Management of acute otitis media in children six months of age and older

An international group of multidisciplinary experts on middle-ear and paediatric infections met to explore where consensus exists on the management of acute otitis media. After informal discussions among several specialists of paediatric infectious disease, the group was expanded to include a larger spectrum of professionals with complementary expertise in middle-ear disease. Acute otitis media is a very common bacterial infection in children worldwide, leading to excessive antibiotic consumption in children in most countries and to a substantial burden of deafness and suppurative complications in developing countries. The group attempted to move beyond the existing controversies surrounding guidelines on acute otitis media, and to propose to clinicians and public health officials their views on the actions needed to be taken to reduce the disease burden caused by acute otitis media and the microbial antibiotic resistance from the resulting use of antibiotics. Definition of acute otitis media and diagnostic accuracy are crucial steps to identify children who will potentially benefit from treatment with antibiotics and to eliminate unnecessary prescribing. Although the group agreed that antibiotics are distributed indiscriminately, even to children who do not seem to have the disease, no consensus could be reached on whether antibiotics should be given to all appropriately diagnosed children, reflecting the wide range of practices and lack of convincing evidence from observational studies. The major unanimous concern was an urgent need to reduce unnecessary prescribing of antibiotics to prevent further increases in antibiotic resistance. Prevention of acute otitis media with existing and future viral and bacterial vaccines seems the most promising approach to affect disease burden and consequences, both in developed and developing countries. 2010 Elsevier Ltd. All rights reserved.

Acute otitis media (AOM) is a common complication of upper respiratory tract infection whose pathogenesis involves both viruses and bacteria. We examined risks of acute otitis media associated with specific combinations of respiratory viruses and acute otitis media bacterial pathogens. Data were from a prospective study of children ages 6 to 36 months and included viral and bacterial culture and quantitative PCR for respiratory syncytial virus (RSV), human bocavirus, and human metapneumovirus. Repeated-measure logistic regression was used to assess the relationship between specific viruses, bacteria, and the risk of acute otitis media complicating upper respiratory tract infection. In unadjusted analyses of data from 194 children, adenovirus, bocavirus, Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis were significantly associated with AOM (P < 0.05 by χ(2) test). Children with high respiratory syncytial virus loads (≥3.16 × 10(7) copies/ml) experienced increased acute otitis media risk. Higher viral loads of bocavirus and metapneumovirus were not significantly associated with acute otitis media. In adjusted models controlling for the presence of key viruses, bacteria, and acute otitis media risk factors, acute otitis media risk was independently associated with high RSV viral load with Streptococcus pneumoniae (odds ratio [OR], 4.40; 95% confidence interval [CI], 1.90 and 10.19) and Haemophilus influenzae (OR, 2.04; 95% CI, 1.38 and 3.02). The risk was higher for the presence of bocavirus and H. influenzae together (OR, 3.61; 95% CI, 1.90 and 6.86). Acute otitis media risk differs by the specific viruses and bacteria involved. Acute otitis media prevention efforts should consider methods for reducing infections caused by respiratory syncytial virus, bocavirus, and adenovirus in addition to acute otitis media bacterial pathogens.

