Comparative Effectiveness of Influenza Vaccines Among US ...

M A J O R A R T I C L E

Relative Influenza Vaccine Effectiveness • cid 2021:73 (1 december) • e4251

Clinical Infectious Diseases

Received 24 August 2020; editorial decision 3 November 2020; published online 19 November 2020.

Correspondence: H. S. Izurieta, CBER/FDA, 10903 New Hampshire Avenue, Silver Spring, MD 20993 ([email protected]).

Clinical Infectious Diseases® 2021;73(11):e4251–9Published by Oxford University Press for the Infectious Diseases Society of America 2020. This work is written by (a) US Government employee(s) and is in the public domain in the US.DOI: 10.1093/cid/ciaa1727

Comparative Effectiveness of Influenza Vaccines Among US Medicare Beneficiaries Ages 65 Years and Older During the 2019–2020 SeasonHector S. Izurieta,1 Michael Lu,2 Jeffrey Kelman,3 Yun Lu,1 Arnstein Lindaas,2 Julie Loc,2 Douglas Pratt,1 Yuqin Wei,2 Yoganand Chillarige,2 Michael Wernecke,2 Thomas E. MaCurdy,2,4 and Richard Forshee1

1Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA, 2Acumen LLC, Burlingame, California, USA, 3Centers for Medicare and Medicaid Services, Washington, DC, USA, and 4Stanford University Department of Economics, Stanford, California, USA

(See the Major Article by Tenforde et al on pages e4244–50.)

Background. Approximately 50 000 influenza-associated deaths occur annually in the United States, overwhelmingly among individuals aged ≥65 years. Although vaccination is the primary prevention tool, investigations have shown low vaccine effectiveness (VE) in recent years, particularly among the elderly. We analyzed the relative VE (RVE) of all influenza vaccines among Medicare beneficiaries aged ≥65 years to prevent influenza hospital encounters during the 2019–2020 season.

Methods. Retrospective cohort study using Poisson regression and inverse probability of treatment weighting (IPTW). Exposures included egg-based high-dose trivalent (HD-IIV3), egg-based adjuvanted trivalent (aIIV3), egg-based standard dose (SD) quadriva-lent (IIV4), cell-based SD quadrivalent (cIIV4), and recombinant quadrivalent (RIV4) influenza vaccines.

Results. We studied 12.7 million vaccinated beneficiaries. Following IPTW, cohorts were well balanced for all covariates and health-seeking behavior indicators. In the adjusted analysis, RIV4 (RVE, 13.3%; 95% CI, 7.4–18.9%), aIIV3 (RVE, 8.2%; 95% CI, 4.2–12.0%), and HD-IIV3 (RVE, 6.8%; 95% CI, 3.3–10.1%) were significantly more effective in preventing hospital encounters than the reference egg-based SD IIV4, while cIIV4 was not significantly more effective than IIV4 (RVE, 2.8%; 95% CI, −2.8%, 8.2%). Our results were consistent across all analyses.

Conclusions. In this influenza B-Victoria and A(H1N1)–dominated season, RIV4 was moderately more effective than other vaccines, while HD-IIV3 and aIIV3 were more effective than the IIV4 vaccines, highlighting the contributions of antigen amount and adjuvant use to VE. Egg adaptation likely did not substantially affect our RVE evaluation. Our findings, specific to the 2019–2020 season, should be evaluated in other studies using virological case confirmation.

Keywords. influenza vaccine; relative vaccine effectiveness (RVE); vaccine effectiveness (VE); influenza hospitalization; real-world evidence.

Every year, influenza causes 140 000–810 000 hospitalizations and 12 000–61 000 deaths in the United States, mostly among the elderly [1]. Although vaccination is the primary prevention tool, recent studies have shown low vaccine effectiveness (VE) [2–11]. A better understanding of the effectiveness of each vac-cine type used among the elderly could help improve the level of protection for this high-risk group against influenza. However, most studies evaluating influenza VE among the elderly either had limited power or comparisons were possible for only a few vaccines [2, 7, 8, 10, 12, 13].

The 2019–2020 influenza season began early, initially with predominant influenza B/Victoria virus circulation (the B/Victoria vaccine component was antigenically similar to circu-lating viruses), followed by A(H1N1)pdm09 virus circulation, which dominated the season since January 2020 [14]. An interim Centers for Disease Control and Prevention (CDC) multicenter analysis of 4112 individuals ages 6 months and older showed an overall VE against medically attended influenza of 45% (95% confidence interval [CI], 36–53%). Vaccine effectiveness was 50% (95% CI, 39–59%) against influenza B/Victoria viruses and 37% (95% CI, 19–52%) against influenza A(H1N1)pdm09 [8].

During the 2019–2020 season, several influenza vac-cine types were available for individuals ages 65 years and older [15]. Two were not manufactured in eggs: a recombi-nant quadrivalent hemagglutinin (HA)-only vaccine pro-duced in insect cells [16], containing 45 μg of HA per strain (RIV4), and a standard-dose (SD) cell-cultured quadrivalent vaccine produced in mammalian cells, containing 15 μg of HA per strain (cIIV4) [15]. All others were egg-based and

Dow

nloaded from https://academ

ic.oup.com/cid/article/73/11/e4251/5992287 by guest on 10 January 2022

mailto:[email protected]?subject=

e4252 • cid 2021:73 (1 december) • Izurieta et al

contained both HA and neuraminidase (NA): a high-dose (HD) trivalent vaccine containing 60 μg of HA for each strain (HD-IIV3) [17], an adjuvanted SD trivalent vaccine (aIIV3) [18], and 3 SD quadrivalent vaccines (IIV4) [15]. Except for RIV4, all other vaccines contained both HA and NA. Also, all vaccines contained antigens from subtypes A(H1N1) and A(H3N2) and a single type B (Victoria lineage) strain, while the quadrivalent vaccines also contained antigens for an ad-ditional type B (Yamagata lineage) strain [15].

