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® F ;.i . fF; . Haa~ risk assessment become too "conservative"? From: RESOURCES, No. 96 (Summer, Adam M. Finkel 1989). Resources for the Future. Momentum is gathering to support the view that risk assessment, especially of carcinogens, tends to be skewed toward overestimating risks. Perhaps influ- enced by these arguments against over- caution, Me Environmental Protection Agency has begun to reevaluate some of its procedures and lower some risk estimates. Adam Finkel of the Center for Risk Management cautions against hasty clzanges and calls for preserving the virtues of both good science and prudence. I uantitative risk assessment (QRA) is a science and an in- dustry, and "risk numbers" are both its language and its currency. These numerical predictions of how many persons will suffer disease or death because of environmental expo- sure, or of the probability that an average person or a particular individual will suc- cumb, now lie at the heart of environmen- tal health regulation, particularly when it involves carcinogenic substances. The recent controversy over damin- ozide (A1ar) in apples, for example, cen- tered around estimates generated by the Natural Resources Defense Council (NRDC) that as many as 5,300 of the current group of 22 million preschool children ir., the United States may contract cancer duting their lifetime as a result of childhood exposure to Alar. This repre- sents an estimated increase of 1 chance in 4,200 (above the background probability we all have of getting cancer) that Alar will cause cancer in a typical child. The NRDC also estimates that about 5 percent of preschool children ingest substantially more food containing Alar than the aver- age child, and that these children face excess cancer risks approaching I in 1,000. Experts and laypeople alike tend to ask two very different kinds of questions when confronted with numbers like these. One set of questions involves ethical judgments about the acceptability of the stated risks; the debate over whether a risk of (say) 1 in 4,200 is too high will depend on personal and group judgments. These judgments concern the voluntariness of the risk, the magnitude of the probability (perhaps in relation to other environ- mental, occupational, or lifestyle risks we are more familiar with ), the costs of elimi- nating or reducing the risk, and the real or perceived benefits of the risky product or activity. This acceptable-risk issue pits those who argue that no involuntary risk is acceptable if it can readily be reduced further against those who believe our society has become preoccupied with trivially small dangers. This is a vigorous debate, with divergent views expressed both within the expert community and the general public as well as between these two groups. The other set of questions has to do with the believability of the estimates them- selves. In contrast to the controversy over acceptable risk, the debate overr whether risk numbers are credible has begun to resolve itself, at least among practitioners and expert observers of QRA. The gen- eral reader may be surprised that this group tentatively has concluded that risk numbers generally are not credible. The conventional wisdom of the experts is that these numbers are systematically skewed in the direction of overestimating risk, because the process used is in danger of being so "conservative"-so overly cau- tious-as to be a caricature of itself. The intellectual and regulatory mo- mentum is clearly on the side of the "revisionist" position, which seeks to replace conservative procedures because the status quo is allegedly causing alarm- ist and counterproductive reactions. The lack of resistance to some of these changes reflects the compelling evidence supporting some revisions, the fact that the public may not be aware that subtle but accelerating changes are under way in QRA, and perhaps simply the natural swing of the pendulum in such matters. In my view, however, the rush to eschew conservatism is fueled in part by an un- critical acceptance of a set of flawed as- sumptions about QRA, so the pendulum swing may itself be counterproductive. I wish to offer a note of caution against hasty or piecemeal changes, and to sug- gest a new approach that may preserve the virtues of both good science and pru- dence. The case against conservatism The fundamental logical flaw of con- servatism is that it can compromise our ability to make clear choices and set ra- tional priorities. The strongest critics of conservatism view this distortion in the broadest possible terms; conservatism, they say, artificially inflates the relative importance of all proposed measures to reduce health and environmental risks. Some revisionists simply do not believe that the hazards of industrial pollution are as dire as the standard QRA procedures imply. But arguments that focus on the need to reduce existing risk numbers and redress the balance between risk and cost probably exacerbate the tension between the experts and the public, and may back- fire. After all, a "realistic" toll of 530 extra deaths from Alar (if revision caused a lowering of this risk number by a factor of 10) might be no more acceptable to the public than a cautious estimate of 5,300 fatalities. Therefore, a more reasoned and per- haps ultimately more successful argu- ment against conservatism is that it cre- ates imperceptible distortions among dif- ferent risks, which we cannot redress simply by paying less attention to cancer risk reduction (or by agreeing that we are spending about the right amount even though we have exaggerated the size of the risks). The insidious aspect of consis- tently analyzing the "worst case" is that some cases are simply "worse" than oth- ers, in the sense of being less plausible or less likely to occur. For instance,, one typical conservative shortcut is to assume SUMMER 1989 11 2025546371

