Abstract
Background
Although the influenza vaccine is recommended for end-stage renal disease (ESRD) patients, little is known about its effectiveness. Observational studies of vaccine effectiveness (VE) are challenging because vaccinated persons may be healthier than unvaccinated persons.
Methods
Using United States Renal Data System data, we estimated VE for influenza-like illness (ILI), influenza/pneumonia hospitalization, and mortality in adult, hemodialysis patients using a natural experiment created by year-to-year variation in the match of the influenza vaccine to the circulating virus. Matched (1998, 1999, 2001) and unmatched (1997) years among vaccinated patients were compared using Cox proportional hazards models. Ratios of hazard ratios compared vaccinated patients between two years and unvaccinated patients between two years. VE was calculated as 1 - effect measure.
Results
Vaccination rates were <50% each year. Conventional analysis comparing vaccinated to unvaccinated patients produced average VE estimates of 13%, 16%, and 30% for ILI, influenza/pneumonia hospitalization and mortality respectively. When restricted to the pre-influenza period, results were even stronger, indicating bias. The pooled ratio of HRs comparing matched seasons to a placebo season resulted in a VE of 0% (95% CI: −3,2%) for ILI, 2% (95% CI: −2,5%) for hospitalization, and 0% (95% CI: −3,3%) for death.
Conclusions
Relative to a mismatched year, we found little evidence of increased VE in subsequent, well-matched years, suggesting that the current influenza vaccine strategy may have a smaller effect on morbidity and mortality in the ESRD population than previously thought. Alternate strategies (high dose vaccine, adjuvanted vaccine, multiple doses) should be investigated.
Keywords: Influenza vaccines, vaccine effectiveness, bias (epidemiology), renal dialysis, cohort studies
Introduction
Influenza causes substantial morbidity and mortality in the general population with approximately 39,000 people dying each year.1 Patients with end-stage renal disease (ESRD) may be at higher risk of illness and death from influenza relative to healthy adults. Trivalent inactivated influenza vaccine has been recommended by the Advisory Committee on Immunization Practices (ACIP) for end-stage renal disease (ESRD) patients for over 40 years.2 Administration of seasonal influenza vaccination has become routine practice at most dialysis clinics over the past two decades. Although hemodialysis patients have lower response rates to influenza vaccine compared with healthy adults, immunogenicity studies show that 50–93% of dialysis patients develop antibody titers after vaccination.3,4 However, it is currently unclear how much morbidity and mortality is prevented by the influenza vaccine in ESRD patients.5 To date, there has been one study among hemodialysis patients that estimated vaccine effectiveness (VE) for influenza/pneumonia hospitalizations to be 12–14% and 25% for all-cause mortality.6 Recent studies in the non-dialysis, elderly population have suggested that large VE effects (up to 50% reduction of all-cause mortality in some studies 7–9) obtained from standard epidemiologic studies may be due to confounding by unmeasured prognostic variables, and the true effect may be small to negligible.10–14
One potential way to avoid confounding by patient-level differences is to exploit the natural experiment that is caused by strong year-to-year variation in the match of the vaccine to the circulating strain. The influenza virus that predominates in a season can undergo antigenic drift after the vaccine strain has been chosen, resulting in a vaccine that provides reduced immunity. In seasons with a well-matched vaccine, vaccination is expected to be effective in preventing influenza related outcomes, whereas in mismatched seasons, vaccination is expected to have a minimal effect. It has been documented that the 1997–98 influenza vaccine strain (A/Wuhan/359/95) did not match the circulating strain (A/Sydney/5/97) 15 and outbreak investigations suggested that the vaccine provided limited protection.16 A randomized controlled trial confirmed that the vaccine did not prevent clinically relevant outcomes during this season among healthy adults younger than 65 years: vaccinated patients had more influenza-like illnesses and upper respiratory tract infections than placebo patients.17 In three of the following four years, the same strain of virus circulated in the community and the vaccine was well matched.18–20
We evaluated the difference in VE between years where the vaccine was well matched and the 1997–98 “placebo” year, where the vaccine was poorly matched and was shown to have provided little benefit. By studying this natural experiment, we sought to reduce confounding bias due to frailty and unmeasured health behaviors to obtain a more accurate measure of VE.
Methods
Study Population
We used Medicare claims from the United States Renal Data System (USRDS). The USRDS is a population-based, national system that collects information on all patients with ESRD in the US. Claims include information on physician services, International Classification of Diseases, 9th rev., Clinical Modification (ICD-9-CM) codes assigned to hospitalizations and outpatient care, information on dialysis care, medication and immunization use. These are captured for all patients with Medicare as a primary payer status (no HMO, or Medicare as a secondary payer).