Our objective was to use real-world data (RWD) from Medicare claims to analyze the relative VE (RVE) of US-licensed influenza vaccines in preventing hospital encoun-ters among beneficiaries ages 65 years and older during the 2019–2020 season.

METHODS

Study Period and Data Sources

We used Medicare fee-for-service (FFS) data for the 2019–2020 season to analyze the RVE of all influenza vaccines used among beneficiaries ages 65 years and older during 4 August 2019–29 February 2020. We cut off our observation period end date at the end of February to avoid potential bias from the overlap be-tween the influenza season and the escalation of the coronavirus disease 2019 (COVID-19) pandemic in the United States [19]. We used Medicare claims and enrollment data for beneficiaries with part A (inpatient services) and part B (outpatient medical care) coverage to define inclusion criteria, exposures, covariates, and outcomes. Medicare part D claims data were used to define influenza intensity using antiviral prescription counts by county. We also used National Respiratory Enteric Virus Surveillance System (NREVSS) data to monitor influenza activity intensity, the National Plan and Provider Enumeration System (NPPES) and the National Council for Prescription Drug Programs (NCPDP) databases to identify whether beneficiaries received their vaccination at a pharmacy, and the Minimum Data Set to identify whether beneficiaries were residing in nursing homes.

Study Population

To ensure full capture of covariates, we included beneficiaries ages 65 years and older continuously enrolled in Medicare parts A/B without enrollment in part C in the 6 months prior to vaccination who received an influenza vaccine during 4 August 2019–31 January 2020. We identified vaccination admin-istrations using Healthcare Common Procedure Coding System (HCPCS) codes (Supplementary Table 1). We further restricted our population to beneficiaries who had aged into Medicare and had not received any other influenza vaccine between the start of the season and their cohort vaccination date. Beneficiaries not res-iding in a region defined in the Department of Health and Human Services regions and those residing in a nursing home and/or hos-pice facility on vaccination date were excluded.

Variables

We used demographics, region of residence, month of vaccina-tion, chronic health conditions, frailty, prior medical encoun-ters, and preventive service usage as covariates (Supplementary Tables 2 and 3). All covariates were adjusted for in all analyses.

As a supplementary analysis, we assessed cohort balance using 7 variables we hypothesized could be associated with health-seeking behavior, including lipomas, eyelid disorders, cataract, hemorrhoids, ingrown nail, wound of hand or finger, and urinary tract infection [20–25]. We restricted these vari-ables to medical office/outpatient setting encounters. In an attempt to further assess cohort balance with respect to phys-ical and mental health, education, and behavior, we evaluated covariate balance for the Medicare Current Beneficiaries Survey (MCBS) linkable population using representative survey ques-tion responses (Supplementary Table 4) [21].

Outcomes

The primary outcome was influenza hospital encounters, which included inpatient hospitalizations and emergency department visits listing an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), code for influ-enza (J09.xx, J10.xx, J11.xx, J129) [26–28]. We restricted the secondary outcome to influenza inpatient hospitalizations only [26].

Person-Time Under Observation

Follow-up began on the 15th day after vaccination date and con-tinued until one of the following occurred (censoring criteria): an outcome, disenrollment from Medicare part B/enrollment in Medicare part C, end of the study period, death, admission into a nursing home and/or hospice care facility, or administration of a subsequent influenza vaccination in the study period. To ensure the accuracy of outcomes identified, we only included person-time observed in regions and weeks with high intensity of influenza circulation. For the primary analysis, we based our influenza circulation intensity on data from CDC’s NREVSS. Throughout the season, we classified region-weeks with 15% or more positive respiratory samples, provided there were at least 2 contiguous weeks with 15% or more positive samples, as high-intensity circulation periods.

For a secondary analysis, we based influenza circulation on an approach in which we used Medicare antiviral prescription rates by county [27, 29, 30]. We classified each calendar week in the study period in each county into high- or low-intensity influenza periods, based on the rates of antiviral treatment pre-scriptions per 10 000 beneficiaries in the county-week. Spatial smoothing was implemented to account for variance in pre-scription rates, particularly among smaller counties [27, 29, 30]. We classified county-weeks with a spatially smoothed antiviral prescription rate of 5 or more prescriptions per 10 000 Medicare beneficiaries as high-season weeks. We found this gave us a

Dow



http://academic.oup.com/cid/article-lookup/doi/10.1093/cid/ciaa1727#supplementary-data





similar percentage of county-weeks classified as high season as the primary analysis seasonality definition. All other county-weeks were classified as low season. For this influenza-intensity definition we used the following antivirals: oral oseltamivir phosphate (Tamiflu, Hoffmann-La Roche), inhaled zanamivir (Relenza, GlaxoSmithKline), intravenous peramivir (Rapivab, BioCryst Pharmaceuticals), and oral baloxavir marboxil (Xofluza, Genentech). Further details on the selection of anti-viral rates and the use of antivirals spatial-smoothing specifica-tions are outlined in the Supplementary Protocol.

Statistical Analysis

We provided descriptive statistics and estimated adjusted RVEs for all vaccine cohorts. We first performed a power analysis (Supplementary Figures 1 and 2), which indicated that all co-hort comparisons were sufficiently powered. Three different primary analysis comparisons were conducted: a 5-vaccine RVE comparison estimated across all vaccine types adminis-tered in the 2019–2020 season and 2 separate 2-vaccine ana-lyses, for which we compared cIIV4 with IIV4 and RIV4 with IIV4. In a post hoc analysis, we also compared RIV4 with cIIV4. We implemented stabilized inverse probability of treatment weighting (IPTW) to adjust for imbalances between cohorts in these analyses. IPTW weights were derived from propensity scores representing each beneficiary’s probability of receiving a particular vaccine (Supplementary Protocol). Propensity scores were estimated using multinomial and binomial logistic regres-sion models for the 5-vaccine and 2-vaccine comparisons, re-spectively. Weights greater than 10 were truncated to 10 in the primary and secondary analyses. We assessed cohort balance for covariates using Austin’s standardized mean difference be-fore and after weighting, with a value of 0.1 or less indicating a negligible difference in proportions between groups [31].

