Hill Considerations Research Articles

Benzene exposure and non-Hodgkin lymphoma: a systematic review and meta-analysis of human studies

SummaryBackgroundNon-Hodgkin lymphoma comprises a heterogeneous group of cancers with unresolved aetiology, although risk factors include environmental exposures to toxic chemicals. Although the ubiquitous pollutant benzene is an established leukemogen, its potential to cause non-Hodgkin lymphoma has been widely debated. We aimed to examine the potential link between benzene exposure and risk of non-Hodgkin lymphoma in humans by evaluating a wide array of cohort and case-control studies using electronic systematic review.MethodsWe did a comprehensive systematic review and meta-analysis of all qualified human epidemiological studies that assessed the relationship between benzene exposure and non-Hodgkin lymphoma. We queried the PubMed and Embase databases for relevant articles published before June 5, 2019, and applied the SysRev platform for study selection. All peer-reviewed human cohort and case-control studies that reported non-Hodgkin lymphoma risk estimates specifically for benzene exposure were eligible for inclusion. Studies that calculated relative risks (RRs) for industries or job types without identifying those specifically exposed to benzene, that combined non-Hodgkin lymphoma with other cancer types, or that reported many different solvent exposures together were excluded. From each study, two investigators independently extracted information on the study design, location, years, sample size, participation rates, age, sex, sources of cases and controls, diagnosis, histological verification, exposure assessment, results, adjustment, and statistical analysis, and subsequently assessed study quality. We calculated the meta-analysis relative risk (meta-RR) and CIs using the fixed effect and random effect models, as well as assessing publication bias.FindingsOur search yielded 2481 articles. After screening and removal of duplicates, 20 case-control studies and eight cohort studies were included in our meta-analysis, which included a total of 9587 patients with non-Hodgkin lymphoma. We reported an increased meta-relative risk (meta-RR) of 33% in highly exposed groups, when data were available (meta-RR 1·33 [95% CI 1·13–1·57], n=28). The meta-RR rose to 1·51 (1·22–1·87, n=18) in the studies that provided results specifically for highly exposed individuals. In particular, we reported a doubling of this risk for diffuse large B-cell lymphoma, a major non-Hodgkin lymphoma subtype (1·67 [1·01–2·77]). We also detected increased risks for follicular lymphoma (1·47 [0·95–2·27]) and hairy cell leukaemia (1·77 [0·99–3·16]), though they were not statistically significant. Funnel plot, Egger’s test (p=0·77) and Begg’s test (p=0·98) did not show evidence of publication bias. We evaluated the major aspects of causal inference and found evidence to support all the Hill considerations for assigning causation.InterpretationOur findings suggest a causal link between benzene exposure and non-Hodgkin lymphoma, especially for diffuse large B-cell lymphoma.

An Adverse Outcome Pathway (AOP) for forestomach tumors induced by non-genotoxic initiating events

The utility of rodent forestomach tumor data for hazard and risk assessment has been examined for decades because humans do not have a forestomach, and these tumors occur by varying modes of action (MOAs). We have used the MOA for ethyl acrylate (EA) to develop an Adverse Outcome Pathway (AOP) for forestomach tumors caused by non-genotoxic initiating events. These tumors occur secondary to site of contact induced epithelial cytotoxicity and regenerative repair-driven proliferation. For EA, the critical initiating event (IE) is epithelial cytotoxicity, and supporting key events (KEs) at the cellular and tissue level are increased cell proliferation (KE1) resulting in sustained hyperplasia (KE2), with the adverse outcome of forestomach papillomas and carcinomas. For EA, a pre-molecular initiating event (pre-MIE) of sustained glutathione depletion is probable. Supporting data from butylated hydroxyanisole (BHA) are also reviewed. Although there may be some variability in the pre-MIEs and IEs for BHA and EA, they share the same KEs, and evidence for BHA confers support for the AOP. Evolved Bradford Hill considerations of biological plausibility, essentiality, and empirical support were evaluated per OECD guidance. Although an MIE is not specifically described, overall confidence in the AOP is high due to well-developed and accepted evidence streams, and the AOP can be used for regulatory applications including hazard identification and risk assessment for chemicals that act by this AOP.

