Results of three analytical approaches on long-term efficacy of etanercept for psoriasis in daily practice

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• 作者：Paula P.M. van Lü ; mig ; MD ; ^{P.vanLumig@derma.umcn.nl} ; Rieke J.B. Driessen ; MD ; PhD ; Wietske Kievit ; PhD ; Jan B.M. Boezeman ; MSc ; Peter C.M. van de Kerkhof ; MD ; PhD ; Elke M.G.J. de Jong ; MD ; PhD
• 关键词：biologics ; daily practice ; etanercept ; long-term efficacy ; method of analysis ; psoriasis ; registry
• 刊名：Journal of the American Academy of Dermatology
• 出版年：2013
• 出版时间：January, 2013
• 年：2013
• 卷：68
• 期：1
• 页码：57-63
• 全文大小：403 K

文摘

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class=""h4"">Background

A problem encountered when analyzing long-term efficacy is that the number of patients in follow-up decreases with time for different reasons. The method used to account for missing observations for the therapy under analysis has a great influence on the inference of efficacy.

class=""h4"">Objective

To describe the long-term efficacy of etanercept for psoriasis in daily practice using 3 analytical approaches.

class=""h4"">Methods

Prospective data from a cohort of patients with psoriasis treated with etanercept for at least 24 weeks were analyzed using 3 analytical approaches: as treated analysis, intention-to-treat analysis (ITT) with last observation carried forward (LOCF) and intention-to-treat analysis with modified nonresponder imputation (modified NRI).

class=""h4"">Results

One hundred thirty-one patients were treated with etanercept during 134 treatment episodes with a mean treatment duration of 2.7 years. The maximum follow-up was 6.0 years. The methodological approach chosen had a great influence. Psoriasis Area and Severity Index (PASI) 75 response rates varied from 60 % in the as-treated approach to 34 % in LOCF and to 29 % in modified NRI at week 264.

class=""h4"">Limitations

All analytical methods applied have limitations. Other outcome measures could be used to overcome the bias introduced by each method of analysis, such as drug survival.

class=""h4"">Conclusions

The methodological approach chosen to analyze long-term efficacy data has a great influence on the inferences that may be drawn regarding the degree of efficacy. Therefore we support the use of different methods to present long-term efficacy data.