1

The Matter of An Arbitration Under the Rules of the

United Nations on International Trade Law

Chevron Corporation and Texaco Petroleum Company

v.

The Republic of Ecuador

PCA Case 2009-23

Opinion of Philippe Grandjean, MD

November 7, 2014

Prepared for Winston & Strawn, LLP

1700 K Street N.W. Washington DC 20006-3817

Prepared by

__________________________________

Philippe Grandjean, MD, DMSc Professor of Environmental Medicine

2

I. Summary of credentials, scope of retention, and underlying basis of opinion A summary of my credentials, scope of retention, and the underlying opinion appears in my

November 22, 2013 report. As in that report, my opinions in this expert report are given to a reasonable degree of scientific probability. They are based on my education, professional experience, information and data available in the scientific literature, and information and data about this lawsuit made available to me at the time these opinions were formulated. If additional information becomes available, I reserve the right to supplement my opinion to reflect such information.

II. Opinions Dr. Suresh Moolgavkar’s May 9, 2014 rebuttal contains several misunderstandings that need to

be corrected.

Risk assessment

Dr. Moolgavkar claims that risk assessment (RA) is conservative and not based on observed risk at low levels of exposure. (Moolgavkar at 3)

This claim is wrong. To the contrary, RAs are not conservative (i.e., protective of health) enough because they rely only on current evidence and therefore do not take into account untested or undocumented effects of chemicals. As noted by the U.S. National Research Council (“NRC”), regulatory action is required only when chemicals have been shown to be harmful.1 Because so many chemicals have yet to be tested (and accordingly are assumed not to be harmful) RAs, even when available, tend to underestimate risk. As pointed out by the NRC, this “untested chemical assumption” is often wrong, resulting in far less protection than is desirable.1 With time, as better documentation becomes available, the risk generally is found to be greater than anticipated. For example, changes in the occupational exposure limits (“Threshold Limit Values” or “TLVs”) determined by the American Conference of Governmental Industrial Hygienists have almost all become lowered with time as better documentation became available. The TLV for benzene – a chemical highly relevant to the present case – had to be lowered repeatedly: the current TLV represents a decrease by more than 100-fold from the original value (http://www.acgih.org/products/tlvintro.htm). Clearly, the RAs underlying each of the previous TLVs for benzene were not protective at all. In addition to documentation being incomplete, underestimation of risk in the present case occurs due to uncertainties in regard to exposure assessment and outcome assessment, as discussed in further detail below.

Bradford Hill’s “aspects”

Dr. Moolgavkar calls Dr. Strauss’s discussion of Austin Bradford Hill’s famous aspects of causality2 “out of context” and “scientifically inappropriate”. (Moolgavkar at 3) This critique is incorrect. Dr. Moolgavkar claims that the Bradford Hill “guidelines … cannot meaningfully be applied to null associations” because they are “intended to be used to evaluate whether an observed statistically significant exposure-disease association can reasonably be interpreted as causal” (Moolgavkar at 3). But Sir Austin never claimed that his causation aspects (sometimes referred to as

3

“criteria”) would refer only to statistically significant associations. In fact, his seminal paper was later analyzed to examine to what extent the absence of any of the specific aspects (including absence of statistical significance) could be taken as an indication that a causal relationship was not present.3,4 While the evidence in support of causal associations in the present case is incomplete, it is Dr. Moolgavkar’s critique that is inappropriate, as he misconstrues the uncertain, though relevant evidence as an indication that no causal association is present. Dr. Moolgavkar’s argument is a non sequitur.

Epidemiology

Dr. Moolgavkar claims that epidemiological studies evaluate what actually did happen, whereas RAs evaluate only what might happen under certain circumstances. (Moolgavkar at 3)

This is only partially true. Epidemiological studies can evaluate what actually did happen, but only in cases where valid exposure data and outcome data are available.5 This is not the case here, as exposure and outcome data are imprecise, if they are available at all. Therefore, the adverse health risks are likely underestimated, as I explained in my previous report (see also below). Additionally, it is not true that RAs must rely on proven risks or causal associations between harmful exposures and adverse health outcomes.  RAs are particularly useful where there are gaps in epidemiological data so that other relevant forms of evidence can be utilized.

Dr. Moolgavkar claims that there is no increase in cancer mortality risk in the oil-producing areas.6 (Moolgavkar at 4-5)

The epidemiology report on the cancer mortality study conducted by Dr. Moolgavkar in 2014

supports a conclusion that, under the circumstances of the study, an increased risk of death from cancer could not be verified in residents living in the Concession Area.6 However, because his 2014 study relies on imprecise indicators of exposure and information on cancer mortality, and because the statistical uncertainty is large (as expressed by the wide confidence limits), Dr. Moolgavkar’s study results cannot exclude the presence of a substantial risk – e.g., almost a 3-fold risk of total cancer per 1,000 well-years. Additionally, the study did not take into account residual confounding factors (such as dependence on access to health care), which Dr. Moolgavkar himself notes (albeit in connection with studies that he is criticizing) can invalidate a study’s findings.

Immune suppression

Dr. Moolgavkar claims that there is no evidence that exposure to oil can result in immune suppression, resulting in increased susceptibility to infection-associated cancers. (Moolgavkar at 4)

Dr. Moolgavkar does not provide any evidence to support or substantiate his position.  Recent

studies indicate that exposure to industrial chemicals may well result in immune suppression in humans. For example, my colleagues and I recently found that perfluorinated alkylate substances (“PFASs”) (compounds derived from hydrocarbons) can seriously affect the immune system in children.7 However, until recently, PFASs were not thought to affect the immune system, and this potential risk was therefore not taken into account by the regulatory agencies when they relied on then-existing toxicology data to derive exposure limits for PFASs.8-10 Thus, due to the incomplete documentation at the time, the

4

exposure limits soon turned out not to be sufficiently protective. Our benchmark calculations have now shown that the current exposure limits for PFASs are at least 100-fold too high,11 thus again demonstrating that the previously mentioned “untested chemical assumption” can result in serious misjudgments in RA. I understand that regulatory agencies in the U.S. and elsewhere plan to modify the exposure limits accordingly.

Given this experience and the general issues discussed in my contribution to the monograph

published by the European Environment Agency,12 as well as the existing evidence referenced in Dr. Strauss’s reports and the report of Dr. Blanca Laffon, it is unreasonable to conclude, as Dr. Moolgavkar does, that there is no risk of immune suppression from exposure to the chemicals from oil exploration and production. To the contrary, that risk is plausible and highly likely.

Occupational health information

Dr. Moolgavkar cautions against evaluating whether certain exposures could cause an excess of

certain diseases if no such disease excess has been documented. (Moolgavkar at 5) This statement runs counter to the cumulated experience regarding how knowledge about

occupational and environmental risks has emerged in the past. The presence of a documented cancer risk is not a prerequisite to evaluate whether exposure to oil may be associated with an increased cancer risk. Indeed, unrealistic demands for documentation of disease has often led to unnecessary and prolonged exposure to risk, as discussed, e.g., by the NRC.1 Many occupational cancers were at first ignored because the risks were seemingly not elevated above the background. Early comparisons of worker populations with the general population initially masked adverse effects because the comparisons did not account for the “healthy worker effect,” i.e., the fact that gainfully employed workers are in better health than the background population.13 With time, when more detailed information became available, and when proper adjustment for the “healthy worker effect” and other inaccuracies were made, the risks became apparent and led to stricter exposure limits and other regulations although with much delay. Benzene, an oil chemical mentioned above, is a proper example.

Dr. Moolgavkar suggests that there is potential for information bias in the worker studies conducted by San Sebastian et al., and that exposures among clean-up workers are not comparable to those of Concession Area residents. (Moolgavkar at 5)

Dr. Moolgavkar’s first statement implicitly renders his second statement incorrect. If the exposure information is biased, the conclusions reached with respect to exposures among the clean-up workers would not only be inapposite to those of the Concession Areas residents but would also be invalid. Although information bias is always difficult to completely exclude, the different sets of studies are comparable because the workers and the residents are exposed to similar toxicants from similar sources. Still, the residents are exposed through multiple pathways including ingestion, which is less likely to affect workers. In addition, workers experience breaks in exposure — going home at night, weekends, vacations — whereas local residents who remain in the exposed neighborhood are continuously exposed. Workers also tend to wear protective gear and garments while residents do not.

5

Thus, the residents may well have an even higher cumulated exposure over time than the workers, many of whom may have moved away from the Concession Area.

Dr. Moolgavkar concludes that the classification of oil production areas by San Sebastian and coworkers14-17 is inferior to his own method of classification. (Moolgavkar at 6-7)

Dr. Moolgavkar’s conclusion is not accurate because his and his associates’ grouping of cantons incorporates populations that were not exposed to oil production activities, thereby diluting risk association (Grandjean 2013 at 7). Additionally, as discussed by Dr. Strauss, Dr. Moolgavkar includes areas of oil production that are outside of the Concession Area, where the oil extraction/disposal practices were unlikely to be similar to TexPet’s (Strauss 2014 Report Section 4.2). Therefore, cancer evaluation should be limited to only the Concession Area, as San Sebastian has done. Dr. Moolgavkar also used “well years” as his metric of exposure from 1972 to 1990, although this metric does not account for how long wells were in existence. In contrast, San Sebastian’s exposure metric was counties with >20 years of oil production vs. those with no oil production. While this method is less quantitative than “well years,” the yes/no nature of it likely yields more accurate information as to whether or not people were significantly exposed.

Misclassification of outcomes

Dr. Moolgavkar claims that residential migration will not lead to underestimated risks. (Moolgavkar at 7-8)

Dr. Moolgavkar states that migratory workers have better access to health care and are thus more likely to be diagnosed with cancer than residents, and that the focus on workers is therefore misplaced. Dr. Moolgavkar’s supposition is wrong for several reasons. First, according to my inquiries (Dr. Raul Harari, pers.comm.), sizeable parts of the worker population were not counted as El Oriente residents. Thus, workers who maintained their residence in Quito (or other major city) – or later on returned to this residence – would not be counted as part of El Oriente population, thereby diluting the results and showing an erroneously lesser risk.

Second, and more importantly, migrant workers typically worked for only three weeks in El

Oriente, returning to their residences in Quito for one week before repeating the cycle. Non-migrant workers, on the other hand, typically stayed longer in El Oriente, but later on often moved away from the area. As a result, residents had more continuous exposure than the migratory workers, in which case the bias would be reversed.

Third, if any of the workers living in El Oriente moved to Quito, e.g., for long-term care, they

would likely be registered as Quito residents at death, even though the exposures happened in El Oriente. Thus, again even if Dr. Moolgavkar were correct that workers are more likely to be diagnosed with cancer than residents, any such tendency or bias will be counteracted by the likelihood of the worker being identified as a Quito resident, i.e., a bias in the opposite direction.

A further issue relates to the validity of the cause of death, as extracted from the death certificate.

Although this is a routine procedure that has often been used in the past, the difficulties in assessment of

6

cancer incidence in the Amazon are well known,18 and may therefore render this approach invalid. In Ecuador, and in particular in El Oriente, the cause of death is usually given as the immediate cause (e.g., pneumonia), not the underlying disease (e.g., leukemia). Thus, even if some workers or residents may have easier access to the Quito hospitals (which I do not believe is correct given the cost and difficulty of traveling from El Oriente to Quito), records would likely be better for subjects residing in Quito, and the bias would result in El Oriente cancer diagnoses not being reflected in the mortality data.

Finally, Dr. Moolgavkar believes that San Sebastian and coworkers used outdated resident

numbers that are too low. While population counts are inherently imprecise, the higher population counts preferred by Dr. Moolgavkar would include temporary residents who would not be likely to contribute to the cancer and other disease outcomes in El Oriente area. In a report prepared for the Pan-American Health Organization, researchers from the University of Wisconsin-Madison raise many of the above concerns, and they conclude that “certain information needed to fully understand health impacts from oil development was often missing or out of date.”19

Misclassified exposures

Dr. Moolgavkar claims that random misclassification will not lead to underestimation and refers

to sources that explain that exceptions occur to the general tendency of underestimation. (Moolgavkar at 7-8)

When exposures (and, to some extent, outcomes) are incompletely known, the estimated association between the exposure and the presumed effect will not reflect the true linkage, and the association will generally be underestimated. In technical terms, occurrence of non-differential errors (i.e., errors that are evenly distributed among study subjects) in the exposure parameter will bias the dose-

response relationship toward the null,* as explained in the major textbook on this matter.20 Dr. Moolgavkar refuses to accept that this general tendency would apply to the Ecuadorean Amazon setting, and he refers to my statement in this regard as being “scientifically unsound.” In reaching this conclusion, Dr. Moolgavkar refers to two brief notes from 1995 and an article from 2005, while ignoring that the same authors have published more extensive papers later on, e.g., in 2008,21 which do not support Dr. Moolgavkar’s position that random misclassification in general will not lead to underestimated risk.

Additionally, although Dr. Moolgavkar claims that such underestimation does not occur, he speculates that it would also affect point estimates (i.e., calculated values for unknown parameters) that happen to be below expectation in his own epidemiology study. If risks below expectation are underestimated, they should in reality deviate even further from expectation. Specifically, Dr. Moolgavkar opines that such cases of low point estimates underestimate the possibility that exposure to oil offers protection against adverse effects. Thus, Dr. Moolgavkar seems to be willing to accept that underestimation may occur, but only if it supports the conclusion that he favors.

                                                            * A null result or finding means only that under the traditional scientific paradigm there was not enough information to reach a “statistically significant” result. Null results, however, are not synonymous with negative results.

7

Confidence limits

Dr. Moolgavkar relies on his own uncertain point estimates of cancer risk and calls consideration of the 95% confidence interval “scientifically unjustifiable”. (Moolgavkar at 8-9)

As already referred to above, Dr. Moolgavkar claims that his study documented an absence of risk, as the results did not deviate significantly from expectation. In addition to the weaknesses and caveats already mentioned, Dr. Moolgavkar ignores that such results must be interpreted in light of statistical uncertainty, which is often expressed in terms of the 95% confidence interval. The upper 95% confidence limit reflects the highest risk that would be in reasonable accordance with Dr. Moolgavkar’s results. When the upper confidence limit for total cancer is 2.9 in regard to 1,000 well-years, it means that an almost 3-fold occurrence of cancer in the exposed population cannot be excluded on the basis of Dr. Moolgavkar’s study. Dr. Moolgavkar’s refusal to accept this standard statistical consideration clearly serves to support the conclusions that he favors, but it is not justifiable.

False positives

Dr. Moolgavkar cites selected sources to document that false positives occur and may seriously impact RAs. (Moolgavkar at 9)

Apart from relying on highly select studies that are not representative of RAs in general, e.g., silicone breast implant studies, Dr. Moolgavkar refers to several papers that deserve comment because they represent one-sided views linked to industry interests, many of which have since been rebutted in published responses from scientists in scholarly journals.

The report by Paolo Boffetta et al.22 was written with colleagues whose research relies on industry support. That Dr. Boffetta attempted to hide his own conflict of interest has been a matter of public scrutiny, particularly in France.23 Dr. Boffetta’s article22 was rebutted by several academics (I was one of the authors of one of the rebuttal papers).24 Although the same is true with other of the articles that Dr. Moolgavkar refers to, nowhere in his report does he acknowledge or refute these rebuttal papers.

Among the literature that Dr. Moolgavkar refers to is an article25 where the authorship overlaps with the Boffetta article,22 as both included the same industry-supported author. Thus, by citing articles by interlinked authors, Dr. Moolgavkar gives the erroneous impression that he refers to independent and substantiated evidence. However, as also shown by the rebuttals that Dr. Moolgavkar has ignored, the references selected are not representative of current science.

Dr. Moolgavkar also refers to an article by Dr. Morfeld,26 but again does not refer to the rebuttal by French and German academic authors who not only reach different conclusions on the merits of false positives but who also highlight Dr. Morfeld’s industry employment27 and how it appeared to influence his views.

As outlined above and in my previous report, false negatives (that erroneously conclude that a true hazard is innocuous) are a particularly serious problem in environmental and occupational health,

8

where the majority of potential hazards have been incompletely characterized and are thus considered harmless (referred to above as the “untested chemical assumption”). Although false positives (those that erroneously claim that a hazard is present when there is none) may occur, they appear to be rare. In a comprehensive study that reviewed alleged cases of false positives in light of subsequent knowledge, most of them turned out to be erroneously classified, as more recent evidence documented that a true hazard was indeed present; only a few cases, such as the swine flu, were found to be true false positives (the feared swine flu epidemic did not materialize).28 Dr. Moolgavkar’s conclusions are contrary to this evidence.

III. Conclusions

In his rebuttal, Dr. Moolgavkar generally refuses to accept that imprecise exposure information can cause bias toward the null, particularly where considerations of bias contradict his views. Curiously, however, Dr. Moolgavkar seems to accept this supposition when imprecise exposure information can be interpreted to support his preferred conclusions. To support his extreme views, Dr. Moolgavkar also refers to outdated, misinterpreted, and/or clearly biased evidence, while simultaneously sidestepping and ignoring more current academic publications. Finally, Dr. Moolgavkar commits a clear error in expressing his certainty in regard to the absence of risk when no such certainty is possible, and in this case implausible, given the incomplete evidence and the weaknesses of his own epidemiology study. Dr. Moolgavkar’s arguments presented for this arbitration would not pass peer review, and his poorly veiled biases clearly show that Dr. Moolgavkar has no support for his extreme opinions.