Weight-of-evidence evaluation of associations between particulate matter exposure and biomarkers of lung cancer

Research suggests that exposure to ambient particulate matter (PM) may be associated with lung cancer; however, no mode of action (MoA) for this has been established. We applied a weight-of-evidence (WoE) approach to evaluate recent evidence from four realms of research (controlled human exposure, epidemiology, animal, and in vitro) to determine whether the overall evidence supports one or more MoAs by which PM could cause lung cancer. We evaluated three general MoAs: DNA damage and repair; other genotoxic effects, including mutagenicity and clastogenicity; and gene expression, protein expression, and DNA methylation. After assessing individual study quality, we evaluated the strength of the evidence within as well as across disciplines using a modified set of Bradford Hill considerations. We conclude that the overall WoE indicates it is plausible that PM of various size fractions may cause direct DNA damage, but the evidence is insufficient regarding the alternative MoAs we evaluated. More research is needed to determine whether DNA damage can lead to downstream events and, ultimately, lung cancer.

Mode-of-action evaluation for the effect of trans fatty acids on low-density lipoprotein cholesterol

The purpose of this work is to systematically consider the data relating to the mode of action (MOA) for the effects of industrially produced trans fatty acid (iTFA) on plasma low-density lipoprotein (LDL) levels. The hypothesized MOA is composed of two key events: increased LDL production and decreased LDL clearance. A substantial database supports this MOA, although the key events are likely to be interdependent, rather than sequential. Both key events are functions of nonlinear biological processes including rate-limited clearance, receptor-mediated transcription, and both positive and negative feedback regulation. Each key event was evaluated based on weight-of-evidence analysis and for human relevance. We conclude that the data are inadequate for a detailed dose-response analysis in the context of the evolved Bradford Hill considerations; however, the weight of evidence is strong and the overall shape of the dose-response curves for markers of the key events and the key determinants of those relationships is well understood in many cases and is nonlinear. Feedback controls are responsible for maintaining homeostasis of cholesterol and triglyceride levels and underlie both of the key events, resulting in a less-than-linear or thresholded relationship between TFA and LDL-C. The inconsistencies and gaps in the database are discussed.

In Response: The path forward for the adverse outcome pathway framework--A regulatory perspective.

In Response: The path forward for the adverse outcome pathway framework--A regulatory perspective.

The adverse outcome pathway for rodent liver tumor promotion by sustained activation of the aryl hydrocarbon receptor

An Adverse Outcome Pathway (AOP) represents the existing knowledge of a biological pathway leading from initial molecular interactions of a toxicant and progressing through a series of key events (KEs), culminating with an apical adverse outcome (AO) that has to be of regulatory relevance. An AOP based on the mode of action (MOA) of rodent liver tumor promotion by dioxin-like compounds (DLCs) has been developed and the weight of evidence (WoE) of key event relationships (KERs) evaluated using evolved Bradford Hill considerations. Dioxins and DLCs are potent aryl hydrocarbon receptor (AHR) ligands that cause a range of species-specific adverse outcomes. The occurrence of KEs is necessary for inducing downstream biological responses and KEs may occur at the molecular, cellular, tissue and organ levels. The common convention is that an AOP begins with the toxicant interaction with a biological response element; for this AOP, this initial event is binding of a DLC ligand to the AHR. Data from mechanistic studies, lifetime bioassays and approximately thirty initiation-promotion studies have established dioxin and DLCs as rat liver tumor promoters. Such studies clearly show that sustained AHR activation, weeks or months in duration, is necessary to induce rodent liver tumor promotion – hence, sustained AHR activation is deemed the molecular initiating event (MIE). After this MIE, subsequent KEs are 1) changes in cellular growth homeostasis likely associated with expression changes in a number of genes and observed as development of hepatic foci and decreases in apoptosis within foci; 2) extensive liver toxicity observed as the constellation of effects called toxic hepatopathy; 3) cellular proliferation and hyperplasia in several hepatic cell types. This progression of KEs culminates in the AO, the development of hepatocellular adenomas and carcinomas and cholangiolar carcinomas. A rich data set provides both qualitative and quantitative knowledge of the progression of this AOP through KEs and the KERs. Thus, the WoE for this AOP is judged to be strong. Species-specific effects of dioxins and DLCs are well known – humans are less responsive than rodents and rodent species differ in sensitivity between strains. Consequently, application of this AOP to evaluate potential human health risks must take these differences into account.

