Literature DB >> 23700026

Competing risk bias to explain the inverse relationship between smoking and malignant melanoma.

Caroline A Thompson1, Zuo-Feng Zhang, Onyebuchi A Arah.   

Abstract

The relationship between smoking and melanoma remains unclear. Among the different results is the paradoxical finding that smoking was shown to be inversely associated with the risk of malignant melanoma in some large cohort and case-control studies, even after control for suspected confounding variables. Smoking is a known risk factor for many non-communicable diseases, including coronary heart disease, stroke, as well as other malignancies; it has been shown to be positively associated with other types of skin cancer, and there remains no clear biologic explanation for a possible protective effect on malignant melanoma. In this paper, we propose a plausible mechanism of bias from smoking-related competing risks that may explain or contribute to the inverse association between smoking and melanoma as spurious. Using directed acyclic graphs for formalization and visualization of assumptions, and Monte Carlo simulation techniques, we demonstrate how published inverse associations might be compatible with selection bias resulting from uncontrolled or unmeasured common causes of competing outcomes of smoking-related diseases and malignant melanoma. We present results from various scenarios assuming a true null as well as a true positive association between smoking and malignant melanoma. Under a true null assumption, we find inverse associations due to the biasing mechanism to be compatible with published results in the literature, especially after the addition of unmeasured confounding variables. This study could be seen as offering a cautionary note in the interpretation of published smoking-melanoma findings.

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Year:  2013        PMID: 23700026      PMCID: PMC3864891          DOI: 10.1007/s10654-013-9812-0

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  33 in total

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Journal:  Stat Med       Date:  1999-03-30       Impact factor: 2.373

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Journal:  Epidemiology       Date:  1999-01       Impact factor: 4.822

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Journal:  Int J Cancer       Date:  1997-05-16       Impact factor: 7.396

6.  The risk for cutaneous malignant melanoma, melanoma in situ and intraocular malignant melanoma in relation to tobacco use and body mass index.

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Journal:  Epidemiology       Date:  2008-09       Impact factor: 4.822

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Journal:  Int J Epidemiol       Date:  1995-06       Impact factor: 7.196

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Journal:  Br J Cancer       Date:  1996-05       Impact factor: 7.640

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  20 in total

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Authors:  Albert Hofman; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; M Arfan Ikram; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Ch Stricker; Henning W Tiemeier; André G Uitterlinden; Meike W Vernooij
Journal:  Eur J Epidemiol       Date:  2015-09-19       Impact factor: 8.082

2.  Bias Due to Confounders for the Exposure-Competing Risk Relationship.

Authors:  Catherine R Lesko; Bryan Lau
Journal:  Epidemiology       Date:  2017-01       Impact factor: 4.822

3.  Analyzing Selection Bias for Credible Causal Inference: When in Doubt, DAG It Out.

Authors:  Onyebuchi A Arah
Journal:  Epidemiology       Date:  2019-07       Impact factor: 4.822

4.  Diet Quality and Risk of Melanoma in an Italian Population.

Authors:  Carlotta Malagoli; Marcella Malavolti; Claudia Agnoli; Catherine M Crespi; Chiara Fiorentini; Francesca Farnetani; Caterina Longo; Cinzia Ricci; Giuseppe Albertini; Anna Lanzoni; Leonardo Veneziano; Annarosa Virgili; Calogero Pagliarello; Marcello Santini; Pier Alessandro Fanti; Emi Dika; Sabina Sieri; Vittorio Krogh; Giovanni Pellacani; Marco Vinceti
Journal:  J Nutr       Date:  2015-06-24       Impact factor: 4.798

5.  History of Keratinocyte Carcinoma and Risk of Melanoma: A Prospective Cohort Study.

Authors:  Shaowei Wu; Eunyoung Cho; Wen-Qing Li; Abrar A Qureshi
Journal:  J Natl Cancer Inst       Date:  2017-04-01       Impact factor: 13.506

6.  The Impact of Smoking on Sentinel Node Metastasis of Primary Cutaneous Melanoma.

Authors:  Maris S Jones; Peter C Jones; Stacey L Stern; David Elashoff; Dave S B Hoon; John Thompson; Nicola Mozzillo; Omgo E Nieweg; Dirk Noyes; Harald J Hoekstra; Jonathan S Zager; Daniel F Roses; Alessandro Testori; Brendon J Coventry; Mark B Smithers; Robert Andtbacka; Doreen Agnese; Erwin Schultz; Eddy C Hsueh; Mark Kelley; Schlomo Schneebaum; Lisa Jacobs; Tawnya Bowles; Mohammed Kashani-Sabet; Douglas Johnson; Mark B Faries
Journal:  Ann Surg Oncol       Date:  2017-02-21       Impact factor: 5.344

Review 7.  Bias from conditioning on live birth in pregnancy cohorts: an illustration based on neurodevelopment in children after prenatal exposure to organic pollutants.

Authors:  Zeyan Liew; Jørn Olsen; Xin Cui; Beate Ritz; Onyebuchi A Arah
Journal:  Int J Epidemiol       Date:  2015-01-19       Impact factor: 7.196

Review 8.  Top ten errors of statistical analysis in observational studies for cancer research.

Authors:  A Carmona-Bayonas; P Jimenez-Fonseca; A Fernández-Somoano; F Álvarez-Manceñido; E Castañón; A Custodio; F A de la Peña; R M Payo; L P Valiente
Journal:  Clin Transl Oncol       Date:  2017-12-07       Impact factor: 3.405

9.  Causal inference in the face of competing events.

Authors:  Jacqueline E Rudolph; Catherine R Lesko; Ashley I Naimi
Journal:  Curr Epidemiol Rep       Date:  2020-07-12

10.  Left truncation bias as a potential explanation for the protective effect of smoking on preeclampsia.

Authors:  Sarka Lisonkova; K S Joseph
Journal:  Epidemiology       Date:  2015-05       Impact factor: 4.822

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