was post-processed by European Centre for Medium-Range Weather Forecasts (ECMWF). Lung cancer incidence, smoking prevalence and socio-demographic index (SDI) were obtained from Global Burden of Disease (GBD). Spearman's rank correlation tests and linear regression analyses were performed to investigate the relationship between RAD and lung cancer incidence. Additionally, a distributed lag non-linear model (DLNM) was utilized to reveal the lag effects of RAD on lung cancer incidence. Results: There were 204 countries and territories and selected subnational locations with information recorded in GBD and radiation exposure was calculated in 272 countries and territories. After excluding missing and abnormal data, as well as Kashmir and Western Sahara which were two disputed districts, this study included 186 countries from 1992 to 2019. After adjusted for smoking and SDI, the Spearman's correlation coefficient ranged from -0.630 to -0.581. In the DLNM for lung cancer adjusted for smoking and SDI, the maximum relative risk (RR) was 1.013 [95% confidence interval (CI): 1.011-1.014], at RAD exposure of 12,760,000 with 5.8 lag years, while the minimum RR was 0.973 (95% CI: 0.947-0.992) at RAD exposure of 12,845,000 with 8.0 lag years. Conclusions: The global rise in lung cancer incidence has been notably associated with low exposure to RAD, whereas the defensive influence of sunlight against lung cancer demonstrated hysteresis. This study shows that properly exposure to sunlight is a possible strategy for lung cancer prevention, which provides scientific support for the formulation of future health strategies. It is also crucial in epidemiological research as it offers a novel pattern for identifying additional potential risk factors for diseases.

Indexed as

distributed lag non-linear model (DLNM)Google Earth Enginelung cancerSolar radiation (RAD)vitamin D

Identifiers

PMID39507019
PMCPMC11535824

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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 OpenQuestion graph.