A nested case-control study of influenza vaccination was a cost-effective alternative to a full cohort analysis

E. Hak, F. Wei, D. E. Grobbee, K. L. Nichol

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

In the absence of trial results that are applicable to the target population, nested case-control studies might be an alternative to full-cohort analysis. We compared relative and absolute estimates of associations in an influenza vaccine study using both designs. Data from elderly persons enrolled during six consecutive influenza seasons were used (147,551 person-periods). The endpoints "hospitalization for pneumonia or influenza" (P&I) or "death" were used combined and separately to define three types of cases. Controls for the case-control samples were randomly selected from the remainder of the total cohort at different ratios (1:1 to 1:4). Logistic regression analysis was used to assess adjusted vaccine effectiveness (VE). Sampling fractions were used to determine the number needed to treat to prevent one outcome. Receiver-operator-curve analysis was conducted to estimate the area under the curve (AUC) as a measure of discriminative capacity of the prognostic model. In all, 978 P&I hospitalizations and 1,339 deaths were observed. The adjusted estimates of relative estimates (VE, AUC) and their corresponding 95% confidence intervals were virtually the same using both study designs, notably when the case-control ratio was high (1:4). A nested case-control design can provide valid and precise estimates of associations and is a cost-effective alternative for full-cohort analysis.

Original languageEnglish (US)
Pages (from-to)875-880
Number of pages6
JournalJournal of Clinical Epidemiology
Volume57
Issue number9
DOIs
StatePublished - Sep 2004

Keywords

  • Case-control study
  • Cohort study
  • Immunization
  • Influenza
  • Methodology

Fingerprint

Dive into the research topics of 'A nested case-control study of influenza vaccination was a cost-effective alternative to a full cohort analysis'. Together they form a unique fingerprint.

Cite this