If there’s one thing about antivaccine activists (a.k.a. antivaxers), it’s that, no matter what, it’s always about the vaccines. Always. Whatever chronic health issue it might be, autism, autoimmune disease, diabetes, or whatever, to the antivaxer, it’s always the vaccines that did it. Always. I’ve just come across a new “study” by Gayle Delong supposedly implicating the HPV vaccine with female infertility that demonstrates this principle again through its sheer awfulness, as you will see.
Before we dive into the study, first I have to make a brief observation about HPV vaccines. To antivaxers, lthough it’s always about the vaccines, to antivaxers, some vaccines are more detested than others. Arguably the vaccine most detested by antivaxers is the HPV vaccine. Be it Gardasil or Cervarix, the HPV vaccine is the target of special fear and loathing among antivaxers. Scientists turned antivaxers like Christopher Exley do horribly designed and executed studies to “prove” that the aluminum adjuvants in Gardasil are dangerous or cause behavioral problems. Others try to link the HPV vaccine to premature ovarian failure using studies that fall apart on the most minimal dissection. If that fails, antivaxers try to convince parents that Gardasil and Cervarix kill again and again and again and again, based on the thinnest of evidence.
Indeed, there’s something about HPV vaccines that imbues them with a strange power over people who are often otherwise reasonable about vaccines. For some reason, HPV vaccines seem to have an uncanny ability to turn such people into raging antivaccinationists almost as loony as the merry band of antivaccine loons over at Age of Autism. At the very least, they seem to make seemingly reasonable people susceptible to blandishments and tropes for which they’d normally otherwise never fall. Truly, Gardasil and Cervarix seem to be vaccines that make reasonable people lose their minds. I tend to think it’s about the sex. After all, HPV is largely a sexually-transmitted virus, hence the tendency for fundamentalist Christians to find it particularly objectionable. Whatever the reason for the outsized negative reaction to Gardasil and Cervarix, antivaccinationists are aware of it. Indeed, they nurture it and take advantage of the undeservedly bad reputation that HPV vaccines have. This brings us back to Gayle Delong’s latest horrible “study” claiming to suggest an adverse health effect from Gardasil.
We’ve met Gayle Delong before, first in 2011 when she published a paper that was the ecological fallacy writ large trying to show that vaccines cause autism. Then, a year later, she published an equally risible paper about “conflicts of interest” in vaccine science that was really an attack on the Vaccine Court. Then, in 2014, Delong blamed her breast cancer diagnosis on dealing with her child’s autism and made it clear that she viewed autism as worse than breast cancer. Another thing that you need to know about Gayle Delong is that she is not a scientist, physician, or epidemiologist. She is, rather, Associate Professor of Economics and Finance in the Bert W. Wasserman Department of Economics and Finance at Baruch’s Zicklin School of Business. None of that’s stopped her from bravely paddling up the river of pseudoscience in topics where she has no expertise. The likely reason is that she filed a claim under the Vaccine Injury Compensation Program on behalf of her autistic daughter and the Special Master dismissed the claim due to untimely filing.
The title of the study, A lowered probability of pregnancy in females in the USA aged 25–29 who received a human papillomavirus vaccine injection, pretty much tells you what Delong claims to have found. She didn’t find anything of the sort (as I will show), but that’s what she thinks she’s found. Basically, Delong thinks she can do epidemiology, but I’m a better epidemiologist than she is and I’m not an epidemiologist, if you know what I mean. In any case, the idea is that, among women 25-29, fertility is lower, supposedly independently from the decline in birthrate that occurred in the wake of the 2007-2008 financial crisis.
Before I get to the science, let me just point out some red flags in the paper. First, in the acknowledgments section, Delong notes:
The author thanks David Geier, Sabastiano Manzan, Jonathan Rose, and Paul Turner as well as Sam Kacew (the editor) and three anonymous reviewers for insightful comments. Any errors are solely the responsibility of the author.
Yes, you read that right: David Geier, the fils from the père et fils team of antivaccine pseudoscientists, a not-so-dynamic duo whose crimes against vaccine science and utter antivaccine quackery I’ve written about more times than I care to remember.
