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--> 8 Latency and Cancer Risk One of the topics of special interest to the Department of Veterans Affairs (DVA) is the potential effect of herbicide exposure on cancer latency. The term ''latency" is used in a variety of ways to denote the effect of the timing of exposure on the subsequent risk of disease. The importance of latency effects as well as other time-related factors, such as age at exposure, in determining cancer risk has long been recognized (Armenian, 1987). Some important practical questions at the heart of the investigation of these time-related factors are: (1) How long does it take after exposure to detect an increase in disease risk? (2) How long do the effects of exposure last? (3) How does the effect of exposure vary with the age at which it was received? and (4) Does a given carcinogen act at an early or late stage of the carcinogenic process? Often, either because of poor exposure assessment or the desire to report a simple summary measure of association, measures of exposure such as ever/never exposed or cumulative exposure are used to summarize exposure histories. Although such measures can be useful for detecting whether there is or is not an association between exposure and disease, it is well-known that timing of exposure plays an important role in determining when and by how much the eventual disease risk is increased (or decreased) by the exposure. In response to the DVA's request to explore latency issues related to Agent Orange, in this chapter the committee: 1) proposes a methodology to address the four questions listed above concerning the timing of herbicide exposure and the risk of cancer; 2) reviews the literature on herbicide exposure and cancers classified in sufficient and suggestive/limited categories for results that describe how timing of exposure affects the relative risk due to exposure; and 3) describes
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--> timing of exposure characteristics of the Vietnam veterans and summarizes the implications of these factors for their risk of cancer. Analysis Of Latency In Epidemiologic Studies In order to discuss latency issues, we need to establish what is meant by "the effect of exposure over time." First, for purposes of epidemiologic research and quantification, we are interested in the rate of disease among exposed individuals compared to the rate that would be expected if the subjects had not been exposed, as discussed more fully below. Thus, we are interested in the relative or excess rate of disease as the measure of comparison. Latency effects are essentially the change in relative or excess rates with "time since exposure." For exposures of short duration, time since exposure is easy to define. This is the case for environmental exposures from industrial accidents, such as the one that occurred in Seveso. If the exposure occurred over a long period of time (a protracted exposure), as with the production workers and pesticide applicators, the time since exposure is more difficult to quantify. Conceptually, we think of the effect of exposure at a particular time in the past as the resulting change in risk that today is ascribable to that exposure. Though perhaps overly simplistic, the effect of an entire exposure history can be usefully thought of as the sum of effects from exposure at each time point in the past. In order to adequately study effects of protracted exposures, detailed exposure histories for each study subject, including the dates that the individual was exposed and, ideally, the level of exposure, are needed. Appropriate statistical methods have been developed for an investigation of the effect of exposure accrued as a function of time since that exposure (Thomas, 1983; Breslow and Day, 1987; Thomas, 1988), but these have not been used in the analysis of any of the herbicide-cancer studies. In general, the ability to investigate the issues of timing of exposure in a given data set will depend on the quality of the exposure measure, the quality of the timing of exposure information, the number of people developing the disease of interest, and variation of exposure over time within the study group. These aspects of study quality are, of course, important in evaluating any epidemiologic investigation. But there are special problems that arise in the evaluation of time-related factors (Enterline and Henderson, 1973; Peto, 1985; Thomas, 1987). Need to control for the effects of aging Progression along the time since exposure scale is paralleled by increasing age. Because the rate of most cancers increases dramatically with age, it is also true that for a given study group, the expected number of cancers per unit of time will increase with time since exposure, simply because the study group is aging. Thus, examination of absolute numbers of cases as time since exposure increases would be misleading. We would expect to see an increase even if there were no change due to the exposure.
