The Conference on the Epidemiology of Medical Devices in Women

Bright, Roselie A.


Guest Editor

Epidemiology Branch

Division of Postmarket Surveillance

Office of Surveillance and Biometrics

Center for Devices and Radiological Health

Food and Drug Administration

1350 Piccard Dr, HFZ-541

Rockville, MD 20850

The views expressed here do not necessarily represent the official position of the Food and Drug Administration or Department of Health and Human Services.

Article Outline

The Conference on the Epidemiology of Medical Devices in Women was held in 1998 to attract attention to this confluence of epidemiology, medical devices, and the specific health concerns of women. The organizers, epidemiologists in the FDA Center for Devices and Radiological Health (CDRH), hoped to introduce epidemiologists to medical devices in relation to women’s health, medical device clinical researchers to epidemiology and women’s health, and the women’s health community to epidemiology and medical device issues. This supplement in Epidemiology is intended to expand the audience beyond the conference attendees.

The legal definition of a device is as follows.

“The term “device”. . .means an instrument, apparatus, implement, machine, contrivance, implant, in vitro reagent, or other similar or related article, including any component, part, or accessory, which is − recognized in the official National Formulary, or the United States Pharmacopeia, or any supplement to them, intended for the use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease, in man or other animals, or intended to affect the structure or function of the body of man or other animals, and which does not achieve its primary intended purposes through chemical action within or on the body of man or other animals and which is not dependent upon being metabolized for the achievement of its primary intended purposes.”1

The conference logo was designed to incorporate the four major categories of devices regulated by CDRH, as follows.

• Implants, exemplified by an artificial hip, including both permanent (pacemakers) and temporary implants (catheters).

• Medical equipment, exemplified by a hypodermic needle, including durable machines (ventilators) and disposable devices (gloves).

• Electronically generated radiation, including machines that generate radiation for diagnostic or therapeutic purposes, as well as consumer products such as cellular phones and electric blankets.

• Diagnostic devices, exemplified by a microscope, including durable machines (this overlaps with the previous category) and disposable kits (home pregnancy test kits).

Medical devices are used at all levels of health care: hospital, nursing home, work place, home, and outdoors. They range from low risk and common (adhesive bandages) to high risk and rare (custom-built prostheses).

The conference was held for 2 days and organized by clinical area (Table 1). The introductory session featured opening remarks by the CDRH Deputy Director for Science, Elizabeth Jacobson, and the director of the FDA Office of Women’s Health (which provided funds for the conference and for this supplement), Audrey Sheppard. Susan Alpert, the Director of the CDRH Office of Device Evaluation, reported that the number of firms registered, either active or pending, to be producing obstetric or gynecologic devices, rose from 315 domestic and 171 foreign firms in 1988 to 501 domestic and 327 foreign firms in 1998. In addition, women’s smaller size and the actions of female hormones are concerns for other types of devices. Another issue that is being developed, is women’s access to care. Susan Zagame, a Vice President of the Health Industry Manufacturers Association, presented data that there are more than 2 million operations per year on women’s reproductive organs, compared with a half million on men’s. She said that there is increasing investor interest and many unmet needs in the areas of interventional gynecology, uterine disorders, fertility, sterilization, minimally invasive surgery, and urinary incontinence, where device manufacturers are focusing interest. There was also a presentation on future trends in medical device technology by William A. Herman, of the CDRH Office of Science and Technology. He and his colleagues had surveyed experts from various government agencies, manufacturers, universities, nonprofit entities, and consulting firms. The most important future trends were expected to be in computer-related technology, molecular medicine, home- and self-care, minimally invasive procedures, combination device and drug products, and organ replacements and organ assistive devices. The introductory session also included a presentation on ethics.

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Using Epidemiology to Study Medical Devices in Women

In the second session, “Methodology and Data Sources,” the first talk was mine, “Using Epidemiology to Study Medical Devices in Women.” The purpose was to give an overview of epidemiology, using device studies as examples, for the sake of audience members in other fields. Because one of my hopes is to attract some of these same types of readers to this supplement, the rest of this section describes epidemiologic concepts in some detail.

