Evidence map›Paper›PMID 37410540›Full record

ArticleCancer communications (London, England)2023

Lung cancer risk score for ever and never smokers in China.

Zhimin Ma, Jun Lv, Meng Zhu, Canqing Yu, Hongxia Ma, Guangfu Jin, Yu Guo, Zheng Bian, Ling Yang, Yiping Chen and 4 more

Abstract read
In one paragraph

Article in Cancer communications (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
–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

22 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Risk prediction for lung cancer screening: a systematic review and meta-regression.European respiratory review : an official journal of the European Respiratory Society · 2026
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  5. Inhibition of RAB7 promotes CD8American journal of cancer research · 2026
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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

14 authors.

Zhimin MaDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Jun LvDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, P. R. China.
Meng ZhuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Canqing YuDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, P. R. China.
Hongxia MaDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.ORCID 0000-0002-2462-9693
Guangfu JinDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Yu GuoChinese Academy of Medical Sciences, Beijing, P. R. China.
Zheng BianChinese Academy of Medical Sciences, Beijing, P. R. China.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK.
Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK.
Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK.
Zhibin HuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.ORCID 0000-0002-8277-5234
Liming LiDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, P. R. China.
Hongbing ShenDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.ORCID 0000-0002-2581-5906

Funding

Cancer Research UK 29186Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Wellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundMost lung cancer risk prediction models were developed in European and North-American cohorts of smokers aged ≥ 55 years, while less is known about risk profiles in Asia, especially for never smokers or individuals aged < 50 years. Hence, we aimed to develop and validate a lung cancer risk estimate tool for ever and never smokers across a wide age range.

methodsBased on the China Kadoorie Biobank cohort, we first systematically selected the predictors and explored the nonlinear association of predictors with lung cancer risk using restricted cubic splines. Then, we separately developed risk prediction models to construct a lung cancer risk score (LCRS) in 159,715 ever smokers and 336,526 never smokers. The LCRS was further validated in an independent cohort over a median follow-up of 13.6 years, consisting of 14,153 never smokers and 5,890 ever smokers.

resultsA total of 13 and 9 routinely available predictors were identified for ever and never smokers, respectively. Of these predictors, cigarettes per day and quit years showed nonlinear associations with lung cancer risk (P

conclusionsThe LCRS can be an effective risk assessment tool designed for ever and never smokers aged 30 to 80 years.

Indexed as

Lung NeoplasmsSmokingChinaHumansRisk FactorsSmokersearly-onset cancerlung cancerlung cancer screeningnever smokersprediction model

Identifiers

PMID37410540
PMCPMC10397566

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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.