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Institute for Response-Genetics (e.V.)

Prof. Dr. Hans H. Stassen, Chairman

(Formerly Associated Institute of the University of Zurich)

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Assessing Onset of Improvement under Antidepressants

Conventional repeated measurements analysis of variance suggests that response to antidepressants is slow, and that differences between antidepressants and placebo do not normally reach statistical significance until the third to fourth week of treatment. This statistical "response lag" has finally led to the "delayed onset of action" hypothesis, although response- to-treatment and onset-of-action represent two principally different concepts that relate to different aspects of efficacy of antidepressant drug therapy. While efficacy in terms of response-to-treatment has its main focus on the proportion of patients in whom antidepressants induce therapeutic response, onset-of-action refers to the speed at which symptoms reduce under antidepressants in comparison to placebo. Standard drug trial procedures tend to obscure differences in onset of action across drugs (as well as across patients), because such procedures rely upon mean depression scores derived from studies which amalgamate separate depressive subgroups, rapid and slow remitters, as well as partial remitters, non-remitters and premature withdrawals.

Survival Analysis and Cure Models

In the conventional repeated mesurements approach, psychopathology scores assessed at weekly intervals are analysed as a function of time, and assessment times are represented as fixed independent variables in a (linear) regression model when testing for time differences in rates of symptom reduction. This is equivalent to a regression of the sample's mean scores on assessement time, so that a justification of the "fast acting" claim of the newer antidepressants is, from the methodological point of view, difficult to accomplish. An alternative approach is survival analysis where time is treated as a function of symptom reduction (dependent variable). This has the advantage that variations around the prespecified, cross-sectional observation days (typically ±2 days) can be incorporated into the model, thus providing (1) a better temporal resolution with respect to the individual course of recovery from depression, (2) a way to distinguish between early and late responders, and (3) the possibility to assess the predictive value of early improvement with respect to later outcome. Additionally, the method allows one to take into account that treatment response has not been observed in a subgroup of patients due to premature withdrawal or the limited observation time.

Early Improvement

Central to all approaches to determining early onset of antidepressant action is the appropriate definition of improvement (used as indicator of a specific drug action). We distinguish between "relative improvement", defined by a percentage baseline score reduction regardless of the subsequent course of depressive illness that may include a significant deterioration; "sustained relative improvement", which requires a prespecified percentage baseline score reduction without subsequent deterioration beyond achieved improvement score; "sustained absolute improvement", which requires a prespecified percentage baseline score reduction along with the attainment of a prespecified threshold value (e.g. HAMD-17 score of 10) without subsequent deterioration.