By the age of 3 years, more than two-thirds of children experience ≥1 episode of acute otitis media (AOM), and about half experience ≥3 episodes [1]. AOM is a leading cause of physician visits and antibiotic prescriptions. Pathogenic bacteria are isolated from middle ear fluid in up to 70% of cases [2], with Streptococcus pneumoniae and nontypeable Haemophilus influenzae together representing 60%–80% of bacterial cases [3–5]. Vaccines against these pathogens thus offer potential public health gains. Use of the 7-valent (7vCRM; Pfizer) pneumococcal conjugate vaccine (PCV) in infants became widespread over the last decade [6]. Two PCVs with higher valency were recently licensed and are gradually replacing 7vCRM. The 10-valent PCV (PHiD-CV; GlaxoSmithKline Biologicals) includes 3 additional serotypes and uses an H. influenzae protein D carrier [7]. The 13-valent PCV (13vCRM; Pfizer) includes the same serotypes as PHiD-CV, plus another 3 [8]. 7vCRM has dramatically reduced invasive pneumococcal disease (IPD), with >90% efficacy in clinical studies [9] and virtual elimination of vaccine-type IPD in immunized cohorts [10]. However, the impact on AOM, a polymicrobial mucosal disease, is less clear. A previous meta-analysis of efficacy trials [11] did not include observational database studies, and the 2 types of results need to be reconciled. Accumulation of effectiveness results for new vaccines takes some years, so OM policy decisions must still be based partly on 7vCRM effectiveness data. METHODS Search Strategy PubMed was searched for articles in English, French, German, and Italian published between January 1998 and September 2010, using the terms “S. pneumoniae,” “pneumococcal conjugate vaccin*,” “vaccine,” “acute otitis media,” “otitis media,” “efficacy,” “effectiveness,” “effect(s),” “impact,” “visit(s),” “episode(s),” “claims,” “trends,” “retrospective,” and “observational” combined with “All child: 0–18 years.” Potentially relevant publications were screened for (1) original study, (2) assessment of PCV efficacy/effectiveness against all-cause AOM episodes or physician visits, and (3) a study population of children aged ≤12 years. Publication bibliographies and recent reviews were examined for further articles. Publications were noted but data not used in evidence tables if they focused specifically on hospitalizations/severe complications, recurrent AOM, and OM with effusion; used schedules other than 3 + 1 or 2 + 1; provided only data after administration of both PCV and the 23-valent pneumococcal polysaccharide vaccine; or calculated cost-effectiveness without providing new effectiveness data. Calculations Where necessary, rates were recalculated as the number of cases per 1000 person-years (PY). For observational database studies, pre-PCV rate changes were calculated as the difference between estimates reported for the first study year and the last year before PCV introduction, and post-PCV rate changes were calculated as the difference between estimates for the last year before PCV introduction and the last study year. Average rates for the periods before and after 7vCRM introduction were not calculated because consistently decreasing trends were seen in most studies. However, if rates were only reported for certain years combined [12–15], these data were used. Unpublished estimates were obtained directly from study investigators [13, 16] or approximated from figures [17]. For Poehling et al, the only available estimates for post-PCV changes were based on ratios of rates for 2–3.5 years. b A negative efficacy indicates an increased risk in the vaccine group. c Most vaccinated children had underlying medical conditions, in contrast to unvaccinated children. Table 2. Summary of the Observational Database Studies Included in the Literature Analysis Reference Country (State, Prov, Pop) Database Age (Years) No. of Subjects Case Definition Case Ascertainment Comparison Baseline Rate (per 1000 Pop or PY) Pre-PCV Decrease (%) Post-PCV Decrease (%) Poehling et al 2004 [18] United States (TN) TN: Medicaid-managed care (government) 80% would be expected to induce herd protection via decrease in nasopharyngeal carriage of vaccination serotypes [30, 31]. Although there is strong evidence for herd protection with IPD, herd protection against vaccine-type AOM in nonvaccinated age groups has not yet been directly demonstrated because tympanocentesis is not routinely performed. Dilution of vaccine-type herd protection within all-cause OM makes it hard to show, and one study failed to detect it in overall AOM visits in older children 2 years after 7vCRM implementation [19]. Near elimination of vaccine-type carriage some years after PCV use, on the assumption of maximum herd protection (with vaccine types eradicated), is a reasonable approximation. Effectiveness against vaccine types would then be 100% instead of 57%, yielding a theoretical effectiveness of approximately 26%. The above calculations do not reflect any replacement with nonvaccine serotypes and bacteria, although some replacement is suggested in clinical studies and postintroduction surveillance [3, 32, 33]. Indeed, a recent model that used actual nasopharyngeal carriage rates in US children for both vaccine