Is the proposed causal relationship consistent with the broader knowledge of the natural history and biology of the disease? Experimental evidence This criterion primarily refers to the availability of experimental/intervention studies where the causal relationship has been investigated, and supported, experimentally. Intervention studies that demonstrate a reduction of a disease outcome from removal or reduction of a postulated causal factor provide strong evidence of a causal relationship, for example, the reduction in the incidence of cholera after Dr John Snow removed the pump handle from the Broad Street pump in the St in 1854 was strong evidence the contaminated water was James’s parish causing the disease. Analogy What do we know about similar/related substances and similar disease or pathology outcomes that might add or subtract support to the proposed causal relationship? Design Limitations in Epidemiology Ioannidis has discussed the statistical basis for the poor reproducibility of many types of epidemiology studies in the literature and proposed a number of criteria on which to judge the likely reliability of the results of such studies. These criteria, in conjunction with those of Bradford Hill, also provide a useful basis for considering the suitability of an epidemiology study for inclusion in a HHRA, and the weight that should be given to the results of these studies in forming risk assessment conclusions. Ioannidis observes that the design factors that tend to lead to unreliable results include: small study size, small effect sizes in relation to background variability, large numbers of variables being tested that are unrelated to a specific prior hypothesis, a high degree of flexibility in study designs, definitions, outcomes, and analytical modes, conflicts of interest including; financial, ideological, philosophical, reputational. There is a degree of overlap between the criteria of Bradford Hill and those of Ioannidis. Strength of association for example is related to study sample sizes and the size of the effect in comparison to background variation. The larger the sample and effect sizes the stronger the statistical significance and apparent association. Epidemiological studies conducted in the absence of a specific (that is a precise/targeted) scientific hypothesis will generally employ a wide range of investigative variables and conduct multiple comparisons in search of “significance”. Studies of this type will frequently yield random statistically significant findings that are not reproducible in subsequent studies. EFSA US EPA Primary sources of variation between the EFSA and US EPA assessments include elements of toxicology, particularly the selection of the PoD, approaches to address the differences in
Is the proposed causal relationship consistent with the broader knowledge of the natural history and biology of the disease? Experimental evidence This criterion primarily refers to the availability of experimental/intervention studies where the causal relationship has been investigated, and supported, experimentally. Intervention studies that demonstrate a reduction of a disease outcome from removal or reduction of a postulated causal factor provide strong evidence of a causal relationship, for example, the reduction in the incidence of cholera after Dr John Snow removed the pump handle from the Broad Street pump in the St James’s parish in 1854 was strong evidence the contaminated water was causing the disease. Analogy What do we know about similar/related substances and similar disease or pathology outcomes that might add or subtract support to the proposed causal relationship? Design Limitations in Epidemiology Ioannidis has discussed the statistical basis for the poor reproducibility of many types of epidemiology studies in the literature and proposed a number of criteria on which to judge the likely reliability of the results of such studies. These criteria, in conjunction with those of Bradford Hill, also provide a useful basis for considering the suitability of an epidemiology study for inclusion in a HHRA, and the weight that should be given to the results of these studies in forming risk assessment conclusions. Ioannidis observes that the design factors that tend to lead to unreliable results include: small study size, small effect sizes in relation to background variability, large numbers of variables being tested that are unrelated to a specific prior hypothesis, a high degree of flexibility in study designs, definitions, outcomes, and analytical modes, conflicts of interest including; financial, ideological, philosophical, reputational. There is a degree of overlap between the criteria of Bradford Hill and those of Ioannidis. Strength of association for example is related to study sample sizes and the size of the effect in comparison to background variation. The larger the sample and effect sizes the stronger the statistical significance and apparent association. Epidemiological studies conducted in the absence of a specific (that is a precise/targeted) scientific hypothesis will generally employ a wide range of investigative variables and conduct multiple comparisons in search of “significance”. Studies of this type will frequently yield random statistically significant findings that are not reproducible in subsequent studies. EFSA US EPA Primary sources of variation between the EFSA and US EPA assessments include elements of toxicology, particularly the selection of the PoD, approaches to address the differences in