Toms River

by Dan Fagin

  CHAPTER TWENTY-THREE

  Associations

  At first, Jerry Fagliano could not tell whether there was a discernible message buried within the stacks of computer printouts crowding his office. It had taken five years to collect all of the information he had sought about children and chemical contamination in Toms River. By the beginning of 2001, he had everything he needed to see whether kids diagnosed with cancer were truly more likely to have been exposed to pollution than healthy children. But there were so many ways to cut the data that it was hard to avoid getting lost in the blizzard of numbers. Prenatal exposure or postnatal? Parkway well water or Holly Street? Chemical plant or nuclear plant? Interview study or birth record study? Infants or schoolchildren? Boys or girls? Which years? Which cancers?

  With so many potential associations to analyze and so few cancer cases (just sixty-three, between the two studies), the data was unlikely to sort itself neatly. Instead, it was likely that some apparent links between exposure and illness would turn up for no reason other than chance, while others would stay forever hidden. This was a perpetual danger of small-number epidemiology: Even an association that passed a one-in-twenty test of statistical significance might still be a fluke. Fagliano knew that finding one or two isolated links between exposure and disease would not be scientifically convincing; there would need to be a pattern of associations, a pattern consistent with a prior hypothesis about what might have caused the cluster. On the other hand, associations between exposure and disease that did not pass a statistical significance test could not necessarily be excluded as suspects. The numbers were too small to be definitive about anything.

  Still, there was something that caught Fagliano’s attention almost immediately. A surprisingly high number of women who had been heavy consumers of Parkway well water while pregnant had children who developed cancer. No matter how he analyzed the data, children who were exposed to Parkway water after their birth did not face a large extra risk, but those who were exposed prenatally did. Similarly, mothers of case children were more likely to have drunk Parkway water than mothers of healthy control children. This observation was consistent with what Fagliano already knew from the interview results: There was a dose-response relationship between how much tap water women remembered drinking during their pregnancies and their risk of having a child with cancer. In other words, more glasses correlated with higher risk. That interview data was probably influenced by recall bias; mothers who had undergone the trauma of having an afflicted child were more likely to remember drinking a lot of water during pregnancy. But now the much more objective water dispersion computer model, which did not rely on anyone’s fuzzy or wishful memories, was backing those subjective interview results.

  At a staff meeting in Trenton early 2001, Fagliano and his collaborators at the health department looked at all of the water data collectively for the first time and were startled by the apparent clarity of the results. Instead of the inconsistent findings they expected from a study of such a small population, the Parkway results seemed to tell a coherent story. “That was a ‘wow’ moment,” Fagliano remembered. “When we looked at the wells that were not contaminated, we didn’t see any differences between cases and controls, but for the Parkway wells a strong association was there. It was pretty dramatic.”

  What was especially impressive about the Parkway well data was that there was an internal logic to the results. Fagliano had hypothesized that young children of women who had drunk a lot of Parkway water while pregnant would be at greatest risk, and now he found that the more tightly he focused his analysis on those children, the greater the calculated risk, as expressed by a standard statistical measure called an adjusted odds ratio.1 For instance, the cancer odds ratio for children in the interview study whose mothers, while pregnant, drank water that was mostly from the Parkway wells was 1.68, which meant that the odds that a child with cancer had been highly exposed prenatally to Parkway water were 68 percent greater than the odds for a healthy child of the same age and sex.2 That was not a huge amount of extra risk, but what caught Fagliano’s attention was that the odds ratios kept rising as he zeroed in on those subgroups that logically would be at greater risk if prenatal exposure to Parkway water really were triggering cancer.

  For example, when Fagliano looked only at prenatally exposed children who were diagnosed with cancer before age five, the odds ratio jumped to 2.51. That made sense, since cancers in older children were less likely to have been caused by exposures during pregnancy. The odds ratio jumped again to 3.01 when he added two other filters by taking into account how much water each woman remembered drinking during pregnancy and by counting only Parkway water consumed after 1981 in the “exposed” category (1982 was the year he assumed Union Carbide waste first reached the Parkway wells). This meant that the odds that young Toms River children with cancer had been prenatally exposed to post-1981 Parkway water were three times higher than the odds that healthy local children of the same age and sex had been. Finally, when he cut the data even finer by zeroing in on types of cancer known to have environmental triggers and also by separating the sexes, the associations grew still stronger: For girls diagnosed with leukemia or nervous system cancers before age five, the odds ratio was 4.60. For boys, it was 1.64. (There was no apparent explanation for the difference in genders.)

  Other permutations of the data yielded even higher odds ratios. For example, when Fagliano changed his assumption of when the Parkway pollution began from 1982 to 1984 and looked at prenatally exposed girls who were diagnosed with leukemia before age twenty, the odds ratio soared to 14.70. In other words, for the thirteen girls with leukemia born in Toms River between 1984 and 1996, the odds were almost fifteen times higher that they had been highly exposed prenatally to Parkway water, compared to the odds for healthy Toms River girls of the same ages.3

  Those were scary numbers, and they posed a dilemma very similar to the one Fagliano and Michael Berry had faced back in 1995 when Berry first identified the cluster in Toms River. The dilemma was this: Risk numbers were high, but so was the uncertainty. As in Berry’s 1995 analysis, each adjusted odds ratio in Fagliano’s studies came with a 95 percent confidence interval; the wider the interval, the more unreliable the result. Almost all of Fagliano’s confidence intervals were exasperatingly wide, just as Berry’s were. The problem was well illustrated by one of Fagliano’s most striking findings, concerning children in the interview study who were exposed prenatally to Parkway water between 1984 and 1996 and diagnosed with leukemia or nervous system cancer before age five. The results table looked like this:

  According to the table, the odds that Toms River children with leukemia and nervous system cancers had been highly exposed prenatally to Parkway water were three times greater than for similar but cancer-free children. But because there were so few highly exposed children in the analysis—just six case children and eleven controls—random variability could be heavily influencing the results. The only thing Fagliano could confidently conclude is that if he re-conducted the study twenty times, nineteen of those times the odds ratio would be somewhere between 0.78 and 11.60. That confidence interval not only was very wide, it also dipped below 1.00, which meant that there was a small but noteworthy chance that mothers who drank a lot of Parkway water while pregnant might actually be reducing their odds of having a child with cancer. It was another unhelpful snowy-or-sunny forecast, just as in Berry’s 1995 cluster study. In fact, because the interval dipped below 1.00, it did not meet the traditional definition of statistical significance, despite the high odds ratio.

  Almost all of the Parkway analyses that had so intrigued Fagliano and his colleagues shared this same problem: They dipped below 1.00 on their lower boundary. There were only a few exceptions, most notably when they looked specifically at leukemia risk in prenatally exposed girls in the interview study who were diagnosed before age twenty, getting these results:

  Even here, with a very high odds ratio and a confidence interval that was enti
rely above 1.00 (with a sky-high upper bound of 31.70) there was a great deal of uncertainty, as indicated by the wide confidence interval. There were only eight highly exposed girls in this analysis, which meant that adding or subtracting just one case would drastically alter the results. Furthermore, the results of Fagliano’s other study, the birth record study, did not yield odds ratios for Parkway exposure as high as the interview study did. Nor did the birth record study results form a distinct pattern of rising odds ratios as Fagliano honed the data for the hypothesized greatest risks.

  More frustration awaited when Fagliano and his colleagues tried to extend their analysis to the long-ago contamination of the riverside Holly Street wells in the 1960s, when Toms River Chemical had dumped billions of gallons of diluted dye waste into the Toms—enough to tint the river brown, give it a repulsive odor, and contaminate dozens of private and public wells. More than thirty years had passed, but until Fagliano’s effort, no one had ever tried to assess the health consequences of the Holly Street well contamination, which had been hushed up at the time. Fagliano soon learned that his attempt had come too late to supply meaningful answers. The wells had been polluted so long ago that the health department could find only a few exposed survivors to include in the studies. Fatal cases were even harder to find, since there was no cancer registry at the time. As a result, there were just three case children in the interview study known to have been highly exposed to Holly Street water between 1962 and 1975—too few to calculate a credible odds ratio. The numbers were slightly better for the birth record study: seven highly exposed cases, with a worrisome odds ratio of 2.73 and an alarming ratio of 10.00 for girls only. But the girls’ odds ratio was based on just two cases, generating an absurd confidence interval spanning all the way from 0.03 to 372.00. With so few cases, it was impossible to draw any conclusions.4 The toll from Toms River Chemical’s secret fouling of the riverside wells all those years ago would forever remain a mystery.

  That left just one major hypothesis to test as a potential cause of the cluster: air pollution, which had always taken a backseat to drinking water as a source of public anxiety in Toms River. The air dispersion model built at Rutgers University was intricate but relied heavily on guesswork, including its dependence on historic wind direction records from almost fifty miles away in Atlantic City. Fagliano doubted that the air model would turn up anything interesting, and his prediction was borne out when he analyzed windborne radiation dispersion patterns from the Oyster Creek nuclear plant ten miles south of town: Case families were not, on average, exposed more heavily to radiation than cancer-free control families.

  When Fagliano ran the numbers for airborne emissions from the Ciba plant, however, he saw something surprising: The data lined up in another dose-response pattern.5 For example, when he looked at downwind prenatal exposure to Ciba air emissions as a risk factor for leukemia and nervous system cancers, in interview study children under age five, the odds ratio for high-exposed children was 1.59, with a confidence interval that ranged from 0.80 to 14.90. When he homed in further, the odds ratios grew, just as they did with the Parkway wells. When he looked at air exposure as a risk factor for just leukemia, and only in girls under age five, he got these results:

  Those odds ratios were very high, and higher exposures to Ciba air generated higher ratios. Furthermore, the lower bound of the confidence interval for high exposure was very close to 1.00, which meant that living directly downwind from the chemical plant very likely increased leukemia risk in young girls. On the other hand, there were just two highly exposed cases, and the confidence interval was extremely wide, suggesting extreme uncertainty. Still, it was a pattern, and it showed up not only in the interview study but also in the birth record study, unlike the Parkway results. For prenatally exposed girls in the birth record study diagnosed with leukemia before age five, for example, the results for Ciba air emissions displayed this dose-response pattern:

  All in all, the computer printouts in Fagliano’s office carried a historic if bewildering message. Neighborhood cancer clusters had been an object of scientific fascination and public dread for a century, spawning hundreds of investigations around the world. Yet only once before, in Woburn, had a credible epidemiological study identified a likely environmental cause of a cancer cluster outside of the workplace. Now Fagliano thought that he had found two causes: air pollution from the chemical plant, and contaminated water from the Parkway wells. But had he really? The pattern of elevated odds ratios was strong, but the confidence intervals were wide and mostly dipped below 1.00, suggesting that there was still a nontrivial chance—unlikely, but certainly possible—that the associations he had uncovered were caused by nothing but random circumstance.

