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Estimating Preventable Fractions of Disease Caused by a Specified Biological Mechanism: PAHs in Smoking Lung Cancers as an Example
Epidemiology textbooks often interpret population attributable fractions based on 2 × 2 tables or logistic regression models of exposure‐response associations as preventable fractions, i.e., as fractions of illnesses in a population that would be prevented if exposure were removed. In general, this...
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Published in: | Risk analysis 2006-08, Vol.26 (4), p.881-892 |
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description | Epidemiology textbooks often interpret population attributable fractions based on 2 × 2 tables or logistic regression models of exposure‐response associations as preventable fractions, i.e., as fractions of illnesses in a population that would be prevented if exposure were removed. In general, this causal interpretation is not correct, since statistical association need not indicate causation; moreover, it does not identify how much risk would be prevented by removing specific constituents of complex exposures. This article introduces and illustrates an approach to calculating useful bounds on preventable fractions, having valid causal interpretations, from the types of partial but useful molecular epidemiological and biological information often available in practice. The method applies probabilistic risk assessment concepts from systems reliability analysis, together with bounding constraints for the relationship between event probabilities and causation (such as that the probability that exposure X causes response Y cannot exceed the probability that exposure X precedes response Y, or the probability that both X and Y occur) to bound the contribution to causation from specific causal pathways. We illustrate the approach by estimating an upper bound on the contribution to lung cancer risk made by a specific, much‐discussed causal pathway that links smoking to a polycyclic aromatic hydrocarbon (PAH) (specifically, benzo(a)pyrene diol epoxide–DNA) adducts at hot spot codons at p53 in lung cells. The result is a surprisingly small preventable fraction (of perhaps 7% or less) for this pathway, suggesting that it will be important to consider other mechanisms and non‐PAH constituents of tobacco smoke in designing less risky tobacco‐based products. |
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We illustrate the approach by estimating an upper bound on the contribution to lung cancer risk made by a specific, much‐discussed causal pathway that links smoking to a polycyclic aromatic hydrocarbon (PAH) (specifically, benzo(a)pyrene diol epoxide–DNA) adducts at hot spot codons at p53 in lung cells. 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In general, this causal interpretation is not correct, since statistical association need not indicate causation; moreover, it does not identify how much risk would be prevented by removing specific constituents of complex exposures. This article introduces and illustrates an approach to calculating useful bounds on preventable fractions, having valid causal interpretations, from the types of partial but useful molecular epidemiological and biological information often available in practice. The method applies probabilistic risk assessment concepts from systems reliability analysis, together with bounding constraints for the relationship between event probabilities and causation (such as that the probability that exposure X causes response Y cannot exceed the probability that exposure X precedes response Y, or the probability that both X and Y occur) to bound the contribution to causation from specific causal pathways. We illustrate the approach by estimating an upper bound on the contribution to lung cancer risk made by a specific, much‐discussed causal pathway that links smoking to a polycyclic aromatic hydrocarbon (PAH) (specifically, benzo(a)pyrene diol epoxide–DNA) adducts at hot spot codons at p53 in lung cells. The result is a surprisingly small preventable fraction (of perhaps 7% or less) for this pathway, suggesting that it will be important to consider other mechanisms and non‐PAH constituents of tobacco smoke in designing less risky tobacco‐based products.</description><subject>7,8-Dihydro-7,8-dihydroxybenzo(a)pyrene 9,10-oxide - metabolism</subject><subject>Cancer</subject><subject>Causality</subject><subject>DNA Adducts - drug effects</subject><subject>DNA Adducts - metabolism</subject><subject>Epidemiology</subject><subject>Estimation</subject><subject>Genes, p53 - drug effects</subject><subject>Humans</subject><subject>Lung cancer</subject><subject>Lung Neoplasms - etiology</subject><subject>Lung Neoplasms - genetics</subject><subject>Lung Neoplasms - metabolism</subject><subject>Lung Neoplasms - prevention & control</subject><subject>Medical research</subject><subject>Models, Biological</subject><subject>Models, Statistical</subject><subject>Mutation</subject><subject>PAH</subject><subject>Polycyclic aromatic hydrocarbons</subject><subject>Polycyclic Aromatic Hydrocarbons - toxicity</subject><subject>population attributable fraction</subject><subject>preventable fraction</subject><subject>Probability</subject><subject>Regression analysis</subject><subject>Risk Assessment</subject><subject>Smoking</subject><subject>Smoking - adverse effects</subject><subject>Statistical analysis</subject><subject>Studies</subject><issn>0272-4332</issn><issn>1539-6924</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><recordid>eNqNkU9v0zAYhy0EYmXwFZDFgVuCE-d1YiQOpbTboMCgQxwtx3093OVPiRNor3xyHFoNicuwLNtRnt9Pth5CaMLiJIwXmzgBLiMh0yxOGRMxY3kB8e4emdz-uE8mLM3TKOM8PSGPvN8wljAG-UNykgiZFaLgE_Jr7ntX69411_Sywx_Y9LqskC46bXrXNp62lr5xHrVHOtODxzUt91TT1RaNsy58vnZt1V47oyv6Hs033Thfv6SX03NPXUNXdXszli-HsMx0Y7DzVIfZ0PlO19sKH5MHVlcenxz3U_JlMb-anUfLj2cXs-kyMpACRKIwCBmWqS2t5GkGpigzBgCFhcQyjnmJUloLvMj1GjnPClmuoeQapdG24Kfk-aF327XfB_S9qp03WFW6wXbwigsQIEHeDXLgQgh2J5hICBfNRQCf_QNu2qFrwmtVynKRJ1k2QsUBMl3rfYdWbbugpturhKlRu9qo0a4a7apRu_qjXe1C9OmxfyhrXP8NHj0H4NUB-Okq3P93sfp8sZqGU8hHh7zzPe5u87q7USLnOaivH87U8lOyulq8e6uA_waPcMpz</recordid><startdate>200608</startdate><enddate>200608</enddate><creator>Cox