{"title":"Non-linearity in cancer dose-response: The role of exposure duration","authors":"Andrey A. Korchevskiy , Arseniy Korchevskiy","doi":"10.1016/j.comtox.2022.100217","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>An apparent deviation from nonlinearity in cancer dose-response was reported for various carcinogens. In particular, some studies hypothesized that in mesothelioma, the exposure-response relationship can be modelled as a power function with exponent from 0.6 to 1. However, various factors can affect the shape of the dose-response, producing the apparent supralinear trend.</p></div><div><h3>Objective</h3><p>To develop a mathematical model that would demonstrate a relationship of mesothelioma lifetime risk and exposure duration, with various assumptions about a hazard rate function.</p></div><div><h3>Methods</h3><p>Two different hazard rate functions – the Peto model and the two-stage clonal expansion (TSCE) model – were considered. The analytical formulas for lifetime risk were developed, with and without a lifetable correction. Standard calculus methods were applied to test the shape of the lifetime risk curve.</p></div><div><h3>Results</h3><p>For both Peto and TSCE models, it was shown that mesothelioma lifetime risk changes supralinearly with duration; the exponent of the power function was ranging from 0.68 to 0.89. However, the dose-response curve by cumulative exposure is close to linearity and is linear if the exposure duration would be constant. The model has been tested for chrysotile asbestos cohorts, with a good agreement demonstrated with published mesothelioma excess mortality (R=0.88, p<0.0041).</p></div><div><h3>Conclusion</h3><p>For mesothelioma, the observed deviation from linearity in the dose-response relationship can be potentially explained by the impact of a change in the duration of exposure. In a meta-analysis, this deviation can be eliminated by standardizing the mortality data for various cohorts by duration of exposure.</p></div><div><h3>Short Abstract</h3><p>An apparent deviation from nonlinearity in cancer dose-response was reported for various carcinogens. We applied two different hazard rate equations – the Peto model and the two-stage clonal expansion (TSCE) model – to pleural mesothelioma mortality. The analytical formulas for lifetime risk were developed. For both the Peto and TSCE models, it was shown that mesothelioma lifetime risk changes supralinearly with duration. However, the dose-response curve for cumulative exposure is close to linearity.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100217"},"PeriodicalIF":3.1000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111322000056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 2
Abstract
Context
An apparent deviation from nonlinearity in cancer dose-response was reported for various carcinogens. In particular, some studies hypothesized that in mesothelioma, the exposure-response relationship can be modelled as a power function with exponent from 0.6 to 1. However, various factors can affect the shape of the dose-response, producing the apparent supralinear trend.
Objective
To develop a mathematical model that would demonstrate a relationship of mesothelioma lifetime risk and exposure duration, with various assumptions about a hazard rate function.
Methods
Two different hazard rate functions – the Peto model and the two-stage clonal expansion (TSCE) model – were considered. The analytical formulas for lifetime risk were developed, with and without a lifetable correction. Standard calculus methods were applied to test the shape of the lifetime risk curve.
Results
For both Peto and TSCE models, it was shown that mesothelioma lifetime risk changes supralinearly with duration; the exponent of the power function was ranging from 0.68 to 0.89. However, the dose-response curve by cumulative exposure is close to linearity and is linear if the exposure duration would be constant. The model has been tested for chrysotile asbestos cohorts, with a good agreement demonstrated with published mesothelioma excess mortality (R=0.88, p<0.0041).
Conclusion
For mesothelioma, the observed deviation from linearity in the dose-response relationship can be potentially explained by the impact of a change in the duration of exposure. In a meta-analysis, this deviation can be eliminated by standardizing the mortality data for various cohorts by duration of exposure.
Short Abstract
An apparent deviation from nonlinearity in cancer dose-response was reported for various carcinogens. We applied two different hazard rate equations – the Peto model and the two-stage clonal expansion (TSCE) model – to pleural mesothelioma mortality. The analytical formulas for lifetime risk were developed. For both the Peto and TSCE models, it was shown that mesothelioma lifetime risk changes supralinearly with duration. However, the dose-response curve for cumulative exposure is close to linearity.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs