A Composite Approach That Includes Dropout Rates When Analyzing Efficacy Data in Clinical Trials of Antipsychotic Medications | Zendy

Jonathan Rabinowitz | Zendy; Ori Davidov | Zendy

Open Access

A Composite Approach That Includes Dropout Rates When Analyzing Efficacy Data in Clinical Trials of Antipsychotic Medications

Author(s) -

Jonathan Rabinowitz,

Ori Davidov

Publication year - 2007

Publication title -

schizophrenia bulletin

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.823

H-Index - 190

eISSN - 1745-1707

pISSN - 0586-7614

DOI - 10.1093/schbul/sbm107

Subject(s) - tolerability , medicine , randomized controlled trial , clinical trial , antipsychotic , dropout (neural networks) , medline , schizophrenia (object oriented programming) , psychology , psychiatry , adverse effect , computer science , machine learning , political science , law

Often, outcomes in clinical trials of antipsychotic medications are examined using last observation carried forward (LOCF). One limitation of LOCF and other common approaches is that they overlook the meaning underpinning trial completion and noncompletion. Noncompletion often relates to lack of drug tolerability. Because long-term treatment is often indicated, noncompletion is an important outcome. An alternative approach is to test the composite hypothesis of the difference between (a) completion rates and (b) efficacy of complete cases. Studies to date have not applied this relatively new method.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research