I started by defining epidemiology as the science of the occurrence of diseases in human populations and explained that epidemiologists combine quantitative skills, clinical medicine, public health orientation, and a good dose of humor to practice their craft. There are two general epidemiologic goals. The first is to describe a population; an example would be to estimate the number of U.S. breast implant recipients. The second is to assess causation, such as estimating the effect of longer continuous contact lens wear time on the risk of corneal ulcer. Readers who are interested in more details may be interested in an introductory book on epidemiology, 2 an advanced epidemiology textbook, 3 and a resource on medical device epidemiology. 4

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Describe a Population

My example of estimating the number of U.S. breast implant recipients came from work based on the Medical Device Implant Supplement to the 1988 National Health Interview Survey, administered by the National Center for Health Statistics (part of the Centers for Disease Control and Prevention) and cosponsored by CDRH. This was an interview survey of a stratified random sample of households that asked about current “medical” implants in household members. For implant recipients, it collected the reason for the implant, duration of implantation, and major adverse effects. For everyone in the overall survey, the interviewer collected data on age, sex, race, adult income, and adult education level. There were 143 women in the sample who were identified as currently having a breast implant. They were calculated to represent 304,000 women in the United States having breast implants. The U.S. prevalence of women with breast implants in 1988 was therefore 0.3% (0.2–0.4%). 5

How does this study compare with others? Table 2 shows the results for three others 6,7 (and J. Daling, unpublished results, 1992; personal communication), which estimate a prevalence of about 1% for approximately the same time period. Therefore, it appears that the Bright et al5 study severely underestimated the prevalence of breast implants. A likely reason is that “cosmetic” implants, or implants not known to the household questionnaire respondent, were not counted. This example illustrates a pitfall in survey design and the value of comparing multiple studies of the same question.

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Assess Causation

An association between exposure and outcome may be due to any single factor or combination of the following:

• Statistical variation (otherwise known as chance).

• Biased study design.

• Alternative explanations.

• Cause and effect.

Of these, epidemiologists expend the bulk of their effort trying to rule out biased study designs and alternative explanations as reasons for observing an association. It is worth noting here that in contrast, randomized clinical trials use patient randomization (resulting in a random distribution of both treatments and other factors) and, to the extent possible, masking, to eliminate biased study designs and alternative explanations as reasons for observing an association. Thus, the causality argument for study results is very strong. However, there are times when randomized clinical trials are impractical. It may be difficult to enroll consenting subjects, or the outcome of interest may be so rare that a trial is too expensive. Furthermore, randomized clinical trials study ideal conditions; the selection criteria for subjects are often strict, and all of the participants are on “best behavior” because they know they are being watched.

If a randomized controlled trial is not feasible, the next best study design choices are cohort and case-control designs. In the cohort study, subjects are chosen on the basis of their exposure; then the subjects are followed in time to observe occurrences of the outcome, ideally by an investigator who is masked to the exposure status of the subjects. In the case-control study, subjects are chosen on the basis of their outcome status, and then their exposure histories are obtained. In variations or combinations of the two, the experience of cases is compared with the experience of a sample of an entire, defined population.

Methodologically weaker, although easier, study designs include the cross-sectional study (in which the investigators are unsure of the relative timings of exposure and outcome), the ecological study (in which data are available for populations, rather than individuals in the populations), and the case series (in which some cases are described and case selection generally is not done on a population basis).

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Assessing Causation with a Cohort Study

An intuitively obvious way to observe (what one hopes is) cause and effect is to compare the experiences of people who have had different exposures. Using a cohort study rather than a randomized clinical trial is particularly advantageous when randomization of treatment would be unethical; other considerations could include the wish to study actual, rather than idealized, behavior, or to quickly study the long-term effects of a treatment. My example is a comparison of “laparoscopic vs traditional appendectomy for suspected appendicitis.”8 All of the study subjects were adults operated for presumed acute appendicitis in the same hospital during a 4-month period. The cohorts were defined by the type of surgery: laparoscopic appendectomy (47 patients), diagnostic laparoscopy (6), laparoscopy converted to open incision (15), and open appendectomy (54). The outcomes included duration of operation, mortality, delayed discharge, and wound complications. Compared with open appendectomy, the rate ratio of wound complications for laparoscopic appendectomy was 0.57, with a 95% confidence interval (CI) of 0.21–1.56, and for laparoscopic converted to open incision, 2.5 (95% CI = 1.2–5.5). There were several issues that relate to the validity of these results:

• There was no explanation of the reason behind the initial choice of surgical type, which may be related to the outcome.

• The surgical roles of the junior and senior surgical residents differed for each surgical type, and may themselves be related to the outcome.

• The choice of surgical type and unplanned procedures were both related to gender. The authors do not report whether the complication rate was also related to gender.

This example illustrates some of the advantages (ease of conceptualization and conduct) and pitfalls (inadequate accounting of alternate explanations of the results) of cohort studies. Careful study design can sidestep most, if not all, pitfalls.