Then, in the introduction, Delong lays down the antivaccine tropes about HPV vaccines:
Reports of young women experiencing primary or premature ovarian failure (POF) after receiving the vaccine were noted (Colafrancesco et al. 2013; Little and Ward 2012, 2014). POF—defined as the onset of menopause before the age of 40—is sometimes referred to as premature ovarian insufficiency and thought to be extremely rare. Symptoms include menstrual disturbances such as primary or secondary amenorrhea as well as hot flashes and mood swings. The estimated incidence for females under the age of 30 is 1 in 1000, rising to 1 in 100 for females under the age of 40 (Rafique, Sterling, and Nelson 2012). However, the use of the birth control pill might mask the existence of POF and thereby understate the incidence of the disorder. Islam and Cartwright (2011) noted that of the 4968 females in a UK birth cohort that had been born in 1958, the number of women who experienced POF was 370 (7.4%). Underlying conditions such as radiation and chemotherapy might give rise to the malady, but 80–90% of POF cases have no apparent cause. POF may be an autoimmune disorder and between 10% and 30% of women with POF also have other autoimmune disorders (Maclaran and Panay 2015).
No. Just no. I’ve written about nearly all of the above antivaccine studies claiming to have found a link between vaccination against HPV and premature ovarian failure. As I said above, there’s no there there.
As if this weren’t enough, Delong goes on to credulously quote the Geiers (always a bad idea if you want to be perceived as anything other than an antivaccine loon):
Geier and Geier (2017) examined the Vaccine Adverse Events Reporting System (VAERS) database to determine whether uptake of the HPV vaccine affected the number of reports of autoimmune reactions. VAERS is a passive system where vaccine administrators or recipients report adverse effects after receiving a vaccine. Between 2006 and 2014, HPV vaccine recipients or their health care providers noted 48 cases of ovarian damage associated with autoimmune reactions. In addition to the Geier and Geier findings, the VAERS database between 2006 and 2017 indicated other symptoms that affect the ability to bear children: spontaneous abortion (214 cases), amenorrhea (130 cases), and irregular menstruation (123 cases).
As I’ve described, again more times than I can remember, the VAERS database is highly unreliable for estimating the frequency or even whether reported adverse reactions are related to vaccines. At best, it can function as an “early warning” system, but at worst it’s hopelessly tainted by antivaxers and their lawyers urging parents of autistic children to report their children’s autism (and any other “vaccine injury” they believe their children have suffered) to VAERS. It’s not for nothing that I refer to the frequent antivaccine technique of doing studies searching VAERS for dubious “vaccine injuries” of the sort that the Geiers do “dumpster diving.”
So we’ve established that Delong’s version of vaccine “science” is hopelessly biased and clueless. Unfortunately, so is the “science” that she does herself. Here’s what she did. She used two databases. The first was the Natality Information section of the CDC Wide-ranging OnLine Data for Epidemiologic Research (WONDER) database recording live births. There didn’t seem to me to be much point to this because all Delong did with it was to show that there was a sharp decline in the US birthrate beginning in 2007 associated with the economic meltdown that hasn’t recovered yet. As they say on Game of Thrones, it is (already) known.
Next, Delong used responses to the National Health and Nutrition Examination Survey (NHANES). This is a survey that collects data on health status of individuals in the United States along with demographic and socioeconomic information. The National Center for Health Statistic (NCHS) at the CDC administers the survey and selected a representative sample of the US population based upon complex sampling procedure. Delong notes that in 1999 NHANES asked females aged 12 and up whether they’ve ever been pregnant (or are pregnant now) and, if so, how many live births, miscarriages, stillbirths, tubal pregnancies, and abortions they’ve had. Then, starting in 2007, the survey started asking females aged 9 or above whether they’ve had an HPV vaccine. Delong then justifies the age range selected thusly:
In 2015, the NCHS moved these questions to the National Health Interview Survey, an annual survey that is not directly compatible with NHANES. The years of study are therefore 2007—when NHANES first asked about HPV vaccine uptake—to 2014, the final year NHANES included the questions concerning pregnancy and HPV shots.
Of course, that makes me suspicious right there. These are CDC-administered surveys and the databases are maintained by the CDC. The NHANES and NHIS datasets can both be accessed through the CDC website. Moreover, if the same basic survey questions were simply moved from one survey to the other, there’s little reason why Delong couldn’t have accessed later data.