  “In a way, it was the worst possible result because we thought we had found something, but we couldn’t be sure,” Fagliano remembered. “We knew right away that this was going to be controversial. We knew it was something we would want to check forward and backwards.” Back in 1995, the health department had reacted to similarly disturbing results in Michael Berry’s incidence analysis by keeping quiet—with disastrous consequences. This time, staying quiet was not an option, not after six years of high anxiety and intense anticipation. This time, the State of New Jersey would eventually have to disclose everything it knew and everything it did not know.

  For the lawyers on the Toms River case, negotiating a potential settlement in the first months of 2001 was like playing high-stakes poker without being able to look at your cards. Thanks to the expert presentations they had heard at the meetings with mediator Eric Green, both sides had a sense of the strengths and weaknesses of their arguments. But the most important, make-or-break information would not be available until the results of the case-control studies were released—and Jerry Fagliano was not divulging anything yet.

  There were obvious advantages to settling now. Jan Schlichtmann had learned the perils of all-or-nothing brinkmanship in the Woburn case the 1980s: His insistence on pursuing it to the bitter end—spurning several settlement offers along the way—left him homeless and bankrupt. This time, against their initial instincts, Linda Gillick and the TEACH families had bought into Schlichtmann’s new strategy of staying out of court and seeking a negotiated solution. If it failed to bear fruit now, they would essentially have to start over or just give up. The companies, too, had good reasons to settle. Dow Chemical, the new owner of Union Carbide, was eager to move on. So was Ciba, which was focused on cleaning up the factory site and then leaving Toms River for good. William Warren, the Union Carbide lawyer who was leaving the case now that Dow was in charge, still believed that the companies would win if there were a trial, but the case-control study was a looming unresolved risk. “I often tell clients that they may look at what’s being put on the table [as a settlement offer] and find it horribly offensive and unacceptable, but you can’t compare that with what may happen” at a trial, Warren would later explain. “You can stand on principle, but there are potential costs to standing on principle.”

  The families’ three principal lawyers—Mark Cuker, Esther Berezofsky, and Schlichtmann—were trying to present a united front to Warren and the other company lawyers. That was not easy. Schlichtmann felt disrespected and underappreciated, while Cuker and Berezofsky thought Schlichtmann was too eager to settle. They admired his creativity and persuasive skills, but he had done much less work on the case than they had, in part because he was distracted by the seemingly endless repercussions of his Woburn-related financial meltdown ten years earlier and also by an unfriendly split from his most recent law firm, San Francisco–based Lieff, Cabraser, Heimann, and Bernstein, to which he had handed off some of his Toms River work. Cuker and Berezofsky had visited Toms River dozens of times to meet with Linda Gillick and other leaders of the families; Schlichtmann had made only a few trips and was not close to the families. Yet Schlichtmann was the lawyer who received most of the press coverage associated with the case, thanks to his celebrity status as the flawed hero of
A Civil Action. As the negotiations began, the three lawyers’ uneasy partnership was fraying.

  Settling the case would require assigning dollar figures to human lives, a fraught process that would be especially challenging in Toms River because of the heterogeneity of the sixty-nine children. The heart of their legal claim was that pollution from Ciba or Union Carbide, conveyed by United Water’s pipes, had triggered their cancers. But that argument was much stronger for certain children than for others. Some were exposed to tainted water for only a few months; others, for their whole lives. Some were diagnosed as infants; others, as teenagers. Some suffered through years of agonizing treatments; others recovered faster. For fifteen children, the suffering was over; cancer had killed them.

  The most difficult distinctions were by cancer type. There were more than a dozen kinds of cancer among the Toms River children, from acute lymphoblastic leukemias (the most common) to a single case of rhabdomyosarcoma, a rare soft-tissue tumor. Since cancer is not one disease but more than 150 unique conditions, it made little sense to treat them all the same. Leukemia victims, for example, had relatively strong claims because there was credible evidence of a leukemia cluster, thanks to the state’s 1995 incidence analysis. There was also a large, if controversial, body of scientific research associating leukemia with industrial chemicals—especially trichloroethylene, which was known to have been present in Parkway water. A young child with leukemia would have an even stronger claim because prenatal chemical exposure would be one of the few credible explanations for what might have caused the disease. For other kinds of cancers, however, there was nothing at all in the medical literature to suggest pollutants might be to blame and no evidence of an unusually high number of cases in Toms River.