We estimated adjusted rate ratios (RRs) for the vaccine com-parisons in the weighted cohorts using a univariate Poisson re-gression model, and defined adjusted RVEs as (1−RR) × 100 (Supplementary Protocol) [26]. In addition, we performed the following sensitivity analyses: (1) a nontruncated weights anal-ysis, (2) a doubly robust analysis in which covariate terms were included in both the propensity score and outcome models, and (3) an analysis with the pharmacy vaccination status adjusted for as a term in the outcome model but not the propensity score model (Supplementary Protocol). We also provided unadjusted outcome rates for all 5 cohorts.

RESULTS

Over 16.5 million Medicare FFS beneficiaries received an in-fluenza vaccination between 4 August 2019 and 31 January 2020, with 12.7 million remaining eligible after implementing population restrictions. Among eligible beneficiaries, 7 177 250 (56.2%), 2 564 628 (20.1%), 1 573 548 (12.3%), 813 838 (6.4%),

and 638 905 (5.0%) received HD-IIV3, aIIV3, IIV4, cIIV4, and RIV4, respectively (Table 1).

In the 5-vaccine comparison, most covariates had some im-balances prior to implementing IPTW (Supplementary Table 3). After weighting, all covariates except month of vaccina-tion were balanced with maximum standardized mean differ-ences (SMDs) of 0.1 or less (Table 1, Supplementary Table 2). For the 2-vaccine comparison analyses, all covariates were bal-anced after weighting with SMDs of 0.02 or less (Supplementary Table 5).

The crude outcome rates analysis showed that RIV4 had the lowest outcome rates among all study cohorts, fol-lowed by HD-IIV3 and aIIV3 (Table 2). The RVE estimates from the IPTW-adjusted 5-vaccine comparison indicated that RIV4 (RVE, 13.3%; 95% CI, 7.4–18.9%), aIIV3 (RVE, 8.2%; 95% CI, 4.2–12.0%), and HD-IIV3 (RVE, 6.8%; 95% CI, 3.3–10.1%) were all significantly more effective against hospital encounters than the IIV4 vaccines (Figure 1, Table 3). For the influenza hospital encounters outcome, RIV4 was significantly more effective than all other vac-cines except for aIIV3, and aIIV3 was significantly more effective than cIIV4 (Figure 1, Table 3). There were no sig-nificant differences between HD-IIV3 and aIIV3 (RVE, −1.6%; 95% CI, −4.8%, 1.6%) or between cIIV4 and IIV4 (RVE, 2.8; 95% CI, −2.8%, 8.2%). The RVE estimates for the influenza inpatient-stay outcome were generally con-sistent with those of the hospital encounters outcome, al-though RIV4 was significantly more effective than aIIV3 (Figure 1, Table 3). The IPTW-adjusted results for the 2-vaccine comparisons also did not show that cIIV4 was significantly more effective than IIV4 for either hospital encounters (RVE, 2.5%; 95% CI, −2.8%, 7.6%) or inpatient stays (RVE, 1.3%; 95% CI, −5.7%, 7.9%). However, RIV4 was significantly more effective than IIV4 (RVE, 12.3%; 95% CI, 6.7–17.6%) and cIIV4 (RVE, 9.1%; 95% CI, 2.5–15.2%) (Figure 1, Supplementary Tables 6 and 7).

Results from the secondary analysis, in which antiviral uptake was used to define high-circulation periods at the county-week level, were largely consistent with those of the primary anal-ysis (Table 3; Supplementary Tables 6, 8, and 9; Supplementary Figure 3). Results from all sensitivity analyses were also con-sistent with the primary analysis (Supplementary Tables 6, 8, and 9).

Our assessment of cohort balance using potential health-seeking behavior indicators showed that, both prior to and fol-lowing IPTW, all cohorts were well balanced for all 7 indicators, with post-IPTW SMDs of 0.1 or less (Table 4, Supplementary Figures 3–7, Supplementary Table 10). In the cohort balance evaluation using the MCBS linkable population, we found that the SMDs for MCBS variables still showed some residual differ-ences despite an improvement in MCBS variable balance after IPTW (Supplementary Figures 8–20).

Dow


















Table 1. Distribution of Main Covariates Across Vaccine Cohorts for the 2019–20 Influenza Season After Implementing IPTW Weights: 5-Vaccine Comparison

