The Illness Density Index (IDI) : A longitudinal measure of treatment efficacy

• Type of Material: Article
• Authors: Mary E Kelley, Emory University; Alexandre R Franco, Emory University; Helen S Mayberg, Emory University; Paul E Holtzheimer, Emory University
• Language: English
• Date: 2012-10
• Publisher: SAGE Publications (UK and US)
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © The Author(s), 2012
• Final Published Version (URL): http://ctj.sagepub.com/content/9/5/596
• Title of Journal or Parent Work: Clinical Trials
• ISSN: 1740-7745
• Volume: 9
• Issue: 5
• Start Page: 596
• End Page: 604
• Grant/Funding Information: This study was financially supported by NIMH 1RO1 MH073719 (HSM), Dana Foundation (HSM), Stanley Medical Research Institute (HSM), Woodruff Foundation (HSM), and K23 MH077869 (PEH).
• Keywords: fluctuations in symptoms; Illness Density Index; quantitative index; psychiatric disorders; variance in change over time; treatment
• Research Categories: Biology, Biostatistics; Psychology, Clinical

Abstract

Background A reliable and meaningful quantitative index of success is paramount in the trial of any new treatment. However, existing methods for defining response and remission for treatments tested for psychiatric disorders are limited in that they often minimize the variance in change over time among individual patients and generally use arbitrarily chosen levels of functioning at specified times during treatment. Purpose To suggest and determine the properties of an alternative measure of treatment success, the Illness Density Index (IDI), that may be more sensitive to fluctuations in symptoms over the course of treatment compared to existing measures. Methods We examined data from 64 depressed patients with multiple assessments of the Hamilton Depression Rating Scale (HDRS) over 12 weeks of randomized treatment in order to compare and contrast varying numerical definitions of response and remission, including percent change and linear slope over time. Results Examination of the indices comparing the within-sample rank of individual patients revealed that these indices agree in cases where patients have little or no response as well as clear and sustained response, while they differ in patients who have a slow (or late) response as well as relapse during the treatment course. Limitations The measure may not be useful for all types of studies, especially short-term treatment trials. Conclusions The IDI is highly correlated with both categorical (e.g., remission) and continuous (e.g., percent change) definitions of treatment success. Furthermore, it differentiates certain trajectories of change that current definitions do not. Thus, the proposed index may be a valuable addition to current measures of efficacy, especially when trying to identify biological substrates of illness or predictors of long-term outcome.