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Human & Experimental Toxicology, Vol. 24, No. 4, 161-201 (2005)
DOI: 10.1191/0960327105ht517oa
© 2005 SAGE Publications

Evidence-based toxicology: a comprehensive framework for causation

Philip S Guzelian

University of Colorado Health Science Center, Denver, CO, USA; Box B-146, 4200 East 9th Avenue, BRB 723, Denver, CO 80262, USAphil.guzelian{at}uchsc.edu

Michael S Victoroff

Recall, Inc., Centennial, CO, USA

N Christine Halmes

Robert C James

Terra, Inc., Tallahassee, FL, USA

Christopher P Guzelian

Northwestern University Law School, Chicago, IL, USA

This paper identifies deficiencies in some current practices of causation and risk evaluation by toxicologists and formulates an evidence-based solution. The practice of toxicology focuses on adverse health events caused by physical or chemical agents. Some relations between agents and events are identified risks, meaning unwanted events known to occur at some frequency. However, other relations that are only possibilities – not known to occur (and may never be realized) – also are sometimes called risks and are even expressed quantitatively. The seemingly slight differences in connotation among various uses of the word ‘risk’ conceal deeply philosophic differences in the epistemology of harm. We label as ‘nomological possibilities’ (not as risks) all predictions of harm that are known not to be physically or logically impossible. Some of these nomological possibilities are known to be causal. We term them ‘epistemic’. Epistemic possibilities are risks. The remaining nomological possibilities are called ‘uncertainties’. Distinguishing risks (epistemic relationships) from among all nomological possibilities requires knowledge of causation. Causality becomes knowable when scientific experiments demonstrate, in a strong, consistent (repeatable), specific, dose-dependent, coherent, temporal and predictive manner that a change in a stimulus determines an asymmetric, directional change in the effect. Many believe that a similar set of characteristics, popularly called the ‘Hill Criteria’, make it possible, if knowledge is robust, to infer causation from only observational (nonexperimental) studies, where allocation of test subjects or items is not under the control of the investigator.

Until the 1980s, medical decisions about diagnosis, prevention, treatment or harm were often made authoritatively. Rather than employing a rigorous evaluation of causal relationships and applying these criteria to the published knowledge, the field of medicine was dominated by authority-based opinions, expressed by experts (or consensus groups of experts) relying on their education, training, experience, wisdom, prestige, intuition, skill and improvisation. In response, evidence-based medicine (EBM) was developed, to make a conscientious, explicit and judicious use of current best evidence in deciding about the care of individual patients. Now globally embraced, EBM employs a structured, ‘transparent’ protocol for carrying out a deliberate, objective, unbiased and systematic review of the evidence about a formally framed question. Not only in medicine, but now in dentistry, engineering and other fields that have adapted the methods of EBM, it is the quality of the evidence and the rigor of the analysis through evidence-based logic (EBL), rather than the professional standing of the reviewer, that leads to evidence-based conclusions about what is known. Recent studies have disclosed that toxicologists (individually or in expert groups), not unlike their medical counterparts prior to EBM, show distressing variations in their biases with regard to data selection, data interpretation and data evaluation when performing reviews for causation analyses. Moreover, toxicologists often fail to acknowledge explicitly (particularly in regulatory and policymaking arenas) when shortcomings in the evidence necessitate reliance upon authority-based opinions, rather than evidence-based conclusions (Guzelian PS, Guzelian CP. Authority-based explanation. Science 2004; 303: 1468-69). Accordingly, for answering questions about general and specific causation, we have constructed a framework for evidence-based toxicology (EBT), derived from the accepted principles of EBM and expressed succinctly as three stages, comprising 12 total steps. These are:

  1. 1) collecting and evaluating the relevant data (Source, Exposure, Dose, Diagnosis);
  2. 2) collecting and evaluating the relevant knowledge (Frame the question, Assemble the relevant (delimited) literature, Assess and critique the literature); and
  3. 3) Joining data with knowledge to arrive at a conclusion (General causation – answer to the framed question, Dose-response, Timing, Alternative cause, Coherence).
The second of these stages (which amounts to an analysis of general causation), is addressed by an EBM-styled approach (adapted for the infrequent availability of human experimental studies in environmental toxicology). This involves assembling literature (through documented algorithms for database queries), excluding irrelevancies by use of delimiters as filters, and ranking and rating the remaining articles for strength of study design and for quality of execution gauged by application of either a ready-made quality assessment instrument or a custom designed checklist or scale. The results of this systematic review (including a structured review of relevant animal and in vitro studies) are then themselves systematically used to determine which causation criteria are fulfilled.

Toxicology is maturing from a derivative science largely devoted to routinized performance and interpretation of safety tests, to a discipline deeply enmeshed in the remarkable advances in biochemistry and molecular biology to better understanding the nature and mechanism of adverse effects caused by chemicals. It is time for toxicologists, like scientists in other fields, to formalize a method for differentiating settled toxicological knowledge of risk from mere nomological possibility, and for communicating their conclusions to other scientists and the public. It is time for EBT.

Key Words: causation • evidence-based • risk

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