Covariate

Cohort

HD-IIV3 aIIV3 IIV4 cIIV4 RIV4 Pre-IPTW Max SMD Post-IPTW Max SMD

Base population, n 7 173 433 2 565 513 1 584 451 824 264 608 433

Vaccinated at pharmacy

Yes 45.6% 45.6% 46.2% 46.7% 42.8% 1.06 0.08

Age brackets

65–74 years 50.1% 50.2% 50.4% 51.1% 50.5% 0.09 0.02

75–84 years 35.4% 35.2% 34.8% 34.5% 34.7% 0.04 0.02

≥85 years 14.6% 14.6% 14.8% 14.5% 14.7% 0.10 0.01

Gender

Female 58.2% 58.3% 58.9% 58.9% 58.6% 0.03 0.01

Male 41.8% 41.7% 41.1% 41.1% 41.4% 0.03 0.01

Race

White 88.6% 88.6% 89.2% 88.9% 88.8% 0.17 0.02

Black 4.3% 4.2% 4.0% 4.1% 4.4% 0.11 0.02

Asian 2.0% 1.9% 1.9% 1.9% 1.9% 0.14 0.01

Hispanic 0.8% 0.8% 0.8% 0.7% 0.8% 0.08 0.01

Other 4.3% 4.5% 4.1% 4.4% 4.2% 0.06 0.02

Dual eligible

Yes 6.0% 5.8% 5.7% 5.6% 6.1% 0.24 0.02

All hospitalizations and observational stay

At least 1 8.7% 8.6% 8.3% 8.7% 8.9% 0.12 0.02

Outpatient ER visits

At least 1 13.8% 13.8% 13.6% 14.0% 14.2% 0.08 0.02

E/M general medical visit Non-overlapping with IP and OP-ER

0 6.9% 7.1% 7.3% 6.8% 6.8% 0.06 0.02

[1–5] 60.3% 60.4% 60.6% 61.2% 60.7% 0.11 0.02

[6–10] 24.3% 24.1% 23.8% 23.8% 24.1% 0.07 0.01

≥11 8.6% 8.4% 8.3% 8.2% 8.4% 0.10 0.01

Respiratory failure and pneumonia

Hospitalizations 1.6% 1.5% 1.5% 1.6% 1.6% 0.08 0.01

ER outpatient visits 0.4% 0.4% 0.3% 0.4% 0.4% 0.03 0.01

Non-ER outpatient visits 0.9% 0.9% 0.8% 0.9% 0.9% 0.04 0.01

Physician office visits 3.7% 3.7% 3.6% 3.7% 3.8% 0.07 0.01

Health conditions

Asthma 6.0% 6.0% 5.9% 6.0% 6.1% 0.03 0.01

Blood disorders 20.8% 20.4% 20.3% 20.1% 20.5% 0.17 0.02

Chronic lung disease 13.8% 13.7% 13.3% 13.3% 14.0% 0.10 0.02

Diabetes 25.7% 25.5% 24.8% 24.5% 26.1% 0.16 0.04

Heart disease 39.0% 38.7% 38.4% 38.0% 39.0% 0.13 0.02

Kidney disorders 20.3% 20.0% 20.0% 20.0% 20.5% 0.11 0.01

Liver disorders 3.6% 3.5% 3.5% 3.5% 3.5% 0.04 0.01

Neurological or neurodevelopmental conditions 12.3% 12.2% 12.1% 12.0% 12.3% 0.08 0.01

Malignant neoplasms 11.5% 11.4% 11.3% 11.4% 11.3% 0.02 0.01

Immunocompromising conditions 5.1% 5.0% 5.0% 5.2% 5.0% 0.02 0.01

Frailty score

0–0.2 80.3% 80.3% 80.3% 80.6% 80.2% 0.18 0.01

0.2–0.4 14.8% 14.7% 14.6% 14.4% 14.8% 0.11 0.01

0.4–1 4.9% 5.0% 5.0% 4.9% 5.0% 0.15 0.01

Other risk covariates

Any other risk condition 3.4% 3.4% 3.3% 3.3% 3.2% 0.10 0.01

Non-vaccination wellness visits

Annual wellness visits 25.1% 24.8% 25.3% 24.9% 25.0% 0.05 0.01

Counseling and health risk assessment 5.2% 5.0% 5.0% 5.2% 5.2% 0.04 0.01

Preventive vaccinations

Pneumococcal vaccination 11.4% 11.4% 11.2% 11.9% 12.0% 0.12 0.02

Tetanus-containing vaccination 3.4% 3.3% 3.4% 3.6% 3.4% 0.05 0.01

Shingrix, GlaxoSmithKline 7.8% 7.8% 8.3% 8.3% 7.3% 0.20 0.04

SMD values of ≥0.1 indicate that the groups are imbalanced on the specified covariates. Five-vaccine comparison refers to the comparison between the cIIV4, RIV4, HD-IIV3, aIIV3, and IIV4 cohorts, with IPTW weights truncated at 10. Post-IPTW distributions for the full list of covariates can be found in Supplementary Table 2. Abbreviations: aIIV3, egg-based adjuvanted triva-lent; cIIV4, cell-cultured standard-dose quadrivalent; ER, emergency room; HD-IIV3, egg-based high-dose trivalent; IIV4, egg-based standard dose quadrivalent; IP, inpatient; IPTW, inverse probability of treatment weighted; Max, maximum; OP-ER, outpatient emergency room; RIV4, recombinant HA-only quadrivalent; SMD, standardized mean difference.

Dow





DISCUSSION

This is the first study to compare the effectiveness of all 5 in-fluenza vaccine types administered to Medicare beneficiaries ages 65 years and older. RIV4, included here, had not been used in sufficient numbers in previous years to permit us to perform meaningful comparisons [20, 26]. Our results show that, among almost 13 million vaccinees, RIV4 was significantly more ef-fective in preventing influenza hospital encounters than other vaccine types except for the aIIV3 vaccine. RIV4 was also sig-nificantly more effective than all other vaccine types, including aIIV3, in the inpatient-stays outcome analysis (Table 3, Figure 1, Supplementary Figure 3, Supplementary Tables 6–9). The aIIV3 and HD-IIV3 vaccines, which did not have significant VE dif-ferences between them, were significantly more effective than the comparator IIV4 for both outcomes. On the other hand, there were no significant differences in VE between cIIV4 and IIV4. To contextualize our RVE estimates, we have provided estimates of the number needed to vaccinate for each vaccine relative to IIV4 to prevent 1 flu outcome event (Supplementary Table 11).

The 2019–2020 season was initially dominated by influenza B/Victoria followed by influenza A(H1N1)pdm09 viruses, with no significant circulation of influenza A(H3N2) [14]. The influ-enza A(H3N2) virus, which is a major contributor to influenza hospitalization and mortality among the elderly, is relatively more prone to egg adaptation, as demonstrated by studies on the 2012–2013 season vaccine antigenicity [6, 32]. For the 2017–2018 season, which was dominated by A(H3N2) viruses, we and others found a moderately higher effectiveness for the cIIV4 compared with IIV4 [26, 33].

