Response to: Prediction of Outcome after Traumatic Brain Injury Using Clinical and Neuroimaging Variables: A Methodological Mistake

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Print ISSN 1738-6586 / On-line ISSN 2005-5013 http://dx.doi.org/10.3988/jcn.2013.9.3.198 LETTER TO THE EDITOR

J Clin Neurol 2013;9:198-198

We appreciate the comments made by Dr. Sabour about our manuscript.

We agree that the term ‘prediction’ can be misleading. We used the term as a general one, since our study employed an explanatory rather than a predictive model.¹ We estimated which factors were associated with an unfavorable outcome (defined as a Glasgow outcome scale ≤4) rather than predict- ing the prognosis of individual patients. Validation using di- vided data sets or bootstrapping, as recommended, is rarely performed for this type of study and cannot be applied to our study because of the smallness of the sample.²

We admit that the confidence intervals for ‘motorcycle accident’ and ‘being an accident victim’ are too wide, which was due to the sample size being insufficient for a multivariable model including all the potential variables. In particular, the effect of being an accident victim requires careful inter- pretation and a detailed analysis to ensure that the number of samples in each group is sufficient, because it can be affected by the cause and severity of injury. We acknowledge this

limitation and hence metioned in the Discussion that a large multicenter study is needed to confirm our findings. Howev- er, the factors ‘motorcycle accident,’ ‘being an accident victim,’ and ‘diffuse axonal injury on brain magnetic resonance imaging’ were found to be consistently and significantly cor- related with unfavorable outcomes in both univariate and multivariate analyses. Not only are these factors statistically significant, but it is also plausible that they could affect the outcome, as described in the Discussion.

Conflicts of Interest

The authors have no financial conflicts of interest.

REFERENCES

1. Katz MH. Common uses of multivariable models. In: Katz MH.

Multivariable Analysis. A Practical Guide for Clinicians. 2nd ed.

New York: Cambridge University Press, 2006;14-23.

2. Katz MH. Validation of models. In: Katz MH. Multivariable Analy- sis. A Practical Guide for Clinicians. 2nd ed. New York: Cambridge University Press, 2006;179-183.

Response to: Prediction of Outcome after Traumatic Brain Injury Using Clinical and Neuroimaging Variables:

A Methodological Mistake

Seo-Young Lee,^a Moo Kyung Oh^b

aDepartment of Neurology and ^bHealth Policy and Management, Kangwon National University Hospital, Chuncheon, Korea Open Access

Received May 3, 2013 Revised May 13, 2013 Accepted May 13, 2013 Correspondence

Seo-Young Lee, MD, Department of Neurology, Kangwon National Uni- versity Hospital, 156 Baengnyeong-ro, Chuncheon 200-722, Korea Tel +82-33-258-2431, Fax +82-33-258-2103

E-mail [email protected]

cc This is an Open Access article distributed under the terms of the Cre- ative Commons Attribution Non-Commercial License (http://creative- commons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the ori- ginal work is properly cited.