Framework for Analysis of Multiple Near-Simultaneous Vaccinations and U.S. Military Hospitalizations Charles Rose, PhD Daniel Payne, PhD, MSPH

Purpose Assess multiple near-simultaneous (MNS) vaccinations and frequency of hospitalizations for non-deployed, active duty, US military personnel using the DMSS database The purpose of our study is to assess whether there is a significant difference between the hospitalization rates during the pre and post multiple vaccination exposure periods. In addition, we want to assess the magnitude, if any, of the post vaccination exposure period to the pre vaccination non-exposed period for the risk of hospitalization.

Why Study MNS Vaccinations and U.S. Military Hospitalizations? At a 2004 Armed Forces Epidemiologic Board meeting, VAU was asked to investigate this as part of our research agenda NVAC, CDC, DoD, and FDA collaborators concurred that this topic was sufficiently important to be included in the VAU research activities In recent years there has been increased interest on adverse event health effects, if any, after receiving multiple vaccinations. This is an emerging safety research topic that has received more attention in the DoD because it is common in the military to receive multiple vaccinations within a short period of time.

Examples of Previous Studies on Multiple Vaccinations Hotopf, et al. – cross-sectional study found a slightly increased risk of reporting multiple symptoms among Gulf War servicemen who received multiple vaccines. Pittman, et al. – follow-up analysis of a cohort of DoD employees who received 5 or more vaccines in a year. With extensive laboratory, lifestyle, and medical data, this study revealed that no significant long-term health effects were associated with this definition of MNS. There are two published studies in the area [i] Hotopf M, David A, Hull L, Ismail K, Unwin C, Wessely S. Role of vaccinations as risk factors for ill health in veterans of the Gulf war: cross sectional study. British Medical Journal. 2000; 320(7246):1363-1367. Pittman, et al.[i] [i] Pittman P, Coonan K, Gibbs P, et al. Long-term health effects of repeated exposure to multiple vaccines. Vaccine 2004. ****** Pittman et al concluded that no long-term adverse effects were observed to be associated with these repeated, large-dosage vaccinations. Some evidence of a chronic inflammatory response was evident, but a causal association to the vaccinations could not be inferred.

Defense Medical Surveillance System (DMSS) Background Active surveillance system of U.S. military (~1.4 million person years each year from 1998-present) Database consists of numerous Oracle tables Hospitalization and outpatient diagnostic (ICD-9), vaccination, demographic, administrative, and deployment data collected A general background of the DMSS and the role of the VAU was presented earlier. The DMSS is a relational database and for this study information will come from several of the tables. The study period of interest is 1998-2003 which includes the DoD’s anthrax vaccination program that began in 1998 and was put on hold in October 2004 and the smallpox vaccination program that began in 2003.

Development of the MNS Study Investigational Framework Define the vaccines to be included an exposure to multiple near-simultaneous vaccinations a hospitalization event observation time period the method for analyzing the MNS vaccinations and inpatient events In the developing the framework for looking at multiple vaccinations and hospitalizations we defined several variables and developed our method. From previous literature and because of the commonality of some vaccines we developed a list of 10 vaccines of interest for this study. We defined a multiple near-simultaneous vaccination exposure. Hospitalization events are defined using ICD-9 codes; however, we excluded some codes for conditions shown considered unlikely to be related to receipt of a vaccine. Finally, we had to define a study time period and method for analyzing the data.

Vaccines of Interest Anthrax Hepatitis B Smallpox Influenza Hepatitis A Yellow Fever Measles/Mumps/ Rubella Typhoid Meningococcal Tetanus/Diphtheria Any possible combinations of vaccine type(s), dose(s), and sequence(s) The DMSS contains information on persons receiving up to ~150 different vaccines – there are about 30 predominant types of vaccines The following were considerations used to include these 10 vaccines for the study: 1. Sample size – (and, commonly administered vaccines) 2. VAERS combinations 3. Mix of biodefense and non-biodefense vaccines

Defining a Multiple Near-Simultaneous Vaccination Exposure Number of the 10 vaccines of interest received We can also look at the number of vaccine antigens introduced into the body aluminum adjuvant–containing vaccines administered live vaccines (or ratio of live to non-live) administered There are several possible definitions for a multiple near-simultaneous vaccination exposure. We intend to look first using the number of the 10 vaccines of interest received. However there are other methods we can use e.g., the number of antigens introduced etc. In addition, we will look to see if there appears to be any dose response relationship between number of vaccines administered and rate of hospitalization for the pre and post exposure periods.

