Abstract
Objectives
The purpose of this study was to evaluate the specificity and sensitivity of two red flag protocols in detecting ear diseases associated with changes in hearing.
Design
The presence of red flag symptoms was determined in a chart review of 307 adult patients from the Mayo Clinic Florida departments of Otorhinolaryngology and Audiology. Participants formed a convenience sample recruited for a separate study. Neurotologist diagnosis was the criterion for comparisons.
Results
Of the 251 patient files retained for analysis, 191 had one or more targeted diseases and 60 had age- or noise-related hearing loss. Food and Drug Administration (FDA) red flags sensitivity was 91% (CI 86–95%) and specificity was 72% (CI 59–83%). American Academy of Otolaryngology (AAO-HNS) red flags sensitivity was 98% (CI 95–99%) and specificity was 20% (CI 11–32%).
Conclusions
Stakeholders must determine which diseases are meaningful contraindications for hearing aid use, and whether these red-flag protocols have acceptable levels of sensitivity and specificity. As direct-to-consumer models of hearing devices increase, a disease detection method that does not require provider intercession would be useful.
INTRODUCTION
The FDA recently announced they would no longer enforce the mandatory medical evaluation or waiver protocols for individuals seeking hearing aids (FDA 2016). This policy change leaves a gap in regulatory guidance for audiologists and hearing aid dispensers. Medical evaluation is potentially important because changes in an individual’s hearing could be a symptom of a disease associated with risks to an individual’s life or health (Kleindienst et al. 2016). Failing to detect such diseases can have significant ramifications for the individual and the healthcare system. For many diseases with symptomatic changes in hearing, timely treatment can lead to improved patient outcomes and a reduced burden on the healthcare system. The potential seriousness of undetected diseases was part of the stated rationale of the earlier FDA surveillance scheme. As part of that scheme, the FDA set forth seven “red flags” that each warrant a full medical evaluation prior to procurement and use of hearing aids (21C.F.R.801.421 2016). In addition, the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) proposed its own set of red flags to provide guidance on when a patient should be evaluated by a physician (AAO-HNS 2014).
With the recent change in FDA policy, the onus is entirely on audiologists and hearing aid dispensers to dutifully screen and appropriately triage individuals suspected of having insidious ear disease. The FDA and AAO-HNS red flag criteria, therefore, may continue to serve as important tools ensuring consumer safety in hearing healthcare. Though the current iteration of the FDA red flags has been in use for over 20 years, we could not find published, peer-reviewed estimates of their effectiveness in screening for diseases related to changes in hearing. This brief report evaluates the FDA and AAO-HNS red flags in a sample of patients with disease-related etiologies and those with age- or noise-related changes in hearing as determined by a board-certified neurotologist (American Board of Otolaryngology 2017). This sample allowed for estimation of the sensitivity and specificity of the screening tools. The stated purpose of both sets of red flags is to suggest medical evaluation when warranted (21C.F.R.801.421 2016, AAO-HNS 2014). This brief report will focus on the red flags’ sensitivity and specificity in detecting disease, and does not comment on whether a hearing aid would be an appropriate option for the study sample. As far as is possible with the large set of diseases and conditions considered by the red flags, this report follows the STARD protocol in reporting its results (Bossuyt et al. 2015)
MATERIALS AND METHODS
Subjects
Patients (n = 307, 48% female) were recruited from the Otorhinolaryngology and Audiology Departments of the Mayo Clinic Florida between June, 2014 and August, 2015 as part of development of the Consumer Ear Disease Risk Assessment (CEDRA, Kleindienst et al. 2017) questionnaire. Participants were between 40–80 years of age (mean = 62.9, SD = 9.8), and were seeking care for ear- or hearing-related complaints. This convenience sample was chosen to have a high percentage of targeted disease-related diagnoses, and was limited to 25% of the patients having age- or noise-related changes in hearing. An a priori power analysis indicated an initial sample size of 300 was sufficient for the Kleindienst et al. study, with 80% power to detect an area under the curve of 0.63 or greater with alpha = .05. No separate power analysis was performed for the current analysis. Participants received treatment according to the standard-of-care at Mayo Clinic, and the study was approved by the Mayo Clinic IRB.
