Abstract
Background
Antimicrobial resistance (AMR) poses a significant challenge for treating pneumococcal disease. This study assessed AMR trends in Streptococcus pneumoniae from US children.
Methods
We evaluated antibiotic resistance, defined as facility antimicrobial susceptibility reports of intermediate/resistant, in 30-day nonduplicate S pneumoniae isolates from children (<18 years of age) with invasive (blood or cerebrospinal fluid/neurological) or noninvasive (respiratory or ear/nose/throat) isolates at 219 US hospital inpatient/outpatient settings in the BD Insights Research Database (January 2011–February 2020). We used descriptive statistics to characterize the percentage of antimicrobial-resistant isolates and generalized estimating equations to assess variations in resistance over time.
Results
Of 7605 S pneumoniae isolates analyzed, 6641 (87.3%) were from noninvasive sources. Resistance rates were higher in noninvasive versus invasive isolates. Isolates showed high observed rates of resistance to ≥1 drug class (56.8%), ≥2 drug classes (30.7%), macrolides (39.9%), and penicillin (39.6%) and significant annual increases in resistance to ≥1 drug class (+0.9%), ≥2 drug classes (+1.8%), and macrolides (+5.0%).
Conclusions
Among US children over the last decade, S pneumoniae isolates showed persistently high rates of resistance to antibiotics and significant increases in ≥1 drug class, ≥2 drug classes, and macrolide resistance rates. Efforts to address AMR in S pneumoniae may require vaccines targeting resistant serotypes and antimicrobial stewardship efforts.
Keywords: antibiotic resistance, children, pneumococcal disease, invasive pneumococcal vaccines, Streptococcus pneumoniae
The introduction of pneumococcal conjugate vaccines (PCVs) against Streptococcus pneumoniae infections transformed the epidemiology of pneumococcal disease (PD) and associated health outcomes in both children and adults [1, 2]. Initial decreases in PD rates following introduction of PCVs were accompanied by reductions in cases of antimicrobial-resistant invasive pneumococcal disease (IPD) in children in the United States (US) and globally [3–7]. PCVs can reduce antimicrobial resistance (AMR) directly by reducing the incidence of resistant pneumococcal infections as well as indirectly by reducing antibiotic use, thereby relieving selective pressure on antibiotic-resistant strains [8, 9]. However, increased AMR over time has been observed in nonvaccine serotypes in pediatric IPD [10] and in both vaccine and nonvaccine serotypes in noninvasive PD pediatric samples [11].
Currently, the Centers for Disease Control and Prevention (CDC) estimates that approximately 30% of IPD cases are caused by S pneumoniae isolates resistant to 1 or more clinically relevant antibiotics. Drug-resistant S pneumoniae isolates caused an estimated 900 000 infections and 3600 deaths per year in all age groups in 2014 and has been designated a serious threat by the CDC [12]. Worldwide, S pneumoniae is the fourth leading pathogen in terms of deaths associated with or attributable to resistance [13]. Current data on AMR in S pneumoniae are essential not only for clinical management, but also to assess evolutionary AMR trends in this important pathogen and prioritize efforts to reduce resistance. However, there is a lack of information on S pneumoniae resistance in the pediatric population, which does not have as many treatment options as adult patients [14]. In particular, there is a dearth of information on resistance in pediatric noninvasive PD infections, which constitute the majority of PD cases [2]. We therefore evaluated AMR in S pneumoniae isolates obtained from children with invasive or noninvasive PD.
METHODS
Study Design
This was a retrospective study of antibiotic susceptibility of specified nonduplicate S pneumoniae isolates (first noncontaminant S pneumoniae isolate within 30 days) collected from hospitalized and ambulatory pediatric patients (aged <18 years at time of culture collection) between January 2011 and February 2020 as part of routine clinical management. IPD cases were defined as those with S pneumoniae isolates obtained from cerebrospinal fluid (CSF)/neurology samples or blood (including valve and ventricle catheter tip sources). Noninvasive PD cases were defined as those with S pneumoniae isolates obtained from respiratory samples or the ear, nose, or throat (ENT). Skin/wound, urine, and other nonsterile sources not listed above were evaluated but excluded from statistical modeling as they are not commonly associated with S pneumoniae infections. Cultures likely to be associated with contamination or colonization, such as environmental/surveillance specimens from rectal or nasal swabs, were excluded by use of a previously described algorithm [15].
Reporting institutions consisted of US hospitals in the BD Insights Research Database (Becton, Dickinson and Company, Franklin Lakes, New Jersey), which includes small and large hospitals in urban and rural areas and provides geographical representation across the US [16, 17]. The study was approved as involving use of a limited retrospective data set for an epidemiology study and deemed exempt from consent by the New England Institutional Review Board/Human Subjects Research Committee (Wellesley, Massachusetts) and conducted in compliance with Health Insurance Portability and Accountability Act requirements.
AMR was evaluated in S pneumoniae isolates based on facility reports; minimal inhibitory concentration (MIC) breakpoints were not standardized across facilities. Antibiotic resistance was assessed using the following definitions:
Penicillin resistant: Intermediate (I) or resistant (R) to penicillin.
Macrolide resistant: I or R to erythromycin, azithromycin, or clarithromycin.
Fluoroquinolone resistant: I or R to levofloxacin or moxifloxacin.
Extended-spectrum cephalosporin (ESC) resistant: I or R to ceftriaxone, cefotaxime, or cefepime.
Tetracycline resistant: I or R to doxycycline or tetracycline.
Any drug class or ≥2 drug class resistant: I or R to any of the tested antibiotics or ≥2 of the drug classes listed above, respectively.