References

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Bhake R, Kluckner V, Stassen HH, Russell GM, Leendertz J, Stevens K, Linthorst ACE, Lightman S: Continuous Free Cortisol Profiles – Circadian Rhythms in Healthy Men. J Clinical Endocrinology & Metabolism 2019; 104(12): 5935-5947
Braun S, Bridler R, Müller N, Schwarz MJ, Seifritz E, Weisbrod M, Zgraggen A, Stassen HH: Inflammatory Processes and Schizophrenia: Two Independent Lines of Evidence from a Study of Twins Discordant and Concordant for Schizophrenic Disorders. Eur Arch Psychiatry Clin Neurosci 2017; 267: 377-389 [get the article]
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Greil W, Zhang X, Stassen HH, Grohmann R, Bridler R, Hasler G, Toto S, Bleich S, Kasper S: Cutaneous adverse drug reactions to psychotropic drugs and their risk factors - a case-control study. Eur Neuropsychopharmacol. 2019; 29(1): 111-121 [get the article]
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Lötscher K, Anghelescu IG, Braun S, Bridler R, Stassen HH: Polypharmacy in psychiatry: clinical practice versus empirical evidence. Eur Neuropsychopharmacol. 2010; 20 (Suppl. 3): 378-379
Mohr C, Braun S, Bridler R, Chmetz F, Delfino JP, Kluckner VJ, Lott P, Schrag Y, Seifritz E, Stassen HH: Insufficient Coping Behavior under Chronic Stress and Vulnerability to Psychiatric Disorders. Psychopathology 2014; 47: 235-243
Moragrega I, Bridler R, Mohr C, Possenti M, Rochat D, Sanchez Parramon J, Stassen HH: Monitoring Mental Health and the Effects of Therapeutic Interventions through Self-Assessment Voice Analyses. Res Psychother. 2021 [submitted for publication]
Motivala SJ, Sarfatti A, Olmos L, Irwin MR. Inflammatory markers and sleep disturbance in major depression. Psychosom Med. 2005; 67(2): 187-194
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Skilton MR, Moulin P, Terra JL, Bonnet F. Associations between anxiety, depression, and the metabolic syndrome. Biol Psychiatry. 2007; 62(11): 1251-1257
Stassen HH, Angst J, Hell D, Scharfetter C, Szegedi A. Is there a common resilience mechanism underlying antidepressant drug response? Evidence from 2848 patients. J Clin Psychiatry. 2007; 68(8): 1195-1205
Stassen HH, Anghelescu IG, Braun S, Hoffmann K, Rujescu D, Scharfetter C, Szegedi A, Tadic A: Vulnerability to major psychiatric disorders, response to treatment and medical comorbidity — shared genetic factors? Eur Neuropsychopharmacol. 2009; 19 (Suppl. 3): 262
Stassen HH, Anghelescu IG, Angst J, Böker H, Lötscher K, Rujescu D, Szegedi A, Scharfetter C: Predicting Response to Psychopharmacological Treatment. Survey of Recent Results. Pharmacopsychiatry 2011; 44: 263-272
Stassen HH, Delfino JP, Kluckner VJ, Lott P, Mohr C: Vulnerabilität und psychische Erkrankung. Swiss Archives of Neurology and Psychiatry 2014; 165(5): 152-157
Stassen HH: Heterogeneity of schizophrenic disorders and link to chronically elevated IgM values. Neurology, psychiatry and brain research 2018; 29: 23-24
Stassen HH, Bachmann S, Bridler R, Cattapan K, Herzig D, Schneeberger A, Seifritz E: Inflammatory Processes linked to Major Depression & Schizophrenic Disorders and the Effects of Polypharmacy in Psychiatry: Evidence from a longitudinal Study of 279 Patients under Therapy. Eur Arch Psychiatry Clin Neurosci. 2021; 271(3): 507-520
[get the article] Stassen HH, Bachmann S, Bridler R, Cattapan K, Herzig D, Schneeberger A, Seifritz E: Detailing the Effects of Polypharmacy in Psychiatry: Longitudinal Study of 320 Patients Hospitalized for Depression or Schizophrenia. Eur Arch Psychiatry Clin Neurosci. 2021 [submitted for publication]
Szegedi A, Jansen WT, Van Willigenburg AP, Van der Meulen E, Stassen HH, Thase ME: Early improvement as a predictor of treatment outcome in patients with major depressive disorder: Why the first 2 weeks really matter —evidence from 6562 patients. J Clin Psychiatry 2009; 70(3): 344-353
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Thase ME. Comparing the methods used to compare antidepressants. Psychopharmacol Bull 2002; 36 Suppl 1: 1-17
Zhang M, Bridler R, Mohr C, Moragrega I, Sun N, Xu Z, Yang Z, Possenti M, Stassen HH: Early Detection of the Risk of Developing Psychiatric Disorders: A Study of 461 Chinese University Students under Chronic Stress. Psychopathology 2019; 52(6): 367-377 [get the article]

 

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cure models
One-dimensional cure models combine "incidence" and "latency" in one single model. The distribution of the times to onset of improvement under imipramine (circles, n=506), moclobemide (triangles, n=580) and placebo (squares, n=191) suggest significant between-treatment differences.
By contrast, 2-dimensional cure models distinguish between "incidence" and "latency". Results show that the observed differences can almost entirely be explained by "incidence" (>90%) whereas "latency" explains less than 10%.
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