Our cohorts consisted of all adult, ESRD patients with Medicare as a primary payer and continuous hemodialysis use. Each yearly cohort consisted of patients who had initiated dialysis prior to October 1 of the preceding year. An eight month window from January 1 – August 31 of each year was used to identify insurance and dialysis status and comorbidities for the patients in that cohort. For example, the cohort identified for the 1997–98 season would have initiated dialysis prior to October 1, 1996 and would have been on continuous hemodialysis and Medicare as a primary payer between January 1 – August 31, 1997. Vaccination and outcome status was assessed beginning on September 1 of each year. Cohort members were followed each year until they experienced the outcome, death, transplant, loss-to-follow up or administrative censoring on August 31 of the following year (e.g. August 31, 1998 for the 1997 influenza season).
Influenza Seasons
We chose to analyze specific years based on the characteristics of each influenza season – years with similar influenza severity and close temporally to the mismatched season. We used years before it was common to pay out of pocket at grocery stores or pharmacies to limit exposure misclassification. Cohorts were created for the following influenza seasons: 1997, 1998, 1999, 2001. Seasons were defined by the year in which vaccination began for that influenza season (the 1997–1998 season was defined as 1997). These four seasons were used due to their similar severity and strain of influenza, but various levels of vaccine match (i.e. how well the vaccine matched the strain circulating in the community).15,18–20 We excluded the 2000 season to limit differences between seasons due to influenza severity; the predominate strain in the community in 2000 was a less severe strain (A/H1N1).21 We estimated the start of each influenza season by using national influenza surveillance data from the Centers for Disease Control and Prevention. We defined the start of the season as the midpoint of the first week where more than 10% of the isolates were positive for influenza. A sensitivity analysis examined the effect of a less restrictive definition, with the start of the season defined as the week with 5% of isolates positive for influenza.
Vaccination Status
Medicare Part A hospital/outpatient files and Part B physician/supplier files were searched for Current Procedural Terminology (CPT) codes 90724, 90656, 90658-60, and HCFA Common Procedure Coding System (HCPCS) codes G0008 and G8482. Because our study population is often hospitalized, we also searched for ICD-9 procedure code 99.52.
Outcomes
We examined three outcomes: all-cause mortality, influenza/pneumonia hospitalization and influenza-like illness (ILI). Mortality is identified by the Centers for Medicare and Medicaid Services form 2746, the ESRD Death Notification Form. We searched the principle discharge diagnoses in the Medicare Part A inpatient hospitalization files for the first instance of ICD-9-CM codes 480.xx – 487.xx to identify influenza/pneumonia hospitalizations. Inpatient and outpatient codes were searched to identify the first instance of ILI as in Lindsay, et al (Appendix 1).22 In a sensitivity analysis, we limited ILI to more specific codes by removing ICD-9 codes 465, 466, and 490.
Covariates
All confounders were identified using the existing evidence base – including the investigative team’s knowledge and the published literature. The Centers for Medicare and Medicaid Services form 2827, the Medical Evidence Form, was used to ascertain age, race, gender, first service date with ESRD, and cause of kidney failure. Part A and B claims were searched during the eight month window from January 1 to August 31 for oxygen use and comorbidities as identified in Liu et al.23: atherosclerotic heart disease, congestive heart failure, cerebrovascular accident/transient ischemic attack, peripheral vascular disease, other cardiac, chronic obstructive pulmonary disease, gastrointestinal bleeding, liver disease, dysrhythmia, cancer, and diabetes. Comorbidities were modeled as dichotomous variables in the final models. Adherence to dialysis was calculated by summing the number of dialysis sessions over the eight month baseline period: patients were considered adherent if they had 95 sessions or more. Patients with no dialysis sessions over the baseline period were dropped from the analysis. We also included the number of hospital days over the baseline period. Use of mobility aids were ascertained by searching Part A and Part B claims for HCPCS equipment codes for wheelchairs, walkers, canes, and assisted bathroom equipment during the baseline period (Appendix 1).
Statistical Analysis
We used Cox proportional hazards models to estimate hazard ratios comparing vaccinated to unvaccinated within each year.24 Vaccination was modeled as a time-varying covariate, with all cohort members entering the analysis in September 1 as unvaccinated. Once vaccinated, patients remained in the vaccinated category until the end of that influenza year (August 31). To quantify bias in these estimates, we ran the same models during the pre-influenza period (September 1 through the day before the influenza season started). When limited to the period prior to the start of influenza season when vaccine effectiveness should be biologically negligible, we would expect the HR estimate to be close to 1.0 if no confounding were present. This method identifies if conventional analyses remain biased even after adjustment.
