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Open Access Highly Accessed Research article

Systematic review with meta-analysis of the epidemiological evidence relating FEV1 decline to lung cancer risk

John S Fry, Jan S Hamling and Peter N Lee*

Author Affiliations

P N Lee Statistics and Computing Ltd, Sutton, Surrey, United Kingdom

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BMC Cancer 2012, 12:498  doi:10.1186/1471-2407-12-498

Published: 27 October 2012

Abstract

Background

Reduced FEV1 is known to predict increased lung cancer risk, but previous reviews are limited. To quantify this relationship more precisely, and study heterogeneity, we derived estimates of β for the relationship RR(diff) = exp(βdiff), where diff is the reduction in FEV1 expressed as a percentage of predicted (FEV1%P) and RR(diff) the associated relative risk. We used results reported directly as β, and as grouped levels of RR in terms of FEV1%P and of associated measures (e.g. FEV1/FVC).

Methods

Papers describing cohort studies involving at least three years follow-up which recorded FEV1 at baseline and presented results relating lung cancer to FEV1 or associated measures were sought from Medline and other sources. Data were recorded on study design and quality and, for each data block identified, on details of the results, including population characteristics, adjustment factors, lung function measure, and analysis type. Regression estimates were converted to β estimates where appropriate. For results reported by grouped levels, we used the NHANES III dataset to estimate mean FEV1%P values for each level, regardless of the measure used, then derived β using regression analysis which accounted for non-independence of the RR estimates. Goodness-of-fit was tested by comparing observed and predicted lung cancer cases for each level. Inverse-variance weighted meta-analysis allowed derivation of overall β estimates and testing for heterogeneity by factors including sex, age, location, timing, duration, study quality, smoking adjustment, measure of FEV1 reported, and inverse-variance weight of β.

Results

Thirty-three publications satisfying the inclusion/exclusion criteria were identified, seven being rejected as not allowing estimation of β. The remaining 26 described 22 distinct studies, from which 32 independent β estimates were derived. Goodness-of-fit was satisfactory, and exp(β), the RR increase per one unit FEV1%P decrease, was estimated as 1.019 (95%CI 1.016-1.021). The estimates were quite consistent (I2 =29.6%). Mean age was the only independent source of heterogeneity, exp(β) being higher for age <50 years (1.024, 1.020-1.028).

Conclusions

Although the source papers present results in various ways, complicating meta-analysis, they are very consistent. A decrease in FEV1%P of 10% is associated with a 20% (95%CI 17%-23%) increase in lung cancer risk.