Procedures
As part of the standard-of-care at Mayo Clinic, audiology examination, case history, and background data were entered into the electronic health record (EHR), which were later extracted for this study’s analysis. All study participants received an examination by a board-certified neurotologist (American Board of Otolaryngology 2017) whose findings were used to determine the presence/absence of any of 104 diseases that may include otologic symptoms (see Text, Supplemental Digital Content, for a complete list; Kleindienst et al. 2016). All examinations were performed according to the practice standards used by Mayo Clinic during the study. The FDA and AAO-HNS red flags were extracted from the audiometric data, background notes, and case history, all of which were accessible to the neurotologist. Only examination information collected equal-to or less than 90 days before or after the neurotologic exam was included in the analysis because these diseases have varying time courses. This resulted in 251 patients for the present analysis.
Two independent coders (NK and DZ) analyzed the de-identified dataset to determine the presence or absence of the red flag symptoms. Both coders had access to the neurotologist diagnosis, but completed their analysis without reference to it. Initial agreement between the two coders was 91%. Examination of the discordant classifications showed that disagreements resulted from different interpretations of the red flags. The study team discussed possible interpretations and decided on a single uniform interpretation for this study. The red flags and the study team’s operationalization of each may be found in Table 1. The results here reflect complete final agreement between the two coders.
Table 1.
FDA Red Flags | Key criteria used in chart review |
---|---|
Visible congenital or traumatic deformity of the ear. | Search for “deformity,” or “malformation,” of the “pinna”, or “external ear”. |
History of active drainage from the ear within the previous 90 days. | Search for “drain,” “pus,” or “otorrhea.” |
History of sudden or rapidly progressive hearing loss within the previous 90 days. | Search for “sudden,” “rapid,” “acute,” and “hearing loss” within 90 days. |
Acute or chronic dizziness. | Search for “dizziness,” or “vertigo.” |
Unilateral hearing loss of sudden or recent onset within the previous 90 days. | Search for “unilateral” or “asymmetric” within 90 days. |
Audiometric air-bone gap equal to or greater than 15 dB at 500 Hz, 1000 Hz, and 2000 Hz.* | Calculate air-bone gap at 500 Hz, 1000 Hz, and 2000 Hz, then calculate the average. |
Visible evidence of significant cerumen accumulation or a foreign body in the ear canal. | Search for “blockage,” “foreign,” “debris,” “object,” “cerumen obstructing clear view of the tympanic membrane,” or “wax obstructing clear view of the tympanic membrane”, “impaction” |
Pain or discomfort in the ear.* | Search for “pain,” “discomfort,” “fullness,” “pressure,” or “otalgia.” |
AAO-HNS Red Flags | |
Hearing loss with a positive history of ear infections, noise exposure, familial hearing loss, TB, syphilis, HIV, Meniere’s disease, autoimmune disorder, ototoxic medication use, otosclerosis, von Recklinghausen’s neurofibromatosis, Paget’s disease of bone, ear or head trauma related to onset. | Hearing loss as PTA.5, 1, 2 kHz > 20 dB HL, and search for “noise,” “familial/family,” “TB/tuberculosis,” “syphilis,” “HIV/AIDS,” “Meniere’s,” “autoimmune,” “ototoxic,” “otosclerosis,” “Recklinghausen,” “neurofibromatosis,” “Paget,” or “trauma” |
History of pain, active drainage, or bleeding from an ear.* | Search for “pain,” “discomfort,” “pressure,” “fullness,” “otalgia,” “drain/drainage,” “blood,” “bleeding,” “pus,” or “otorrhea.” |
Sudden onset or rapidly progressive hearing loss. | Search for “sudden,” “rapid,” or “acute.” |
Acute, chronic, or recurrent episodes of dizziness. | Search for “dizziness” or “vertigo.” |
Evidence of congenital or traumatic deformity of the ear. | Search for “deformity,” or “malformation,” of the “pinna”, or “external ear”. |
Visualization of blood, pus, cerumen plug, foreign body, or other material in the ear canal. | Search for “blood,” “bleeding,” “pus,” “blockage,” “foreign,” “debris,” “object,” “cerumen,” or “wax.” |
An unexplained conductive hearing loss or abnormal tympanogram. | Tympanograms with pressure < −100 daPa, or classified as type “B” or “C.” |
Unilateral or asymmetric hearing loss (a difference of greater than 15 dB Pure Tone Average between ears); or bilateral hearing loss > 30 dB.* | Calculated PTA.5,1,2 kHz for each ear and subtracted. For bilateral, flagged if both ears’ PTA > 30 dB HL. |
Unilateral or pulsatile tinnitus. | Search for “tinnitus” with “pulsatile” or “unilateral.” |
Unilateral or asymmetrically poor speech discrimination scores (a difference of greater than 15% between ears); or bilateral speech discrimination scores <80%. | Examine scores from NU-6 for each ear and subtract. For bilateral, flagged if both ears’ speech scores were < 80%. |
Alternate operationalizations were attempted for these red flags, which resulted in moderate changes to the sensitivity and specificity. The authors finalized the analysis using the descriptions listed in the table.
