Safety study of live, oral human rotavirus vaccine: A cohort study in United States health insurance plans.

As part of a regulatory commitment for post-licensure safety monitoring of live, oral human rotavirus vaccine (RV1), this study compared the incidence rates (IR) of intussusception, acute lower respiratory tract infection (LRTI) hospitalization, Kawasaki disease, convulsion, and mortality in RV1 recipients versus inactivated poliovirus vaccine (IPV) recipients in concurrent (cIPV) and recent historical (hIPV) comparison cohorts. Vaccine recipients were identified in 2 claims databases from August 2008 - June 2013 (RV1 and cIPV) and January 2004 - July 2008 (hIPV). Outcomes were identified in the 0-59 days following the first 2 vaccine doses. Intussusception, Kawasaki disease, and convulsion were confirmed via medical record review. Outcome IRs were estimated. Incidence rate ratios (IRRs) were obtained from Poisson regression models. A post-hoc self-controlled case series (SCCS) analysis compared convulsion IRs in a 0-7 day post-vaccination period to a 15-30 day post-vaccination period. We identified 57,931 RV1, 173,384 cIPV, and 159,344 hIPV recipients. No increased risks for intussusception, LRTI, Kawasaki disease, or mortality were observed. The convulsion IRRs were elevated following RV1 Dose 1 (cIPV: 2.07, 95% confidence interval [CI]: 1.27 - 3.38; hIPV: 2.05, 95% CI: 1.24 - 3.38), a finding which is inconclusive as it was observed in only one of the claims databases. The IRR following RV1 Dose 1 in the SCCS analysis lacked precision (2.40, 95% CI: 0.73 - 7.86). No increased convulsion risk was observed following RV1 Dose 2. Overall, this study supports the favorable safety profile of RV1. Continued monitoring for safety signals through routine surveillance is needed to ensure vaccine safety.

Validation of current procedural terminology codes for rotavirus vaccination among infants in two commercially insured US populations.

PURPOSE: We validated procedure codes used in health insurance claims for reimbursement of rotavirus vaccination by comparing claims for monovalent live-attenuated human rotavirus vaccine (RV1) and live, oral pentavalent rotavirus vaccine (RV5) to medical records. METHODS: Using administrative data from two commercially insured United States populations, we randomly sampled vaccination claims for RV1 and RV5 from a cohort of infants aged less than 1 year from an ongoing post-licensure safety study of rotavirus vaccines. The codes for RV1 and RV5 found in claims were confirmed through medical record review. The positive predictive value (PPV) of the Current Procedural Terminology codes for RV1 and RV5 was calculated as the number of medical record-confirmed vaccinations divided by the number of medical records obtained. RESULTS: Medical record review confirmed 92 of 104 RV1 vaccination claims (PPV: 88.5%; 95% CI: 80.7-93.9%) and 98 of 113 RV5 vaccination claims (PPV: 86.7%; 95% CI: 79.1-92.4%). Among the 217 medical records abstracted, only three (1.4%) of vaccinations were misclassified in claims-all were RV5 misclassified as RV1. The medical records corresponding to 9 RV1 and 15 RV5 claims contained insufficient information to classify the type of rotavirus vaccine. CONCLUSIONS: Misclassification of rotavirus vaccines is infrequent within claims. The PPVs reported here are conservative estimates as those with insufficient information in the medical records were assumed to be incorrectly coded in the claims. Copyright © 2016 John Wiley & Sons, Ltd.

Development and evaluation of an algorithm to identify users of Prolia(®) during the early postmarketing period using health insurance claims data.

PURPOSE: The goal of this study is to develop and validate an algorithm to identify Prolia(®) users within a health insurance claims database. METHODS: Patients with a denosumab-specific or nonspecific administration claim during the early period of Prolia availability in the USA (June 1, 2010 to March 31, 2012) were classified as definite, probable, possible, and nonusers of Prolia using an algorithm consisting of nine different components based on claims patterns consistent with Prolia use. Medical record review confirmed a sample of definite, probable, and possible users and the positive predictive value (PPV) was estimated. RESULTS: The PPV of the claims-based algorithm components varied (17.8-95.8%). Requiring claims for a bone or cartilage disorder or osteoporotic fracture after excluding claims for cancer prior to a denosumab-specific administration code gave the highest PPV (95.8%), followed by requiring a Prolia National Drug Code on the same claim as a denosumab-specific or nonspecific administration code (88.2%). Among the 87 confirmed Prolia users, osteoporosis diagnoses were seen more frequently in the medical record than in claims (83% vs 62%). CONCLUSIONS: Prolia users are most accurately identified with administration code claims in conjunction with claims for Prolia National Drug Code and bone disorder treatment and diagnosis codes. Osteoporosis diagnoses may be under-recorded in claims data. The algorithm may require reassessment as uptake for more recently approved indications increases.