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--> Thus, it is standard epidemiologic practice to "normalize" the comparison by reference to an appropriate unexposed group. "Appropriate" in this context means a group with the same age structure at otherwise similar risk of disease as the study group so that we are measuring the effect of exposure in the development of cancers over and above those increases in disease rate that would be expected if the study group were simply aging with no exposure. Correlation between various time factors It is important to keep in mind that duration of exposure, time since exposure, age of exposure, and exposure level itself may well be correlated with each other, so that an observed pattern for one of these factors may actually be due to correlation with one of the others. Thus, exploration of one factor within each level of the other, either by stratifying of the analysis or by modeling their effect, is commonly needed to disentangle the confounding of time-related variables. Realistically, however, most data sets do not have sufficient data to explore these issues, and for the most part, these considerations merely serve as a cautionary note in the interpretation of results. The following hypothetical situations help to illustrate how the various time-related factors are intertwined. For illustration, we refer to the exposure of interest as "the agent." a) Two people are born in 1945. Both are continuously exposed to the agent for ten years. One person begins exposure at age 20 (continuing to age 30), and the other begins at age 30 (continuing to age 40). In 1995, at age 50, the first person has 30 years since his first exposure, whereas the second had only 20 years since first exposure. Thus, age at first exposure and time since first exposure, for a given duration of exposure, are linked. b) One person begins exposure to the agent in 1970, a second starts in 1975. Both are the same age at first exposure and continue exposure until 1985. When evaluated in 1995, the first person has both a longer duration of exposure (15 vs. 10 years) and a longer time since first exposure (25 vs. 20 years), showing the link between those two factors for a given age at first exposure. c) Two people are born in 1945. One starts exposure at age 20, the other at age 30. Both stop exposure at age 40. The first person has started at a younger age, has a longer duration of exposure, and a longer time since first exposure, showing that all three factors may be potentially linked. d) Two people are both exposed at the same intensity, in the sense that the airborne concentration of the agent (e.g., in parts per million) is the same for both. The person with the longer duration of exposure will, by definition, have a higher cumulative exposure. Although it is possible to construct counter-examples to the above, we believe these examples are fairly typical of what happens in many occupational settings and present them primarily to illustrate that interpreting an examination of the
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--> effects of one time-related factor may be difficult without information on the others. Need for sufficient variation in time-related factors In evaluating the evolution of relative risk with time, the value of a study is limited by the amount of time that has elapsed along the time scale of interest. For instance, the ability to explore the pattern of relative risks as a function of time since exposure depends on the range of time since exposure among the study group. We note that this is not necessarily the "follow-up" time for the study group, although the amount of information about time-related factors increases with the amount of follow-up. Rather, it depends on the variation of the factors within the group. Thus, a case-control study with cases obtained over a short period of time may be very informative about latency effects if both cases and controls have a wide range of times of exposure. Mortality and incidence studies for examining latency Generally, it is believed that carcinogenic agents increase the chance of cancer occurence but do not increase the likelihood of death once the cancer has occurred. If this is true, as we will assume, then studies of cancer incidence are preferable to those of mortality since exposure after the development of the cancer has no role in its etiology. In terms of the investigation of latency, the changes in relative risks with time since exposure will occur later for mortality studies compared to incidence studies, by an amount of time approximately equal to the average time from occurrence of the cancer to death. With the exception of Asp et al. (1994), the studies that reported latency results in the reviewed literature for the cancers we examined were mortality studies. We do not discuss this issue further in our description of the results, under the assumption that the exposure is associated with the cancer but does not change the risk of death once cancer occurs. However, it should be noted that mortality studies will result in a pattern of relative risks "shifted to the right" of the pattern that would have been observed in the corresponding incidence study. This phenomenon may also have implications for the number of "events" (deaths vs. cases) available for study at any given point in time, particularly for cancers with high survival rates. This, in turn, may have implications, especially in cohort studies, for statistical power. Measurement errors that are time-related In many instances, in epidemiologic studies, misclassification of exposed individuals as unexposed, and vice versa, tends to produce bias toward showing no association between exposure and disease when, in fact, an association may truly exist. This type of bias, called random misclassification, can generally be found when the misclassification of exposure status is unrelated to a person's ultimate disease status. In attempts to evaluate how time-related factors influence risk, this general principle still applies, but is far more complicated than in simple cases of classifying people as
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--> exposed or unexposed. Because of the complexity of the relationships, the effect of misclassification of time-related factors is difficult to predict in a straightforward, generalizable manner. Questions Addressed by the Committee For each question outlined in the introduction to this chapter, we discuss the measures that we are seeking in the reports of study results, how these measures are examined to address the particular question, the types of data a study would need in order to be informative about this question, and problems associated with the measures we have chosen. How long does it take after exposure to see an increase in disease risk? Measures of interest Relative risks for specific intervals of time since exposure are the appropriate measures of interest for this question. One must examine the pattern of relative risks, looking for the earliest indication of an increase in risk relative to the unexposed comparison group. For protracted exposures, it is sufficient to examine the relative risks by time since first exposure because it is likely that the earliest detectable increase in relative risk is a manifestation of the earliest exposure. In fact, relative risks for specific times since first exposure are the only measures reported for the herbicide effects studies with protracted exposure. Data requirements The critical data item for this measure is the date of first exposure. This is needed in order to determine the time that each subject spent in each time since first exposure category. If full exposure histories are available, more sophisticated analyses are possible. Potential problems with this approach The "earliest indication of an increase in relative risk" is not a fixed value, and it will be refined as more data are collected. First, it is likely that changes in risk occur continuously rather than suddenly jumping from "normal" to "above normal." Actual changes in relative risk probably would occur earlier than indicated by the analysis, but this would not be detectable. Second, "indication" necessarily means statistically detectable, and detectability is a function of the size of the particular data set as well as the magnitude of both the background level of risk and the relative increase in risk. In addition, the higher the quality of the exposure data, and the larger the exposure, the more likely the data would be to detect changes that occur earlier. In our evaluations, we determine the earliest increase in relative risk that can be detected based on the study results described in the literature. These are, of course, subject to change as more information becomes available.