A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes
Objectives: To describe the modeling techniques used for early prediction of outcome in traumatic brain injury (TBI) and to identify aspects for potential improvements. Study Design and Setting: We reviewed key methodological aspects of studies published between 1970 and 2005 that proposed a prognostic model for the Glasgow Outcome Scale of TBI based on admission data. Results: We included 31 papers. Twenty-four were single-center studies, and 22 reported on fewer than 500 patients. The median of the number of initially considered predictors was eight, and on average five of these were selected for the prognostic model, generally including age, Glasgow Coma Score (or only motor score), and pupillary reactivity. The most common statistical technique was logistic regression with stepwise selection of predictors. Model performance was often quantified by accuracy rate rather than by more appropriate measures such as the area under the receiver-operating characteristic curve. Model validity was addressed in 15 studies, but mostly used a simple split-sample approach, and external validation was performed in only four studies. Conclusion: Although most models agree on the three most important predictors, many were developed on small sample sizes within single centers and hence lack generalizability. Modeling strategies have to be improved, and include external validation.
|Keywords||Glasgow Outcome Scale, Prognostic models, Regression analysis, Systematic review, Traumatic brain injury, Validation|
|Persistent URL||dx.doi.org/10.1016/j.jclinepi.2007.06.011, hdl.handle.net/1765/29816|
|Journal||Journal of Clinical Epidemiology|
Mushkudiani, N, Hukkelhoven, C.W.P.M, Hernández, A.V, Murray, G.D, Choi, S.C, Maas, A.I.R, & Steyerberg, E.W. (2008). A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes. Journal of Clinical Epidemiology, 61(4), 331–343. doi:10.1016/j.jclinepi.2007.06.011