Special Issue on the Role of Linear and Nonlinera Dose-Response Models in Public Decision-Making
Journal Volume
Articles
Dose-Response Vol 10, no 2, Cover
(2012-06-01)
Dose-Response, Vol 10, no 2, Table of Contents
(2014-06-01)
REGULATORY-SCIENCE: BIPHASIC CANCER MODELS OR THE LNT—NOT JUST A MATTER OF BIOLOGY!
(2014-06-01) Ricci, Paolo F; Sammis, Ian R
There is no doubt that prudence and risk aversion must guide public decisions when the associated adverse outcomes are either serious or irreversible. With any carcinogen, the levels of risk and needed protection before and after an event occurs, are determined by dose-response models. Regulatory law should not crowd out the actual beneficial effects from low dose exposures—when demonstrable—that are inevitably lost when it adopts the linear non-threshold (LNT) as its causal model. Because regulating exposures requires planning and developing protective measures for future acute and chronic exposures, public management decisions should be based on minimizing costs and harmful expo- sures. We address the direct and indirect effects of causation when the danger consists of exposure to very low levels of carcinogens and toxicants. The societal consequences of a policy can be deleterious when that policy is based on a risk assumed by the LNT, in cases where low exposures are actually beneficial. Our work develops the science and the law of causal risk modeling: both are interwoven. We suggest how their relevant characteristics differ, but do not attempt to keep them separated; as we demonstrate, this union, however unsatisfactory, cannot be severed.
OF REDUCTIONISM AND THE PENDULUM SWING: CONNECTING TOXICOLOGY AND HUMAN HEALTH
(2012-06-01) Hanekamp, Jaap C; Bast, Aalt; Kwakman, Jan HJM
In this contribution we will show that research in the field of toxicology, pharmacolo- gy and physiology is by and large characterised by a pendulum swing of which the amplitudes represent risks and benefits of exposure. As toxicology usually tests at higher levels than the populace routinely is exposed to, it reverts to mostly linear extrapolative models that express the risks of exposure, irrespective of dosages, only. However, as we will explicate in two examples, depending on dosages, it is less easy to separate risks and benefits than current toxicological research and regulatory efforts suggest. The same chemical compound, in the final analysis, is represented within the boundaries of both amplitudes, that is, show a biphasic, hormetic, dose-response. This is notable, as low-level exposures from the food-matrix are progressively more under scrutiny as a result of increasing analytical capabilities. Presence of low-level concentrations of a chemical in food is a regulatory proxy for human health, but in light of this hormetic dose-response objectionable. Moreover, given that an ecological threshold probably holds for most, if not all, man-made (bio)organic chemicals, these will be found to be naturally present in the food matrix. Both aspects require toxicology to close the gap between reductionist models and its extrapolative deficiencies and real-life scenarios.
CHANGING THE RISK PARADIGMS CAN BE GOOD FOR OUR HEALTH: J-SHAPED, LINEAR AND THRESHOLD DOSE-RESPONSE MODELS
(2012-06-01) Ricci, Paolo F; Straja, SR; Cox, Jr, AL
Both the linear (at low doses)-no-threshold (LNT) and the threshold models (S- shapes) dose-response lead to no benefit from low exposure. We propose three new models that allow and include, but do not require – unlike LNT and S-shaped models — this strong assumption. We also provide the means to calculate benefits associated with bi-phasic biological behaviors, when they occur and propose: 1. Three hormetic (phasic) models: the J-shaped, inverse J-shaped, the min-max, and 2. Method for calculating the direct benefits associated with the J and inverse J- shaped models. The J-shaped and min-max models for mutagens and carcinogenic agents include an experimentally justified repair stage for toxic and carcinogenic damage. We link these to stochastic transition models for cancer and show how abrupt transitions in cancer hazard rates, as functions of exposure concentrations and durations, can emerge naturally in large cell populations even when the rates of cell-level events increase smoothly (e.g., proportionally) with concentration. In this very general family of models, J-shaped dose- response curves emerge. These results are universal, i.e., independent of specific biological details represented by the stochastic transition networks. Thus, using them suggests a more complete and realistic way to assess risks at low doses or dose-rates.