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Assessing Causation with a Case Control Study

As another example, suppose one wanted to estimate the effect of longer continuous contact lens wear time on the risk of corneal ulcer. Would a randomized controlled trial be appropriate? Unfortunately, it wouldn’t, because corneal ulcers are rare and their occurrence depends on wearer behavior, which would in turn be affected by the subjects’ knowledge that they are being “watched.” As it happens, a few epidemiologic studies have already been done, out of which I selected a pair to use in the example. One is a case-control, and the other is a case-base study. Because they were designed by the same study team, many study features are similar and won’t obscure my comparison of the two designs.

The example study by Schein et al9 defined its population as U.S. residents at risk of ulcerative keratitis who were at least 12 years old, spoke English or Spanish, and wore cosmetic soft contact lenses. The cases were from six university ophthalmology centers across the United States. They had ulcerative keratitis that had been confirmed by culture, treated with antibiotics, and verified by a corneal specialist. Of 109 eligible cases, 99 were enrolled and 86 (79%) completed the telephone interview.

Two sets of controls were selected in different ways. “Hospital controls” were selected from the same six university centers as the cases. They had conditions unrelated to lens use: minor trauma, floaters, headache, or other problems. The controls were frequency matched to cases by sex and center. Sixty-seven hospital controls enrolled and 61 (91%) completed the telephone interview. “Population controls” were chosen by, for each case, dialing the same area code, same first four digits of the case’s phone number, and a random last three digits to get eligible controls. Most cases had at least four controls. Ninety-two per cent of contacted households cooperated, and 410 population controls enrolled in the study.

The telephone interviews were used to assess exposure by asking about the type of lens, lens use and care in the prior 2 months, lens care instructions that had been received, previous use of lenses, general medical and ophthalmic history, and demographic characteristics.

The odds ratio, which estimates the relative risk, was calculated separately, using the two control groups. Using the hospital controls, the odds ratio was 4.21 (95% CI = 1.95–9.08). Using the population controls, the odds ratio was 3.90 (95% CI = 2.35–6.48). Fortunately, the odds ratios are very similar.

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Assessing Causation with a Case-Base Study

Over the last 15 years, new study designs have combined features of both cohort and case-control studies. An example is the “case base” study, in which the exposure history of cases is compared with the exposure history of the “population base” that gave rise to the cases. 10 With this method, one can study a rare outcome and obtain estimates of population rates.

Poggio et al11 estimated both the risk of corneal ulcer and the causal role of longer continuous contact lens wear time. The study population was all wearers of contact lenses in the self-contained area of Maine, Vermont, New Hampshire, Rhode Island, and Massachusetts (except Berkshire County). This area has more than 9 million residents and minimal crossing of the study area boundaries for medical care.

The study authors estimated contact lens exposure with a household telephone survey that used the random-digit dialing technique. The household respondent had to be at least 16 years old to answer questions about the age and sex of all lens wearers who were at least 12 years old. Information on the type of lens (soft extended or soft daily wear) and the reason for wear (if for cataract, excluded from study) was collected. This survey was completed for 60% of 6,990 sample households.

The corneal ulcer outcome was measured with a complete ophthalmologist survey that asked about all ulcerative keratitis cases in the 4-month study period that were treated with antibiotics. For the cases that were eligible for the study (lens wearers who were at least 12 years old), information on the type of lens (soft extended or soft daily wear) and the reason for wear (if for cataract, excluded from the study) were collected from the ophthalmologist. This survey was completed for 99% of practices in the study area.

The corneal ulcer rate was much higher among users of extended rather than daily wear lenses. That increase was expressed as the relative rate, or 20.9/4.1 = 5.15. The 95% confidence interval on the relative rate is 3.47–7.65. The relative rate approximates the relative risk.

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Assessing Causation by Comparing Studies

Table 3 shows the main results from the Poggio et al11 and Schein et al9 studies, and two other related studies. 12,13 Epidemiologists generally derive some reassurance from a situation like this, in which independent studies show generally the same results. The association between extended lens wear and microbial corneal ulcer was strongly positive in each study, despite differing designs and slightly different study questions. The very weak effect occurring only with sterile corneal ulcer as the outcome points to a suggestion that the extended wear risk is specific to the type of ulcer. Specificity of study results, in the absence of major design flaws, is generally seen as supportive of causality.

As a point of interest, both the Schein et al9 and Dart et al12 studies were able to examine detailed aspects of exposure (see Table 4). Among other features, both chose to measure the effect of various lengths of lens use. Schein et al9 found that risk increased with each category of increased length of wear, whereas Dart et al9 found a stepped effect at 7 days. The breadth of the confidence intervals indicates that these results are statistically consistent with each other, and making a choice between the two apparent patterns would require either combining the underlying data from the two studies or a new, larger data collection effort.