To estimate effects between seasons, we ran proportional hazards models with an interaction between vaccination status and year, with vaccination status treated as above. Kaplan-Meier survival curves are reported for the comparison of different years among vaccinated patients. We report the antilog of the beta coefficient for the interaction term, which represents the ratio of two hazard ratios: comparing the vaccinated in a matched year to the vaccinated in the unmatched year divided by the comparison of the unvaccinated in a match year to the unvaccinated in the unmatched year. Because patients could be in multiple cohorts, robust variance was initially used to account for the possibility of having multiple events in the analysis of non-death events. Using robust variance did not change the variance estimate, thus we report standard variances.
Adjusted models in all analyses controlled for age, race, sex, cause of ESRD, length of time with ESRD (vintage), adherence to dialysis, number of mobility aids as a proxy for functional status, oxygen use, hospital days, ESRD network and comorbidities. The proportional hazard assumption was checked graphically. To examine the effect of non-proportional hazards, we limited our final model to run only through the end of the influenza season, which is approximately the time when the curves crossed. Analyses were conducted using SAS 9.2 (Cary, NC) using Efron’s method for tied event times.25 This study was considered exempt from human subjects review by the institutional review board at the University of North Carolina.
Results
There were more than 100,000 patients who met the inclusion criteria in each influenza season cohort and vaccination rates were approximately 47% each year, which were similar to previously reported estimates (Table 1).6,26 Patients who received the influenza vaccine were older, had fewer years with ESRD, were more likely to be white and had better adherence to dialysis. These differences persisted over the study time period. Additionally, the mean age of the vaccinated cohorts increased, and the proportion with diabetes as the cause of ESRD increased over the study time period.
Table 1.
Description of study cohorts
| Variable | 1997 | 1998 | 1999 | 2001 | ||||
|---|---|---|---|---|---|---|---|---|
| Vaccinated N=52,287 N (%) |
Unvaccinated N=55,178 N (%) |
Vaccinated N=53,884 N (%) |
Unvaccinated N=59,225 N (%) |
Vaccinated N=56,796 N (%) |
Unvaccinated N=60,248 N (%) |
Vaccinated N=61,800 N (%) |
Unvaccinated N=64,899 N (%) |
|
| Mean age at Sept. 1 (SD) | 62.3 (14.2) | 60.3 (15.0) | 62.7 (14.1) | 60.6 (15.0) | 63.1 (14.2) | 61.0 (14.9) | 63.9 (14.0) | 61.7 (14.8) |
| Male sex | 27,310 (52.2) | 27,827 (50.4) | 28,363 (52.6) | 30,213 (51.0) | 29,963 (52.8) | 30,621 (50.8) | 32,727 (53.0) | 33,476 (51.6) |
| Race | ||||||||
| White | 29,625 (56.7) | 25,975 (47.1) | 30,744 (57.1) | 27,857 (47.0) | 32,100 (56.5) | 28,606 (47.5) | 35,571 (57.6) | 31,631 (48.7) |
| Black | 20,443 (39.1) | 26,384 (47.8) | 20,659 (38.3) | 28,271 (47.7) | 21,978 (38.7) | 28,428 (47.2) | 23,150 (37.5) | 29,629 (45.7) |
| Other | 2,219 (4.2) | 2,819 (5.1) | 2,481 (4.6) | 3,097 (5.2) | 2,718 (4.8) | 3,214 (5.3) | 3,079 (5.0) | 3,639 (5.6) |
| Cause of ESRD | ||||||||
| Diabetes | 19,988 (38.2) | 20,277 (36.8) | 21,453 (39.8) | 22,550 (38.1) | 23,336 (41.1) | 23,614 (39.2) | 26,457 (42.8) | 27,044 (41.7) |
