Development of an evidence-based risk assessment framework

Meeting Report Special Issue

Aiassa, E., Merten, C. and Martino, L. (2022). EFSA’s framework for evidence-based scientific assessments: A case study on uncertainty analysis. ALTEX 39, 451-462. doi:10.14573/altex.2004211

Allen, B., Zeiger, E., Lawrence, G. et al. (2005). Dose-response modeling of in vivo genotoxicity data for use in risk assessment: Some approaches illustrated by an analysis of acrylamide. Regul Toxicol Pharmacol 41, 6-27. doi:10.1016/j.yrtph.2004.09.006

Anastas, P. T., Sonich-Mullin, C. and Fried, B. (2010). Designing science in a crisis: The Deepwater Horizon oil spill. Environ Sci Technol 44, 9250-9251. doi:10.1021/es103700x

Andersen, M. E., McMullen, P. D., Phillips, M. B. et al. (2019). Developing context appropriate toxicity testing approaches using new alternative methods (NAMs). ALTEX 36, 523-534. doi:10.14573/altex.1906261

Armstrong, V., Karyakina, N., Nordheim, E. et al. (2020). Overview of REACH: Issues involved in the registration of metals. Neurotoxicology 83, 186-198. doi:10.1016/j.neuro.2020.01.010

Aspinall, W. (2008). Expert judgment elicitation using the Classical Model and EXCALIBUR. In Briefing notes for Seventh Session of the Statistics and Risk Assessment Section’s International Expert Advisory Group on Risk Modeling: Iterative Risk Assessment Processes for Policy Development Under Conditions of Uncertainty/Emerging Infectious Diseases: Round IV. http://dutiosc.twi.tudelft.nl/~risk/extrafiles/EJcourse/Sheets/Aspinall%20Briefing%20Notes.pdf

Aspinall, W. (2010). A route to more tractable expert advice. Nature 463, 294-295. doi:10.1038/463294a

Baan, R. A. and Straif, K. (2022). The Monographs programme of the international agency for research on cancer: A brief history of its Preamble. ALTEX 39, 443-450. doi:10.14573/altex.2004081

Balshem, H., Helfand, M., Schünemann, H. J. et al. (2011). GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol 64, 401-406. doi:10.1016/j.jclinepi.2010.07.015

Barnes, D. G. and Dourson, M. (1988). Reference dose (RfD): Description and use in health risk assessments. Regul Toxicol Pharmacol 8, 471-486. doi:10.1016/0273-2300(88)90047-5

Blettner, M., Sauerbrei, W., Schlehofer, B. et al. (1999). Traditional reviews, meta-analyses and pooled analyses in epidemiology. Int J Epidemiol 28, 1-9. doi:10.1093/ije/28.1.1

Bolt, H. M. (2019). Highlight report: Adverse outcome pathways: The need of research on mechanisms of toxicity. Arch Toxicol 93, 3385‐3386. doi:10.1007/s00204-019-02596-2

Burns, P. B., Rohrich, R. J. and Chung, K. C. (2011). The levels of evidence and their role in evidence-based medicine. Plast Reconstr Surg 128, 305-310. doi:10.1097/PRS.0b013e318219c171

Cardis, E., Armstrong, B. K., Bowman, J. D. et al. (2011). Risk of brain tumours in relation to estimated RF dose from mobile phones: Results from five Interphone countries. Occup Environ Med 68, 631-640. doi:10.1136/oemed-2011-100155

Chambers, A., Krewski, D., Birkett, N. et al. (2010). An exposure-response curve for copper excess and deficiency. J Toxicol Environ Health B Crit Rev 13, 546-578. doi:10.1080/10937404.2010.538657

Checkoway, H. (1991). Data pooling in occupational studies. J Occup Med 33, 1257-1260.

