Literature DB >> 9921701

Predictors of response to acute treatment of chronic and double depression with sertraline or imipramine.

R M Hirschfeld1, J M Russell, P L Delgado, J Fawcett, R A Friedman, W M Harrison, L M Koran, I W Miller, M E Thase, R H Howland, M A Connolly, R J Miceli.   

Abstract

BACKGROUND: The literature on predictors of response to treatment of nonchronic major depression has identified shorter duration of illness, acute onset, and less severity of illness as positive predictors. Unfortunately, there are almost no data on predictors of response to treatment for chronic depression. This study examined predictors of response to pharmacotherapy (sertraline or imipramine) in the treatment of outpatients who had DSM-III-R-defined chronic major or double depression.
METHOD: The acute phase of the Chronic Major Depression and Double Depression Study is a double-blind, randomized, parallel-group 12-week comparison of sertraline and imipramine. Analyses are based on 623 patients who comprised the intent-to-treat sample, of whom 299 were nonresponders and 324 were responders, defined by a priori criteria as either remission or satisfactory therapeutic response. A stepwise logistic multiple regression analysis was performed on candidate clinical, psychosocial, and demographic variables previously identified as statistically significant in an attempt to develop a predictive model of positive antidepressant response.
RESULTS: The sociodemographic variables that were predictive of positive response included living with spouse or partner or being at least a high school graduate. With regard to symptomatology and clinical history, responders had significantly lower baseline depression severity scores. In general, comorbid anxiety, substance abuse, and personality disorders did not influence rates of response. However, the presence of depressive personality traits was associated with a higher nonresponse rate. Among psychosocial variables, longer duration of personal relationships as well as higher baseline quality of life were associated with positive response. A stepwise logistic multiple regression identified 5 variables-living with spouse or partner, higher educational level, passive-aggressive personality, lower introverted-tense personality traits, and higher quality of life--that significantly and independently contributed to the predictive model. This model correctly classified 67% of patients.
CONCLUSION: A higher baseline quality of life, living with spouse or partner, and having more education were the strongest predictors of response to acute pharmacotherapy among chronically depressed patients. Clinical variables and comorbidity were not identified as independent predictors, although personality traits did appear to influence treatment response. Overall, the predictive value of these baseline measures was modest, and therefore of limited clinical utility.

Entities:  

Mesh:

Substances:

Year:  1998        PMID: 9921701     DOI: 10.4088/jcp.v59n1205

Source DB:  PubMed          Journal:  J Clin Psychiatry        ISSN: 0160-6689            Impact factor:   4.384


  18 in total

1.  The impact of comorbid dysthymic disorder on outcome in personality disorders.

Authors:  David J Hellerstein; Andrew E Skodol; Eva Petkova; Hui Xie; John C Markowitz; Shirley Yen; John Gunderson; Carlos Grilo; Maria T Daversa; Thomas H McGlashan
Journal:  Compr Psychiatry       Date:  2010-01-08       Impact factor: 3.735

Review 2.  Pharmacogenetics in psychiatry: are we ready for widespread clinical use?

Authors:  Maria J Arranz; Shitij Kapur
Journal:  Schizophr Bull       Date:  2008-08-27       Impact factor: 9.306

3.  Augmentation of Physician Assessments with Multi-Omics Enhances Predictability of Drug Response: A Case Study of Major Depressive Disorder.

Authors:  Arjun Athreya; Ravishankar Iyer; Drew Neavin; Liewei Wang; Richard Weinshilboum; Rima Kaddurah-Daouk; John Rush; Mark Frye; William Bobo
Journal:  IEEE Comput Intell Mag       Date:  2018-07-20       Impact factor: 11.356

4.  The severity of psychiatric disorders.

Authors:  Mark Zimmerman; Theresa A Morgan; Kasey Stanton
Journal:  World Psychiatry       Date:  2018-10       Impact factor: 49.548

Review 5.  Severe depression: is there a best approach?

Authors:  S B Sonawalla; M Fava
Journal:  CNS Drugs       Date:  2001       Impact factor: 5.749

Review 6.  Prevalence and outcome of partial remission in depression.

Authors:  Richard Tranter; Claire O'Donovan; Praful Chandarana; Sidney Kennedy
Journal:  J Psychiatry Neurosci       Date:  2002-07       Impact factor: 6.186

Review 7.  Psychosocial and clinical predictors of response to pharmacotherapy for depression.

Authors:  R Michael Bagby; Andrew G Ryder; Carolina Cristi
Journal:  J Psychiatry Neurosci       Date:  2002-07       Impact factor: 6.186

8.  Socioeconomic status and anxiety as predictors of antidepressant treatment response and suicidal ideation in older adults.

Authors:  Alex Cohen; Stephen E Gilman; Patricia R Houck; Katalin Szanto; Charles F Reynolds
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2008-09-25       Impact factor: 4.328

Review 9.  Treatment-resistant depression: are animal models of depression fit for purpose?

Authors:  Paul Willner; Catherine Belzung
Journal:  Psychopharmacology (Berl)       Date:  2015-08-21       Impact factor: 4.530

10.  Prediction of response to medication and cognitive therapy in the treatment of moderate to severe depression.

Authors:  Jay C Fournier; Robert J DeRubeis; Richard C Shelton; Steven D Hollon; Jay D Amsterdam; Robert Gallop
Journal:  J Consult Clin Psychol       Date:  2009-08
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.