Live or Non-Live (attenuated) Aluminum adjuvant Vaccine Number of antigens Live or Non-Live (attenuated) Aluminum adjuvant Anthrax 2 Non-live [Cell-free, inactivated] Yes Hepatitis B 1 Non-live [Inactivated] Smallpox 198 Live [Lyophilized (freeze dried) live virus] No Typhoid fever: Vi-CPS (IM) Ty21a (oral) Phenol-killed* Acetone-killed** Live [Purified capsular polysaccharide] Live [Live attenuated] Non-live [Whole cell killed] Influenza (IM) 3 Yellow fever 10 MMR 24 Tetanus/Diphtheria Non-live [Toxoid] Hepatitis A Meningococcal 4 Non-live [Freeze-dried preparation of polysaccharide antigens] This table shows a list of the vaccines of interest according to the number of antigens contained, live/nonlive status, and whether they contain aluminum adjuvant (AVA does).

Defining Hospitalization Event of Interest Group Code ICD9 set Description 1 (001-139) Infectious and parasitic diseases 2 (140-239) Neoplasms 3 (240-279) Endocrine, nutrition, immunity 4 (280-289) Hematologic disorders 5 (290-319) Mental disorders 6 (320-389) Nervous disorders 7 (390-459) Circulatory system 8 (460-519) Respiratory system 9 (520-579) Digestive system 10 (580-629) Genitourinary system 11 (630-679) Pregnancy * excluded * 12 (680-709) Dermatological diseases 13 (710-739) Musculoskeletal disorders 14 (740-759) Congenital anomalies * excluded * 15 (760-779) Conditions originating in the perinatal period 16 (780-799) Ill-defined conditions 17 (800-999) Injury and poisoning 18 (V-,E-codes) V-codes, E-codes We excluded certain ICD-9 hospitalization codes because they were considered unlikely to related to receipt of a vaccine (pregnancy and congenital anomalies). However, during the analysis stage we will look at the frequencies of the ICD-9 grouping by pre and post exposure periods to determine if any abnormalities exist among the pre and post exposure groups.

Our intended study population includes all military personnel who received a vaccine between 1998-2003. The same study subjects are in both time periods – their pre-vaccination baseline risk of hospitalization is compared to that of the period following the vaccination event. Note that we go back 180 days but we will only analyze the first 120 days because it is felt that there will be a natural drop-off in the number of hospitalizations as we move closer to the exposure date because of the healthy worker effect.

Study Design Pre / Post exposure cohort design Eligible subjects for inclusion in study Hospitalizations are observed during the pre/post exposure periods Periods defined as 180 days Analysis period is the first 120 days No additional vaccines of interest are given during the post-MNS vaccination period MNS vaccination event is defined as receipt of 2 or more vaccines within a day This slide outlines our study. We will compare the risk of hospitalization from the same group of subjects before and after their multiple vaccine exposures. We intend to focus on non deployed, active duty, 18-65 years of age eligible subjects. We have chosen a period of observation, pre and post exposure, of 180 days. However, we will only analyze the first 120 days as explained earlier. We will also exclude from the analysis any person who received any of the 10 vaccines after the exposure period and the end of the observation period, i.e., anyone who had one of the 10 vaccine from day 2-180 was excluded. Although we define a MNS as receipt of 2 or more vaccines within a 2 day period we intend to further analyze the data to determine if there is a dose response relationship.

Model Covariates: Static Race black white other Ethnicity Hispanic non-Hispanic Gender All multivariable modeling efforts will begin by including the following static and dynamic (next slide) covariates. We will account for the change in status within a subject for the time varying covariates.

Model Covariates: Dynamic Service Army Marines Air Force Navy Age Categories 18 to <25 years 25 to <35 years 35 to <45 years 45 to 65 years Occupation Categories Medical/Research/Science Hazardous Front-line Office/Administrative Communication

Modeling Methods Cox proportional hazards model Account for time varying covariates Assess the risk of hospitalization of the pre versus post exposure period after controlling for considered variables Dose-response, e.g., is there a trend in the post versus pre exposure risk as the number of vaccines administered increases? We will fit a Cox proportional hazards model for 2 or more vaccines. In addition, we will fit the Cox model for 1, 2, 3, … vaccines independently to determine if there appears to be a dose response pattern.

Next Steps Complete analysis Share with collaborators We are currently beginning the analysis of the data and expect to have results to disseminate by late May 2005.

MNS Vaccination Future Topics Broaden our scope to include all vaccines Define and account for a cumulative effect of vaccination Data mining Others? Our future plans include assessing these additional approaches to the topic in the near future. I mentioned earlier the database has information on individuals who have received more than ~100 vaccines. We will also look at the cumulative effect of receiving many vaccines and see if there is a dose response relationship. Some of the future topics may be handled using data mining techniques.

Acknowledgements CDC DoD NVAC FDA (Robert Ball) Anthrax Vaccine Safety Team (Aaron Aranas, Susan Duderstadt, Mike McNeil) Immunization Safety Branch (Frank DeStefano) DoD Army Medical Surveillance Activity (Col. Mark Rubertone) MILVAX (Col. John Grabenstein) NVAC FDA (Robert Ball)