Chiu, W. A. and Slob, W. (2015). A unified probabilistic framework for dose-response assessment of human health effects. Environ Health Perspect 123, 1241-1254. doi:10.1289/ehp.1409385

Chiu, W. A., Wright, F. A. and Rusyn, I. (2017). A tiered, Bayesian approach to estimating of population variability for regulatory decision-making. ALTEX 34, 377-388. doi:10.14573/altex.1608251

Chiu, W. A., Axelrad, D. A., Dalaijamts, C. et al. (2018). Beyond the RfD: Broad application of a probabilistic approach to improve chemical dose-response assessments for noncancer effects. Environ Health Perspect 126, 067009-067009. doi:10.1289/EHP3368

Colson, A. R. and Cooke, R. M. (2017). Cross validation for the classical model of structured expert judgment. Reliab Eng Syst Saf 163, 109-120. doi:10.1016/j.ress.2017.02.003

Cooke, R. M. and Goossens, L. L. H. J. (2008). TU Delft expert judgment database. Reliab Eng Syst Saf 93, 657-674. doi:10.1016/j.ress.2007.03.005

Cooke, R. M. (2013). Validating Expert Judgment with the Classical Model. http://www.expertsinuncertainty.net/LinkClick.aspx?fileticket=HlcTmEoDunY%3D&tabid=4385&mid=8296

Cooke, R. M. (2015). The aggregation of expert judgment: Do good things come to those who weight? Risk Anal 35, 12-15. doi:10.1111/risa.12353

Corley, R. A., Kabilan, S., Kuprat, A. P. et al. (2012). Comparative computational modeling of airflows and vapor dosimetry in the respiratory tracts of rat, monkey, and human. Toxicol Sci 128, 500-516. doi:10.1093/toxsci/kfs168

Cote, I., Andersen, M. E., Ankley, G. T. et al. (2016). The next generation of risk assessment multi-year study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124, 1671-1682. doi:10.1289/ehp233

Crump, K. S. (1984). A new method for determining allowable daily intakes. Fundam Appl Toxicol 4, 854-871. doi:10.1016/0272-0590(84)90107-6

Darby, S., Hill, D., Auvinen, A. et al. (2005). Radon in homes and risk of lung cancer: Collaborative analysis of individual data from 13 European case-control studies. BMJ 330, 223. doi:10.1136/bmj.38308.477650.63

Dorman, D. C., Struve, M. F., Wong, B. A. et al. (2008). Derivation of an inhalation reference concentration based upon olfactory neuronal loss in male rats following subchronic acetaldehyde inhalation. Inhal Toxicol 20, 245-256. doi:10.1080/08958370701864250

Dourson, M. L., Teuschler, L. K., Durkin, P. R. et al. (1997). Categorical regression of toxicity data: A case study using aldicarb. Regul Toxicol Pharmacol 25, 121-129. doi:10.1006/rtph.1996.1079

ECHA (2013). Guidance for Human Health Risk Assessment (Vol. 3, Part B). https://echa.europa.eu/documents/10162/23492134/biocides_guidance_vol_iii_part_b_v10_superseded_en.pdf/8ce06b02-2a0b-a348-7a44-162a8c83e633

ECHA (2017). The use of alternatives to testing on animals for the REACH Regulation: Third report under Article 117(3) of the REACH Regulation. https://echa.europa.eu/documents/10162/13639/alternatives_test_animals_2017_en.pdf/075c690d-054c-693a-c921-f8cd8acbe9c3 (accessed 15.06.2020).

ECHA – European Chemicals Agency (2020). OECD and EU test guidelines. https://echa.europa.eu/support/oecd-eu-test-guidelines (accessed 15.06.2020).

EFSA – European Food Safety Authority (2010). Application of systematic review methodology to food and feed safety assessments to support decision making. EFSA J 8, 1637. doi:10.2903/j.efsa.2010.1637

EFSA (2014). Guidance on expert knowledge elicitation in food and feed safety risk assessment. EFSA J 12, 1831-4732. doi:10.2903/j.efsa.2014.3734

EFSA (2015a). Principles and process for dealing with data and evidence in scientific assessments. EFSA J 13, 4121-4136. doi:10.2903/j.efsa.2015.4121

EFSA (2015b). Conclusion on the peer review of the pesticide risk assessment of the active substance glyphosate. EFSA J 13, 4302. doi:10.2903/j.efsa.2015.4302

EPA – US Environmental Protection Agency (1994). Methods for Derivation of Inhalation Reference Concentrations (RfCs) and Application of Inhalation Dosimetry. Washington, DC, USA: US EPA. https://www.epa.gov/risk/methods-derivation-inhalation-reference-concentrations-and-application-inhalation-dosimetry

EPA (1995). The Use of the Benchmark Dose Approach in Health Risk Assessment. Washington, DC, USA: US EPA. http://hero.epa.gov/index.cfm/reference/download/reference_id/5992