A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations

Big longitudinal observational medical data potentially hold a wealth of information and have been recognised as potential sources for gaining new drug safety knowledge. Unfortunately there are many complexities and underlying issues when analysing longitudinal observational data. Due to these complexities, existing methods for large-scale detection of negative side effects using observational data all tend to have issues distinguishing between association and causality. New methods that can better discriminate causal and non-causal relationships need to be developed to fully utilise the data.In this paper we propose using a set of causality considerations developed by the epidemiologist Bradford Hill as a basis for engineering features that enable the application of supervised learning for the problem of detecting negative side effects. The Bradford Hill considerations look at various perspectives of a drug and outcome relationship to determine whether it shows causal traits. We taught a classifier to find patterns within these perspectives and it learned to discriminate between association and causality. The novelty of this research is the combination of supervised learning and Bradford Hill’s causality considerations to automate the Bradford Hill’s causality assessment.We evaluated the framework on a drug safety gold standard known as the observational medical outcomes partnership’s non-specified association reference set. The methodology obtained excellent discrimination ability with area under the curves ranging between 0.792 and 0.940 (existing method optimal: 0.73) and a mean average precision of 0.640 (existing method optimal: 0.141). The proposed features can be calculated efficiently and be readily updated, making the framework suitable for big observational data.

A Supervised Adverse Drug Reaction Signalling Framework Imitating Bradford Hill's Causality Considerations

Big longitudinal observational medical data potentially hold a wealth of information and have been recognised as potential sources for gaining new drug safety knowledge. Unfortunately there are many complexities and underlying issues when analysing longitudinal observational data. Due to these complexities, existing methods for large-scale detection of negative side effects using observational data all tend to have issues distinguishing between association and causality. New methods that can better discriminate causal and non-causal relationships need to be developed to fully utilise the data.In this paper we propose using a set of causality considerations developed by the epidemiologist Bradford Hill as a basis for engineering features that enable the application of supervised learning for the problem of detecting negative side effects. The Bradford Hill considerations look at various perspectives of a drug and outcome relationship to determine whether it shows causal traits. We taught a classifier to find patterns within these perspectives and it learned to discriminate between association and causality. The novelty of this research is the combination of supervised learning and Bradford Hill’s causality considerations to automate the Bradford Hill’s causality assessment.We evaluated the framework on a drug safety gold standard know as the observational medical outcomes partnership’s nonspecified association reference set. The methodology obtained excellent discriminate ability with area under the curves ranging between 0.792-0.940 (existing method optimal: 0.73) and a mean average precision of 0.640 (existing method optimal: 0.141). The proposed features can be calculated effciently and be readily updated, making the framework suitable for big observational data.

Is there a causal link between knee loading and knee osteoarthritis progression? A systematic review and meta-analysis of cohort studies and randomised trials

ObjectiveWe performed a systematic review, meta-analysis and assessed the evidence supporting a causal link between knee joint loading during walking and structural knee osteoarthritis (OA) progression.DesignSystematic review, meta-analysis and application...

Mode of action human relevance (species concordance) framework: Evolution of the Bradford Hill considerations and comparative analysis of weight of evidence.

The mode of action human relevance (MOA/HR) framework increases transparency in systematically considering data on MOA for end (adverse) effects and their relevance to humans. This framework continues to evolve as experience increases in its application. Though the MOA/HR framework is not designed to address the question of “how much information is enough” to support a hypothesized MOA in animals or its relevance to humans, its organizing construct has potential value in considering relative weight of evidence (WOE) among different cases and hypothesized MOA(s). This context is explored based on MOA analyses in published assessments to illustrate the relative extent of supporting data and their implications for dose–response analysis and involved comparisons for chemical assessments on trichloropropane, and carbon tetrachloride with several hypothesized MOA(s) for cancer. The WOE for each hypothesized MOA was summarized in narrative tables based on comparison and contrast of the extent and nature of the supporting database versus potentially inconsistent or missing information. The comparison was based on evolved Bradford Hill considerations rank ordered to reflect their relative contribution to WOE determinations of MOA taking into account increasing experience in their application internationally. This clarification of considerations for WOE determinations as a basis for comparative analysis is anticipated to contribute to increasing consistency in the application of MOA/HR analysis and potentially, transparency in separating science judgment from public policy considerations in regulatory risk assessment. Copyright © 2014. The Authors. Journal of Applied Toxicology Published by John Wiley & Sons Ltd.The potential value of the mode of action (MOA)/human relevance (species concordance) framework in considering relative weight of evidence (WOE) amongst different cases and hypothesized MOA(s) is explored based on the content of several published assessments. The comparison is based on evolved Bradford Hill considerations rank ordered to reflect their relative contribution to WOE determinations for MOA based on experience internationally.