| Hypertension | 16,503 (31.6) | 18,055 (32.7) | 16,650 (30.9) | 18,947 (32.0) | 17,207 (30.3) | 18,988 (31.5) | 18,365 (29.7) | 19,923 (30.7) |
| Glomerulonephritis | 6,998 (13.4) | 7,595 (13.8) | 6,931 (12.9) | 8,002 (13.5) | 7,114 (12.5) | 7,842 (13.0) | 7,300 (11.8) | 7,784 (12.0) |
| Cystic Kidney | 1,838 (3.5) | 1,677 (3.0) | 1,781 (3.3) | 1,705 (2.9) | 1,772 (3.1) | 1,649 (2.7) | 1,739 (2.8) | 1,643 (2.5) |
| Other | 6,960 (13.3) | 7,574 (13.7) | 7,069 (13.1) | 8,021 (13.5) | 7,367 (13.0) | 8,155 (13.5) | 7,939 (12.9) | 8,505 (13.1) |
| 1 or more mobility aid | 4,096 (7.8) | 4,767 (8.6) | 3,840 (7.1) | 4,563 (7.7) | 3,910 (6.9) | 4,141 (6.9) | 4,080 (6.6) | 4,411 (6.8) |
| Vintage (years) | ||||||||
| 0 | 1,048 (2.0) | 1,092 (2.0) | 1,212 (2.3) | 1,267 (2.1) | 1,211 (2.1) | 1,208 (2.0) | 1,211 (2.0) | 1,247 (1.9) |
| 1–2 | 22,345 (42.7) | 22, 313 (40.4) | 22,715 (42.2) | 23,473 (39.6) | 23,750 (41.8) | 23,667 (39.3) | 25,283 (40.9) | 25,279 (39.0) |
| 3–4 | 13,588 (26.0) | 13,867 (25.1) | 13,944 (25.9) | 14,976 (25.3) | 14,644 (25.8) | 14,868 (24.7) | 16,214 (26.2) | 16,244 (25.0) |
| 5–9 | 11,154 (21.3) | 12,521 (22.7) | 11,783 (21.9) | 13,766 (23.2) | 12,981 (22.9) | 14,247 (23.7) | 14,042 (22.7) | 15,725 (24.3) |
| 10+ | 4,152 (7.9) | 5,385 (9.8) | 4,230 (7.9) | 5,743 (9.7) | 4,210 (7.4) | 6,258 (10.4) | 5,050 (8.2) | 6,404 (9.9) |
| Adherent to dialysis | 45,103 (86.3) | 43,760 (79.3) | 48,130 (89.3) | 48,103 (81.2) | 50,383 (88.7) | 49,028 (81.4) | 55,611 (90.0) | 53,753 (82.8) |
| Mean hospital days (SD) | 8.4 (14.8) | 10.3 (18.1) | 8.3 (14.6) | 10.5 (18.3) | 8.6 (15.2) | 11.0 (19.0) | 8.9 (15.8) | 11.6 (19.6) |
| Oxygen Use | 5,090 (9.7) | 6,085 (11.0) | 5,574 (10.3) | 6,890 (11.6) | 6,218 (10.9) | 7,954 (13.2) | 7,258 (11.7) | 9,058 (14.0) |
| Atherosclerotic heart disease | 17,993 (34.4) | 18,675 (33.9) | 17,886 (33.2) | 19,050 (32.2) | 19,478 (34.3) | 19,901 (33.0) | 23,584 (38.2) | 24,461 (37.7) |
| Congestive heart failure | 18,572 (35.5) | 20,585 (37.3) | 17,885 (33.2) | 20,961 (35.4) | 19,174 (33.8) | 21,444 (35.6) | 22,408 (36.3) | 25.428 (39.2) |
| TIA | 7,197 (13.8) | 8,602 (15.6) | 6,725 (12.5) | 8,540 (14.4) | 7,102 (12.5) | 8,389 (13.9) | 8,675 (14.0) | 10,430 (16.1) |
| Peripheral vascular disease | 16,028 (30.7) | 17,680 (32.0) | 15,315 (28.4) | 17,794 (30.0) | 16,423 (28.9) | 17,938 (29.8) | 19,759 (32.0) | 21,761 (33.5) |
| Other cardiac | 13,950 (26.7) | 15,004 (27.2) | 12,602 (23.4) | 14,684 (24.8) | 13,693 (24.1) | 14,933 (24.8) | 16,178 (26.2) | 18,084 (27.9) |
| Liver disease | 13,060 (25.0) | 14,513 (26.3) | 3,712 (6.9) | 4,853 (8.2) | 3,005 (5.3) | 4,267 (7.1) | 2,705 (4.4) | 3,556 (5.5) |
| COPD | 7,563 (14.5) | 8,406 (15.2) | 7,435 (13.8) | 8,523 (14.4) | 8,207 (14.5) | 8,932 (14.8) | 10,104 (16.4) | 11,210 (17.3) |
| Gastrointestinal bleed | 5,212 (10.0) | 6,191 (11.2) | 5,118 (9.5) | 6,215 (10.5) | 5,108 (9.0) | 6,182 (10.3) | 5,706 (9.2) | 6,951 (10.7) |
| Dysrhythmia | 13,354 (25.5) | 13,883 (25.2) | 11,443 (21.2) | 12,745 (21.5) | 12,129 (21.4) | 13,123 (21.8) | 14,158 (22.9) | 15,547 (24.0) |
| Cancer | 4,031 (7.7) | 4,161 (7.5) | 3,272 (6.1) | 3,648 (6.2) | 3,331 (5.9) | 3,501 (5.8) | 3,897 (6.3) | 4,028 (6.2) |
| Diabetes | 26,598 (50.9) | 27,609 (50.0) | 26,106 (48.5) | 28,402 (48.0) | 27,819 (49.0) | 28,690 (47.6) | 32,682 (52.9) | 33,863 (52.2) |
All influenza seasons were predominated by the A/H3N2 strain and were severe influenza seasons. Influenza seasons began between late November and early January (Table 2).
