Smoking Is Associated With COVID-19 Progression: A Meta-analysis

  1. Roengrudee Patanavanich
  2. Stanton A Glantz

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Abstract

Introduction

Smoking depresses pulmonary immune function and is a risk factor contracting other infectious diseases and more serious outcomes among people who become infected. This paper presents a meta-analysis of the association between smoking and progression of the infectious disease COVID-19.

Methods

PubMed was searched on April 28, 2020, with search terms “smoking”, “smoker*”, “characteristics”, “risk factors”, “outcomes”, and “COVID-19”, “COVID”, “coronavirus”, “sar cov-2”, “sar cov 2”. Studies reporting smoking behavior of COVID-19 patients and progression of disease were selected for the final analysis. The study outcome was progression of COVID-19 among people who already had the disease. A random effects meta-analysis was applied.

Results

We identified 19 peer-reviewed papers with a total of 11,590 COVID-19 patients, 2,133 (18.4%) with severe disease and 731 (6.3%) with a history of smoking. A total of 218 patients with a history of smoking (29.8%) experienced disease progression, compared with 17.6% of non-smoking patients. The meta-analysis showed a significant association between smoking and progression of COVID-19 (OR 1.91, 95% confidence interval [CI] 1.42-2.59, p = 0.001). Limitations in the 19 papers suggest that the actual risk of smoking may be higher.

Conclusions

Smoking is a risk factor for progression of COVID-19, with smokers having higher odds of COVID-19 progression than never smokers.

Implications

Physicians and public health professionals should collect data on smoking as part of clinical management and add smoking cessation to the list of practices to blunt the COVID-19 pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.13.20063669: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We conducted a systematic search using PubMed database on April 6, 2020, with the search term: ((smoking) OR (characteristics) OR (risk factors) OR (outcomes) OR (smoker*)) AND ((COVID-19) OR (COVID) OR (coronavirus) OR (sars cov-2) OR (sars cov 2)) for studies published between January 1, 2020 and April 6, 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. The definition of “smoking” sometimes includes former smokers and sometimes does not. Only three studies9,16,19 separated current and former smokers in different categories, which was not enough data to do a meta-analysis for current and former smokers separately. Because the lung recovers after someone stops smoking, including former smokers in the exposed group biases the effect estimate to the null. Reported smoking prevalence patients in all studies was substantially below smoking prevalence in the corresponding populations. Smoking prevalence in the 10 studies in China ranged from 3.8% to 14.6% vs 27.7% (52.1% for men and 2.7% for women) in the population in 2015,20 18.5% in the Korean patients vs. 21.1%21 (37.0% for men and 5.2% for women) in 2017, and 3.6% in the US patients vs. 13.7%22 (15.6% for men and 12.0% for women) in 2018. It is highly likely that many smokers were misclassified as nonsmokers, which also biases the risk estimate toward the null. We computed and assessed unadjusted odds ratios based on the numbers of patients reported in the studies. Only one11 of the studies reported unadjusted and adjusted ORs using multivariate analysis; after adjusting for confounding, the effect of smoking on disease severity was higher (unadjusted: OR 12.19, 95% CI 1.76-84.31, p=0.011; adjusted: OR 14.29, 95% CI 1.58-25.0, p=0.018). None of these studies assessed e-cigarette use. All these limitations suggest that this analysis underestim...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1093/ntr/ntaa082
  3. Version published to 10.1101/2020.04.13.20063669v1 on medRxiv