New developments in the evolution and application of the WHO/IPCS framework on mode of action/species concordance analysis

The World Health Organization/International Programme on Chemical Safety mode of action/human relevance framework has been updated to reflect the experience acquired in its application and extend its utility to emerging areas in toxicity testing and non-testing methods. The underlying principles have not changed, but the framework’s scope has been extended to enable integration of information at different levels of biological organization and reflect evolving experience in a much broader range of potential applications. Mode of action/species concordance analysis can also inform hypothesis-based data generation and research priorities in support of risk assessment.The modified framework is incorporated within a roadmap, with feedback loops encouraging continuous refinement of fit-for-purpose testing strategies and risk assessment. Important in this construct is consideration of dose–response relationships and species concordance analysis in weight of evidence. The modified Bradford Hill considerations have been updated and additionally articulated to reflect increasing experience in application for cases where the toxicological outcome of chemical exposure is known.The modified framework can be used as originally intended, where the toxicological effects of chemical exposure are known, or in hypothesizing effects resulting from chemical exposure, using information on putative key events in established modes of action from appropriate in vitro or in silico systems and other lines of evidence.This modified mode of action framework and accompanying roadmap and case examples are expected to contribute to improving transparency in explicitly addressing weight of evidence considerations in mode of action/species concordance analysis based on both conventional data sources and evolving methods.

Work-relatedness of low back pain in nursing personnel: a systematic review

Although non-specific low back pain (LBP) is known to be multifactorial, studies from across the globe have documented their higher prevalence in nurses. This systematic review was conducted to ascertain whether this much-documented association constitutes a causal relationship, and whether there is a discernible threshold of exposures associated with this elevated risk. PRISMA guidelines were followed and standard critical appraisal tools were applied. The outcome of interest was non-specific LBP or back injury; exposure was "performing nursing duties." Applicable studies, published in English during 1980-2012, were identified through database searches, screened against preset inclusion/exclusion criteria. Ergonomic assessments of nursing tasks were included along with epidemiological studies. Bradford Hill considerations for causation were utilized as a framework for discussing findings. Of 987 studies identified, 89 qualified for inclusion, comprising 21 longitudinal, 36 cross-sectional analytic, 23 descriptive biomechanical/ergonomic, and 9 review studies. Overall studies showed that nursing activities conferred increased risk for, and were associated with back disorders regardless of nursing technique, personal characteristics, and non-work-related factors. Patient handling appears to confer the highest risk, but other nursing duties are also associated with elevated risk, and confound dose-response assessments related to patient handling alone. Associations were strong, consistent, temporally possible, plausible, coherent, and analogous to other exposure-outcomes, with risk estimates ranging from 1·2 to 5·5 depending on definitions. A threshold of nursing activities below which the risk of back disorders is not elevated has not been established. Notwithstanding the bio-psycho-social nature of LBP, and complexities of studying this area, sufficient evidence exists of a causal relationship between nursing tasks and back disorders to warrant new policies.

Getting causal considerations back on the right track

In their commentary on my paper Phillips and Goodman suggested that counterfactual causality and considerations on causality like those by Bradford Hill are only "guideposts on the road to common sense". I argue that if common sense is understood to mean views that the vast majority of researchers share, Hill's considerations did not lead to common sense in the past – precisely because they are so controversial. If common sense is taken to mean beliefs that are true, then Hill's considerations can only lead to common sense in the simple and well-understood causal systems they apply to. Counterfactuals, however, are largely common sense in the latter meaning.I suggest that the road of scientific endeavour should lead epidemiologic research toward sound strategies that equip researchers with skills to separate causal from non-causal associations with minimal error probabilities. This is undeniably the right direction and the one counterfactual causality leads to. Hill's considerations are merely heuristics with which epidemiologists may or may not find this direction, and they are likely to fail in complex landscapes (causal systems). In such environments, one might easily lose orientation without further aids (e.g., defendable assumptions on biases). Counterfactual causality tells us when and how to apply these heuristics.

The Bradford Hill considerations on causality: a counterfactual perspective

Bradford Hill's considerations published in 1965 had an enormous influence on attempts to separate causal from non-causal explanations of observed associations. These considerations were often applied as a checklist of criteria, although they were by no means intended to be used in this way by Hill himself. Hill, however, avoided defining explicitly what he meant by "causal effect".This paper provides a fresh point of view on Hill's considerations from the perspective of counterfactual causality. I argue that counterfactual arguments strongly contribute to the question of when to apply the Hill considerations. Some of the considerations, however, involve many counterfactuals in a broader causal system, and their heuristic value decreases as the complexity of a system increases; the danger of misapplying them can be high. The impacts of these insights for study design and data analysis are discussed. The key analysis tool to assess the applicability of Hill's considerations is multiple bias modelling (Bayesian methods and Monte Carlo sensitivity analysis); these methods should be used much more frequently.