EPA (2011). Recommended Use of Body Weight 3/4 as the Default Method in Derivation of the Oral Reference Dose. Washington, DC, USA: US EPA. https://www.epa.gov/risk/recommended-use-body-weight-34-default-method-derivation-oral-reference-dose

EPA (2012). Benchmark Dose Technical Guidance. https://www.epa.gov/sites/production/files/2015-01/documents/benchmark_dose_guidance.pdf

EPA (2017). Categorical Regression (CATREG) User Guide Version 3.1.0.7. https://www.epa.gov/sites/default/files/2016-03/documents/catreg_user_guide.pdf

EPA (2018). Basic Information about the Integrated Risk Information System. https://www.epa.gov/iris/basic-information-about-integrated-risk-information-system

EPA (2019a). List of Alternative Test Methods and Strategies (or New Approach Methodologies [NAMs]). https://www.epa.gov/sites/production/files/2019-12/documents/alternative_testing_nams_list_first_update_final.pdf

EPA (2019b). First Annual Conference on the State of the Science on Development and Use of New Approach Methods (NAMs) for Chemical Safety Testing. https://www.epa.gov/chemical-research/first-annual-conference-state-science-development-and-use-new-approach-methods-0 (accessed 15.06.2020)

Farhat, N., Saunders-Hastings, P., Morgan, R. et al. (2022). Best practices in systematic review. ALTEX 39, 463-479. doi:10.14573/altex.2004111

Farrell, P. J., Milton, B., Ramoju, S. et al. (2022). The use of categorical regression in evidence integration. ALTEX 39, online ahead of print. doi:10.14573/altex.2012022

Farrugia, P., Petrisor, B. A., Farrokhyar, F. et al. (2010). Practical tips for surgical research: Research questions, hypotheses and objectives. Can J Surg 53, 278-281.

Fehringer, G., Brenner, D. R., Zhang, Z. F. et al. (2017). Alcohol and lung cancer risk among never smokers: A pooled analysis from the international lung cancer consortium and the SYNERGY study. Int J Cancer 140, 1976-1984. doi:10.1002/ijc.30618

Felix, A. S., Gaudet, M. M., La Vecchia, C. et al. (2015). Intrauterine devices and endometrial cancer risk: A pooled analysis of the epidemiology of endometrial cancer consortium. Int J Cancer 136, E410-422. doi:10.1002/ijc.29229

Field, R. W., Krewski, D., Lubin, J. H. et al. (2006). An overview of the North American residential radon and lung cancer case-control studies. J Toxicol Environ Health A 69, 599-631. doi:10.1080/15287390500260960

Friedenreich, C. M. (1993). Methods for pooled analyses of epidemiologic studies. Epidemiology 4, 295-302. doi:10.1097/00001648-199307000-00004

Gannon A. M., Moreau, M., Farmahin, R. et al. (2019). Hexabromocyclododecane (HBCD): A case study applying tiered testing for human health risk assessment. Food Chem Toxicol 131, 110581. doi:10.1016/j.fct.2019.110581

Gaudet, M. M., Olshan, A. F., Chuang, S. C. et al. (2010). Body mass index and risk of head and neck cancer in a pooled analysis of case-control studies in the international head and neck cancer epidemiology (INHANCE) consortium. Int J Epidemiol 39, 1091-1102. doi:10.1093/ije/dyp380

Gift, J. S., McGaughy, R., Singh, D. V. et al. (2008). Health assessment of phosgene: Approaches for derivation of reference concentration. Regul Toxicol Pharmacol 51, 98-107. doi:10.1016/j.yrtph.2008.03.004

Guyatt, G. H., Oxman, A. D., Kunz, R. et al. (2008). Going from evidence to recommendations. BMJ 336, 1049-1051. doi:10.1136/bmj.39493.646875.AE

Guyatt, G. H., Oxman, A. D., Kunz, R. et al. (2011a). GRADE guidelines: 2. Framing the question and deciding on important outcomes. J Clin Epidemiol 64, 395-400. doi:10.1016/j.jclinepi.2010.09.012

Guyatt, G. H., Oxman, A. D., Sultan, S. et al. (2011b). GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol 64, 1311-1316. doi:10.1016/j.jclinepi.2011.06.004

Guyatt, G. H., Oxman, A. D., Kunz, R. et al. (2011c). GRADE guidelines: 8. Rating the quality of evidence – Indirectness. J Clin Epidemiol 64, 1303-1310. doi:10.1016/j.jclinepi.2011.04.014

