Evidence map›Paper›PMID 40361147›Full record

ArticleHarm reduction journal2025

Comparing smoking-related disease rates from e-cigarette use with those from tobacco cigarette use: a reanalysis of a recently-published study.

Peter N Lee, Konstantinos Farsalinos

Abstract readComparative StudyLetter
In one paragraph

Article in Harm reduction journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

2 authors.

Peter N LeeP.N.Lee Statistics and Computing Ltd, 17 Cedar Road, Sutton, SM2 5DA, UK.
Konstantinos FarsalinosUniversity of West Attica, Agiou Spiridinos, Egaleo, 12243, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA recent meta-analysis by Glantz et al. combined odds ratios (ORs) relating e-cigarette use (vaping) to cardiovascular disease, stroke, chronic obstructive pulmonary disease (COPD) and other endpoints. They assessed all included studies as having a low risk of bias, and concluded that vaping and smoking have a "comparable" disease odds, with dual use associated with more risk than smoking.

aimTo examine the accuracy of these conclusions, giving particular attention to myocardial infarction (MI), stroke and COPD.

methodsWe determined (1) whether the pooled random-effect estimates were correctly calculated from the ORs included, (2) whether the detailed outcomes were correctly described and appropriate and whether additional OR estimates could have been included from the studies considered, (3) whether the data were correctly extracted from the source papers, (4) whether some studies should definitely or possibly have been excluded, (5) what the pooled OR estimates were for MI, stroke and COPD after excluding definitely invalid results and restricting attention to data based on appropriate disease definitions, (6) how estimates of the excess risk (ER = OR - 1) for vaping compare to those we estimate for quitting, (7) whether various sources of bias were adequately accounted for, and (8) whether conclusions were confirmed in studies where reverse causation was not an issue, i.e. where disease onset could not have preceded uptake of vaping.

resultsWe found no major issues regarding pooled estimation, description of diagnoses and extraction of data from the source papers, but some studies should have been excluded, and one further result was available for MI. Using data appropriately extracted for valid diagnoses, we derived pooled OR estimates for vaping vs. smoking of 0.48 (95%CI: 0.35-0.67) for MI, 0.65 (0.49-0.86) for stroke and 0.46 (0.35-0.60) for COPD. These showed a significantly reduced risk for vaping, similar to or lower than expected for quitting smoking for 5 to 10 years, highly relevant given the short period of vaping following earlier smoking for most study participants. For dual use vs. smoking, pooled OR estimates were 1.41 (1.18-1.68) for MI, 1.39 (1.06-1.82) for stroke and 1.32 (1.17-1.50) for COPD. The studies considered were predominantly cross-sectional so could not account for reverse causation, or for those who smoked and became dual users possibly having smoked more cigarettes or smoked for a longer period than those not doing so. Only three publications accounted for reverse causation, each using the same data source, and each found a significant effect of smoking, but not vaping, on the diseases considered.

conclusionThe claim in the original meta-analysis that the studies had a low risk of bias is demonstrably incorrect, and even the biased data suggests that switching to e-cigarettes may reduce disease risk similarly to quitting. Biases may also explain the somewhat higher risk observed in those who smoked and vaped than in those smoking exclusively. Very limited unbiased data found no significant effect of vaping on the diseases considered. Though more good studies are urgently needed, the conclusions of Glantz et al. are not supported by the currently available evidence.

Indexed as

Cardiovascular DiseasesElectronic Nicotine Delivery SystemsMyocardial InfarctionPulmonary Disease, Chronic ObstructiveStrokeVapingHumansMeta-Analysis as TopicOdds RatioBiasCigarettesCOPDDual useE-cigarettesMeta-analysisMyocardial infarctionSmokingStroke

Identifiers

PMID40361147
PMCPMC12070775

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.