However, the A(H3N2) virus did not circulate significantly in the 2019–2020 season. In addition, the B-Yamagata lineage viruses, which are absent in trivalent vaccines, did not circulate widely either. An H1N1 strain with change at amino acid 156 did emerge, but this occurred late in the season and likely did

not substantially affect VE against influenza A(H1N1)pdm09 viruses in the United States during our study period [34]. These factors provided us with an opportunity to better analyze some potential contributors to RVE, such as antigen amount and adjuvant use.

Of the 2 vaccines not cultured in eggs (cIIV4 and RIV4), only RIV4 showed higher effectiveness in comparison to IIV4. A number of factors could have contributed to this finding: the higher HA amount in RIV4 (45 μg of HA per antigen vs 15 μg in SD vaccines), the direct sequencing of the RIV4 HA using the published genome of the World Health Organization– recommended wild strains [35], and potentially other factors. The higher HA content of the HD-IIV3 (60 μg per antigen) [17] could help explain its higher RVE, and the use of the adjuvant (MF59) [18] may have contributed to the higher RVE of aIIV3, which contains the same HA amount as IIV4 and cIIV4 (15 μg). Because the Food and Drug Administration does not require the NA amount determination for vaccine lot release, the es-timation of the NA’s contribution to VE is difficult to estimate [36, 37]. However, NA plays no role in the protection afforded by RIV4, which contains only HA.

The higher RVE we observed for RIV4 is compatible with the limited data available on the relative efficacy of RIV4. A study of 8604 participants ages 50 years and older (mean age, 62.5 years) randomized during the 2014–2015 season (dom-inated by influenza A[H3N2] viruses antigenically dissimilar to the vaccine antigens) to receive RIV4 or an IIV4 compar-ator found a 30% (95% CI, 10–47%) RVE against virologically confirmed influenza. However, both RIV4 and IIV4 performed similarly against B viruses, which represented close to 20% of the strains identified [16]. The RVE of HD-IIV3 compared with SD inactivated vaccines has been previously investigated by our team, using real-world evidence, and by others. Consistent with our 2019–2020 findings, these studies found higher RVE for the HD-IIV3 vaccine for most seasons [26–28, 38]. The

Table 2. Unadjusted Outcome Rates During the High Influenza Periods for the 5 Vaccine Cohorts, 2019–2020 Season

Outcome Type and Cohort No. of Outcomes Total Person-Timea Outcome Rate (95% CI)

Flu hospital encounters

IIV4 3956 1832 2.16 (2.09, 2.23)

cIIV4 2092 965 2.17 (2.08, 2.26)

aIIV3 4991 3017 1.65 (1.61, 1.70)

HD-IIV3 14 612 8429 1.73 (1.71, 1.76)

RIV4 1179 770 1.53 (1.44, 1.62)

Flu inpatient stays

IIV4 2309 1833 1.26 (1.21, 1.31)

cIIV4 1255 965 1.30 (1.23, 1.37)

aIIV3 2783 3018 0.92 (.89, .96)

HD-IIV3 8192 8433 0.97 (.95, .99)

RIV4 640 770 0.83 (.77, .90)

Abbreviations: aIIV3, egg-based adjuvanted trivalent; CI, confidence interval; cIIV4, cell-cultured standard-dose quadrivalent; HD-IIV3, egg-based high-dose trivalent; IIV4, egg-based standard-dose quadrivalent; RIV4, recombinant HA-only quadrivalent; RVE, relative vaccine effectiveness.aPerson-time is in 10 000 person-weeks.

Dow







Figure 1. IPTW adjusted RVE estimates for primary outcome analyses. The 2019–2020 season RVE point estimates and 95% confidence intervals for the cIIV4 vs IIV4, RIV4 vs IIV4, and RIV4 vs cIIV4 2-vaccine comparisons and the 5-vaccine comparison are presented for both study outcomes. Notes: The 5-vaccine comparison refers to the comparison between the cIIV4, RIV4, HD-IIV3, aIIV3, and IIV4 cohorts, with IPTW weights truncated at 10. The RIV4 vs cIIV4 2-vaccine comparison was conducted as part of a post hoc analysis. Abbreviations: aIIV3, egg-based adjuvanted trivalent; cIIV4, cell-cultured standard-dose quadrivalent; HD-IIV3, egg-based high-dose trivalent; IIV4, egg-based standard-dose quadrivalent; IPTW, inverse probability of treatment weighted; RIV4, recombinant HA-only quadrivalent; RVE, relative vaccine effectiveness.

Dow




effectiveness data on aIIV3 among the elderly are not as ex-tensive. However, some observational studies, including ours, have found higher RVE for aIIV3 compared with SD inacti-vated vaccines [26, 39].

The very large sample size of this study allowed us to per-form analyses for serious and rare outcomes such as hospi-talizations that are typically not evaluated in randomized trials due to the low frequency of such events. Our study

Table 3. Inverse Probability of Treatment Weighted Adjusted Pairwise RVE Estimates for the 2019–2020 Season: 5-Vaccine Cohort Comparison

Outcome Type and Cohort

Reference Group

IIV4 aIIV3 HD-IIV3 RIV4

RVE (%)a 95% CI RVE (%) 95% CI RVE (%) 95% CI RVE (%) 95% CI

Primary analysis resultsb


cIIV4 2.8 (−2.8, 8.2) −5.8* (−11.7, −.3)* −4.2 (−9.4, .8) −12.1* (−20.6, −4.2)*

RIV4 13.3* (7.4, 18.9)* 5.6 (−.6, 11.4) 7.0* (1.4, 12.4)* … …

HD-IIV3 6.8* (3.3, 10.1)* −1.6 (−4.8, 1.6) … … … …

aIIV3 8.2* (4.2, 12.0)* … … … … … …

Flu inpatient stays

cIIV4 3.7 (−3.9, 10.7) −3.4 (−11.0, 3.8) −3.5 (−9.4, .8) −15.7* (−27.7, −4.8)*

RIV4 16.8* (9.0, 23.8)* 10.7* (2.7, 17.9)* 10.6* (3.1, 17.4)* … …

HD-IIV3 6.9* (2.3, 11.4)* 0.1 (−4.1, 4.2) … … … …

aIIV3 6.8* (1.4, 11.9)* … … … … … …

Secondary analysis resultsc


cIIV4 2.0 (−3.9, 7.6) −9.0* (−15.2, −3.2)* −6.2 (−11.6, 1.0) −11.4* (−20.1, −3.4)*

