Literature DB >> 21285969

That lung cancer incidence falls in ex-smokers: misconceptions 2.

J Peto.   

Abstract

Misconceptions and ill-founded theories can arise in all areas of science. However, the apparent accessibility of many epidemiology findings and popular interest in the subject can lead to additional misunderstandings. The article below continues an occasional series of short editorials highlighting some current misinterpretations of epidemiological findings. Invited authors will be given wide scope in judging the prevalence of the misconception under discussion. We hope that this series will prove instructive to cancer researchers in other disciplines as well as to students of epidemiology. Adrian L Harris and Leo Kinlen.

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Year:  2011        PMID: 21285969      PMCID: PMC3049571          DOI: 10.1038/sj.bjc.6606080

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


There is a widespread misconception in the general population, and even among some epidemiologists, that the incidence rate of lung cancer declines in ex-smokers. In fact, when smoking ceases, the rate stops increasing steeply and remains almost constant (Figure 1: Halpern ). This misconception presumably arose because the relative risk falls rapidly in ex-smokers, as it is calculated by dividing the roughly constant ex-smokers’ rate by the rising rate in non-smokers. (Whether the slight increase in incidence after stopping smoking is greater than the increase in non-smokers of the same age, as Figure 1 suggests, may never be known. Many ex-smokers relapse, and some may fail to admit it.) The lifelong increased risk in those who started smoking when they were very young indicates that smoking initiates lung carcinogenesis, but the incidence pattern in ex-smokers is particularly informative. The immediate effect of stopping suggests that smoking also acts at a late stage in carcinogenesis, but as the rate does not fall when smoking ceases it seems that the final event that a cell must undergo to become fully malignant is unaffected by smoking (Cairns, 2006). The age distribution of cancer, and particularly of lung cancer in smokers and non-smokers, led to multi-stage models of carcinogenesis long before altered genes were observed in human cancer (Armitage and Doll, 1954; Doll, 1978). Various alternative models have been proposed (Altshuler, 1989; Samet ), and which (if any) is correct must ultimately be decided from molecular rather than statistical studies. Molecular biologists should, however, be aware of these epidemiological observations, as they must be relevant to understanding the significance of the somatic changes in lung cancer that are now being discovered (Pleasance ).
Figure 1

Lung cancer mortality in continuing smokers, ex-smokers and non-smokers. Data from Halpern .

  7 in total

1.  Cancer and the immortal strand hypothesis.

Authors:  John Cairns
Journal:  Genetics       Date:  2006-11       Impact factor: 4.562

2.  Models of smoking and lung cancer risk: a means to an end.

Authors:  Jonathan M Samet; Michael J Thun; Amy Berrington de Gonzalez
Journal:  Epidemiology       Date:  2007-09       Impact factor: 4.822

Review 3.  An epidemiological perspective of the biology of cancer.

Authors:  R Doll
Journal:  Cancer Res       Date:  1978-11       Impact factor: 12.701

4.  Patterns of absolute risk of lung cancer mortality in former smokers.

Authors:  M T Halpern; B W Gillespie; K E Warner
Journal:  J Natl Cancer Inst       Date:  1993-03-17       Impact factor: 13.506

Review 5.  Quantitative models for lung cancer induced by cigarette smoke.

Authors:  B Altshuler
Journal:  Environ Health Perspect       Date:  1989-05       Impact factor: 9.031

6.  The age distribution of cancer and a multi-stage theory of carcinogenesis.

Authors:  P Armitage; R Doll
Journal:  Br J Cancer       Date:  2004-12-13       Impact factor: 7.640

7.  A small-cell lung cancer genome with complex signatures of tobacco exposure.

Authors:  Erin D Pleasance; Philip J Stephens; Sarah O'Meara; David J McBride; Alison Meynert; David Jones; Meng-Lay Lin; David Beare; King Wai Lau; Chris Greenman; Ignacio Varela; Serena Nik-Zainal; Helen R Davies; Gonzalo R Ordoñez; Laura J Mudie; Calli Latimer; Sarah Edkins; Lucy Stebbings; Lina Chen; Mingming Jia; Catherine Leroy; John Marshall; Andrew Menzies; Adam Butler; Jon W Teague; Jonathon Mangion; Yongming A Sun; Stephen F McLaughlin; Heather E Peckham; Eric F Tsung; Gina L Costa; Clarence C Lee; John D Minna; Adi Gazdar; Ewan Birney; Michael D Rhodes; Kevin J McKernan; Michael R Stratton; P Andrew Futreal; Peter J Campbell
Journal:  Nature       Date:  2009-12-16       Impact factor: 49.962

  7 in total
  6 in total

1.  From stem cells to the law courts: DNA methylation, the forensic epigenome and the possibility of a biosocial archive.

Authors:  Caroline L Relton; Fernando Pires Hartwig; George Davey Smith
Journal:  Int J Epidemiol       Date:  2015-08       Impact factor: 7.196

2.  Prediction of lung cancer risk based on age and smoking history.

Authors:  Jason H T Bates; Katharine L Hamlington; Garth Garrison; C Matthew Kinsey
Journal:  Comput Methods Programs Biomed       Date:  2022-01-25       Impact factor: 5.428

3.  That the effects of smoking should be measured in pack-years: misconceptions 4.

Authors:  J Peto
Journal:  Br J Cancer       Date:  2012-07-24       Impact factor: 7.640

Review 4.  Recognising Lung Cancer in Primary Care.

Authors:  Stephen H Bradley; Martyn P T Kennedy; Richard D Neal
Journal:  Adv Ther       Date:  2018-11-29       Impact factor: 3.845

5.  Life Course Tobacco Smoking and Risk of HPV-Negative Squamous Cell Carcinomas of Oral Cavity in Two Countries.

Authors:  Sreenath Madathil; Marie-Claude Rousseau; Doris Durán; Babatunde Y Alli; Lawrence Joseph; Belinda Nicolau
Journal:  Front Oral Health       Date:  2022-03-30

6.  Quantification of the smoking-associated cancer risk with rate advancement periods: meta-analysis of individual participant data from cohorts of the CHANCES consortium.

Authors:  José Manuel Ordóñez-Mena; Ben Schöttker; Ute Mons; Mazda Jenab; Heinz Freisling; Bas Bueno-de-Mesquita; Mark G O'Doherty; Angela Scott; Frank Kee; Bruno H Stricker; Albert Hofman; Catherine E de Keyser; Rikje Ruiter; Stefan Söderberg; Pekka Jousilahti; Kari Kuulasmaa; Neal D Freedman; Tom Wilsgaard; Lisette Cpgm de Groot; Ellen Kampman; Niclas Håkansson; Nicola Orsini; Alicja Wolk; Lena Maria Nilsson; Anne Tjønneland; Andrzej Pająk; Sofia Malyutina; Růžena Kubínová; Abdonas Tamosiunas; Martin Bobak; Michail Katsoulis; Philippos Orfanos; Paolo Boffetta; Antonia Trichopoulou; Hermann Brenner
Journal:  BMC Med       Date:  2016-04-05       Impact factor: 8.775

  6 in total

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