Table 2.
Description of influenza season
| 1997 | 1998 | 1999 | 2001 | |
|---|---|---|---|---|
| % Serologic Match | 19% | 90% | 97% | 100% |
| Predominate strain | A(H3N2) | A(H3N2), B | A(H3N2) | A(H3N2), B |
| Start of flu season (10%) | 12/31/1997 | 1/13/1999 | 11/24/1999 | 1/9/2002 |
| Start of flu season (5%) | 12/24/1997 | 12/30/1998 | 11/10/1999 | 12/19/2001 |
Conventional analysis comparing vaccinated to unvaccinated patients resulted in average, adjusted VE estimates of 13%, 16%, and 30% for ILI, influenza/pneumonia hospitalization and death, respectively (Table 3). Adjustment for measured confounders increased all VE estimates slightly. However, when limited to the period prior to the start of influenza season the estimates were similar or stronger, which strongly suggests that confounding bias is present. The adjusted HR for death in the pre-influenza period ranged from 0.36 to 0.51, indicating that there is severe bias in the comparison between vaccinated and unvaccinated for the outcome of all-cause mortality. Defining the start of influenza season with an earlier date (5% of isolates positive) resulted in even more biased estimates (Table 3).
Table 3.
Estimates of vaccine effectiveness comparing vaccinated vs. unvaccinated by year
| Year | No. Events | No. Lost/ Transplant |
Crude HR 95% CI |
Adjusted HR* 95% CI |
Adjusted HR in pre- flu period† 95% CI |
Adjusted HR in pre- flu period‡ 95% CI |
|---|---|---|---|---|---|---|
| 1997 | ||||||
| ILI | 30,107 | 2,807 | 0.95 (0.93, 0.97) | 0.89 (0.87, 0.91) | 0.90 (0.88, 0.92) | 0.76 (0.73, 0.79) |
| Influenza/Pneumonia hosp. | 16,081 | 3,035 | 0.92 (0.89, 0.95) | 0.86 (0.83, 0.89) | 0.87 (0.85, 0.90) | 0.75 (0.70, 0.80) |
| Death | 23,397 | 3,144 | 0.77 (0.75, 0.79) | 0.70 (0.68, 0.72) | 0.48 (0.46, 0.51) | 0.47 (0.44, 0.49) |
| 1998 | ||||||
| ILI | 33,552 | 2,848 | 0.94 (0.92, 0.96) | 0.88 (0.86, 0.90) | 0.77 (0.74, 0.80) | 0.74 (0.71, 0.77) |
| Influenza/Pneumonia hosp. | 17,969 | 3,048 | 0.91 (0.88, 0.94) | 0.84 (0.81, 0.87) | 0.75 (0.71, 0.80) | 0.73 (0.68, 0.78) |
| Death | 25,768 | 3,159 | 0.79 (0.77, 0.81) | 0.72 (0.70, 0.74) | 0.51 (0.48, 0.53) | 0.46 (0.44, 0.49) |
| 1999 | ||||||
| ILI | 34,837 | 2,783 | 0.94 (0.92, 0.96) | 0.87 (0.85, 0.89) | 0.67 (0.64, 0.71) | 0.62 (0.58, 0.66) |
| Influenza/Pneumonia hosp. | 18,893 | 3,020 | 0.90 (0.87, 0.93) | 0.84 (0.81, 0.86) | 0.63 (0.58, 0.68) | 0.56 (0.51, 0.62) |
| Death | 26,904 | 3,150 | 0.76 (0.74, 0.78) | 0.70 (0.68, 0.72) | 0.36 (0.33, 0.39) | 0.28 (0.25, 0.31) |
| 2001 | ||||||
| ILI | 40,768 | 3,031 | 0.90 (0.88, 0.92) | 0.86 (0.84, 0.88) | 0.76 (0.73, 0.79) | 0.69 (0.66, 0.72) |
| Influenza/Pneumonia hosp. | 22,658 | 3,280 | 0.87 (0.85, 0.90) | 0.82 (0.80, 0.85) | 0.71 (0.68, 0.76) | 0.64 (0.60, 0.69) |
| Death | 30,221 | 3,417 | 0.76 (0.74, 0.78) | 0.70 (0.68, 0.71) | 0.46 (0.44, 0.49) | 0.40 (0.37, 0.43) |
Adjusted for age, race, sex, cause of ESRD, vintage, adherence, hospital days, mobility aids, network, comorbidities, and oxygen use
Pre-flu period as defined by 10% of isolates positive for influenza
Pre-flu period as defined by 5% of isolates positive for influenza