RIV4 12.0* (5.9, 17.8)* 2.2 (−4.4, 8.3) 4.7 (−1.3, 10.3) … …

HD-IIV3 7.7* (4.1, 11.1)* −2.6 (−6.0, .6) … … … …

aIIV3 10.1* (6.0, 14.0)* … … … … … …

Flu inpatient stays

cIIV4 2.6 (−5.2, 9.9) −5.6 (−13.6, 1.8) −4.7 (−12.0, 2.1) −15.4* (−27.7, −4.3)*

RIV4 15.7* (7.6, 23.0)* 8.5* (.2, 16.2)* 9.3* (1.5, 16.5)* … …

HD-IIV3 7.0* (2.2, 11.6)* -0.9 (−5.3, 3.3) … … … …

aIIV3 7.8* (2.3, 13.0)* … … … … … …

*Statistically significant. Abbreviations: aIIV3, egg-based adjuvanted trivalent; CI, confidence interval; cIIV4, cell-cultured standard-dose quadrivalent; HD-IIV3, egg-based high-dose trivalent; IIV4, egg-based standard-dose quadrivalent; RIV4, recombinant HA-only quadrivalent; RVE, relative vaccine effectiveness.aAll pairwise comparison RVE estimates that are significant at the P < .05 level are indicated by an asterisk (*), along with the corresponding 95% confidence intervals.bPrimary analysis: Region-weeks with ≥15% positive respiratory samples (provided there are at least 2 contiguous weeks with ≥15% positive samples, in which case both weeks would be considered high-circulation weeks) will be classified as high-intensity periods, while all other weeks will be classified as low-intensity periods.cSecondary analysis: Influenza circulation will be based on Medicare antiviral prescription rates by county. Each calendar week in the study period in each county will be classified into high- or low-intensity influenza periods based on the number of antiviral treatment prescriptions in the county-week, with spatial smoothing implemented. County-weeks with a spatially smoothed antiviral prescription rate of ≥5 prescriptions/10 000 Medicare beneficiaries will be classified as high-intensity, whereas all others will be classified as low-intensity.

Table 4. Distribution of Health-Seeking Behavior Indicators across 5 Vaccine Cohorts for the 2019–20 Influenza Season After Implementing IPTW Weights

Covariate

Cohort

HD-IIV3 aIIV3 IIV4 cIIV4 RIV4 Pre-IPTW Max SMD Post-IPTW Max SMD

Base population, n 7 173 433 2 565 513 1 584 451 824 264 608 433

Health-seeking behavior indicators

Cataracts 8.8% 8.8% 8.9% 8.7% 8.8% 0.04 0.01

Eyelid disorders 0.8% 0.8% 0.8% 0.8% 0.8% 0.02 0.01

Hemorrhoids 0.4% 0.4% 0.4% 0.4% 0.4% 0.01 0.00

Ingrown nail 1.1% 1.1% 1.1% 1.1% 1.0% 0.03 0.01

Lipomas 0.2% 0.2% 0.2% 0.2% 0.2% 0.01 0.00

UTI 4.4% 4.4% 4.4% 4.5% 4.5% 0.04 0.01

Wound of hand or finger 0.3% 0.2% 0.3% 0.3% 0.2% 0.00 0.00

“5-Vaccine” comparison refers to the comparison between the cIIV4, RIV4, HD-IIV3, aIIV3, and IIV4 cohorts, with IPTW weights truncated at 10. Medical office visit and OP non-ER claims with first-line diagnoses for the 7 health-seeking behavior indicators in the 183 days prior to vaccination date were included in the table. Abbreviations: aIIV3, egg-based adjuvanted trivalent; cIIV4, cell-cultured standard-dose quadrivalent; HD-IIV3, egg-based high-dose trivalent; IIV4, egg-based standard-dose quadrivalent; IPTW, inverse probability of treatment weighted; Max, maximum; RIV4, recombinant HA-only quadrivalent; SMD, standardized mean difference; UTI, urinary tract infection.

Dow




was limited by the lack of access to virological case con-firmation, which could have caused some nondifferential misclassification of the outcomes and might have led us to underestimate the magnitude of the differences. In addition, although the balance between study cohorts for all measured covariates was excellent, residual confounding by unmeas-ured covariates such as health-seeking behavior could have affected our results. To address these concerns, we studied only serious outcomes such as hospitalizations, which are less affected by outcome misclassification or health-seeking behavior bias [20, 21, 26]. Moreover, to further reduce risk of outcome misclassification, we restricted our study outcomes to hospital encounters or inpatient stays that occurred in high-influenza-circulation periods with an influenza-specific ICD code. These outcomes were used in prior studies, with results comparable to those from clinical trials [20, 26–28]. To avoid potential bias from overlaps between the influenza season and the escalation of the COVID-19 pandemic in the United States, we cut off our observation period end date at 29 February 2020 [19]. To determine whether unmeasured confounders could still have affected our results, we also evaluated the balance across all 5 study cohorts for 7 selected negative/falsification outcomes used by us and others in prior studies as potential indicators of health-seeking behavior [21, 23–25, 40]. We found excellent alignment of all 7 outcomes across all study cohorts, both before and after IPTW, with SMDs of 0.01 or less for all comparisons following IPTW (Table 4, Supplementary Table 10, Supplementary Figures 4–7). We suggest that these indicators be further explored in other studies to confirm or refute their usefulness.

