Prospective Derivation and Validation of a Clinical Prediction Rule for Recurrent Clostridium difficile Infection
Background & Aims
Prevention of recurrent Clostridium difficile infection (CDI) is a substantial therapeutic challenge. A previous prospective study of 63 patients with CDI identified risk factors associated with recurrence. This study aimed to develop a prediction rule for recurrent CDI using the above derivation cohort and prospectively evaluate the performance of this rule in an independent validation cohort.
Methods
The clinical prediction rule was developed by multivariate logistic regression analysis and included the following variables: age >65 years, severe or fulminant illness (by the Horn index), and additional antibiotic use after CDI therapy. A second rule combined data on serum concentrations of immunoglobulin G (IgG) against toxin A with the clinical predictors. Both rules were then evaluated prospectively in an independent cohort of 89 patients with CDI.
Results
The clinical prediction rule discriminated between patients with and without recurrent CDI, with an area under the curve of the receiver-operating-characteristic curve of 0.83 (95% confidence interval [CI]: 0.70–0.95) in the derivation cohort and 0.80 (95% CI: 0.67–0.92) in the validation cohort. The rule correctly classified 77.3% (95% CI: 62.2%–88.5%) and 71.9% (95% CI: 59.2%–82.4%) of patients in the derivation and validation cohorts, respectively. The combined rule performed well in the derivation cohort but not in the validation cohort (area under the curve of the receiver-operating-characteristic curve, 0.89 vs 0.62; diagnostic accuracy, 93.8% vs 69.2%, respectively).
Conclusions
We prospectively derived and validated a clinical prediction rule for recurrent CDI that is simple, reliable, and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent recurrence.
Abbreviations used in this paper: AUC, area under the curve, CDI, Clostridium difficile infection, NPV, negative predictive value, PPV, positive predictive value, ROC, receiver-operating-characteristic curve
Conflicts of interest The authors disclose the following: During the past 2 years, Ciarán P. Kelly has acted as a scientific consultant for Acambis, Actelion, BioHelix, Genzyme, Replidyne, Salix, and ViroPharm and has received research grant funding from Actelion Inc, Genzyme Inc, Massachusetts Biologics Laboratories, Medarex Inc, and Salix Pharmaceuticals, companies that are producing or developing treatments for C difficile infection. No potential conflicts of interest exist for other authors.
Funding Supported by grants from the National Institutes of Health (RO-1 AI053069 (to C.P.K.); K30-HL04095 for the Scholars in Clinical Science Program at Harvard Medical School (in which Mary Y. Hu was enrolled); and T32-DK0776 (to S.M. and D.A.L.); and the Irish Health Research Board (RP/2005/72, to L.K.).
PII: S0016-5085(08)02262-2
doi:10.1053/j.gastro.2008.12.038
© 2009 AGA Institute. Published by Elsevier Inc. All rights reserved.
Refers to article:
- Reining in Recurrent Clostridium difficile Infection—Who's at Risk? , 26 February 2009
