Copyright ©2013 Baishideng. All rights reserved.
World J Meta-Anal. Aug 26, 2013; 1(2): 57-77
Published online Aug 26, 2013. doi: 10.13105/wjma.v1.i2.57
Dose-response relationship of lung cancer to amount smoked, duration and age starting
John S Fry, Peter N Lee, Barbara A Forey, Katharine J Coombs
John S Fry, Peter N Lee, Barbara A Forey, Katharine J Coombs, PN Lee Statistics and Computing Ltd., Sutton, Surrey SM2 5DA, United Kingdom
Author contributions: Lee PN, Fry JS and Forey BA planned the study; Literature searches were carried out by Coombs KJ, assisted by Lee PN and Forey BA; Data entry was carried out by Coombs KJ and checked by Forey BA, or carried out by Forey BA and checked by Lee PN; Where appropriate, difficulties in interpreting published data or in the appropriate methods for derivation of RRs were discussed by Forey BA and Lee PN; The statistical analyses were conducted by Fry JS along lines discussed and agreed with Lee PN; Lee PN and Fry JS jointly drafted the paper, which was critically reviewed by Forey BA and Coombs KJ.
Supported by Philip Morris Products SA
Correspondence to: Peter N Lee, MA, Director, PN Lee Statistics and Computing Ltd., 17 Cedar Road, Sutton, Surrey SM2 5DA, United Kingdom.
Telephone: +44-20-86428265 Fax: +44-20-86422135
Received: April 2, 2013
Revised: May 9, 2013
Accepted: August 4, 2013
Published online: August 26, 2013

AIM: To quantify smoking/lung cancer relationships accurately using parametric modelling.

METHODS: Using the International Epidemiological Studies on Smoking and Lung Cancer database of all epidemiological studies of 100+ lung cancer cases published before 2000, we analyzed 97 blocks of data for amount smoked, 35 for duration of smoking, and 27 for age started. Pseudo-numbers of cases and controls (or at risk) estimated from RRs by dose level formed the data modelled. We fitted various models relating loge RR to dose (d), including βd, βdY and βloge (1 + Wd), and investigated goodness-of-fit and heterogeneity between studies.

RESULTS: The best-fitting models for loge RR were 0.833 loge [1 + (8.1c/10)] for cigarettes/d (c), 0.792 (y/10)0.74 for years smoked (y) and 0.176 [(70 - a)/10]1.44 for age of start (a). Each model fitted well overall, though some blocks misfitted. RRs rose from 3.86 to 22.31 between c = 10 and 50, from 2.21 to 13.54 between y = 10 and 50, and from 3.66 to 8.94 between a = 30 and 12.5. Heterogeneity (P < 0.001) existed by continent for amount, RRs for 50 cigarettes/d being 7.23 (Asia), 26.36 (North America) and 22.16 (Europe). Little heterogeneity was seen for duration of smoking or age started.

CONCLUSION: The models describe the dose-relationships well, though may be biased by factors including misclassification of smoking status and dose.

Keywords: Smoking, Lung neoplasms, Dose-response, Meta-analysis, Review, Amount smoked, Duration of smoking, Age at starting to smoke

Core tip: This paper, for the first time, meta-analyses smoking/lung cancer dose-relationships. Based on data from 71 studies published before 2000, single parameter models were fitted to summarize how the RR increased with increasing amount smoked, longer duration of smoking, and earlier age of starting to smoke. Overall, the models fitted well. Little heterogeneity was seen for duration of smoking or age of start, but the rise in RR with amount smoked was much steeper in North America and Europe than in Asia. The fitted models can be used to more precisely estimate the lung cancer risk from smoking.