Vaccinated patients in all matched years had more events than vaccinated patients in the unmatched year, and there was little difference in the survival curves for each outcome (Figure 1). The models for 1998 vs. 1997 and 1999 vs. 1997 produced similar results, showing no benefit for any of the three outcomes. The comparison between 2001 vs. 1997 produced a small beneficial effect. The pooled ratio of hazard ratios comparing matched seasons to a placebo season resulted in a VE of 0% (95% CI: −3,2%) for ILI, 2% (95% CI: −2,5%) for influenza/pneumonia hospitalization, and 0% (95% CI: −3,3%) for death (Table 4). Neither limiting the model to run only through the end of the influenza season (data not shown) nor restricting the ILI definition (Appendix 2) appreciably changed the estimates. Starting follow-up on December 1 resulted in slightly stronger estimates, with the confidence intervals for ILI and hospitalization excluding the null (Appendix 2).
Figure 1.
Unadjusted, pooled survival curves among the vaccinated for A) ILI B) Influenza/pneumonia hospitalization C) Death
Table 4.
Ratio of hazard ratios (RHR) that estimate VE by comparing matched vs mismatched years among vaccinated vs. unvaccinated
| 1998 vs. 1997 Crude RHR 95% CI |
Adjusted RHR* 95% CI |
1999 vs. 1997 Crude RHR 95% CI |
Adjusted RHR 95% CI |
2001 vs. 1997 Crude RHR 95% CI |
Adjusted RHR 95% CI |
Pooled vs. 1997 Adjusted RHR 95% CI |
|
|---|---|---|---|---|---|---|---|
| ILI | 1.03 (1.00, 1.07) | 1.03 (1.00, 1.07) | 1.01 (0.98, 1.04) | 1.00 (0.97, 1.03) | 0.97 (0.94, 1.00) | 0.98 (0.95, 1.01) | 1.00 (0.98, 1.03) |
| Influenza/pneumonia hospitalization | 1.02 (0.97, 1.06) | 1.01 (0.97, 1.06) | 1.00 (0.96, 1.05) | 0.99 (0.95, 1.04) | 0.95 (0.92, 0.99) | 0.95 (0.91, 0.99) | 0.98 (0.95, 1.02) |
| Death | 1.03 (0.99, 1.06) | 1.02 (0.99, 1.06) | 0.99 (0.96, 1.03) | 1.00 (0.96, 1.03) | 0.99 (0.96, 1.03) | 0.99 (0.96, 1.03) | 1.00 (0.97, 1.03) |
Adjusted for age, race, sex, cause of ESRD, vintage, adherence, hospital days, mobility aids, network, comorbidities, and oxygen use
Comment
In this population-based study, we analyzed the natural experiment created by year-to-year variation in the match of the influenza vaccine to the circulating virus. We used the vaccine during a mismatched year as a working “placebo” and compared its effectiveness to well-matched vaccines in subsequent years. We found little evidence that the well-matched vaccines were more effective than the mismatched vaccine for the prevention of ILI, influenza/pneumonia hospitalization and all-cause mortality among hemodialysis patients.
We also conducted traditional analyses, comparing vaccinated and unvaccinated patients. These analyses revealed strong evidence of unobserved confounding. In all years, we found that the vaccinated patients were at decreased risk for all outcomes even before influenza began circulating in the community. Despite adjusting for many clinical factors, these analyses remained biased. Comparing patients who are vaccinated in one year to patients who are vaccinated in another year was a way to implicitly control for unmeasured aspects of health, functional status, and health behaviors that may differ between the vaccinated and unvaccinated.27
It has been shown that ESRD patients have some level of immune dysfunction that may limit their ability to respond adequately to the influenza vaccine. Specifically, these patients have fewer B-cells due to apoptosis and inflammatory cytokines pushing immune cell differentiation toward the T-cell pathway.28,29 While immunogenicity studies have shown that ESRD patients can produce antibodies, antibody production may not be sufficient to provide protection from influenza infection.
