Abstract
Recently, the key characteristics of carcinogens (KCC) have been proposed as an organizational approach for the evaluation of mechanistic data related to carcinogenicity. Our objective was to develop a framework to systematically and quantitatively integrate KCC data using elements that are important to risk assessment. Methods for developing the framework included: defining objectives, identifying and accommodating key considerations for components, input, and output of the framework, and operational development via iterative testing by a multidisciplinary team. The proposed framework involves 3 steps: (1) a structured, yet flexible, appraisal of individual studies and endpoints, (2) a structured and transparent evaluation of the body of evidence for each key characteristic, and (3) an evaluation of all of the KCC-relevant data relative to tumors and/or cancer types. In step 1, data are assessed and scored for reliability, strength, and activity. In step 2, a mathematical algorithm is used to integrate (and weight) the quality, relevance, and activity for each of the KCCs. These scores facilitate subsequent evaluations related to the overall body of evidence in step 3 in which KCCs can be linked, assessing potential adverse outcome pathways or networks, and finally, considered in the context of observed carcinogenic responses in animals and/or humans. The output is an overall conclusion regarding KCC activity as it relates to carcinogenic responses. The proposed framework provides a flexible solution to quantitatively integrate KCC data in a systematic and transparent manner that provides weighting of data most well-suited for the assessment of potential human carcinogenicity.
Highlights
Systematic reviews (SRs), which have long been used in medical and other scientific fields, have been recognized as a tool that can facilitate the modernization of evidence-based decision making in toxicology (EFSA, 2010; Guzelian et al, 2005; NAS, 2014; OHAT, 2015; Rooney et al, 2014)
In step 2, a mathematical algorithm is used to integrate the quality, relevance, and activity for each of the key characteristics of carcinogens (KCC). These scores facilitate subsequent evaluations related to the overall body of evidence in step 3 in which KCCs can be linked, assessing potential adverse outcome pathways or networks, and considered in the context of observed carcinogenic responses in animals and/or humans
The output is an overall conclusion regarding KCC activity as it relates to carcinogenic responses
Summary
Systematic reviews (SRs), which have long been used in medical and other scientific fields, have been recognized as a tool that can facilitate the modernization of evidence-based decision making in toxicology (EFSA, 2010; Guzelian et al, 2005; NAS, 2014; OHAT, 2015; Rooney et al, 2014). The evidence stream of mechanistic data has been recognized as complex, due to (1) the lack of applicable SR evaluation frameworks for this type of evidence, and (2) the tremendous diversity of study types (eg, ranging from in silico prediction of receptor binding to gene mutations in humans reported in a case-control study), and because of the everincreasing volume of high-content and/or high-throughput data (eg, high-throughput screening [HTS] assays such as those included in the ToxCast/Tox databases) (EFSA, 2017b; USEPA, 2015), together contributing to this evidence stream One such effort to incorporate a systematic process in the evaluation of mechanistic data has been proposed by Smith et al (2016), in which mechanistic data are organized according to the key characteristics of carcinogens (KCC). This framework provides a systematic—yet flexible—approach that we anticipate will increase the utility of the KCC organizational approach by providing a transparent, objective, and reproducible process (ie, reduced bias) for the assessment and integration of mechanistic data in the evaluation of human cancer hazard
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