Haber, L., Strickland, J. and Guth, D. J. (2001). Categorical Regression Analysis of Toxicity Data (Vol. 7). https://www.tera.org/Publications/catreg2001.pdf

Hagiwara, S., Paoli, G., Price, P. S. et al. (2022). A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing. Risk Anal, online ahead of print. doi:10.1111/risa.13931

Hattis, D., Baird, S. and Goble, R. (2002). A straw man proposal for a quantitative definition of the RfD. Drug Chem Toxicol 25, 403-436. doi:10.1081/dct-120014793

HEI Diesel Epidemiology Panel (2015). Diesel Emissions and Lung Cancer: An Evaluation of Recent Epidemiological Evidence for Quantitative Risk Assessment. Boston, MA, USA: Health Effects Institute. https://www.healtheffects.org/publication/diesel-emissions-and-lung-cancer-evaluation-recent-epidemiological-evidence-quantitative

Hertzberg, R. C. and Miller, M. (1985). A statistical model for species extrapolation using categorical response data. Toxicol Ind Health 1, 43-57. doi:10.1177/074823378500100405

Hooijmans, C. R., de Vries, R. B. M., Ritskes-Hoitinga, M. et al. (2018). Facilitating healthcare decisions by assessing the certainty in the evidence from preclinical animal studies. PLoS One 13, e0187271. doi:10.1371/journal.pone.0187271

IARC (1978). IARC monographs on the evaluation of the carcinogenic risk of chemicals to humans: Some N-nitroso compounds. IARC Monogr Eval Carcinog Risk Chem Man 17, 1-349.

IARC (2019). Preamble to the IARC Monographs on the Identification of Carcinogenic Hazards to Humans. Lyon, France: International Agency for Research on Cancer.

Jaworska, J., Gabbert, S. and Aldenberg, T. (2010). Towards optimization of chemical testing under REACH: A Bayesian network approach to integrated testing strategies. Regul Toxicol Pharmacol 57, 157-167. doi:10.1016/j.yrtph.2010.02.003

Johnson, P. I., Sutton, P., Atchley, D. S. et al. (2014). The navigation guide – Evidence-based medicine meets environmental health: Systematic review of human evidence for PFOA effects on fetal growth. Environ Health Perspect 122, 1028-1039. doi:10.1289/ehp.1307893

Johnson, P. I., Koustas, E., Vesterinen, H. M. et al. (2016). Application of the navigation guide systematic review methodology to the evidence for developmental and reproductive toxicity of triclosan. Environ Int 92-93, 716-728. doi:10.1016/j.envint.2016.03.009

Kheifets, L., Ahlbom, A., Crespi, C. M. et al. (2010). Pooled analysis of recent studies on magnetic fields and childhood leukaemia. Br J Cancer 103, 1128-1135. doi:10.1038/sj.bjc.6605838

Koustas, E., Lam, J., Sutton, P. et al. (2014). The navigation guide – Evidence-based medicine meets environmental health: Systematic review of nonhuman evidence for PFOA effects on fetal growth. Environ Health Perspect 122, 1015-1027. doi:10.1289/ehp.1307177

Krewski, D., Lubin, J. H., Zielinski, J. M. et al. (2006). A combined analysis of North American case-control studies of residential radon and lung cancer. J Toxicol Environ Health A 69, 533-597. doi:10.1080/15287390500260945

Krewski, D., Chambers, A., Stern, B. R. et al. (2010). Development of a copper database for exposure-response analysis. J Toxicol Environ Health A 73, 208-216. doi:10.1080/15287390903340815

Krewski, D., Westphal, M., Andersen, M. E. et al. (2014). A framework for the next generation of risk science. Environ Health Perspect 122, 796-805. doi:10.1289/ehp.1307260

Krewski, D., Barakat-Haddad, C., Donnan, J. et al. (2017). Determinants of neurological disease: Synthesis of systematic reviews. Neurotoxicology 61, 266-289. doi:10.1016/j.neuro.2017.04.002

Krewski, D., Anderson, M., Tyshenko, M. et al. (2020). Toxicity testing in the 21st century: Progress in the past decade and future perspectives. Arch Toxicol 94, 1-58. doi:10.1007/s00204-019-02613-4

