Using the entire cohort in the receiver operating characteristic analysis maximizes precision of the minimal important difference

Dan Turner*, Holger J. Schünemann, Lauren E. Griffith, Dorcas E. Beaton, Anne M. Griffiths, Jeffrey N. Critch, Gordon H. Guyatt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

87 Scopus citations

Abstract

Objective: We compared the minimal important difference (MID) values obtained by the receiver operating characteristics (ROC) curve approach using different strategies on four outcome measures to guide the optimal use of ROC curve. Study Design and Setting: Studies of two psychometric scales (Rhinoconjunctivitis Quality-of-Life Questionnaire [RQLQ] and Chronic Respiratory Questionnaire [CRQ]) and two clinimetric indices (Pediatric Ulcerative Colitis Activity Index [PUCAI] and Pediatric Crohn's Disease Activity Index [PCDAI]) instruments provided prospective longitudinal data. The MID was calculated from 7- and 15-point global ratings of change dichotomized in multiple ways, using the ROC curve method. Analysis was performed twice: first, using only the two groups adjacent to the dichotomization point (e.g., including only patients who had a small vs. moderate change); and second, using the entire cohort split at the same cutoff (e.g., including both unchanged subjects with those with small change vs. those who experienced moderate or large change combined). Results: Using the entire cohort, rather than just those with ratings adjacent to the dichotomization point, yielded more precise and sensible MID estimates. With one exception, high precision was obtained when using the ROC curve method for any cutoff on the rating scale. Conclusion: When calculating the MID using the ROC curve method, the use of the entire cohort maximizes precision.

Original languageAmerican English
Pages (from-to)374-379
Number of pages6
JournalJournal of Clinical Epidemiology
Volume62
Issue number4
DOIs
StatePublished - Apr 2009
Externally publishedYes

Bibliographical note

Funding Information:
No funding was received for this study. Dr Beaton was supported by a CIHR New Investigators award during the conduct of this research. Dr. Holger J. Schünemann was funded by a European Commission: The human factor, mobility and Marie Curie Actions. Scientist Reintegration Grant (IGR 42192).

Keywords

  • CRQ
  • MID
  • PCDAI
  • PUCAI
  • ROC
  • RQLQ

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