Outcomes
For each category of resistance defined above, we evaluated the percentage of resistance (mean number of resistant isolates per total isolates tested) overall, by invasive versus noninvasive PD, and by year, sex, age group, and hospital characteristics.
Statistical Analysis
Descriptive statistics of the percentage of resistant isolates over time were presented by cross-tabulation. For the multivariate analyses, the generalized estimating equation (GEE) method and logistic regression with a first order autoregressive variance-covariance matrix was used to evaluate the quarterly trends of percentage AMR. In the GEE framework, the time series data (count of resistant isolates) were viewed as repeated measures and hospital/facility modeled as random effect. All analyses were also stratified by invasive and noninvasive source type. Key additional factors included in the analyses were setting of isolate collection (ambulatory, admission period [first 3 days of admission, with day of admission considered day 1], and hospital-onset period [>3 days postadmission]), age group, sex, and source type (blood, CSF/neurological, respiratory, and ENT). Multivariate analyses were controlled for hospital demographics (bed size, urban/rural location, teaching status, and geographic location [US census region]), age, sex, setting, and quarter. All statistical analyses were conducted using R version 4.0.3 software (R Core Team 2020) and the R geepack package. P values <.05 were considered statistically significant.
RESULTS
A total of 219 hospitals provided data during the 10-year study period (Supplementary Table 1). The number of hospitals contributing data over the years ranged from 77 in 2011 to 188 in 2019. Urban facilities accounted for 61.2% of facilities and the South US census region (51.1%) had the highest proportion of hospitals followed by the Midwest (18.7%), Northeast (16.4%), and West (13.7%) regions. Among the 7605 S pneumoniae isolates analyzed over the study period, 28.1% were from patients <2 years, 36.9% were from patients 2–4 years, and 35.1% were from patients 5–17 years (Table 1). Almost 90% of the isolates (6641 [87.3%]) were from noninvasive PD cases, primarily ENT (n = 3201) and respiratory (n = 2211) cultures, while the remainder (964 [12.7%]) were from IPD sources (872 from blood and 92 from CSF/neurological cultures).
Table 1.
Distribution of 30-Day Nonduplicate Streptococcus pneumoniae Isolates by Invasive and Noninvasive Pneumococcal Disease Source in Pediatric Patients
| Characteristic | Invasive PD | Noninvasive PD | Total | |||
|---|---|---|---|---|---|---|
| No. | (%) | No. | (%) | No. | (%) | |
| Overall | 964 | (100) | 6641 | (100) | 7605 | (100) |
| Age, y | ||||||
| <2 | 328 | (34.0) | 1807 | (27.2) | 2135 | (28.1) |
| 2–4 | 308 | (32.0) | 2495 | (37.6) | 2803 | (36.9) |
| 5–17 | 328 | (34.0) | 2339 | (35.2) | 2667 | (35.1) |
| Sex | ||||||
| Female | 407 | (42.2) | 2904 | (43.7) | 3311 | (43.5) |
| Male | 557 | (57.8) | 3737 | (56.3) | 4294 | (56.5) |
| Source | ||||||
| Blood | 872 | (90.5) | … | … | 872 | (11.5) |
| Neurological | 2 | (0.2) | … | … | 2 | (<0.1) |
| CSF | 90 | (9.3) | … | … | 90 | (1.2) |
| Respiratory | … | … | 2211 | (33.3) | 2211 | (29.1) |
| ENT | … | … | 3201 | (48.2) | 3201 | (42.1) |
| Wound | … | … | 934 | (14.1) | 934 | (12.3) |
| Urine | … | … | 204 | (3.1) | 204 | (2.7) |
| Other | … | … | 84 | (1.3) | 84 | (1.1) |
| Onset | ||||||
| Ambulatory | 491 | (50.9) | 5158 | (77.7) | 5649 | (74.3) |
| Admission | 429 | (44.5) | 1214 | (18.3) | 1643 | (21.6) |
| Hospital | 44 | (4.6) | 269 | (4.1) | 313 | (4.1) |
Totals may not equal 100% due to rounding.
Abbreviations: CSF, cerebrospinal fluid; ENT, ear, nose, and throat; PD, pneumococcal disease.
Antimicrobial Resistance in S pneumoniae Isolates
The majority (56.8%) of isolates were resistant to at least 1 drug class (≥1 drug class) during the study period, and 30.7% of isolates were resistant to ≥2 drug classes (Figure 1; Table 2). There were too few isolates with resistance to ≥3 drug classes for meaningful analyses (n = 637).
Figure 1.
Resistance profiles of Streptococcus pneumoniae isolates by number of drugs based on observed data for all (N = 7605), invasive pneumococcal disease (IPD) (n = 964), and noninvasive pneumococcal disease (PD) (n = 6641) isolates.
Table 2.
Observed Antimicrobial Resistance in Streptococcus pneumoniae Isolates in Children (January 2011–February 2020)
| Antibiotic | Invasive PD (n = 964) |
Noninvasive PD (n = 6641) |
Total (N = 7605) |
|---|---|---|---|
| Resistance to ≥1 drug class | 407 (42.2) | 3915 (59.0) | 4322 (56.8) |
| Resistance to ≥2 drug classes | 143 (14.8) | 2193 (33.0) | 2336 (30.7) |
| Resistance by antibiotic class | |||
| Macrolide | 306 (31.7) | 2731 (41.1) | 3037 (39.9) |
| Penicillin | 199 (20.6) | 2813 (42.4) | 3012 (39.6) |
| Tetracycline | 72 (7.5) | 761 (11.5) | 833 (11.0) |
| ESC | 34 (3.5) | 483 (7.3) | 517 (6.8) |
| Fluoroquinolone | 4 (0.4) | 29 (0.4) | 33 (0.4) |
Data are presented as No. (%). Totals may not equal 100% due to rounding.