As ESRD patients may have similar levels of immune deficiency as the elderly, our results are consistent with recent work in the elderly population. Fireman et al. reported an estimate of VE for all-cause mortality of 5% (1,8%),30 while Baxter et al. reported estimates for influenza/pneumonia hospitalizations of 12% (2,22%) in persons aged 50–64, and 9% (3,14%) in those aged 65 years and older.14 Jackson et al. estimated VE for community-acquired pneumonia among the elderly as 8% (−10,23%).12 Caution is needed, however, in comparing ESRD patients to the general elderly population. ESRD patients are seen at medical facilities 2–3 times per week for dialysis, therefore the reasons for being vaccinated may be different.
Our results comparing different influenza seasons differed from a previous observational study of influenza VE in ERSD patients. The previous study compared vaccinated to unvaccinated patients and reported VE estimates during the 1998–99 matched season of 14% (8%, 23%) for influenza/pneumonia hospitalizations and 23% (19%, 27%) for all-cause mortality.6 These results were similar to our conventional adjusted estimates. By limiting our conventional analysis to the pre-influenza period, we showed that the traditional epidemiologic approach may exaggerate the benefits of vaccination.
There are limitations to this study. First, we have assumed that the vaccine was ineffective in preventing clinical outcomes in the 1997 season. If the vaccine provided some benefit, the difference in effectiveness between the match and the mismatched years would be narrowed and thus our estimate would be closer to the null than the true estimate. However, evidence from a randomized controlled trial showed that the vaccine did not protect against clinical outcomes among younger, healthier people.17 Moreover, the vaccine is even less likely to have provided protection to an immune-compromised population. Second, because we used administrative claims data, we may have not adequately captured all of the important confounders, particularly variables that changed between years, such as quality of care, temperature variations, or other circulating viruses. We did however; adjust for a variety of clinical characteristics and this is the first study of our knowledge to account for adherence to dialysis, which may be an important predictor of exposure to preventive healthcare services. Additionally, we limited the comparisons to a five year period to limit temporal changes. Third, it is likely that the ILI outcome was under-ascertained. Unless physicians were making their diagnosis based in part on the patient’s vaccination status during the visit, this misclassification would be non-differential. If a true effect did exist, we would expect the estimate to be stronger for a more specific influenza outcome, such as ILI, as compared to a less specific outcome, such as mortality. Our estimates did not reflect this trend, therefore, it is possible that our estimate for ILI may be biased toward the null. Finally, we may have missed some vaccinations if patients received a vaccine that was paid out of pocket. Because influenza vaccine is covered by Medicare for our study population and dialysis patients have healthcare encounters 2–3 times per week, we expect that the number of people who paid out of pocket would be low. These limitations cannot rule out a protective effect of the vaccine; however, we think our findings suggest the effect may be smaller than previously believed.
The findings of this study should not be interpreted to mean that the practice of influenza vaccination be discouraged. Rather, it suggests that current strategies for vaccination, which rely on single dosing with a trivalent inactivated influenza virus, should be re-evaluated. Alternative vaccine formulations exist, and may be more suitable for the dialysis population. For example, adjuvants such as AS03 and MF59 can act as a delivery system for the virus and potentiate the immunogenic response. One recent study demonstrated a significantly higher antibody response in hemodialysis patients using AS03a adjuvant vaccine compared to the standard vaccine.31 High dose vaccine that contains three times the amount of virus as compared to standard vaccine, also offers an alternative strategy. Future studies should examine the clinical effectiveness of these alternate vaccination strategies.
In summary, our analysis suggests that the potential health benefits of the current influenza vaccine may be small to negligible in the dialysis population. Conventional analyses examining vaccinated to unvaccinated groups are prone to bias. While it is premature to discontinue vaccinating high-risk patients, alternate vaccination strategies should be investigated in ESRD patients to achieve better health outcomes.
Acknowledgments
Financial disclosures: Dr. Weber serves as consultant and speaker for Merck, Pfizer, Sanofi Pastuer. Dr. Brookhart received research support from Amgen and has served as a scientific advisor for Amgen, Rockwell Medical, and Pfizer (honoraria declined, donated, or paid to institution). He received consulting fees from Crimson Health, DaVita Clinical Research, the Foundation for the National Institutes of Health, and World Health Information Consultants. Dr. Sturmer received salary support from the UNC Center of Excellence in Pharmacoepidemiology and Public Health and receives salary support from unrestricted research grants from pharmaceutical companies to UNC.