Table 1. some Potentially "Conservative" Assumptions and Alternatives t;ommoniy Used in QRA Assumption Dose-response functioh is linear, so slope at low doses ec,uals thatat high doses Possible alternative Fit "sublinear" or threshold function to ob- served data Response of most sensitive rodent species/ sex tested predicts human risk All rodent 1:wnors are predictive of human cancer risk "Maximally exposed individual" (MEI) lives at plant or site boundary MEI's exposure is determined by upper- bound values of human uptake parameters (for example, breathing rate, water inges- tion) Concentration for all "not detected" samples is set as if it were just below the limit of detection that the most highly exposed individual near a chernical plant or a hazardous waste site live3 at the property boundary, and that he or she is downwind of the pollutant source 24 hours a day. In some cases, the resulting rislc estimate will be quite consenrative, if no one actually lives near the bourtdary or in the direction of the prevailing winds. In other instances, the estimate may be nearly correct. If the cancer risk estimate cited for the former situationwas 1 in 10,000, for the latter was 1 in 100,000, the former would seem more risky even though (unknown to the investigator) this esti- mate was less credible than its counter- part. Steps toward revisi®nism. Perhaps influenced by these arguments against conservatism, the U.S. Environ- mental Protection Agency (EPA) has recently begun to reconsider some of the official risk estimates it developed in earlier years.'I'o date, all of the proposed reevaluations- have resulted in lowered risk numbers, generally by about a factor of 10.The most noteworthy of these cases involve methylene chloride (a solvent Pool the responses of all rodent groups tested Discard data involving tumor sites and/or mechanisms that do not exist in humans Obtain case-specific data on MEI Use uptake parameters that represent the "average" human Assume these represent instances of zero concentration used, among other things, to decaffeinate coffee), arsenic, and TCDD, also known as dioxin. Potentially more farreaching than these ad hoc changes in specific risk assess- ments is EPA's September 1988 decision to rewrite its influential series of guide- lines for quantitative risk assessment, which had been published in 1986. These guidelines determine which assumptions should be used under various circum- stances, and indicate in general terms when professional judgment should sup- plant formulaic procedures. Although it is too early to tell specifically how the new guidelines will reflect what has been called the new era of post-conservative risk assessments, they may encourage the use of alternatives (see table 1). Conservatism in perspective A number of pervasive misperceptions about conservatism cloud the issue of whether risk numbers are credible and QRA procedures are reasonable. The fol- lowing points refute three of the broad categories of misperceptions. Existing procedures are not so unscien- tific or unreasonable. Critics tend to malign different kinds of conservative as- sumptions with the same broad brush, failing to distinguish those that are gratui- tous from those dictated by prudence or common sense. For instance, in contrast to the use of simplistic worst-case as- sumptions about exposure that could readily be refuted by reliable data, the commonly criticized use of the upper confidence limit when fitting a dose-re- sponse curve to animal data is a caution- ary step of a quite different variety. This procedure recognizes that as we learn more about cancer potency, the truth may well fail to converge toward a lower re- sult. To put it another way, suppose the owner of a baseball team approached one of his star players four days into the sea- son and asked him to take a pay cut on the grounds that he was batting .050 at the time. The player would doubtless argue that he has always had about a 1 in 3 chance of getting a hit each time at bat, and that his current 1-for-20 string is too scanty a basis forclaiming that that under- lying probability has changed at all. By the same token, observing 5 tumors in a group of 50 rats does imply that each rat had about a 1 in 10 chance of getting cancer at that dose, but is only weak evidence against the more prudent as- sumption that the probability might be several times larger. In addition, it is easy to carp about possible errors of commission in the QRA process without acknowledging that vari- ous errors of omission may make risk estimates more "nonconservative" for all or part of the human population. Of most significance, risk assessments commonly fail to account for the often-dominant indirect exposures (such as inhaling or- ganic compounds that volatilize from hot tap water during showering and bathing) and for the likelihood that individual humans differ widely in their inherent susceptibility to carcinogenic stimuli (we currently assume that all humans are as homogeneous in their responses as are the inbred strains of rodents we test in con- trolled environments). Thus, the current mix of assumptions may contain certain margins of safety necessary to account for our inability to fully flesh out important considerations. 12 RESOURC DES