Lam, J., Koustas, E., Sutton, P. et al. (2014). The navigation guide – Evidence-based medicine meets environmental health: Integration of animal and human evidence for PFOA effects on fetal growth. Environ Health Perspect 122, 1040-1051. doi:10.1289/ehp.1307923

Lam, J., Sutton, P., Kalkbrenner, A. et al. (2016). A systematic review and meta-analysis of multiple airborne pollutants and autism spectrum disorder. PLoS One 11, e0161851. doi:10.1371/journal.pone.0161851

Lam, J., Lanphear, B. P., Bellinger, D. et al. (2017). Developmental PBDE exposure and IQ/ADHD in childhood: A systematic review and meta-analysis. Environ Health Perspect 125, 086001. doi:10.1289/ehp1632

Lehman, A. J. and Fitzhugh, O. G. (1954). 100-fold margin of safety. Quarterly Bulletin of Food and Drug Officials 18, 33-35. https://hero.epa.gov/hero/index.cfm/reference/details/reference_id/3195

Lucas, R. M. and McMichael, A. J. (2005). Association or causation: Evaluating links between “environment and disease”. Bull World Health Organ 83, 792-795.

Makowski, D., Albert, I., Bonvallot, N. et al. (2016). Opinion of the French agency for food, environmental and occupational health and safety regarding the progress report on the assessment of the weight of evidence at ANSES: Critical literature review and recommendations at the hazard identification stage. ANSES Opinion Request, No 2015-SA-0089.

Martin, P., Bladdier, C., Meek, B. et al. (2018). Weight of evidence for hazard identification: A critical review of the literature. Environ Health Perspect 126, 1-15. doi:10.1289/EHP3067

Masic, I., Miokovic, M. and Muhamedagic, B. (2008). Evidence based medicine – New approaches and challenges. Acta Inform Med 16, 219-225. doi:10.5455/aim.2008.16.219-225

Menon, J., Struijs, F. and Whaley, P. (2022). The methodological rigour of systematic reviews in environmental health. Cri Rev Toxicol 52, 167-187. doi:10.1080/10408444.2022.2082917

Milton, B., Farrell, P. J., Birkett, N. et al. (2017a). Modeling U-shaped exposure-response relationships for agents that demonstrate toxicity due to both excess and deficiency. Risk Anal 37, 265-279. doi:10.1111/risa.12603

Milton, B., Krewski, D., Mattison, D. R. et al. (2017b). Modeling U-shaped dose-response curves for manganese using categorical regression. Neurotoxicology 58, 217-225. doi:10.1016/j.neuro.2016.10.001

Moher, D., Liberati, A., Tetzlaff, J. et al. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 6, e1000097. doi:10.1371/journal.pmed.1000097

Morgan, R. L., Whaley, P., Thayer, K. A. et al. (2018). Identifying the PECO: A framework for formulating good questions to explore the association of environmental and other exposures with health outcomes. Environ Int 121, 1027-1031. doi:10.1016/j.envint.2018.07.015

Morgan, R. L., Thayer, K. A., Santesso, N. et al. (2019). A risk of bias instrument for non-randomized studies of exposures: A users’ guide to its application in the context of GRADE. Environ Int 122, 168-184. doi:10.1016/j.envint.2018.11.004

Munafo, M., Nosek, B., Bishop, D. et al. (2017). A manifesto for reproducible science. Nat Hum Behav 1, 0021. doi:10.1038/s41562-016-0021

Murad, M. H., Asi, N., Alsawas, M. et al. (2016). New evidence pyramid. Evid Based Med 21, 125-127. doi:10.1136/ebmed-2016-110401

NAS – National Academies of Sciences (2001). Standard Operating Procedures for Developing Acute Exposure Guideline Levels. Washington, DC, USA: National Academies Press. https://www.nap.edu/catalog/10122/standing-operating-procedures-for-developing-acute-exposure-guideline-levels-for-hazardous-chemicals

NASEM – National Academies of Sciences Engineering and Medicine (2017). Guiding Principles for Developing Dietary Reference Intakes Based on Chronic Diseases. Washington, DC, USA: NASEM. http://www.nationalacademies.org/hmd/Reports/2017/guiding-principles-for-developing-dietary-reference-intakes-based-on-chronic-disease.aspx

NASEM (2018). Progress Toward Transforming the Integrated Risk Information System (IRIS) Program: A 2018 Evaluation. Washington, DC, USA: The National Academies Press. https://www.nap.edu/catalog/25086/progress-toward-transforming-the-integrated-risk-information-system-iris-program