Our findings suggest that, for individuals ages 65 years and older, influenza vaccines with higher HA amount or an adju-vant may have higher effectiveness. However, these findings are specific to the 2019–2020 season, characterized by an absence of significant influenza A(H3N2) virus circulation. Our results should not be generalized or extrapolated to other seasons or vaccine products. Moreover, our findings should be confirmed by investigations performed during multiple seasons dominated by different viruses, ideally using virological case confirmation.

The continuous analysis of the real-world evidence studies performed by us and others over multiple seasons should pro-vide timely and valuable information for influenza control and pandemic preparedness and help guide the future use of real-world evidence by manufacturers, regulators, and public health decision-makers to advance the development and evaluation of new and improved vaccines.

NotesAuthors’ contributions. H. S. I., J. K., Y. L., D. P., Y. C., and R. F. con-

tributed to the study conception and design, data interpretation, manu-script writing, and review. M. L., A. L., J. L., Y. W., Y. C., M. W., and T. E. M. contributed to the study design, data collection and analysis, manuscript writing, and review.

Acknowledgments. We acknowledge Carol Weiss and Maryna Eichelberger, Center for Biologics Evaluation and Research, Food and Drug Administration, for critical review and advise, and Chianti Shi, Acumen LLC, for contributions to statistical programming.

Financial support. This work was supported by the Food and Drug Administration (FDA) as part of the SafeRx Project, a joint initiative of the Centers for Medicare and Medicaid Services and FDA.

Potential conflicts of interest. The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

References1. Centers for Disease Control and Prevention. Disease burden of influenza.

Available at: https://www.cdc.gov/flu/about/burden/index.html. Accessed 28 June 2020.

2. Kissling E, Rose A, Emborg HD, et al. Interim 2018/19 influenza vaccine effec-tiveness: six European studies, October 2018 to January 2019. Euro Surveill 2019; 24. doi:10.2807/1560-7917.ES.2019.24.1900121

3. Monto AS. Moving toward improved influenza vaccines. J Infect Dis 2017; 215:500–2.

4. Paules CI, Sullivan SG, Subbarao K, Fauci AS. Chasing seasonal influenza—the need for a universal influenza vaccine. N Engl J Med 2018; 378:7–9.

5. Rolfes MA, Flannery B, Chung J, et al. Effects of influenza vaccination in the United States during the 2017–2018 influenza season. Clin Infect Dis 2019; 71:e368–76.

6. Skowronski DM, Janjua NZ, De Serres G, et al. Low 2012-13 influenza vaccine effectiveness associated with mutation in the egg-adapted H3N2 vaccine strain not antigenic drift in circulating viruses. PLoS One 2014; 9:e92153.

7. Tenforde MW, Chung J, Smith ER, et al. Influenza vaccine effectiveness in inpa-tient and outpatient settings in the United States, 2015-2018. Clin Infect Dis 2020. Available at: https://doi.org/10.1093/cid/ciaa407.

8. Dawood FS, Chung JR, Kim SS, et al. Interim estimates of 2019-20 seasonal influ-enza vaccine effectiveness—United States, February 2020. MMWR Morb Mortal Wkly Rep 2020; 69:177–82.

9. Flannery B, Fry AM. Comparing influenza vaccine types: the path toward im-proved influenza vaccine strategies. J Infect Dis 2019; 220:1237–9.

10. Flannery B, Garten Kondor RJ, Chung JR, et al. Spread of antigenically drifted influenza A(H3N2) viruses and vaccine effectiveness in the United States during the 2018–2019 season. J Infect Dis 2020; 221(1):8–15.

11. Grohskopf LA, Alyanak E, Broder KR, Walter EB, Fry AM, Jernigan DB. Prevention and control of seasonal influenza with vaccines: recommendations of the advisory committee on immunization practices—United States, 2019–20 in-fluenza season. MMWR Recomm Rep 2019; 68:1–21.

12. Skowronski DM, Leir S, Sabaiduc S, et al. Interim estimates of 2018/19 vaccine effectiveness against influenza A(H1N1)pdm09, Canada, January 2019. Euro Surveill 2019; 24. doi:10.2807/1560-7917.ES.2019.24.4.1900055

13. Doyle JD, Chung JR, Kim SS, et al. Interim estimates of 2018-19 seasonal influ-enza vaccine effectiveness—United States, February 2019. MMWR Morb Mortal Wkly Rep 2019; 68:135–9.

14. Centers for Disease Control and Prevention. Weekly U.S. influenza surveillance report. Available at: https://www.cdc.gov/flu/weekly/index.htm. Accessed 19 July 2020.

15. Centers for Disease Control and Prevention. Influenza vaccines—United States, 2019–20 influenza season. Available at: https://www.cdc.gov/flu/professionals/vaccines.htm. Accessed 18 July 2020.

16. Food and Drug Administration. Flublock package insert. Available at: https://www.fda.gov/media/123144/download. Accessed 20 July 2020.

17. Food and Drug Administration. Fluzone high dose package insert. Available at: https://www.fda.gov/media/119870/download. Accessed 20 July 2020.

18. Centers for Disease Control and Prevention. Flu vaccine with adjuvant. Available at: https://www.cdc.gov/flu/prevent/adjuvant.htm. Accessed 20 July 2020.

19. Jernigan DB; CDC COVID-19 Response team. Update: public health response to the coronavirus disease 2019 outbreak—United States, February 24, 2020. MMWR Morb Mortal Wkly Rep 2020; 69:216–9.

20. Izurieta HS, Chillarige Y, Kelman J, et al. Relative effectiveness of influenza vaccines among the United States elderly, 2018–2019. J Infect Dis 2020; 222:278–87.

21. Izurieta HS, Wu X, Lu Y, et al. Zostavax vaccine effectiveness among US eld-erly using real-world evidence: addressing unmeasured confounders by using multiple imputation after linking beneficiary surveys with Medicare claims. Pharmacoepidemiol Drug Saf 2019; 28:993–1001.