and nonvaccine serotypes, taking into account their specific abilities to cause AOM, projected a maximum theoretical effectiveness of 7vCRM against overall AOM of only 12% [34]. This suggests that estimates well beyond these theoretical limits may be substantially confounded and biased. Variability in Baseline Incidence Baseline AOM episode rates in clinical trials varied 10-fold. The high baseline rate in FinOM [3] is similar to US rates (900–1500 AOM episodes per 1000 children) [20, 35, 36], whereas the low rate in the POET trial is closer to those reported in other European studies (154–400 AOM episodes per 1000 PY) [37]. In general, stronger vaccine effects would be expected on samples that use tighter diagnostic definitions and, hence, lower baseline case incidence, but they face sample size challenges. This, plus possible intrinsic differences in populations or differences in healthcare uptake beyond those of diagnostic definition, suggest that one should be cautious in considering between-study comparisons of vaccines. Among the database analyses, baseline rates also varied across studies, even after taking into account age differences [12, 15, 16, 18]. Strong evidence for demographic, immunological, or microbiological differences between such populations is lacking, so such baseline rate differences are more appropriately attributed to differences in case severity or diagnostic code for case definition. Changes Before Versus After Vaccine Introduction In observational database studies, OM visit rates decreased by 19% on average after 7vCRM introduction. However, among studies also presenting data before 2000, all [12–15, 17] but one [16] observed OM visits declining by 15% on average before 7vCRM introduction. This suggests that long-term decreases in consultations before 7vCRM introduction, which are unlikely to have halted, have added to apparent postintroduction decreases. Poehling et al and Grijalva et al controlled for annual trend via differential effect by age, arriving at 4%–19% decreases due to 7vCRM [12, 18]. However, this minimizes any herd protection affecting the nonimmunized portion of the younger cohort. In addition, non–vaccine-related factors, such as age stratification of <2/≥2 years in antibiotic prescription guidelines, could affect OM visit rates over time differentially by age. De Wals et al moved in the appropriate direction by estimating a post-PCV rate with time-series regression to adjust for annual trend [19]; the raw decrease in OM claims in 2000–2007 was 25%, but the adjusted decrease attributable to 7vCRM was only approximately 13%. To determine whether the decrease in consultations is due to 7vCRM introduction, analysis must be made over a few years and according to when and to what extent the vaccine was introduced. For example, a recent study in an Athens hospital found that, beginning in 2005, emergency department visits by children aged <15 years decreased by 38% and 48% for all-cause and pneumococcal otorrhea, respectively [38]. However, this drop occurred 1–2 years before mass pneumococcal vaccination in Greece, at the time of (presumably low) private market 7vCRM use, and, even after the decrease, vaccine serotypes still represented the majority of pneumococcal otorrhea. Upon implementation of mass vaccination in 2006, no further drop was seen, indicating that the reduction in 2005 was largely due to nonvaccine factors. Potential Nonvaccine Factors Several other factors might explain why OM rates decreased before PCV introduction and continued decreasing after. First, changes in AOM perception, consultation rates, and frequency and type of antibiotic use date from the early 1990s. The increasing acceptance by parents and physicians of observation without antibiotic use (“watchful waiting”), which is officially recommended for some AOM patients [39], could reduce the apparent AOM incidence if parents do not consult physicians for mild AOM if they expect little benefit for their child. Stricter diagnostic criteria [39] may have reduced not only inappropriate antibiotic use [13] but also apparent AOM consultation rates. Second, a shift to higher antibiotic dosage or the doubling of long-acting macrolide use in US children around the same time as 7vCRM introduction [40] could have reduced relapses and, therefore, reduced the total number of AOM visits per episode, thus reducing the healthcare burden [17]. Third, awareness of vaccination status could affect care-seeking behavior. In a recent observer-blinded randomized trial in Sweden of children at risk for recurrent AOM conducted before universal PCV, receipt of 7vCRM reduced overall reported AOM episodes by 26% and AOM hospital visits by 36% [41]. Because these apparent effects are larger than the above theoretical effectiveness estimate, there may have been some differential contribution from parents seeking medical assistance depending on vaccination status, with less care-seeking for vaccinated children because of the belief that vaccine would probably prevent the more serious forms or complications of disease. Fourth, the decline in OM rates has paralleled the decreasing exposure of children to secondhand tobacco smoke, a strong AOM risk factor [42]. Fifth, influenza