Abbreviations: ESC, extended-spectrum cephalosporins; PD, pneumococcal disease.
Approximately 40% of isolates were resistant to macrolides (39.9%) or to penicillin (39.6%) (Table 2). Tetracycline resistance was observed in 11.0% of isolates, ESC resistance in 6.8%, and fluoroquinolone resistance in 0.4% of the isolates. The remainder of the analyses were focused on resistance to macrolides or penicillin, as tetracycline is generally not recommended in pediatric patients aged <8 years [14] and the proportions of isolates with ESC and fluoroquinolone resistance were low.
A higher proportion of noninvasive PD compared with IPD isolates was resistant to ≥1 drug class (59.0% vs 42.2%), ≥2 drug classes (33.0% vs 14.8%), macrolides (41.1% vs 31.7%), and penicillin (42.4% vs 20.6%) (Table 2). Multivariate models confirmed the statistical significance of these differences in adjusted analyses (all P < .001; Table 3).
Table 3.
Adjusted Streptococcus pneumoniae Resistance Rates Overall and by Age and Culture Source
| Characteristic | % Resistance to ≥1 Drug Class | % Resistance to ≥2 Drug Classes | % Macrolide-Resistant Isolates | % Penicillin-Resistant Isolates | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IPD | Noninvasive PD | Total | IPD | Noninvasive PD | Total | IPD | Noninvasive PD | Total | IPD | Noninvasive PD | Total | |
| Overall | 41.7 (39.7–43.6) |
58.4 (57.4–59.4) |
56.1 (55.6–56.6) |
15.1 (13.7–16.5) |
34.7 (33.7–35.6) |
31.6 (30.9–32.2) |
32.9 (31.4–34.4) |
47.5 (46.3–48.6) |
45.1 (44.1–46.2) |
18.9 (17.2–20.7) |
41.9 (40.6–43.2) |
40.2 (38.1–42.2) |
| Age, y, P value | .009 | <.001 | <.001 | .161 | <.001 | <.001 | .141 | <.001 | <.001 | .068 | <.001 | <.001 |
| <2 | 40.7 (38.9–42.5) |
65.7 (64.0–67.3) |
61.9 (60.8–63.1) |
14.7 (12.7–16.6) |
39.1 (37.2–40.9) |
35.1 (33.6–36.5) |
33.0 (31.0–35.0) |
52.9 (51.2–54.6) |
49.5 (48.5–50.5) |
17.0 (15.9–18.1) |
48.0 (46.5–49.6) |
44.8 (43.6–46.1) |
| 2–4 | 47.3 (45.4–49.3) |
60.1 (58.6–61.5) |
58.2 (57.3–59.2) |
18.3 (16.2–20.3) |
36.2 (34.6–37.7) |
33.5 (32.2–34.7) |
38.2 (36.1–40.4) |
49.1 (47.6–50.6) |
47.3 (46.4–48.2) |
22.7 (21.4–23.9) |
42.8 (41.4–44.3) |
41.5 (40.3–42.7) |
| 5–17 | 37.3 (35.5–39.1) |
50.7 (49.2–52.1) |
48.9 (48.0–49.8) |
12.6 (10.6–14.6) |
29.4 (27.9–31.0) |
26.6 (25.4–27.9) |
27.8 (25.8–29.8) |
41.3 (39.8–42.7) |
38.9 (37.8–40.1) |
17.3 (16.2–19.3) |
35.8 (34.4–37.3) |
34.8 (33.6–35.9) |
| Source, P value | .012 | .179 | <.001 | .028 | .556 | <.001 | <.001 | .002 | <.001 | .667 | .844 | <.001 |
| Blood | 42.4 (41.4–43.5) |
… | 47.0 (45.2–48.7) |
15.7 (14.2–17.2) |
… | 18.1 (15.9–20.4) |
34.6 (33.0–36.2) |
… | 37.7 (36.3–39.1) |
18.7 (16.9–20.6) |
… | 20.3 (18.9–21.7) |
| CSF/neurological | 34.3 (32.0–36.6) |
… | 38.6 (35.6–41.6) |
9.7 (7.3–12.1) |
… | 12.4 (10.1–14.7) |
16.8 (14.8–18.7) |
… | 21.9 (19.8–23.9) |
20.6 (18.0–23.1) |
… | 21.0 (19.4–22.6) |
| Respiratory | … | 59.7 (58.0–61.4) |
59.2 (58.0–60.5) |
… | 34.7 (33.0–36.5) |
34.3 (32.8–35.8) |
… | 49.7 (48.0–51.4) |
49.1 (47.9–50.2) |
… | 42.1 (40.5–43.7) |
42.0 (40.6–43.4) |
| ENT | … | 57.5 (55.3–58.7) |
56.9 (56.1–57.8) |
… | 34.6 (33.3–35.9) |
33.9 (32.8–35.0) |
… | 45.9 (44.6–47.2) |
44.9 (43.1–46.7) |
… | 41.8 (40.4–43.1) |
41.8 (40.7–43.0) |
Unless otherwise indicated, data are presented as estimated percentage resistance (95% confidence interval). Models were adjusted by age, sex, setting, quarter, hospital demographics, and United States census region. Additional variables are presented in Supplementary Table 2.
Abbreviations: CSF, cerebrospinal fluid; ENT, ear, nose, throat; IPD, invasive pneumococcal disease; PD, pneumococcal disease.
Association of Demographic and Hospital Characteristics With S pneumoniae Resistance
In multivariate analyses of total S pneumoniae isolates, significant differences among age groups were observed for resistance to ≥1 drug class, ≥2 drug classes, macrolides, and penicillin (Table 3). The <2-year-old age group had the highest levels of resistance and the 5- to 17-year-old age group had the lowest. As mentioned above, resistance was higher in noninvasive PD (respiratory, ENT) than in IPD (blood, CSF/neurological) isolates. Other characteristics associated with higher rates of S pneumoniae resistance included hospital bed size (≥1 drug class), hospital-onset cultures (all drug categories), and geographic region (all drug categories) (Supplementary Table 2).
Noninvasive PD isolates showed similar age patterns to total isolates. Macrolide resistance rates were significantly higher for respiratory versus ENT isolates, but resistance rates for ≥1 drug class, ≥2 drug classes, and penicillin were similar for these sources. Other characteristics associated with higher resistance rates in noninvasive PD isolates included hospital bed size (≥2 drug classes and macrolides), hospital-onset cultures (all drug categories), urban/rural location (macrolides), teaching versus nonteaching hospitals (macrolides), and geographic region (all drug categories) (Supplementary Table 2).
In contrast to the age pattern observed for total and noninvasive PD isolates, for IPD isolates the 2 to 4-year-old age group had the highest levels of resistance to ≥1 drug class, ≥2 drug classes, macrolides, and penicillin (Table 3). Resistance to all evaluated drug categories was higher for blood versus CSF/neurological isolates. Other characteristics associated with higher resistance rates in IPD isolates included hospital bed size (≥1 drug class and macrolides), hospital-onset cultures (≥2 drug classes, macrolides, and penicillin), teaching versus nonteaching hospitals (≥1 drug class), and geographic region (all drug categories) (Supplementary Table 2).
Trends in AMR Over Time
In adjusted analyses, S pneumoniae resistance to ≥1 drug class and ≥2 drug classes increased significantly from January 2011 to February 2020 (Table 4). The annual rate of increase was +0.9% per year for ≥1 drug class and +1.8% per year for ≥2 drug classes over this time period (P < .001 for both analyses). Noninvasive PD isolates showed similar increases (+0.6% per year for ≥1 drug class and +2.2% per year for ≥2 drug classes; P < .001 for both analyses). The rate of IPD isolates with resistance to ≥1 or ≥2 drug classes fluctuated during this time period, but trends were not significant.
Table 4.
Model-Estimated Rates of Resistance and Annual Percentage Change in Streptococcus pneumoniae Resistance to ≥1 and ≥2 Drugs in Isolates Collected From US Children (January 2011–February 2020)
| Year | Estimated % Resistance to ≥1 Drug Class | Estimated % Resistance to ≥2 Drug Classes | Estimated % Resistance to Macrolides | Estimated % Resistance to Penicillins | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IPD | Noninvasive PD | Total | IPD | Noninvasive PD | Total | IPD | Noninvasive PD | Total | IPD | Noninvasive PD | Total | |
| 2011 | 40.1 (35.4–44.8) |
56.7 (54.0–59.5) |
54.3 (52.1–56.5) |
20.2 (18.2–22.1) |
29.5 (27.5–31.5) |
27.9 (26.4–29.5) |
26.8 (24.3–29.2) |
25.5 (23.0–28.0) |
25.6 (23.7–27.4) |
26.8 (24.8–28.9) |
48.7 (46.6–50.8) |
47.4 (45.6–49.1) |
| 2012 | 38.1 (33.2–43.0) |
52.8 (51.0–55.7) |
50.6 (48.3–53.0) |
14.0 (11.2–16.9) |
22.1 (19.9–24.2) |
20.4 (18.6–22.1) |
22.7 (20.2–25.2) |
21.3 (18.7–24.0) |
21.2 (19.2–23.1) |
21.6 (19.6–23.6) |
43.5 (41.3–45.4) |
41.6 (39.8–43.5) |
| 2013 | 43.5 (38.4–48.5) |
52.8 (50.1–55.5) |
51.3 (49.1–53.5) |
13.4 (11.2–15.6) |
21.1 (19.1–23.1) |
19.5 (17.9–21.1) |
36.9 (35.2–38.6) |
24.7 (22.2–27.2) |
25.8 (24.0–27.6) |
17.6 (15.3–20.0) |
41.4 (39.3–43.4) |
39.4 (37.7–41.2) |
| 2014 | 46.4 (42.5–50.4) |
57.2 (54.3–60.0) |
55.6 (53.3–58.0) |
14.0 (11.2–16.9) |
32.4 (30.2–34.6) |
29.4 (27.6–31.1) |
32.1 (30.6–33.7) |
45.3 (42.7–47.9) |
42.9 (40.9–44.8) |
23.6 (20.5–26.7) |
41.9 (39.8–44.0) |
40.8 (39.0–42.6) |
| 2015 | 36.2 (33.6–38.8) |
64.6 (61.9–67.3) |
60.3 (58.2–62.4) |
13.9 (12.9–15.0) |
44.6 (42.6–46.6) |
39.5 (37.9–41.0) |
28.2 (26.9–29.6) |
63.7 (61.3–66.2) |
57.6 (55.8–59.3) |
16.8 (15.6–17.9) |
45.8 (43.8–47.8) |
43.3 (41.6–45.0) |
| 2016 | 38.4 (35.5–41.3) |
58.6 (56.2–61.0) |
55.8 (53.8–57.7) |
14.2 (12.8–15.6) |
41.2 (39.5–42.9) |
36.9 (35.2–38.6) |
33.8 (32.1–35.5) |
58.5 (56.2–60.7) |
54.5 (52.9–56.0) |
16.1 (14.6–17.5) |
42.0 (40.1–43.9) |
39.6 (38.0–41.2) |
| 2017 | 42.6 (39.7–45.6) |
61.0 (58.3–63.6) |
58.3 (56.2–60.4) |
19.1 (17.8–20.4) |
40.9 (38.9–42.9) |
37.4 (35.9–38.9) |
37.6 (36.0–39.3) |
61.1 (58.6–63.5) |
57.1 (55.4–58.8) |
19.4 (18.0–20.8) |
38.9 (36.9–40.9) |
37.9 (36.2–39.6) |
| 2018 | 46.2 (42.6–49.8) |
58.2 (56.1–60.3) |
56.7 (54.2–59.2) |
16.0 (14.1–17.9) |
38.2 (36.7–37.7) |
34.8 (32.9–36.7) |
37.9 (36.5–39.2) |
59.7 (57.0–62.5) |
56.1 (54.0–58.1) |
19.8 (17.7–21.8) |
37.1 (34.9–39.3) |
36.4 (34.5–38.3) |
| 2019 | 43.0 (39.4–46.6) |
61.4 (59.6–63.3) |
58.5 (56.3–60.8) |
9.7 (7.9–11.5) |
39.8 (38.6–41.0) |
35.0 (33.3–36.7) |
35.6 (34.2–36.9) |
61.8 (59.2–64.4) |
57.4 (55.6–59.3) |
11.6 (9.6–13.6) |
37.8 (35.7–39.9) |
35.4 (33.6–37.2) |
| 2020 (Jan–Feb) | 50.4 (47.6–53.2) |
66.1 (63.0–69.1) |
64.2 (60.9–67.5) |
17.9 (15.4–20.4) |
39.9 (37.3–42.4) |
36.4 (33.7–38.9) |
41.4 (39.3–43.5) |
69.1 (65.7–72.5) |
64.3 (61.8–67.8) |
19.5 (15.6–23.4) |
37.2 (34.1–39.3) |
35.8 (32.2–39.3) |
| Annual % change | +0.05% (−.03 to .12) |
+0.6% (.2–1.1) |
+0.9% (.4–1.3) |
−0.3% (−.9 to .3) |
+2.2% (1.7–2.7) |
+1.8% (1.4–2.3) |
+1.4% (.3–2.5) |
+5.7 (5.2–6.2) |
+5.0 (4.5–5.5) |
−1.0 (−1.9 to .2) |
−1.1 (−1.6 to .6) |
−1.1 (−1.5 to .7) |
| P value | .353 | <.001 | <.001 | .480 | <.001 | <.001 | .005 | <.001 | <.001 | .006 | <.001 | <.001 |
Unless otherwise indicated, data are presented as estimated percentage resistance (95% confidence interval). Models were adjusted by age, sex, setting, quarter, hospital demographics, and United States census region.
Abbreviation: IPD, invasive pneumococcal disease; PD, pneumococcal disease.
For total S pneumoniae isolates, resistance to macrolides increased (+5.0% per year, P < .001) and resistance to penicillin decreased (−1.1% per year, P < .001) (Table 4). The same pattern was observed for noninvasive PD (+5.7% per year for macrolides, P < .001; −1.1% for penicillin, P < .001) and IPD isolates (+1.4% per year for macrolides, P = .005; −1.0% for penicillin, P = .006).
DISCUSSION
Streptococcus pneumoniae remains an important cause of pediatric infections despite marked decreases in disease incidence following introduction of PCVs. Effective antibiotics against pneumococci are available, but management of this pathogen can be complicated by AMR. As documented in this study, more than half (56.1%) of 7605 S pneumoniae isolates from US children were resistant to at least 1 drug class in the adjusted analyses, and there were persistently high levels of AMR, particularly to macrolides and penicillin, over the last decade. Multivariate analyses demonstrated significant increasing trends in the proportion of total and noninvasive PD isolates resistant to ≥1 drug class and ≥2 drug classes, and a significant increasing trend in macrolide-resistant isolates for both noninvasive PD and IPD sources. The magnitudes of increasing resistance to ≥2 drug classes (+1.8%/year) and macrolides (+5.0%/year) were particularly alarming. High and increasing S pneumoniae resistance to macrolides has also been documented in adults with PD [16, 17]. More encouraging results were observed with penicillin resistance, which showed a significant decreasing trend, although the approximately 35% resistance rate for total isolates in the most recent data (2019–2020) is still quite substantial. Our findings are consistent with a meta-analysis that reported high levels of penicillin and macrolide resistance in S pneumoniae in children globally [7].
A notable result from this study was higher resistance rates in noninvasive PD isolates compared with IPD isolates, regardless of the drug category evaluated. A similar observation has also been made in adults [17]. Although noninvasive PD cases are generally less severe, they contribute to widespread antibiotic use [18–20] and exert a heavy burden on the healthcare system, including an estimated 382 182 pneumonia hospitalizations and 93 million office visits for otitis media in US children between 1997 and 2019 [2]. It is likely that the observed resistance in pediatric noninvasive PD isolates is related to high levels of antibiotic use for outpatient respiratory infections, as has been suggested by some studies [21, 22]. We also found higher resistance rates in children under the age of 2 compared with older age groups for total and noninvasive PD isolates. This finding is of significant concern, as children <2 years of age are more vulnerable to S pneumoniae infections and deaths than older pediatric age groups [23, 24].
