Predictive factors of response to intravenous ciclosporin in severe ulcerative colitis: the development of a novel prediction formula

Authors


Correspondence to:

Dr T. Katsuno, Department of Medicine and Clinical Oncology (K1), Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba-shi 260-8670, Japan.

E-mail: katsuno@faculty.chiba-u.jp

Summary

Background

When treating patients with severe ulcerative colitis (UC), accurate prediction of drug efficacy contributes to early clinical decision-making.

Aim

To identify predictive factors and to develop a reliable prediction formula and a decision tree of response to intravenous ciclosporin treatment for severe UC.

Methods

Patients included in this study were those diagnosed with refractory severe UC who had undergone ciclosporin treatment between December 2004 and March 2011 at a tertiary referral centre in Japan. Demographic and clinical parameters from all patients were analysed by multivariate statistics.

Results

Fifty-two patients were included in this study (36.5% men with an average age of ciclosporin initiation of 40.2 ± 15.6 years). Thirty-four patients (65.4%) were responders to the treatment with ciclosporin and avoided colectomy, 18 patients (34.6%) were nonresponders and underwent colectomy. Stepwise multiple logistic regression analysis identified four independent predictive factors of response to intravenous ciclosporin: age at hospitalisation (AGE), platelet count (×104/μL) on the first day (PLA), Lichtiger score on the third day (LIC) and total protein (g/dL) on the third day minus total protein on the first day (ΔTP). The calculation formula (8.5 − 0.16 × AGE + 0.21 × PLA − 0.61 × LIC + 2.3 × ΔTP < 0) predicted colectomy with an accuracy of 88.5% and the decision tree predicted colectomy with an accuracy of 90.4%.

Conclusion

The novel calculation formula and the decision tree effectively predict the clinical outcome of ciclosporin treatment for severe ulcerative colitis as early as on day 3 after starting ciclosporin treatment.

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