When choosing between study types, one bears in mind the symmetry of strengths and weaknesses. Cohort designs have particular advantages for studying rare exposures and multiple outcomes from the same exposures, whereas case-control studies are the best choice for study questions involving rare outcomes with many possible exposures to be examined. If neither situation applies, or if both the exposure and outcome are rare, then combination designs, such as the case-base type, may offer significant advantages.

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Other Presentations on Methodology and Data Sources

The next presentation was on “Methods of Health Technology Assessment.” Vivian Coates explained that these methods include information synthesis, expert opinion, group judgment, epidemiologic or other observational studies, clinical trials, and laboratory tests. Each method offers its own advantages and disadvantages. She reported that at her organization, ECRI, technology assessment is an information synthesis based on a systematic analysis of data from published, peer-reviewed clinical literature, gray literature (eg, meeting abstracts and proprietary reports), registries, and administrative databases. Her colleagues develop evidence models and evidence tables, use quantitative meta-analysis, create computerized decision models for cost-effectiveness analysis, conduct both internal and external review, and use an external audit committee. She gave examples of recent analyses that have been done for topics of particular interest to women and emphasized that “findings are not written in stone, and must be re-examined periodically in light of new findings.” She also said that the “assessment of medical technology is often limited by the lack of strong evidence for improved patient outcomes and cost-effectiveness relative to alternatives,” the small number of controlled trials, and flawed study designs and reporting of study results. “In spite of this, evidence-based technology assessment is essential for deciding what works best for patients.”

The presentation on data sources is published in this supplement. 14 It was followed by a talk on “Methods of Device Evaluation” by Katherine Detre, of the University of Pittsburgh.

Deborah Blum and her colleagues, of the CDRH Office of Surveillance and Biometrics, in a poster, discussed the difficulties of using adverse medical device event reports submitted to the FDA to study gender-related issues arising from the very low frequency with which gender is noted on the report.

Karen Witkin and Rosanne McTyre of the Weinberg Group, presented a poster on methodologic issues related to evaluating implant safety and performance and discussed the analysis of product complaints, explant retrieval and analysis, and clinical follow-up studies. Another poster, by Kathleen Neill of Georgetown University, reported on focus groups that were used to learn about women’s incentives, barriers, expectations from the research team, and disincentives to participating in clinical trials. 15

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Two of the presentations, on home pregnancy tests 16 and prenatal ultrasound, 17 are included in this supplement. Mary D’Alton, of New England Medical Center, gave a talk on telemedicine, “the use of telecommunications technology to provide medical services across a geographical separation,” in obstetrics. She described the sonography system based at the New England Medical Center in Boston, MA, and presented results from two published studies. 18,19 She predicted that both academic and commercial networks will grow, especially as the following potential problems are resolved: licensure for interpreting images sent across state lines, credentialing, antitrust laws, medicolegal liability, and patient confidentiality and privacy.

Julian Parer, University of California San Francisco, presented “Findings from Studies of Intrapartum Fetal Monitoring, and the Need for New Technologies,” which has been published as a review article. 20 An independent poster by Sonia Swayze of the CDRH Office of Surveillance and Biometrics summarized shortcomings of electronic fetal monitors associated with serious birth outcomes that have been reported to FDA. 21

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There were two talks on cervical cytology screening by David Wilbur 22 and Tom Sedlacek. 23 Unfortunately, Dr. Sedlacek died before his paper could be updated, so a brief update by Max Robinowitz is included in this supplement. 24 A talk by Alula Hadgu (Centers for Disease Control and Prevention), “Bias in the Evaluation of Medical Diagnostic Devices for Detecting Infectious Diseases,” was based on one of his publications. 25

Tanya Spirtos, of Stanford University, addressed the treatment of menorrhagia. She described the etiology, the impact of menorrhagia on women and the health care system, diagnostic approach, and the current treatment course, based on scientific literature. 26–29 After detailing the effectiveness and deficiencies of current therapies, she described the evolution and outcomes of endometrial ablation technologies: hysteroscopic, rollerball, heated saline, laser, phototherapy, microwave, radiotherapy hyperthermia, and thermal transfer balloon, also based on publications. 30–36

A poster by Sonia Swayze showed that toxic shock syndrome associated with tampons is still being reported to FDA.