NRC – National Research Council (1994). Science and Judgement in Risk Assessment. Washington, DC, USA: National Academies Press. doi:10.17226/2125

NRC (2007). Toxicity Testing in the 21st Century: A Vision and Strategy. https://www.nap.edu/catalog/11970/toxicity-testing-in-the-21st-century-a-vision-and-a

NRC (2008). Phthalates and Cumulative Risk Assessment: The Task Ahead. Washington, DC, USA: National Academies Press. https://www.ncbi.nlm.nih.gov/pubmed/25009926

NRC (2009). Science and Decisions: Advancing Risk Assessment. Washington, DC, USA: National Academies Press. https://www.nap.edu/catalog/12209/science-and-decisions-advancing-risk-assessment

NRC (2011). Review of the Environmental Protection Agency’s Draft IRIS Assessment of Formaldehyde. Washington, DC, USA: The National Academies Press. https://www.nap.edu/catalog/13142/review-of-the-environmental-protection-agencys-draft-iris-assessment-of-formaldehyde

NRC (2014a). Review of EPA's Integrated Risk Information System (IRIS) Process. Washington, DC, USA: National Academics Press. https://www.nap.edu/catalog/18764/review-of-epas-integrated-risk-information-system-iris-process

NRC (2014b). Review of the Environmental Protection Agency's State-of-the-science Evaluation of Nonmonotonic Dose-response Relationships as They Apply to Endocrine Disruptors. Washington, DC, USA: National Academies Press. https://bit.ly/3LA4GZZ

OECD (2019a). Case Study on the Use of an Integrated Approach to Testing and Assessment for Estrogen Receptor Active Chemicals. Series on Testing and Assessment, No. 309. https://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=ENV/JM/MONO(2019)28&docLanguage=en

OECD (2019b). Guiding Principles and Key Elements for Establishing a Weight of Evidence for Chemical Assessment. Series on Testing and Assessment, No. 311. Environment, Health and Safety Division, Environment Directorate. https://www.oecd.org/chemicalsafety/risk-assessment/guiding-principles-and-key-elements-for-establishing-a-weight-of-evidence-for-chemical-assessment.pdf

Paoli, G., Momoli, F., Tyshenko, M. G. et al. (2022). Problem formulation for EFSA Scientific Assessments. EFSA Supporting Publications 19, 7349E. doi:10.2903/sp.efsa.2022.EN-7349

Paul Friedman K., Gagne, M., Loo, L. H. et al. (2020). Utility of in vitro bioactivity as a lower bound estimate of in vivo adverse effect levels and in risk-based prioritization. Toxicol Sci 173, 202-225. doi:10.1093/toxsci/kfz201

Peres, L. C., Risch, H., Terry, K. L. et al. (2018). Racial/ethnic differences in the epidemiology of ovarian cancer: A pooled analysis of 12 case-control studies. Int J Epidemiol 47, 1011. doi:10.1093/ije/dyy054

Perkins, E. J., Ashauer, R., Burgoon, L. et al. (2019a). Building and applying quantitative adverse outcome pathway models for chemical hazard and risk assessment. Environ Toxicol Chem 38, 1850-1865. doi:10.1002/etc.4505

Perkins, E. J., Gayen, K., Shoemaker, J. E. et al. (2019b). Chemical hazard prediction and hypothesis testing using quantitative adverse outcome pathways. ALTEX 36, 91-102. doi:10.14573/altex.1808241

Petrisor, B. and Bhandari, M. (2007). The hierarchy of evidence: Levels and grades of recommendation. Indian J Orthop 41, 11-15. doi:10.4103/0019-5413.30519

Price, P. S., Jarabek, A. M., and Burgoon, L. D. (2020). Organizing mechanism-related information on chemical interactions using a framework based on the aggregate exposure and adverse outcome pathways. Environ Int 138, 105673. doi:10.1016/j.envint.2020.105673

Price, P. S., Hubbell, B., Hagiwara, S. et al. (2021). A framework that considers the impacts of time, cost, and uncertainty in the determination of the cost effectiveness of toxicity-testing methodologies. Risk Anal 42, 707-729. doi:10.1111/risa.13810

Rathman, J. F., Yang, C. and Zhou, H. (2018). Dempster-Shafer theory for combining in silico evidence and estimating uncertainty in chemical risk assessment. Comput Toxicol 6, 16-31. doi:10.1016/j.comtox.2018.03.001

