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Published on: April 14, 2016
Minimally clinically significant differences for adolescents with chronic pain-variability of ROC-based cut points
Gerrit Hirschfeld1, Julia Wager1, Pia Schmidt1
1German Paediatric Pain Centre, Children's and Adolescents' Hospital, Datteln, Germany; and Department of Children's Pain Therapy and Paediatric Palliative Care, School of Medicine, Faculty of Health, Witten/Herdecke University, Witten, North Rhine-Westphalia, Germany.
Unlabelled:
Assessing if an individual patient has achieved clinically meaningful changes in pain intensity is a core aspect in the evaluation of pain treatments. The aim of the present study was to define minimally clinically significant differences (MCSDs) for the numerical rating scale (0-10 NRS) in adolescents with chronic pain. Data from 153 adolescents who completed an inpatient treatment were analyzed. MCSDs were defined as those cut points that yielded an optimal balance between sensitivity and specificity with regard to patients' global impression of change. The variability of the empirically defined cut points was quantified using bootstrapping. Our results show that raw changes of 1 NRS point and percent changes of 12.5% can be considered MCSDs both within the full sample and within various subsamples of patients. Applying the MCSDs developed for adults to pediatric patients yielded extremely low sensitivities; for example, only 22% of the children who described global improvement met the 50% decrease in pain criterion. Studies evaluating chronic pain treatments for adolescents should use MCSDs that are specifically developed for this group of patients. Raw changes of 1 point and 12.5% on the 0 to 10 NRS should be considered clinically meaningful. On a methodological level, we call for more systematic studies aimed at defining MCSDs that also address the variability of cut point estimates so as to foster the integration of findings.
Perspective:
Many studies are aimed at empirically defining cut points for clinically relevant pain using receiver operating characteristic-based methods. For the first time, we apply these methods to children and show that even when taking into account the variability of the method, cut points specific for children are needed.
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