Dow





https://www.cdc.gov/flu/about/burden/index.html

https://doi.org/10.2807/10.2807/1560-7917.ES.2019.24.1900121

https://doi.org/10.1093/cid/ciaa407

https://doi.org/10.2807/1560-7917.ES.2019.24.4.1900055

https://www.cdc.gov/flu/weekly/index.htm

https://www.cdc.gov/flu/professionals/vaccines.htm

https://www.cdc.gov/flu/professionals/vaccines.htm

https://www.fda.gov/media/123144/download



https://www.cdc.gov/flu/prevent/adjuvant.htm


22. Tseng HF, Smith N, Harpaz R, Bialek SR, Sy LS, Jacobsen SJ. Herpes zoster vac-cine in older adults and the risk of subsequent herpes zoster disease. JAMA 2011; 305:160–6.

23. Tseng HF, Chi M, Smith N, Marcy SM, Sy LS, Jacobsen SJ. Herpes zoster vac-cine and the incidence of recurrent herpes zoster in an immunocompetent elderly population. J Infect Dis 2012; 206:190–6.

24. Young-Xu Y, Snider JT, van Aalst R, et al. Analysis of relative effectiveness of high-dose versus standard-dose influenza vaccines using an instrumental vari-able method. Vaccine 2019; 37:1484–90.

25. Bravo-Alcántara P, Pérez-Vilar S, Molina-León HF, et al; LANVAP (Latin American Network for VAccine Pharmacovigilance). Building capacity for active surveillance of vaccine adverse events in the Americas: a hospital-based multi-country network. Vaccine 2018; 36:363–70.

26. Izurieta HS, Chillarige Y, Kelman J, et al. Relative effectiveness of cell-cultured and egg-based influenza vaccines among the U.S. elderly, 2017–18. J Infect Dis 2018; 220:179.

27. Izurieta HS, Thadani N, Shay DK, et al. Comparative effectiveness of high-dose versus standard-dose influenza vaccines in US residents aged 65 years and older from 2012 to 2013 using Medicare data: a retrospective cohort analysis. Lancet Infect Dis 2015; 15:293–300.

28. Shay DK, Chillarige Y, Kelman J, et al. Comparative effectiveness of high-dose versus standard-dose influenza vaccines among US medicare beneficiaries in preventing postinfluenza deaths during 2012–2013 and 2013–2014. J Infect Dis 2017; 215:510–7.

29. Dahlgren FS, Shay DK, Izurieta HS, et al. Evaluating oseltamivir prescriptions in Centers for Medicare and Medicaid Services medical claims records as an indicator of seasonal influenza in the United States. Influenza Other Respir Viruses 2018; 12:465–74.

30. Dahlgren FS, Shay DK, Izurieta HS, et al. Patterns of seasonal influenza activity in U.S. core-based statistical areas, described using prescriptions of oseltamivir in Medicare claims data. Epidemics 2019; 26:23–31.

31. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 2009; 28:3083–107.

32. Belongia EA, McLean HQ. Influenza vaccine effectiveness: defining the H3N2 problem. Clin Infect Dis 2019; 69:1817–23.

33. Divino V, K G, Pelton SI, et al. A real-world study evaluating the relative vac-cine effectiveness of a cell-based quadrivalent influenza vaccine compared to egg-based quadrivalent influenza vaccine in the US during the 2017–18 influenza season. Vaccine. In press.

34. World Health Organization. Recommended composition of influenza virus vac-cines for use in the 2021 Southern Hemisphere influenza season. Available at: https://www.who.int/influenza/vaccines/virus/recommendations/202009_rec-ommendation.pdf?ua=1. Accessed 24 October 2020.

35. World Health Organization. Candidate vaccine viruses and potency testing reagents for development and production of vaccines for use in the northern hemisphere 2019–2020 influenza season. Available at: https://www.who.int/influenza/vaccines/virus/candidates_reagents/2019_20_north/en/. Accessed 28 July 2020.

36. Weiss CD, Wang W, Lu Y, et al. Neutralizing and neuraminidase antibodies cor-relate with protection against influenza during a late season A/H3N2 outbreak among unvaccinated military recruits. Clin Infect Dis 2019. doi:10.1093/cid/ciz1198

37. Eichelberger MC, Monto AS. Neuraminidase, the forgotten surface antigen, emerges as an influenza vaccine target for broadened protection. J Infect Dis 2019; 219:75–80.

38. Lu Y, Chillarige Y, Izurieta HS, et al. Effect of age on relative effectiveness of high-dose versus standard-dose influenza vaccines among US Medicare beneficiaries aged ≥65 years. J Infect Dis 2019; 220:1511–20.

39. Van Buynder PG, Konrad S, Van Buynder JL, et al. The comparative effectiveness of adjuvanted and unadjuvanted trivalent inactivated influenza vaccine (TIV) in the elderly. Vaccine 2013; 31:6122–8.

40. Izurieta HS, Wernecke M, Kelman J, et al. Effectiveness and duration of protec-tion provided by the live-attenuated herpes zoster vaccine in the medicare popu-lation ages 65 years and older. Clin Infect Dis 2017; 64:785–93.

Dow



https://www.who.int/influenza/vaccines/virus/recommendations/202009_recommendation.pdf?ua=1

https://www.who.int/influenza/vaccines/virus/recommendations/202009_recommendation.pdf?ua=1

https://www.who.int/influenza/vaccines/virus/candidates_reagents/2019_20_north/en/

https://www.who.int/influenza/vaccines/virus/candidates_reagents/2019_20_north/en/

https://doi.org/10.1093/cid/ciz1198

https://doi.org/10.1093/cid/ciz1198

Comparative Effectiveness of Influenza Vaccines Among US ...

Documents

Transcript of Comparative Effectiveness of Influenza Vaccines Among US ...