Jr, Louis Anthony (Tony)</creator><creator>Sanders, Edward</creator><general>Blackwell Publishing Inc</general><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U7</scope><scope>7U9</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>FQK</scope><scope>FR3</scope><scope>H94</scope><scope>JBE</scope><scope>JQ2</scope><scope>KR7</scope><scope>M7N</scope><scope>SOI</scope><scope>7T2</scope><scope>7U1</scope><scope>7U2</scope><scope>F28</scope></search><sort><creationdate>200608</creationdate><title>Estimating Preventable Fractions of Disease Caused by a Specified Biological Mechanism: PAHs in Smoking Lung Cancers as an Example</title><author>Cox Jr, Louis Anthony (Tony) ; Sanders, Edward</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5255-68ce54eb2fbf93245c8b405558f51f03e7be99ff5387ade33489bd5b3ae9caf83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>7,8-Dihydro-7,8-dihydroxybenzo(a)pyrene 9,10-oxide - metabolism</topic><topic>Cancer</topic><topic>Causality</topic><topic>DNA Adducts - drug effects</topic><topic>DNA Adducts - metabolism</topic><topic>Epidemiology</topic><topic>Estimation</topic><topic>Genes, p53 - drug effects</topic><topic>Humans</topic><topic>Lung cancer</topic><topic>Lung Neoplasms - etiology</topic><topic>Lung Neoplasms - genetics</topic><topic>Lung Neoplasms - metabolism</topic><topic>Lung Neoplasms - prevention & control</topic><topic>Medical research</topic><topic>Models, Biological</topic><topic>Models, Statistical</topic><topic>Mutation</topic><topic>PAH</topic><topic>Polycyclic aromatic hydrocarbons</topic><topic>Polycyclic Aromatic Hydrocarbons - toxicity</topic><topic>population attributable fraction</topic><topic>preventable fraction</topic><topic>Probability</topic><topic>Regression analysis</topic><topic>Risk Assessment</topic><topic>Smoking</topic><topic>Smoking - adverse effects</topic><topic>Statistical analysis</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cox Jr, Louis Anthony (Tony)</creatorcontrib><creatorcontrib>Sanders, Edward</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Environment Abstracts</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>Risk analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cox Jr, Louis Anthony (Tony)</au><au>Sanders, Edward</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating Preventable Fractions of Disease Caused by a Specified Biological Mechanism: PAHs in Smoking Lung Cancers as an Example</atitle><jtitle>Risk analysis</jtitle><addtitle>Risk Anal</addtitle><date>2006-08</date><risdate>2006</risdate><volume>26</volume><issue>4</issue><spage>881</spage><epage>892</epage><pages>881-892</pages><issn>0272-4332</issn><eissn>1539-6924</eissn><abstract>Epidemiology textbooks often interpret population attributable fractions based on 2 × 2 tables or logistic regression models of exposure‐response associations as preventable fractions, i.e., as fractions of illnesses in a population that would be prevented if exposure were removed. In general, this causal interpretation is not correct, since statistical association need not indicate causation; moreover, it does not identify how much risk would be prevented by removing specific constituents of complex exposures. This article introduces and illustrates an approach to calculating useful bounds on preventable fractions, having valid causal interpretations, from the types of partial but useful molecular epidemiological and biological information often available in practice. The method applies probabilistic risk assessment concepts from systems reliability analysis, together with bounding constraints for the relationship between event probabilities and causation (such as that the probability that exposure X causes response Y cannot exceed the probability that exposure X precedes response Y, or the probability that both X and Y occur) to bound the contribution to causation from specific causal pathways. We illustrate the approach by estimating an upper bound on the contribution to lung cancer risk made by a specific, much‐discussed causal pathway that links smoking to a polycyclic aromatic hydrocarbon (PAH) (specifically, benzo(a)pyrene diol epoxide–DNA) adducts at hot spot codons at p53 in lung cells. The result is a surprisingly small preventable fraction (of perhaps 7% or less) for this pathway, suggesting that it will be important to consider other mechanisms and non‐PAH constituents of tobacco smoke in designing less risky tobacco‐based products.</abstract><cop>Malden, USA</cop><pub>Blackwell Publishing Inc</pub><pmid>16948683</pmid><doi>10.1111/j.1539-6924.2006.00785.x</doi><tpages>12</tpages></addata></record> |
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subjects | 7,8-Dihydro-7,8-dihydroxybenzo(a)pyrene 9,10-oxide - metabolism Cancer Causality DNA Adducts - drug effects DNA Adducts - metabolism Epidemiology Estimation Genes, p53 - drug effects Humans Lung cancer Lung Neoplasms - etiology Lung Neoplasms - genetics Lung Neoplasms - metabolism Lung Neoplasms - prevention & control Medical research Models, Biological Models, Statistical Mutation PAH Polycyclic aromatic hydrocarbons Polycyclic Aromatic Hydrocarbons - toxicity population attributable fraction preventable fraction Probability Regression analysis Risk Assessment Smoking Smoking - adverse effects Statistical analysis Studies |
title | Estimating Preventable Fractions of Disease Caused by a Specified Biological Mechanism: PAHs in Smoking Lung Cancers as an Example |
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