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Breast Health

The systematic collection of data to be used for research will hopefully lead to improvements in breast cancer detection by mammography. Bonnie Yankaskas, of the University of North Carolina at Chapel Hill, described the motivation, data sources, structure, and administration of the Carolina Mammography Registry. The pathology information from biopsies is entered into a linked database to enable the study of practice patterns and health outcomes in the community. Many of the methodologic, validation, and administrative issues have since been published. 37–40

Rachel Brem, of Johns Hopkins Hospital, discussed the limitations of mammography as a motivation for developing enhanced or new methods. She reviewed the types of minimally invasive breast biopsy: fine-needle aspiration, core needle biopsy with stereotactic and ultrasound guidance, stereotactically guided vacuum-assisted directed biopsy, and Advanced Breast Biopsy Instrumentation for en mass percutaneous excision of tissue. She also discussed computer-aided diagnosis of film mammograms, digital mammography, magnetic resonance imaging, and nuclear imaging. She has since published studies of some of these topics. 41–44

A poster by Richard Kisielewski and his CDRH colleagues displayed a summary of reports to FDA of residual metal shavings and fragments associated with core biopsy needles, along with a laboratory analysis that apparently narrowed the problem to models with a side-notch angle of 90 degrees. 45,46

The presentations on silicone gel breast implants have been published. The first one, “Breast Implants and Breast Cancer: Risk, Stage at Diagnosis and Survival,” has been reported in two papers. 47,48 The second talk, “Epidemiology of Breast Implants,” by Lori Brown, is included in this supplement. 49 She also presented a poster that has since been published elsewhere. 50

At the poster session, Kathleen Neill presented an update of a previously published paper on decision making by women contemplating breast reconstruction. 51 Another poster, by Martha A. Embrey et al (Breast Implant Public Health Project, LLC), reported results from interviewing 25 women with breast implants about their perceptions. A third poster (Arthur Brawer of Monmouth Medical Center), “Amelioration of systemic disease after removal of silicone breast implants,” reported on the experience of 156 breast implant recipients with systemic disease, before and after breast implant removal.

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After the first two talks of this session, on the epidemiology of osteoporosis 52 and “Use of Bone Mineral Density to Predict Fracture Risk,”53 Peter Steiger of Hologic, Inc, presented “Bone Densitometry for the Evaluation of the Patient at Risk for Osteoporosis.” After discussing the basic epidemiology and physiology of osteoporosis, he talked about considerations for bone site selection for assessment and the history of bone assessment techniques. Biochemical markers and their measurement parameters, as well as considerations for the appropriate use of T-scores and Z-scores for monitoring patients, were also presented.

The final talk in this session, presented by CDRH statisticians, was on the statistical methodology for comparing two diagnostic modalities, the examples being ultrasound and x-ray bone densitometry. The “ROC” curve (first developed for radio and radar technology) for any diagnostic test is plotted as (1 − specificity) on the x-axis and sensitivity on the y-axis. Plotting the curves for two diagnostic tests on one graph allows a fair comparison of the relative strengths of each. In the example given, the curves were very similar when (1 − specificity) and the sensitivity were both low. But when each of them were high, ultrasound performed better. Several methods for statistically comparing the areas under the curves were presented.

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Cardiovascular Devices

The last topical session was on cardiovascular devices. Two of the presentations are included in these proceedings. 54,55 Judith Kramer, of Duke Clinical Research Institute, talked about results from the National Cardiovascular Network, which had 19 contributing high-volume institutions. The researchers found that between 1994 and 1996, balloon and atherectomy procedures declined, whereas stent placement increased, for each sex. Overall, the higher acute death rate of women after procedures was explained by their higher burden of risk factors. A substudy of postmenopausal women found that those who used estrogen experienced less restenosis after percutaneous coronary interventions. 56

The poster by Elizabeth Kennard, of the University of Pittsburgh, and her colleagues, presented a comparison of stenting with balloon angioplasty among women enrolled in a registry.

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Other Issues of Concern to Women

Joan Todd, of the CDRH Office of Surveillance and Biometrics, presented a poster that summarized a publication on the dangers of hospital bed side rails. 57 Elderly women with low body weight and cognitive impairment are apparently at the highest risk of death and injury from bed side rail entrapment.

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The epidemiology of medical devices in women is a broad topic. Although this conference was the first to draw attention to this research area as a whole, there has been a strong history of work in individual specialties (obstetrics, gynecology, breast health, osteoporosis, and cardiovascular devices) of particular concern to women. However, much remains to be done. I encourage readers to consider these areas: epidemiologists to study medical devices of particular concern to women, clinical specialists already studying devices to also consider epidemiologic research in their areas, and women’s health researchers to include device issues in their studies. The confluence of these areas should enable better health for women.

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