Data Analysis
For each of the FDA and AAO-HNS red flag sets, a patient was coded as a “refer” in the presence of any red flag sign or symptom, and as a “pass” only when no red flags were present. Sensitivity was calculated as the number of correctly identified diseased cases divided by the total number of diseased cases. Specificity was calculated as the number of correctly identified non-diseased cases divided by the total number of non-diseased cases. The sensitivity and specificity of the screening tools are reported using the neurotologist’s diagnosis as the criterion, with the exact binomial 95% confidence intervals in parentheses.
RESULTS
The sensitivity and specificity for the FDA red flags was 91% (CI 86–95%) and 72% (CI 59–83%), respectively. The sensitivity and specificity for the AAO-HNS red flags was 98% (CI 95–99%) and 20% (CI 11–32%), respectively. See Table 2 for cross tables. We could not find peer-reviewed estimates of the cumulative prevalence of these diseases, so the positive predictive value (PPV) and negative predictive value (NPV) were estimated using three prevalence levels: 0.5%, 2%, and 5%. The highest prevalence rate chosen is close to the highest described by the recent National Academies of Science, Engineering, and Medicine report (Committee on Accessible and Affordable Hearing Health Care for Adults, 2016), which reflects the most common diseases that may affect hearing. The PPVs and NPVs are summarized in Table 3.
Table 2.
FDA | Diseased | Age- or noise-related loss | Totals | AAO-HNS | Diseased | Age- or noise-related loss | Totals |
---|---|---|---|---|---|---|---|
Flagged | 174 | 17 | 191 | Flagged | 187 | 48 | 235 |
Passed | 17 | 43 | 60 | Passed | 4 | 12 | 16 |
Totals | 191 | 60 | 251 | Totals | 191 | 60 | 251 |
Of the 191 individuals with targeted diseases, 42 had multiple diagnoses. 118 diagnoses were of sensorineural or labyrinthine disorders, 14 were related to the posterior fossa or central auditory nervous system, 79 were conductive, middle ear, or mastoid-related, and 22 were eighth nerve-related. See Kleindienst et al. (2016) for details and categorizations of the 104 targeted diseases.
Table 3.
0.5% prevalence | 2% prevalence | 5% prevalence | ||||
---|---|---|---|---|---|---|
PPV | NPV | PPV | NPV | PPV | NPV | |
FDA | 1.6% | 99.9% | 6.2% | 99.7% | 14.6% | 99.3% |
AAO-HNS | 0.6% | 99.9% | 2.4% | 99.8% | 6.1% | 99.5% |
DISCUSSION
The data presented here provide the first published estimates of the sensitivity and specificity of the FDA and AAO-HNS red flags in screening for any of the 104 ear diseases described in Kleindienst et al. (2016). Sensitivity and specificity are characteristics of the tests themselves, and do not vary with the prevalence of the disease. The PPV and NPV estimates provide some context for these characteristics by factoring in how rare or common the diseases are in the general population, and are provided for illustrative purposes only, as the true cumulative prevalence of ear diseases is unknown. These results highlight the relatively low PPV of these tests: for the AAO-HNS red flags in the highest prevalence case, only 6% of individuals referred for further diagnosis have a disease. For the FDA red flags in the highest prevalence case, that number rose to 14.6%. Conversely, under reasonable prevalence estimates, passing either set of red flags indicated that the individual likely has no disease, with >99% passing the test being disease-free.
