A new strategy for meta-analysis of continuous covariates in observational studies

被引:29
作者
Sauerbrei, Willi [1 ]
Royston, Patrick [2 ,3 ]
机构
[1] Univ Freiburg, Med Ctr, IMBI, D-79100 Freiburg, Germany
[2] MRC Clin Trials Unit, London WC2B 6NH, England
[3] UCL, London WC2B 6NH, England
基金
英国医学研究理事会;
关键词
prognostic research; risk assessment; meta-analysis; regression modelling; fractional polynomials; confounder model; DOSE-RESPONSE DATA; FRACTIONAL POLYNOMIALS; ALCOHOL-CONSUMPTION; PROGNOSTIC MARKERS; DIAGNOSTIC MODELS; TRANSFORMATION; PREDICTORS; REGRESSION; CANCER; METHODOLOGY;
D O I
10.1002/sim.4333
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
When several studies are available, a meta-analytic assessment of the effect of a risk or prognostic factor on an outcome is often required. We propose a new strategy, requiring individual participant data, to provide a summary estimate of the functional relationship between a continuous covariate and the outcome in a regression model, adjusting for confounding factors. Our procedure comprises three steps. First, we determine a confounder model. Ideally, the latter should include the same variables across studies, but this may be impossible. Next, we estimate the functional form for the continuous variable of interest in each study, adjusted for the confounder model. Finally, we combine the individual functions by weighted averaging to obtain a summary estimate of the function. Fractional polynomial methodology and pointwise weighted averaging of functions are the key components. In contrast to a pooled analysis, our approach can reflect more variability between functions from different studies and more flexibility with respect to confounders. We illustrate the procedure by using data from breast cancer patients in the Surveillance, Epidemiology, and End Results Program database, where we consider data from nine individual registries as separate studies. We estimate the functional forms for the number of positive lymph nodes and age. The former is an example where a strong prognostic effect has long been recognized, whereas the prognostic effect of the latter is weak or even controversial. We further discuss some general issues that are found in meta-analyses of observational studies. Copyright (C) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:3341 / 3360
页数:20
相关论文
共 46 条
[1]   Systematic review of multiple studies of prognosis: The feasibility of obtaining individual patient data [J].
Altman, Douglas G. ;
Trivella, Marialena ;
Pezzella, Francesco ;
Harris, Adrian L. ;
Pastorino, Ugo .
ADVANCES IN STATISTICAL METHODS FOR THE HEALTH SCIENCES: APPLICATIONS TO CANCER AND AIDS STUDIES, GENOME SEQUENCE ANALYSIS, AND SURVIVAL ANALYSIS, 2007, :3-+
[2]   Fractional polynomial model selection procedures: Investigation of type I error rate [J].
Ambler, G ;
Royston, P .
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2001, 69 (01) :89-108
[3]  
[Anonymous], 2008, Multivariable model-building: a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables
[4]   Flexible meta-regression functions for modeling aggregate dose-response data, with an application to alcohol and mortality [J].
Bagnardi, V ;
Zambon, A ;
Quatto, P ;
Corrao, G .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2004, 159 (11) :1077-1086
[5]  
Beral V, 1997, LANCET, V350, P1047, DOI 10.1016/S0140-6736(97)08233-0
[6]   Traditional reviews, meta-analyses and pooled analyses in epidemiology [J].
Blettner, M ;
Sauerbrei, W ;
Schlehofer, B ;
Scheuchenpflug, T ;
Friedenreich, C .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 1999, 28 (01) :1-9
[7]   Mortality among workers employed in the titanium dioxide production industry in Europe [J].
Boffetta, P ;
Soutar, A ;
Cherrie, JW ;
Granath, F ;
Andersen, A ;
Anttila, A ;
Blettner, M ;
Gaborieau, V ;
Klug, SJ ;
Langard, S ;
Luce, D ;
Merletti, F ;
Miller, B ;
Mirabelli, D ;
Pukkala, E ;
Adami, HO ;
Weiderpass, E .
CANCER CAUSES & CONTROL, 2004, 15 (07) :697-706
[8]   TRANSFORMATION OF INDEPENDENT VARIABLES [J].
BOX, GEP ;
TIDWELL, PW .
TECHNOMETRICS, 1962, 4 (04) :531-&
[9]   Prognostic value of admission blood pressure in traumatic brain injury: Results from the IMPACT study [J].
Butcher, Isabella ;
Maas, Andrew I. R. ;
Lu, Juan ;
Marmarou, Anthony ;
Murray, Gordon D. ;
Mushkudiani, Nino A. ;
McHugh, Gillian S. ;
Steyerberg, Ewout W. .
JOURNAL OF NEUROTRAUMA, 2007, 24 (02) :294-302
[10]   Systematic reviews in epidemiology: why are we so far behind? [J].
Dickersin, K .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2002, 31 (01) :6-12