Multivariate meta‐analysis of prognostic factor studies with multiple cut‐points and/or methods of measurement
| العنوان: | Multivariate meta‐analysis of prognostic factor studies with multiple cut‐points and/or methods of measurement |
|---|---|
| المؤلفون: | Eleni G. Elia, Karla Hemming, Gemma Malin, Malcolm Price, Richard D Riley |
| المصدر: | Statistics in Medicine |
| بيانات النشر: | Wiley, 2015. |
| سنة النشر: | 2015 |
| مصطلحات موضوعية: | Statistics and Probability, Multivariate statistics, Prognostic factor, Lung Neoplasms, Epidemiology, multivariate meta‐analysis, Breast Neoplasms, Disease, Biostatistics, Models, Biological, cut‐points, Infant Mortality, Statistics, Econometrics, Humans, Research Articles, Mathematics, odds ratios and hazard ratios, Models, Statistical, Infant, Newborn, prognostic factors, Infant, Prediction interval, Variance (accounting), Prognosis, Random effects model, 3. Good health, Ki-67 Antigen, Nonlinear Dynamics, Meta-analysis, Microvessels, Multivariate Analysis, Apgar Score, Linear Models, Female, Apgar score, heterogeneity, RA, Research Article |
| الوصف: | A prognostic factor is any measure that is associated with the risk of future health outcomes in those with existing disease. Often, the prognostic ability of a factor is evaluated in multiple studies. However, meta‐analysis is difficult because primary studies often use different methods of measurement and/or different cut‐points to dichotomise continuous factors into ‘high’ and ‘low’ groups; selective reporting is also common. We illustrate how multivariate random effects meta‐analysis models can accommodate multiple prognostic effect estimates from the same study, relating to multiple cut‐points and/or methods of measurement. The models account for within‐study and between‐study correlations, which utilises more information and reduces the impact of unreported cut‐points and/or measurement methods in some studies. The applicability of the approach is improved with individual participant data and by assuming a functional relationship between prognostic effect and cut‐point to reduce the number of unknown parameters. The models provide important inferential results for each cut‐point and method of measurement, including the summary prognostic effect, the between‐study variance and a 95% prediction interval for the prognostic effect in new populations. Two applications are presented. The first reveals that, in a multivariate meta‐analysis using published results, the Apgar score is prognostic of neonatal mortality but effect sizes are smaller at most cut‐points than previously thought. In the second, a multivariate meta‐analysis of two methods of measurement provides weak evidence that microvessel density is prognostic of mortality in lung cancer, even when individual participant data are available so that a continuous prognostic trend is examined (rather than cut‐points). © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. |
| وصف الملف: | application/pdf |
| تدمد: | 1097-0258 0277-6715 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a515a8b94bdcfdc379d15641af336675 https://doi.org/10.1002/sim.6493 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....a515a8b94bdcfdc379d15641af336675 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 10970258 02776715 |
|---|