ff Beyond that, the common characteriza- tion of QP:A as a "cascade" of conserva- tive steps that yields progressively more unbelievable estimates may confuse is- sues of probability and magnitude. It is true that if one multiplies five estimates that each have only a5 percent probability of being underestimates, the product will have much less than a 5 percent chance of being too low. However, many of the individual uncertainties in risk analysis are right-skewed; that is, the highest pos- sible values in the "tail" are much greater in absolute terms than the more central values. The fact that extreme values are unlikely to occur becomes less and less important ,ts the consequences of those values being true become greater. For example, the average indoor radon level in a sample of 5,000 homes in Pennsylva- nia was about 10, picocuries per liter (pCi/1) even though a randomly selected house had only about a 20 percent chance of containing more than 10 pCi/1. Deci- sion makers and the public need to con- sider that while it is easy to ridicule a risk estimate fcr being . exaggerated (in the sense of unlikely to be too low), such estimates may be more reasonable than less cautious ones. Data do exist to validate some existing numbers and procedures. Critics of conservatis m sometimes fail to acknowl- edge that e vidence exists to support the "reality content" of risk assessment pro- cedures or of the risk numbers them- selves. For example, researchers at the Harvard School of Public Health recently concluded that on average, the linear dose-respoaise function is not unduly conservative; for many chemicals, the best-fitting curve was in fact steeper at low doses 1han at higher ones. Similar challenges lo the notion that the current estimates ane systematically conservative come from recent studies of the disper- sion models used to predict the movement of pollutatu:; in air and water, which have shown that the models often underpredict actual concentrations, especially when the terrain o.r atmospheric environment is complicated. The mosr. direct "reality check" on QRA involves comparing the predictions of animal ex trapolation to the actual can- cer toll among humans exposed to known levels of a particular substance. Such a comparison can only be made for about two dozen substances (for example, ciga- rette smoke, vinyl chloride, and chro- mium) where both human and animal data on exposures and tumors are reasonably reliable. The basis for generalization is therefore limited, and the human potency estimates may be nonconservative (they generally come from data on small groups of relatively healthy workers). However, one research group recently found that, on average, conservative extrapolation pro- cedures yield estimates of human cancer potency that agree fairly well with the actual potencies observed in epidemio- logic studies. Alternative methods may substitute one set of flaws for another. The prospect of replacing conservative assumptions with "best estimates" of actual risk may be no less problematic than the status quo. Al- though conservative estimates have been widely derided as "policy choices mas- querading as scientific facts," central or average estimates themselves embody subtle value judgments regarding the implicit social costs of erring on the high or low sides. In this respect, bestestimates are no better than conservative ones, which simply strike this balance more in favor of caution about underestimation, and may reflect a desire to minimize large absolute errors of underestimation. In addition, while it is desirable to reduce the ambiguity about how conservative esti- mates of different risks are, one can show that errors in ranking uncertain risks are also endemic even when best estimates are consistently used. Reframing the question Many of the problems engendered by the use of conservative risk numbers (as well as their "real" counterparts) can be overcome by one deceptively simple step-abandoning the quest for single estimates of risk in favor of quantitative descriptions of the uncertainty surround- ing these numbers. Such descriptions, which would take into account random and systematic sources of uncertainty in potency, exposure, and uptake, would reveal all of the possible true values of risk and the likelihood associated with each. If uncertainty analyses became routine, we could move beyond the narrow debate over whether the estimates were too high or too low and could instead choose the degree of conservatism explicitly and with appreciation of the scientific nu- ances and societal value judgments specific to each case. For example, re- searchers from the National Institute of Environmental Health Sciences recently conducted an uncertainty analysis show- ing that if the EPA wanted to retain an es- timate of methylene chloride's potency that was a 95th-percentile conservative estimate, it might well have raised the of- ficial estimate by a factor of 1.5 (rather than lowering it by a factor of 9, as was done). Quantitative uncertainty analyses can also facilitate dialogue between risk man- agers and the public concerning how much society is willing to pay to reduce the possibility of particular levels of harm, and can help regulators perceive which uncertainties are dominant and thereby set strategies for research. All of these benefits come at a price, however. Uncertainty analyses are expensive to conduct, sometimes difficult to explain, amenable to subtle manipulation by inter- ested parties, and may be foreboding in that they reveal how little the experts actually know about the likelihood of different levels of harm. Nevertheless, the real challenge of QRA in the next decade will be to recognize that while ac- knowledging uncertainty may be as diffi- cult as stepping out of one's own shadow, only through the attempt can we discern from what direction the shadows are cast and in which directions to move so that they might ebb.  Adam M. Finkel is a fellow in the Center for Risk Management at RFF. This articl e is adapted from a paper in the Spring 1989 issue of the Columbia Journal of Environmental LaW. SUMMER 1989 13