While there is some indication from studies in the acute phase of antidepressant treatment that there are differences in the timing of improvement in symptoms, relatively little work has explored the patterns of change for specific symptom clusters and the predictability of these changes to signal eventual response during the acute phase of treatment. This article investigates the use of clusters of symptoms on the 17-item Hamilton Rating Scale for Depression (HAM-D-17) to define the pattern of late response versus nonresponse to antidepressant medication.
Using principal component analysis, the HAM-D-17 was divided into 4 symptom clusters (mood, sleep/psychic anxiety, appetite, and somatic anxiety/weight). Data for 996 patients with major depressive disorder (DSM-III-R criteria), who participated in a 12-week acute phase study with nefazodone, were subjected to a post hoc analysis of changes in symptom cluster scores. Patients were divided into 3 groups: early responders (< 4 weeks), late responders (4-12 weeks), and nonresponders (> 12 weeks) as defined by < 50% reduction in HAM-D-17 scores from baseline. The late-responder and nonresponder groups were subjected to the principal component analysis. Data were collected from October 1992 to November 1994.
There were significant differences in the pattern of symptom change on the mood cluster (weeks 3-4) (p < .0001), the sleep/psychic anxiety cluster (weeks 3-4) (p < .003), and the somatic anxiety/weight cluster (weeks 3-4) (p < .01) for the late responders compared to the nonresponders. Using change scores, a discriminant function analysis correctly assigned 127 of the 182 late responders and 85 of the 133 nonresponders, or 70% of the late responders and 64% of the nonresponders, to their final response groups.
Monitoring changes in symptom clusters from the HAM-D-17 during this crucial early stage (first 4 weeks) can be used to distinguish late responders (after week 4) from nonresponders. Successful identification of nonresponders based on symptom cluster change in the first 4 weeks would facilitate a shortening of an ineffective treatment trial and allow for necessary changes in treatment strategy, helping physicians more closely follow treatment guidelines.
"Examples of potential demographic predictors of treatment response have included age, gender, marital status, family history of treatment response, and socioeconomic factors
. Clinical predictors have included diagnostic subtype
[21,22], severity of depression
, symptom profiles
, patient treatment preference
, early life stress
, personality profiles
, previous treatment
, psychomotor speed
, and co-morbid diagnoses
. Physiologic predictors have included auditory evoked potentials
, event-related potentials
, and quantitative electroencephalograms
[Show abstract][Hide abstract] ABSTRACT: Background
Limited controlled data exist to guide treatment choices for clinicians caring for patients with major depressive disorder (MDD). Although many putative predictors of treatment response have been reported, most were identified through retrospective analyses of existing datasets and very few have been replicated in a manner that can impact clinical practice. One major confound in previous studies examining predictors of treatment response is the patient’s treatment history, which may affect both the predictor of interest and treatment outcomes. Moreover, prior treatment history provides an important source of selection bias, thereby limiting generalizability. Consequently, we initiated a randomized clinical trial designed to identify factors that moderate response to three treatments for MDD among patients never treated previously for the condition.
Treatment-naïve adults aged 18 to 65 years with moderate-to-severe, non-psychotic MDD are randomized equally to one of three 12-week treatment arms: (1) cognitive behavior therapy (CBT, 16 sessions); (2) duloxetine (30–60 mg/d); or (3) escitalopram (10–20 mg/d). Prior to randomization, patients undergo multiple assessments, including resting state functional magnetic resonance imaging (fMRI), immune markers, DNA and gene expression products, and dexamethasone-corticotropin-releasing hormone (Dex/CRH) testing. Prior to or shortly after randomization, patients also complete a comprehensive personality assessment. Repeat assessment of the biological measures (fMRI, immune markers, and gene expression products) occurs at an early time-point in treatment, and upon completion of 12-week treatment, when a second Dex/CRH test is also conducted. Patients remitting by the end of this acute treatment phase are then eligible to enter a 21-month follow-up phase, with quarterly visits to monitor for recurrence. Non-remitters are offered augmentation treatment for a second 12-week course of treatment, during which they receive a combination of CBT and antidepressant medication. Predictors of the primary outcome, remission, will be identified for overall and treatment-specific effects, and a statistical model incorporating multiple predictors will be developed to predict outcomes.
The PReDICT study’s evaluation of biological, psychological, and clinical factors that may differentially impact treatment outcomes represents a sizeable step toward developing personalized treatments for MDD. Identified predictors should help guide the selection of initial treatments, and identify those patients most vulnerable to recurrence, who thus warrant maintenance or combination treatments to achieve and maintain wellness.
Clinicaltrials.gov Identifier: NCT00360399. Registered 02 AUG 2006. First patient randomized 09 FEB 2007.
"A number of features could be measured with a number of instruments. This article is not aimed for a review of all possible predictors [10,13,14,16,17]. We followed the guideline of investigating features previously associated with outcome and using validated instruments used in previous studies. "
[Show abstract][Hide abstract] ABSTRACT: Clinicians face everyday the complexity of depression. Available pharmacotherapies and psychotherapies improve patients suffering in a large part of subjects, however up to half of patients do not respond to treatment. Clinicians may forecast to a good extent if a given patient will respond or not, based on a number of data and sensations that emerge from face to face assessment. Conversely, clinical predictors of non response emerging from literature are largely unsatisfactory.
Here we try to fill this gap, suggesting a comprehensive assessment of patients that may overcome the limitation of standardized assessments and detecting the factors that plausibly contribute to so marked differences in depressive disorders outcome.
For this aim we present and discuss two clinical cases. Mr. A was an industrial manager who came to psychiatric evaluation with a severe depressive episode. His employment was demanding and the depressive episode undermined his capacity to manage it. Based on standardized assessment, Mr. A condition appeared severe and potentially dramatic. Mrs. B was a housewife who came to psychiatric evaluation with a moderate depressive episode. Literature predictors would suggest Mrs. B state as associated with a more favourable outcome.
However the clinician impression was not converging with the standardized assessment and in fact the outcome will reverse the prediction based on the initial formal standard evaluation.
Although the present report is based on two clinical cases and no generalizability is possible, a more detailed analysis of personality, temperament, defense mechanisms, self esteem, intelligence and social adjustment may allow to formalize the clinical impressions used by clinicians for biologic and pharmacologic studies.
Annals of General Psychiatry 02/2007; 6(1):5. DOI:10.1186/1744-859X-6-5 · 1.40 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A revision of the British Association for Psychopharmacology guidelines for treating depressive disorders with antidepressants was undertaken in order to specify the scope and target of the guidelines and to update the recommendations based explicitly on the available evidence. A consensus meeting, involving experts in depressive disorders and their treatment, reviewed key areas and considered the strength of evidence and clinical implications. The guidelines were drawn up after extensive feedback from participants and interested parties. A literature review is given which identifies the quality of evidence followed by recommendations, the strength of which are based on the level of evidence. The guidelines cover the nature and detection of depressive disorders, acute treatment with antidepressant drugs, choice of drug versus alternative treatment, practical issues in prescribing, management when initial treatment fails, continuation treatment, maintenance treatment to prevent recurrence and stopping treatment.
Journal of Psychopharmacology 04/2000; 14(1):3-20. DOI:10.1177/026988110001400101 · 3.59 Impact Factor
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