Funding/support: This work was supported by an unrestricted fellowship from the UNC-GlaxoSmithKline Center of Excellence in Pharmacoepidemiology and Public Health at the University of North Carolina, Gillings School of Global Public Health.
Role of the sponsor: The sponsor had no role in the study design, data analysis or manuscript preparation.
The data reported here have been supplied by the United States Renal Data System (USRDS). The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the U.S. government.
Abbreviations
- CI
confidence interval
- ESRD
end-stage renal disease
- HR
hazard ratio
- ILI
influenza-like illness
- RHR
ratio of hazard ratios
- VE
vaccine effectiveness
Appendix 1
Codes used to define ILI and use of mobility aids
|
ILI outcome Condition |
ICD-9-CM Code | % of ILI outcome (all years) |
| Influenza | 487.0, 487.1, 487.8 | 3.2 |
| Upper respiratory infections | 465 | 8.7 |
| Acute laryngitis and tracheitis | 464 | 0.4 |
| Acute bronchitis and bronchiolitis | 466 | 11.5 |
| Bronchitis not specified | 490 | 7.3 |
| Pulmonary collapse | 518.0 | 9.1 |
| Acute respiratory failure | 518.81 | 14.9 |
| Unspecified viral pneumonia | 480.9 | 0.4 |
| Bronchopneumonia organism unspecified | 485 | 1.3 |
| Pneumonia organism unspecified | 486 | 41.3 |
| Secondary bacterial pneumonias: | ||
| Klebsiella pneumoniae, Haemophilus influenzae, Streptococcus, Staphylococcus | 482.0, 482.2, 482.3, 482.4 | 1.9 |
|
Mobility aid Description |
HCPCS code | |
| Use of wheelchair | E0950 – E1228, E1230, E1240 – E1298 | |
| Use of walker/cane | E0130, E0135, E0140, E0141, E0143, E0144, E0147, E0148, E0149, E0105, E0100 | |
| Use of modified bathroom equipment | E0240 – E0248 | |
Appendix 2
Sensitivity analyses: ratio of hazard ratios (RHR) that estimate VE by comparing matched vs mismatched years among vaccinated vs. unvaccinated
| 1998 vs. 1997 | 1999 vs. 1997 | 2001 vs. 1997 | Pooled vs. 1997 | ||||
|---|---|---|---|---|---|---|---|
| Crude RHR 95% CI |
Adjusted RHR* 95% CI |
Crude RHR 95% CI |
Adjusted RHR 95% CI |
Crude RHR 95% CI |
Adjusted RHR 95% CI |
Adjusted RHR 95% CI |
|
| Specific ILI codes | 1.04 (1.00, 1.07) | 1.03 (1.00, 1.06) | 1.01 (0.98, 1.04) | 1.00 (0.97, 1.03) | 0.97 (0.94, 1.00) | 0.98 (0.95, 1.02) | 1.00 (0.98, 1.03) |
| Start follow-up on 12/1 | |||||||
| ILI | 1.00 (0.97, 1.04) | 0.99 (0.96, 1.03) | 0.98 (0.95, 1.02) | 0.97 (0.93, 1.00) | 0.93 (0.90, 0.96) | 0.94 (0.91, 0.97) | 0.97 (0.94, 0.99) |
| Hospitalization | 0.98 (0.94, 1.03) | 0.98 (0.93, 1.02) | 0.99 (0.94, 1.03) | 0.97 (0.93, 1.02) | 0.92 (0.88, 0.96) | 0.93 (0.89, 0.97) | 0.96 (0.92, 0.99) |
| Death | 1.01 (0.97, 1.05) | 1.01 (0.97, 1.06) | 0.99 (0.95, 1.03) | 1.00 (0.96, 1.04) | 0.95 (0.91, 0.99) | 0.95 (0.92, 0.99) | 0.99 (0.95, 1.02) |
Adjusted for age, race, sex, cause of ESRD, vintage, adherence, hospital days, mobility aids, network, comorbidities, and oxygen use
Footnotes
Author contributions: Leah McGrath, Alan Brookhart, and Lily Wang had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study design: McGrath, Kshirsagar, Cole, Weber, Sturmer, Brookhart.
Acquisition of the data: Brookhart, Wang.
Analysis and interpretation of the data: McGrath, Wang, Brookhart, Kshirsagar.
Drafting the manuscript: McGrath, Brookhart.
Critical revision of the manuscript: McGrath, Kshirsagar, Cole, Weber, Sturmer, Brookhart.
Statistical analysis: McGrath, Wang, Brookhart.
Study supervision: Brookhart.
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