Drug-resistant S pneumoniae infections represent one of the few antibiotic-resistant threats that can be mitigated by vaccines [12]. Although US childhood PCV vaccination rates are generally high (82%–92%), lagging vaccination rates are observed in some populations, including uninsured children and children living below the poverty level, and coronavirus disease 2019–related disruptions in vaccination schedules have further exacerbated these disparities [25]. Pneumococcal vaccines reduce AMR by decreasing the frequency of S pneumoniae serotypes that are more likely to be antibiotic resistant [3, 7] and by reducing respiratory infections that result in antibiotic use [9]. Reductions in rates of PD are also associated with reductions in antimicrobial-resistant S pneumoniae caused by serotypes covered by vaccines [3]. However, there has been a recent increase in antimicrobial-resistant S pneumoniae due to serotypes not covered by 13-valent PCV (PCV13) [3].
Accordingly, another potential defense against antimicrobial-resistant pneumococcal infections is expanded-valency vaccines. New PCVs covering additional serotypes (15-valent PCV [PCV15] and 20-valent PCV [PCV20]) have recently been approved for adults in the US [26, 27], and PCV15 has also been approved for children in the US [27]. PCV15 and PCV20 cover several additional serotypes that contribute to resistant IPD [3]. Modeling studies indicate that these extended-valency vaccines have the potential to substantially reduce the burden of PD in US children [28, 29]. The profound effect of vaccines on disease burden is further expanded when economic evaluations of AMR reduction are included [30]. Both the World Health Organization and the US National Vaccine Advisory Committee have endorsed the use of vaccines to decrease levels of antibiotic-resistant bacteria [31, 32].
Although vaccines are a critical component of initiatives to combat AMR in S pneumoniae, effective antimicrobial stewardship efforts are also needed to combat resistance in S pneumoniae and other pathogens. Antibiotic overuse continues to be a problem that drives community AMR for S pneumoniae [21, 33]. The issue of inappropriate antibiotic use in US children has been well documented [19, 34–36]. Although antibiotics are not routinely recommended for pediatric outpatients with community-acquired pneumonia (CAP), which is often due to viral infections, 73.9% of US children aged 1–6 years with CAP between 2008 and 2015 were nonetheless prescribed antibiotics based on nationwide data [19]. Counter to current guidelines, macrolides are the most common antibiotic class prescribed for ambulatory CAP in children, with approximately 40% of pediatric patients receiving macrolide treatment [19, 34, 35]. This widespread usage is likely a contributor to the high (adjusted rate of 45.1%) and increasing macrolide resistance rate observed in our study and suggests that targeted antimicrobial stewardship efforts may be required to reduce AMR in S pneumoniae. Both inpatient and outpatient stewardship programs are key to achieving this goal [37, 38]. Our data may also be useful in the critical examination of guidelines for treating common respiratory diseases [39].
Our study has limitations, including the use of facility reports to assess AMR, which may have influenced reported resistance rates and contributed to a lack of consistency in resistance thresholds across different facilities. This consideration is particularly relevant for penicillin resistance rates. In 2013, the Clinical and Laboratory Standards Institute (CLSI) increased the nonmeningitis nonsusceptibility breakpoint for parenteral penicillin from an MIC of >0.06 mg/L to >2 mg/L [40]. Use of the lower breakpoint could cause inflated rates of resistance and may have influenced trends in resistance over time. In a recent analysis of US S pneumoniae isolates (n = 7901), primarily (88.5%) from respiratory tract infections, penicillin-nonsusceptible rates were 38.8% using the meningitis/oral penicillin breakpoint (>0.06 mg/L) and 6.2% using the parenteral penicillin breakpoint (>2 mg/L) [41]. CLSI changes can take many years to be fully adopted at the clinical laboratory level [42]; a recent survey of 1490 US clinical laboratories reported that between 30% and 62% of laboratories used obsolete breakpoints for at least 1 of the pathogens evaluated, although S pneumoniae was not included in this study [43]. It is therefore possible that delayed adoption of this CLSI change increased the percentage of penicillin-resistant S pneumoniae isolates reported by facilities, which could explain the discrepancy between our data and lower numbers (3.6%) reported by the CDC, which utilizes a central laboratory for resistance rate assessment [24]. Changing resistance breakpoints may also have influenced the decreased resistance to penicillin observed in our study. It is important to note, however, that the data presented here reflect the susceptibility data on isolates available to clinicians during daily management of their patients. Other potential limitations of our study include lack of information on associated infections; our analyses were based solely on culture-positive isolates, and the presence of symptomatic PD was not confirmed. Selection bias, which can affect all microbiologic surveillance studies, may increase estimates of resistance due to a higher likelihood of testing more severely ill patients. We did not evaluate S pneumoniae serotypes or the pneumococcal vaccination status of patients. These data would be valuable additions to a future analysis.
In conclusion, our data document high levels of resistance to macrolides and penicillin in S pneumoniae isolates among US children with IPD and noninvasive PD infections. These data may help inform initial treatment decisions for pediatric outpatients and inpatients with suspected pneumococcal infections. The rates of resistance to ≥1 drug class,≥2 drug classes, and macrolides have increased in pediatric S pneumoniae isolates over the past 10 years, despite overall disease reductions attributable to vaccines. Addressing the high and increasing rates of S pneumoniae resistance may require PCVs with expanded serotype coverage and targeted antimicrobial stewardship efforts [3, 37, 38].
Supplementary Material
Contributor Information
Salini Mohanty, Center for Observational and Real World Evidence (CORE), Merck & Co, Inc, Rahway, New Jersey, USA.
Kristen Feemster, Center for Observational and Real World Evidence (CORE), Merck & Co, Inc, Rahway, New Jersey, USA.
Kalvin C Yu, Becton, Dickinson & Company, Franklin Lakes, New Jersey, USA.
Janet A Watts, Becton, Dickinson & Company, Franklin Lakes, New Jersey, USA.
Vikas Gupta, Becton, Dickinson & Company, Franklin Lakes, New Jersey, USA.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Notes
Acknowledgments . We thank Sharon L. Cross, PhD, Fusion MD Medical Science Network (Montreal, Canada), for providing manuscript support with funding from Becton, Dickinson & Company.
Financial support . This work was funded by a grant from Merck Sharp & Dohme LLC (MSD), a subsidiary of Merck & Co, Inc, to Becton, Dickinson & Company (BD). Medical writing was supported by BD.
References
- 1. Baxter R, Aukes L, Pelton SI, et al. Impact of the 13-valent pneumococcal conjugate vaccine on invasive pneumococcal disease after introduction into routine pediatric use. J Pediatric Infect Dis Soc 2021; 10:141–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Wasserman M, Chapman R, Lapidot R, et al. Twenty-year public health impact of 7- and 13-valent pneumococcal conjugate vaccines in US children. Emerg Infect Dis 2021; 27:1627–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Bajema KL, Gierke R, Farley MM, et al. Impact of pneumococcal conjugate vaccines on antibiotic-nonsusceptible invasive pneumococcal disease in the United States. J Infect Dis 2022; 226:342–51. [DOI] [PubMed] [Google Scholar]
- 4. Moore MR, Ling-Gelles R, Schaffner W, et al. Effectiveness of 13-valent pneumococcal conjugate vaccine for prevention of invasive pneumococcal disease in children in the USA: a matched case-control study. Lancet Respir Med 2016; 4:399–406. [DOI] [PubMed] [Google Scholar]
- 5. Tomczyk S, Lynfield R, Schaffner W, et al. Prevention of antibiotic-nonsusceptible invasive pneumococcal disease with the 13-valent pneumococcal conjugate vaccine. Clin Infect Dis 2016; 62:1119–25. [DOI] [PubMed] [Google Scholar]
- 6. Gaviria-Agudelo CL, Jordan-Villegas A, Garcia C, McCracken GH Jr. The effect of 13-valent pneumococcal conjugate vaccine on the serotype distribution and antibiotic resistance profiles in children with invasive pneumococcal disease. J Pediatric Infect Dis Soc 2017; 6:253–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Andrejko K, Ratnasiri B, Hausdorff WP, Laxminarayan R, Lewnard JA. Antimicrobial resistance in paediatric Streptococcus pneumoniae isolates amid global implementation of pneumococcal conjugate vaccines: a systematic review and meta-regression analysis. Lancet Microbe 2021; 2:e450–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Buchy P, Ascioglu S, Buisson Y, et al. Impact of vaccines on antimicrobial resistance. Int J Infect Dis 2020; 90:188–96. [DOI] [PubMed] [Google Scholar]
- 9. Klugman KP, Black S. Impact of existing vaccines in reducing antibiotic resistance: primary and secondary effects. Proc Natl Acad Sci U S A 2018; 115:12896–901. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Lo SW, Gladstone RA, van Tonder AJ, et al. Pneumococcal lineages associated with serotype replacement and antibiotic resistance in childhood invasive pneumococcal disease in the post-PCV13 era: an international whole-genome sequencing study. Lancet Infect Dis 2019; 19:759–69. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Kaur R, Pham M, Yu KOA, Pichichero ME. Rising pneumococcal antibiotic resistance in the post-13-valent pneumococcal conjugate vaccine era in pediatric isolates from a primary care setting. Clin Infect Dis 2021; 72:797–805. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Centers for Disease Control and Prevention . Antibiotic resistance threats in the United States, 2019. Available at:www.cdc.gov/DrugResistance/Biggest-Threats.html. Accessed 21 June 2022.
- 13. Antimicrobial Resistance Collaborators . Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 2022; 399:629–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Kline JM, Wietholder JP, Kline VT. Pediatric antibiotic use: a focused review of fluoroquinolones and tetracyclines. US Pharmacist 2012; 37:56–9. [Google Scholar]
- 15. Brossette SE, Hacek DM, Gavin PJ, et al. A laboratory-based, hospital-wide, electronic marker for nosocomial infection: the future of infection control surveillance? Am J Clin Pathol 2006; 125:34–9. [PubMed] [Google Scholar]
- 16. Gupta V, Yu KC, Schranz J, Gelone SP. A multicenter evaluation of the US prevalence and regional variation in macrolide-resistant S. pneumoniae in ambulatory and hospitalized adult patients in the United States. Open Forum Infect Dis 2021; 8:ofab063. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Mohanty S, Johnson KD, Yu KC, et al. A multicenter evaluation of trends in antimicrobial resistance among Streptococcus pneumoniae isolates from adults in the United States. Open Forum Infect Dis 2022; 9:ofac420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Suaya JA, Gessner BD, Fung S, et al. Acute otitis media, antimicrobial prescriptions, and medical expenses among children in the United States during 2011–2016. Vaccine 2018; 36:7479–86. [DOI] [PubMed] [Google Scholar]
- 19. Florin TA, Byczkowski T, Gerber JS, et al. Diagnostic testing and antibiotic use in young children with community-acquired pneumonia in the United States, 2008–2015. J Pediatric Infect Dis Soc 2020; 9:248–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Poole NM, Shapiro DJ, Kronman MP, Hersh AL. Ambulatory antibiotic prescribing for children with pneumonia after publication of national guidelines: a cross-sectional retrospective study. Infect Dis Ther 2020; 9:69–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Hicks LA, Chien YW, Taylor TH Jr, Haber M, Klugman KP; Active Bacterial Core Surveillance (ABCs) Team . Outpatient antibiotic prescribing and nonsusceptible Streptococcus pneumoniae in the United States, 1996–2003. Clin Infect Dis 2011; 53:631–9. [DOI] [PubMed] [Google Scholar]
- 22. Hart JD, Samikwa L, Meleke H, et al. Prevalence of nasopharyngeal Streptococcus pneumoniae carriage and resistance to macrolides in the setting of azithromycin mass drug administration: analysis from a cluster-randomised controlled trial in Malawi, 2015–17. Lancet Microbe 2022; 3:e142–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Simonsen L, Taylor RJ, Young-Xu Y, Haber M, May L, Klugman KP. Impact of pneumococcal conjugate vaccination of infants on pneumonia and influenza hospitalization and mortality in all age groups in the United States. mBio 2011; 2:e00309-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Centers for Disease Control and Prevention . Active Bacterial Core Surveillance (ABCs) report, Emerging Infections Program Network, Streptococcus pneumoniae, 2019. Available at: https://www.cdc.gov/abcs/downloads/SPN_Surveillance_Report_2019.pdf. Accessed 21 June 2022.
- 25. Hill HA, Yankey D, Elam-Evans LD, Singleton JA, Sterrett N. Vaccination coverage by age 24 months among children born in 2017 and 2018—National Immunization Survey–Child, United States, 2018–2020. MMWR Morb Mortal Wkly Rep 2021; 70:1435–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. US Food and Drug Administration . Vaxneuvance. Available at: https://www.fda.gov/vaccines-blood-biologics/vaccines/vaxneuvance. Accessed 17 September 2022.
- 27. US Food and Drug Administration . Prevnar 20. Available at: https://www.fda.gov/vaccines-blood-biologics/vaccines/prevnar-20. Accessed 17 September 2022.
- 28. Hu T, Weiss T, Owusu-Edusei K, Petigara T. Health and economic burden associated with 15-valent pneumococcal conjugate vaccine serotypes in children in the United States. J Med Econ 2020; 23:1653–60. [DOI] [PubMed] [Google Scholar]
- 29. Huang L, Wasserman M, Grant L, et al. Burden of pneumococcal disease due to serotypes covered by the 13-valent and new higher-valent pneumococcal conjugate vaccines in the United States. Vaccine 2022; 40:4700–8. [DOI] [PubMed] [Google Scholar]
- 30. Sevilla JP, Bloom DE, Cadarette D, Jit M, Lipsitch M. Toward economic evaluation of the value of vaccines and other health technologies in addressing AMR. Proc Natl Acad Sci U S A 2018; 115:12911–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. National Vaccine Advisory Committee . A call for greater consideration for the role of vaccines in national strategies to combat antibiotic-resistant bacteria: recommendations from the National Vaccine Advisory Committee. Public Health Rep 2016; 131:11–6. [PMC free article] [PubMed] [Google Scholar]
- 32. World Health Organization . Leveraging vaccines to reduce antibiotic use and prevent antimicrobial resistance. An action framework and annexe to immunization agenda 2030.2021. Available at: https://www.who.int/publications/m/item/leveraging-vaccines-to-reduce-antibiotic-use-and-prevent-antimicrobial-resistance. Accessed 17 September 2022.
- 33. Olesen SW, Barnett ML, MacFadden DR, et al. The distribution of antibiotic use and its association with antibiotic resistance. Elife 2018; 7:e39435. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Handy LK, Bryan M, Gerber JS, Zaoutis T, Feemster KA. Variability in antibiotic prescribing for community-acquired pneumonia. Pediatrics 2017; 139:e20162331. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Lipssett SC, Hall M, Ambroggio L, et al. Antibiotic choice and clinical outcomes in ambulatory children with community-acquired pneumonia. J Pediatr 2021; 229:207–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Griffith H, Wiese AD, Mitchel EF Jr, Grijalva CG. The impact of the 13-valent pneumococcal conjugate vaccine on otitis media-related antibiotic use among young children in Tennessee, USA. Open Forum Infect Dis 2022; 9:ofac019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Gerber JS, Jackson MA, Tama PD, et al. Policy statement: antibiotic stewardship in pediatrics. J Pediatric Infect Dis Soc 2021; 10:641–9. [DOI] [PubMed] [Google Scholar]
- 38. Centers for Disease Control and Prevention . Core elements of antibiotic stewardship.2021. Available at: https://www.cdc.gov/antibiotic-use/core-elements/index.html. Accessed 21 June 2022.
- 39. Musher DM. Macrolides as empiric therapy for outpatients with pneumonia. Open Forum Infect Dis 2021; 8:ofab062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Clinical and Laboratory Standards Institute (CLSI) . Performance standards for antimicrobial susceptibility testing. CLSI document M100. 31st ed. Wayne, PA: CLSI; 2021. [Google Scholar]
- 41. Sader HS, Carvalhaes CG, Streit JM, Shortridge D, Mendes RE, Castanheira M. Evaluation of the in vitro activity of ceftaroline and comparators against Streptococcus pneumoniae isolates from the United States: results from 10 years of the AWARE surveillance program (2011–2020). In: CHEST 2021, American College of Chest Physicians Virtual Meeting, 17–20 October 2021.
- 42. Humphries RM, Abbott AN, Hindler JA. Understanding and addressing CLSI breakpoint revisions: a primer for clinical laboratories. J Clin Microbiol 2019; 57:e00203-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Simner PJ, Rauch CA, Martin IW, et al. Raising the bar: improving antimicrobial resistance detection by clinical laboratories by ensuring use of current breakpoints. Open Forum Infect Dis 2022; 9:ofac007. [DOI] [PMC free article] [PubMed] [Google Scholar]
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