SOURCES

1. National Research Council. Science and decisions: advancing risk assessment. Washington, D.C.: National Academy Press; 2009. 2. Hill AB. The environment and disease: Association or causation? Proc R Soc Med 1965;58:295-300. 3. Kaufman JS, Poole C. Looking back on “causal thinking in the health sciences”. Ann Rev Publ Health 2000;21:101-19. 4. Susser M. Causal thinking in the health sciences; concepts and strategies of epidemiology. Ch. 11. New York: Oxford University Press; 1973. 5. Baker DB, Nieuwenhuijsen MJ. Environmental epidemiology: study methods and application. Ch. 2. Oxford: Oxford University Press; 2008. 6. Moolgavkar SH, Chang ET, Watson H, Lau EC. Cancer mortality and quantitative oil production in the Amazon region of Ecuador, 1990-2010. Cancer Causes Contr 2014;25:59-72. 7. DeWitt JC, Peden-Adams MM, Keller JM, Germolec DR. Immunotoxicity of perfluorinated compounds: recent developments. Toxicol Pathol 2012;40:300-11. 8. European Food Safety Authority. Opinion of the Scientific Panel on Contaminants in the Food chain on Perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA) and their salts. The EFSA Journal 2008;653:1-131. 9. U.S. Environmental Protection Agency. Provisional health advisories for perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Washington, DC: U.S. Environmental Protection Agency; 2009 January 8, 2009. 10. Agency for Toxic Substances and Disease Registry. Draft toxicological profile for perfluoroalkyls, 2009.

9

11. Grandjean P, Budtz-Jorgensen E. Immunotoxicity of perfluorinated alkylates: calculation of benchmark doses based on serum concentrations in children. Environ Health 2013;12:35. 12. Grandjean P. Science for precautionary decision-making. In: Gee D, Grandjean, P., Hansen, S.F., van den Hove, S., MacGarvin, M., Martin, J., Nielsen, G., Quist, D., Stanners, D., ed. Late Lessons from Early Warnings. Copenhagen: European Environment Agency; 2013:517-35. 13. Steenland K, Deddens J, Salvan A, Stayner L. Negative bias in exposure-response trends in occupational studies: modeling the healthy workers survivor effect. Am J Epidemiol 1996;143:202-10. 14. San Sebastian M, Armstrong B, Cordoba JA, Stephens C. Exposures and cancer incidence near oil fields in the Amazon basin of Ecuador. Occup Environ Med 2001;58:517-22. 15. San Sebastian M, Armstrong B, Stephens C. Outcomes of pregnancy among women living in the proximity of oil fields in the Amazon basin of Ecuador. Int J Occup Environ Health 2002;8:312-9. 16. Hurtig AK, San Sebastian M. Incidence of childhood leukemia and oil exploitation in the Amazon basin of Ecuador. Int J Occup Environ Health 2004;10:245-50. 17. Hurtig AK, San Sebastian M. Geographical differences in cancer incidence in the Amazon basin of Ecuador in relation to residence near oil fields. Int J Epidemiol 2002;31:1021-7. 18. Moore SP, Forman D, Pineros M, Fernandez SM, de Oliveira Santos M, Bray F. Cancer in indigenous people in Latin America and the Caribbean: a review. Cancer Med 2014;3:70-80. 19. Long J, Motew M, Mayes M, Limaye V. A preliminary analysis of oil and health in the Western Amazon. Madison, WI: University of Wisconsin-Madison; 2011. 20. Fuller WA. Measurement error models. Ch. 1, section 1.1.1. Hoboken, N.J.: John Wiley & Sons, Inc.; 2006. 21. Jurek AM, Greenland S, Maldonado G. How far from non-differential does exposure or disease misclassification have to be to bias measures of association away from the null? Int J Epidemiol 2008;37:382-5. 22. Boffetta P, McLaughlin JK, La Vecchia C, Tarone RE, Lipworth L, Blot WJ. False-positive results in cancer epidemiology: a plea for epistemological modesty. J Nat Cancer Inst 2008;100:988-95. 23. Foucart S. Epidémiologie: des liaisons dangereuses. Le Monde 18 December 2013. 24. Blair A, Saracci R, Vineis P, et al. Epidemiology, public health, and the rhetoric of false positives. Environ Health Perspect 2009;117:1809-13. 25. Ioannidis JP, Tarone R, McLaughlin JK. The false-positive to false-negative ratio in epidemiologic studies. Epidemiology 2011;22:450-6. 26. Morfeld P. A plea for rigorous and honest science: false positive findings and biased presentations in epidemiological studies. Arch Toxicol 2009;83:105-6. 27. Slama R, Cyrys J, Herbarth O, Wichmann HE, Heinrich J. A further plea for rigorous science and explicit disclosure of potential conflicts of interest. Arch Toxicol 2009;83:293-5. 28. Hansen SF, Krayer von Krauss MP, Tickner JA. Categorizing mistaken false positives in regulation of human and environmental health. Risk Anal 2007;27:255-69.