Rhomberg, L. R., Goodman, J. E., Bailey, L. A. et al. (2013). A survey of frameworks for best practices in weight-of-evidence analyses. Crit Rev Toxicol 43, 753-784. doi:10.3109/10408444.2013.832727

Rogiers, V., Benfenati, E., Bernauer, U. et al. (2020). The way forward for assessing the human health safety of cosmetics in the EU – Workshop proceedings. Toxicology 436, 152421. doi:10.1016/j.tox.2020.152421

Rooney, A. A., Boyles, A. L., Wolfe, M. S. et al. (2014). Systematic review and evidence integration for literature-based environmental health science assessments. Environ Health Perspect 122, 711-718. doi:10.1289/ehp.1307972

Sackett, D. L. (1997). Evidence-based medicine. Semin Perinatol 21, 3-5. doi:10.1016/s0146-0005(97)80013-4

Samet, J. M., Chiu, W. A., Cogliano, V. et al. (2019). The IARC Monographs: Updated procedures for modern and transparent evidence synthesis in cancer hazard identification. J Natl Cancer Inst 112, 30-37. doi:10.1093/jnci/djz169

Sand, S., Portier, C. J. and Krewski, D. (2011). A signal-to-noise crossover dose as the point of departure for health risk assessment. Environ Health Perspect 119, 1766-1774. doi:10.1289/ehp.1003327

Sand, S., Lindqvist, R., von Rosen, D. et al. (2018). Dose-related severity sequence, and risk-based integration, of chemically induced health effects. Toxicol Sci 165, 74-89. doi:10.1093/toxsci/kfy124

Sand, S. (2022). A novel method for combining outcomes with different severities. ALTEX 39, 480-497. doi:10.14573/altex.2004212

Schroeter, J. D., Kimbell, J. S., Gross, E. A. et al. (2008). Application of physiological computational fluid dynamics models to predict interspecies nasal dosimetry of inhaled acrolein. Inhal Toxicol 20, 227-243. doi:10.1080/08958370701864235

Schünemann, H. J., Oxman, A. D., Brozek, J. et al. (2008). Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ 336, 1106-1110. doi:10.1136/bmj.39500.677199.AE

Schünemann, H. J., Cuello, C., Akl, E. A. et al. (2019a). GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence. J Clin Epidemiol 111, 105-114. doi:10.1016/j.jclinepi.2018.01.012

Schünemann, H. J., Zhang, Y. and Oxman, A. D. (2019b). Distinguishing opinion from evidence in guidelines. BMJ 366, l4606. doi:10.1136/bmj.l4606

Shamseer, L., Moher, D., Clarke, M. et al. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ 350, g7647. doi:10.1136/bmj.g7647

Smith, M. T., Guyton, K. Z., Gibbons, C. F. et al. (2016). Key characteristics of carcinogens as a basis for organizing data on mechanisms of carcinogenesis. Environ Health Perspect 124, 713-721. doi:10.1289/ehp.1509912

Stephens, M. L., Andersen, M., Becker, R. A. et al. (2013). Evidence-based toxicology for the 21st century: Opportunities and challenges. ALTEX 30, 74-103. doi:10.14573/altex.2013.1.074

Stern, B. R., Solioz, M., Krewski, D. et al. (2007). Copper and human health: Biochemistry, genetics, and strategies for modeling dose-response relationships. J Toxicol Environ Health B Crit Rev 10, 157-222. doi:10.1080/10937400600755911

Taher, M. K., Farhat, N., Karyakina, N. A. et al. (2019). Critical review of the association between perineal use of talc powder and risk of ovarian cancer. Reprod Toxicol 90, 88-101. doi:10.1016/j.reprotox.2019.08.015

Teeguarden, J. G., Bogdanffy, M. S., Covington, T. R. et al. (2008). A PBPK model for evaluating the impact of aldehyde dehydrogenase polymorphisms on comparative rat and human nasal tissue acetaldehyde dosimetry. Inhal Toxicol 20, 375-390. doi:10.1080/08958370801903750

Thomas, D. C., Jerrett, M., Kuenzli, N. et al. (2007). Bayesian model averaging in time-series studies of air pollution and mortality. J Toxicol Environ Health A 70, 311-315. doi:10.1080/15287390600884941

Thomas, R. S., Clewell, 3rd, H. J., Allen, B. C. et al. (2012). Integrating pathway-based transcriptomic data into quantitative chemical risk assessment: A five chemical case study. Mutat Res 746, 135-143.

