Comparison of two smoothing methods for exploring waning vaccine effects

被引:13
作者
Durham, LK [1 ]
Halloran, ME [1 ]
Longini, IM [1 ]
Manatunga, AK [1 ]
机构
[1] Emory Univ, Atlanta, GA 30322 USA
关键词
smoothing; survival analysis; time-dependent relative risk; vaccine efficacy;
D O I
10.1111/1467-9876.00160
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider the statistical evaluation and estimation of vaccine efficacy when the protective effect wanes with time. We reanalyse data from a 5-year trial of two oral cholera vaccines in Matlab, Bangladesh. In this field trial, one vaccine appears to confer better initial protection than the other, but neither appears to offer protection for a period longer than about 3 years. Time-dependent vaccine effects are estimated by obtaining smooth estimates of a time-varying relative risk RR(t) using survival analysis. We compare two approaches based on the Cox model in terms of their strategies for detecting time-varying vaccine effects, and their estimation techniques for obtaining a time-dependent RR(t) estimate. These methods allow an exploration of time-varying vaccine effects while making minimal parametric assumptions about the functional form of RR(t) for vaccinated compared with unvaccinated subjects.
引用
收藏
页码:395 / 407
页数:13
相关论文
共 22 条
  • [1] Time-dependent hazard ratio: Modeling and hypothesis testing with application in lupus nephritis
    Abrahamowicz, M
    MacKenzie, T
    Esdaile, JM
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1996, 91 (436) : 1432 - 1439
  • [2] Chambers J.M., 1991, Statistical Models in S
  • [3] FIELD TRIAL OF ORAL CHOLERA VACCINES IN BANGLADESH - RESULTS FROM 3-YEAR FOLLOW-UP
    CLEMENS, JD
    SACK, DA
    HARRIS, JR
    VANLOON, F
    CHAKRABORTY, J
    AHMED, F
    RAO, MR
    KHAN, MR
    YUNUS, M
    HUDA, N
    STANTON, BF
    KAY, BA
    WALTER, S
    EECKELS, R
    SVENNERHOLM, AM
    HOLMGREN, J
    [J]. LANCET, 1990, 335 (8684) : 270 - 273
  • [4] COX DR, 1972, J R STAT SOC B, V34, P187
  • [5] Durham LK, 1998, AM J EPIDEMIOL, V147, P948, DOI 10.1093/oxfordjournals.aje.a009385
  • [6] RANDOM-EFFECTS MODELS FOR LONGITUDINAL DATA USING GIBBS SAMPLING
    GILKS, WR
    WANG, CC
    YVONNET, B
    COURSAGET, P
    [J]. BIOMETRICS, 1993, 49 (02) : 441 - 453
  • [7] A SIMPLE TEST OF THE PROPORTIONAL HAZARDS ASSUMPTION
    GILL, R
    SCHUMACHER, M
    [J]. BIOMETRIKA, 1987, 74 (02) : 289 - 300
  • [8] GRAMBSCH PM, 1994, BIOMETRIKA, V81, P515
  • [9] Halloran ME, 1996, AM J EPIDEMIOL, V144, P83, DOI 10.1093/oxfordjournals.aje.a008858
  • [10] STUDY DESIGNS FOR DEPENDENT HAPPENINGS
    HALLORAN, ME
    STRUCHINER, CJ
    [J]. EPIDEMIOLOGY, 1991, 2 (05) : 331 - 338