vaccination can reduce AOM incidence during the influenza season by reducing viral coinfection [43]. However, influenza routine vaccination in the US began in 2004, with the sharpest increase around 2007–2008 [44], after the attributable post-7vCRM decrease in OM. Study Population Possible differences among populations, chiefly their relative risks, cannot be overlooked in explaining the heterogeneity of results. However, convincing demonstrations are lacking. The failure of O'Brien et al to detect a statistically significant 7vCRM impact on AOM in high-risk American Indians may be due to the lack of statistical power [20]. Likewise, a favorable, although nonsignificant, vaccine effect (adjusted relative risk, 0.88 [95% CI, .69–1.13]) was found in successive cohorts of 51 nonvaccinated and 97 vaccinated (7vCRM plus a 23-valent polysaccharide booster dose) high-risk Australian aboriginal children [45]. Finally, the authors of the nonrandomized, nonblinded 7vCRM German trial [23] suggested that the achievable efficacy was possibly biased against the vaccine because more children in the 7vCRM group than the control group had a medical risk factor (66% vs 18%) or were born prematurely (40% vs 6%). The assumption behind all these studies is that high-risk, otitis-prone children generate a weaker immune response, for which there is some evidence [46]. Limited statistical power currently prevents clear conclusions, but possible differences in vaccine effectiveness between populations deserve consideration. Diagnostic Codes Included as OM Observational database studies identify OM cases according to broad diagnostic codes that are based often on a single clinician's judgment rather than on precise protocols and measurements. In the International Classification of Diseases, Ninth Revision coding system, codes 381.x refer mainly to nonsuppurative AOM, codes 382.x to suppurative AOM, and codes 383.x to mastoiditis. Code choice could greatly affect absolute OM visit count, and study-specific differences in case definition or even OM type distribution could influence 7vCRM effectiveness estimates [28, 47]. Unfortunately, no studies reported the proportions of the different codes used. Grijalva et al defined OM diagnosis as 381.x–382.x in one study [12] and as 381.x–383.x in the other [13], whereas Poehling et al used 381.0–381.4 and 382.x [15]. Zhou et al used 381.00–381.6, 382.00–382.02, 382.3, and 382.9 [16] but, unlike the other studies, only considered first-listed codes, possibly explaining why they reported the largest decrease (43%) [16]. Indeed, where AOM antibiotic use is strictly controlled, some physicians may use AOM less as a primary code, preferring a symptom-based equivalent code. Design Considerations for Future Studies Vaccine impact will always be assessed by large observational studies. However, one key requirement is adjustment for non–vaccine-related confounders. Adjustment for secular trends [48–50], preferably via time-series modeling [19], should always be performed. Modeling would also allow distinction between year-to-year variation (random and viral) and longer-term trends. At a minimum, projections from prevaccine trends should provide the expected null value from which an observed deviation may be taken as evidence for vaccine effect [48–50]. In addition, measurement of time trends of other diseases could provide additional control, with the caveat that some nonvaccine trends could affect unrelated diseases differently. The central public health questions are whether vaccination causes an overall decrease in AOM and associated healthcare burden. Tympanocentesis-based efficacy studies, even at the population level, would at least help specify how much of an overall decrease is limited to target pathogens/serotypes, but it remains unusual and ethically problematic to perform routinely, and determining vaccine effectiveness against individual serotypes necessitates large sample sizes. PCV effects on AOM can be measured economically and with good control in case-control studies, as for IPD [51–53]. However, finding appropriate controls in a well-immunized population is difficult. The presumably present herd protection is seen as a depressed incidence in controls and is not directly measurable with this design, meaning the effect is nearer to an efficacy than to an effectiveness estimate. Finally, the problem of quality of case definition has long been remarked in AOM studies. Some hope of reducing variability from this source is given by 2 recent high-quality randomized studies on AOM treatment that used stringent and reproducible criteria applicable to all designs except routine practice databases [54, 55]. In conclusion, observed OM visit rates have decreased by approximately 19% following 7vCRM introduction, but long-term reductions in OM visits preceding 7vCRM introduction of approximately 15% suggest that continuing influences other than PCV vaccination have caused some of the subsequent reduction. Caution is therefore needed in the report and interpretation of these data, and no single study should be quoted as representing the “true” effect of 7vCRM on AOM. Study methods need to be improved to more accurately estimate true PCV effectiveness.