The present study highlights two potential concerns in implementing the red flags. First, an individual seeking a hearing aid must see a provider (e.g. audiologist or hearing instrument specialist) to obtain the required audiometric data included in both the FDA and AAO-HNS red flags. Though this step potentially avoids individuals unnecessarily seeing a physician for non-medically treatable conditions, it still requires the outlay of time and money for the provider assessment. With increasing direct-to-consumer sales of hearing devices, a disease detection method with acceptable levels of sensitivity and specificity that does not require provider participation could be more efficient. Kleindienst et al. (2017) developed a consumer questionnaire that requires no examination and possesses test characteristics comparable to the FDA red flags, and with better specificity than the AAO-HNS red flags.
The second potential concern in using the red flags is that some items in both the FDA and AAO-HNS red flag descriptions are ambiguously defined. For example, does the FDA red flag “audiometric air-bone gap equal to or greater than 15 decibels at 500, 1,000, and 2,000 Hz” apply to gaps at all three frequencies, any frequency, or an average of the three? In the initial coding, one author coded a patient reporting “pressure” or “fullness” as a flag for both the FDA and AAO-HNS, and the other author did not. For this project the final coding was determined by consensus among the research team, but the ambiguous definitions leave open the possibility of variance in how these red flags are used. Indeed, in preliminary analyses (not shown), these different interpretations were found to change the sensitivity and specificity of the red flags. This could cause individuals to not be referred when they have a disease or non-diseased individuals to pursue unnecessary care, simply depending on the dispenser’s or audiologist’s interpretation of the red flags.
This study has limitations. First, we studied a clinical sample (n = 251), that does not represent the population prevalence of ear disease. The high prevalence of disease, however, provided a more rigorous test of the red flag’s sensitivity than would have been possible in a random sample of the hearing aid seeking population. The concern is therefore that the diseased and control individuals in this study may be systematically different than the general population. An ongoing research project is evaluating the red flag criteria and CEDRA in a larger, more representative population of individuals seeking hearing healthcare. A second limitation is that the red flag symptoms were derived from a retrospective analysis of case history and examination data. The symptoms noted by the clinicians therefore had to be interpreted to determine if they matched any red flag. The high agreement between coders indicates that the possibility of the interpretative process skewing the results is small, but that different interpretations of the red flags themselves affect the outcomes. The ongoing research project discussed above is explicitly examining the red flag criteria as interpreted by practicing audiologists. The 104 diseases targeted here have not been independently evaluated as meaningful contraindications of hearing device acquisition and use. The ratings provided by neurotologists in Kleindienst et al. (2016) covered a range of severity should the disease go undetected. Here, however, the red flags were tested for their effectiveness at determining the presence or absence of a disease, not the potential consequence of missed detection. Whether an otolaryngologist would clear a patient for hearing aid use, regardless of the presence of a disease or condition other than presbycusis, is part of the ongoing research described above. Finally, the authors note that neurotologist diagnosis is not a strictly defined reference test as set forth in the STARD protocol (Bossuyt et al., 2015). Board certification in neurotology represents the highest medical subspecialty credential for assessing ear disease, and provides the best available standardization for any effort to replicate these results.
For any screening effort, the relative costs and benefits of the procedure must be weighed. Whether screening for these diseases is appropriate and necessary, and the acceptable sensitivity and specificity for a screener, are questions that must be considered by the public and policymakers. The results presented here can help inform such decision-making.
Supplementary Material
Acknowledgments
All authors contributed equally to this work. N.K. and D.Z. provided analyses. S.K. reviewed analyses and provided critical interpretation. D.Z., L.L., and S.K. contributed to data collection. S.K., R.A. and D.Z. pulled and de-identified data for analysis. N.K. wrote the initial draft of this work. All authors reviewed, edited, and approved the final paper.
Footnotes
Financial Disclosures/Conflicts of Interest:
Research was supported by NIH/NIDCD (R21/33 DC013115) [Dhar, Zapala] and the Knowles Hearing Center at Northwestern University [Dhar, Zapala, Nielsen]
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