Be that as it may, Delong used the dataset as described above. The study thus used various analyses to determine whether the odds of having been pregnant (the response variable) were influenced by explanatory variables such as receiving the HPV vaccine. What she found was this. Approximately 61% of women who had never received the HPV vaccine had become pregnant at least once, whereas only 35% of those who were exposed to the vaccine did. Among married women, 77% of women who had not received the vaccine had conceived, while only 51% of those who had received the vaccine had become pregnant. She then estimates that if 100% of females in the study had received the HPV vaccine there would have been 2 million fewer pregnancies. Among never-married women 44% of those who did not receive the HPV vaccine had been pregnant, while 28% of those who had received it had conceived. By univariate analyses, the results for all women and married women were statistically significant. However, when covariates (factors that could be confounders) were included in the model and logistic regression carried out, the results for never-married were no longer statistically significant.
Where it really gets interesting is the logistic regression including covariates in which the number of HPV shots received (one, two, or three) was related to the likelihood of getting pregnant. In this model, almost none of the comparisons were statistically significant. The only two where there was a statistically significant result were for the full sample, one shot versus no shots and three shots versus no shots. To me this is a huge red flag that the results are not robust and that there is no dose-response observed. If HPV vaccination was truly causative for infertility, there should be a dose-response curve. The effect seen should be bigger and more robust across more groups as the number of HPV vaccines received increases. It’s not.
There’s also another huge problem with this study. One of the most important covariates that could impact pregnancy rates is (obviously) usage of contraception. Yet nowhere in the analysis is there a consideration of contraception usage. Yes, Delong brings up the lack of statistical significance of the results among never-married women by suggesting that maybe most of them want to avoid pregnancy (which could be true), but, again, contraceptive use is an incredibly important factor, which was not even included as a covariate. My first thought was that maybe it was a question that wasn’t asked. It’s possible. Oh, wait. It’s not. The questionnaire asks whether a female has ever used oral contraceptives, if she is taking them now, and how long she’s taken them. So why did Delong not include oral contraceptive use in her analysis? She could have. She doesn’t even really discuss it other than discussion of contraceptive failure rates. I strongly suspect there was a reason for this. I also strongly suspect that a correlation between HPV uptake and oral contraceptive use (which is not unreasonable to hypothesize) could explain the results Delong observed and that correcting for oral contraceptive use in the survey sample would likely have resulted in the results of the logistic regression no longer being statistically significant. In fairness, if the correlation is not positive but negative (i.e., HPV vaccination is associated with less oral contraceptive use), the results could be more robust than what Gayle found.
In any case, I can see only two explanations for Gayle Delong’s not having done this analysis, given that the data appear to have been available. Either she was clueless and didn’t even consider it as a covariate, or she did some exploratory analyses and with contraceptive use included the effects that she saw disappeared. After all, they weren’t very robust; so I suspect that it wouldn’t take much. I welcome comments from the epidemiologists who read this blog. After all, existing evidence largely contradicts Delong’s findings, with HPV vaccination having no effect on fertility except in one group. The group? In females with a history of sexually transmitted infections or pelvic inflammatory disease (i.e. a group at high risk of exposure to HPV infection), HPV vaccination made pregnancy more likely.
In the end, though, regardless of whether the inclusion of oral contraceptive use as a covariate would have affected the analysis, what we have here is another example of amateur hour. Gayle Delong did the analysis basically by herself with the help of an incompetent (David Geier), another economist (Sabastiano Manzano), and a professor of history who is her husband (Jonathan Rose). Having read a number of epidemiology papers and co-authored a couple (with, I hasten to add, actual epidemiologists, population scientists, and statisticians), I got the distinct feeling reading Delong’s paper that she didn’t know what she was doing.
That’s why my sincere advice to her is two-fold. First, if you publish in a journal like the Journal of Toxicology and Environmental Health, don’t expect to be taken seriously. It’s where Delong’s published antivaccine nonsense before—at least twice!—as have other antivaccinationists. Second and finally, the next time you think you want to do a population studies/epidemiology paper like this, get yourself an actual epidemiologist and an actual statistician as co-authors.
Really. You’ll thank me later.