Thomas, R. S., Philbert, M. A., Auerbach, S. S. et al. (2013). Incorporating new technologies into toxicity testing and risk assessment: Moving from 21st century vision to a data-driven framework. Toxicol Sci 136, 4-18. doi:10.1093/toxsci/kft178

Thomas, R. S., Bahadori, T., Buckley, T. J. et al. (2019). The next generation blueprint of computational toxicology at the U.S. Environmental Protection Agency. Toxicol Sci 169, 317-332. doi:10.1093/toxsci/kfz058

Tobias, A., Saez, M. and Kogevinas, M. (2004). Meta-analysis of results and individual patient data in epidemiological studies. J Mod Appl Stat Meth 3, 176-185. https://pdfs.semanticscholar.org/819f/aa4d45cbdacc501d97293e1a4914c3a175c1.pdf

Vermeulen, R., Silverman, D. T., Garshick, E. et al. (2014). Exposure-response estimates for diesel engine exhaust and lung cancer mortality based on data from three occupational cohorts. Environ Health Perspect 122, 172-177. doi:10.1289/ehp.1306880

Vesterinen, H. M., Johnson, P. I., Atchley, D. S. et al. (2015). Fetal growth and maternal glomerular filtration rate: A systematic review. J Matern Fetal Neonatal Med 28, 2176-2181. doi:10.3109/14767058.2014.980809

Wang, M. D., Gomes, J., Cashman, N. R. et al. (2014). A meta-analysis of observational studies of the association between chronic occupational exposure to lead and amyotrophic lateral sclerosis. J Occup Environ Med 56, 1235-1242. doi:10.1097/jom.0000000000000323

Webster, F., Gagné, M., Patlewicz, G. et al. (2019). Predicting estrogen receptor activation by a group of substituted phenols: An integrated approach to testing and assessment case study. Regul Toxicol Pharmacol 106, 278-291. doi:10.1016/j.yrtph.2019.05.017

West, G. B. (1999). The fourth dimension of life: Fractal geometry and allometric scaling of organisms. Science 284, 1677-1679. doi:10.1126/science.284.5420.1677

Whaley, P. (2015). Improving the evaluation of evidence: A framework for systematic review and integrated assessments. https://www.researchgate.net/publication/279537641 (accessed 31.07.2022).

WHO/IPCS (2009). Principles for Modelling Dose-Response for the Risk Assessment of Chemicals. Geneva, Switzerland: World Health Organization International Program on Chemical Safety. https://apps.who.int/iris/handle/10665/43940

WHO/IPCS (2014). Guidance Document on Evaluating and Expressing Uncertainty in Hazard Characterization. Geneva, Switzerland: World Health Organization International Program on Chemical Safety. https://apps.who.int/iris/handle/10665/259858

Wigle, D. T., Arbuckle, T. E., Turner, M. C. et al. (2008). Epidemiologic evidence of relationships between reproductive and child health outcomes and environmental chemical contaminants. J Toxicol Environ Health B Crit Rev 11, 373-517. doi:10.1080/10937400801921320

Woodruff, T. J. and Sutton, P. (2011). An evidence-based medicine methodology to bridge the gap between clinical and environmental health sciences. Health Aff (Millwood) 30, 931-937. doi:10.1377/hlthaff.2010.1219

Woodruff, T. J. and Sutton, P. (2014). The navigation guide systematic review methodology: A rigorous and transparent method for translating environmental health science into better health outcomes. Environ Health Perspect 122, 1007-1014. doi:10.1289/ehp.1307175

Wyss, A., Hashibe, M., Chuang, S. C. et al. (2013). Cigarette, cigar, and pipe smoking and the risk of head and neck cancers: Pooled analysis in the international head and neck cancer epidemiology consortium. Am J Epidemiol 178, 679-690. doi:10.1093/aje/kwt029

Yetley, E. A., MacFarlane, A. J., Greene-Finestone, L. S. et al. (2017). Options for basing dietary reference intakes (DRIs) on chronic disease endpoints: Report from a joint US-/Canadian-sponsored working group. Am J Clin Nutr 105, 249s-285s. doi:10.3945/ajcn.116.139097