Optimizing early treatment central in reducing burden of resistant depression

Treatment-resistant depression is associated with a high disease burden, functional impairment, poor health-related quality of life and reduced productivity, according to recent real-world evidence from a European cohort study.1 The fact that resistant depression is a common – but treatable -- condition enhances the importance of early and effective intervention.

Affected individuals and society in general bear a heavy cost due to treatment resistant depression (TRD), Allan Young (King’s College, London, UK) told a satellite meeting at EPA Virtual 2021.

A recent study of 411 patients with TRD (45% of whom had not responded adequately to three or more antidepressants) showed overall work impairment in 61%, unemployment in 30% and long-term sick leave in 19%.1 On the Clinical Global Impressions Scale for Severity, more than half were classified as markedly ill and 14% as severely ill.

According to a generally used definition of failure to respond to at least two consecutive and adequate trials of antidepressants, a third of patients with MDD are resistant to treatment, and this is associated with considerable distress, health care costs including hospitalization and visits to emergency departments, and suicide risk, Professor Young said.2-5  

The best chance of achieving remission is within six months of MDD onset

 

Early window of opportunity

Taking up the theme, Diane McIntosh (Vancouver, British Columbia, Canada) positioned TRD within the wider context of partial responders and those with residual symptoms and functional impairment, and emphasized the window of opportunity afforded by effective early treatment. The best chance of achieving remission is within six months of the first onset of MDD,6 she reported.

In her clinical experience, full symptom resolution should almost always be an initial aim. Where therapy does not prove adequate, the question is between switching to a different monotherapy on the one hand or adjunctive medication on the other.

Every antidepressant is a unique chemical entity, Dr McIntosh emphasized. Patient preference is always a factor, and guidelines such as those from CANMAT may prove helpful7– but treatment should always be tailored to the individual needs of the patient.

At the moment, the only guidance we have is based on clinical factors. But she looked forward to the near future in which there will be markers of likely response to different therapies based on brain structure and function.

Gene expression profiling and inflammatory markers may predict response and help subtype MDD

Examples include patterns of dysfunctional connectivity in limbic and frontostriatal networks, right hippocampal volume, and anterior cingulate activity.8,9

 

The “-omics” will come to our aid

Genomics will also eventually contribute to personalized psychiatry, she suggested. Genetic polymorphisms that may interfere with HPA axis function and limit the normalization induced by antidepressants provide one example. Epigenetic phenomena influencing gene expression that may influence the efficacy of agents acting through the serotonin pathway are another.

Transcriptomics and proteomics are also set to contribute. In the Genome-based Therapeutic Drugs for Depression study, non-responders had higher baseline leukocyte mRNA expression of the pro-inflammatory cytokine interleukin-1β, macrophage inhibiting factor (MIF) and TNF-α.10

There are also data suggesting that likelihood of response relates to levels of C-reactive protein in peripheral blood.11

 

The satellite symposium was supported by Janssen Pharmaceutical Companies of Johnson and Johnson in EMEA

 

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Our correspondent’s highlights from the symposium are meant as a fair representation of the scientific content presented. The views and opinions expressed on this page do not necessarily reflect those of Lundbeck.

References

1. Heerlein K et al. J Affect Disord 2021 Mar 15;283:115-122. doi: 10.1016/j.jad.2020.11.124.

2. Bartova L et al. World J Biol Psychiatry 2019; 20: 427-448

3. Lépine J-P, Briley M. Neuropsychiatr Dis Treat 2011; 7(Suppl 1): 3-7

4. Demyttenaere K, Van Duppen Z. Int J Neuropsychopharmacol 2019; 22: 85-92

5. Jaffe DH et al. BMC Psychiatry 2019 Aug 7;19(1):247

6. Bukh JD et al. J Affect Disord 2013; 145 :42-8

7. Kennedy SH et al. Can J Psychiatry 2016; 61: 540–56

8. Drysdale AT et al. Nat Med 2017; 23: 28-38

9. Fu CHY et al. Neurobiol Dis 2013; 52: 75-83

10. Cattaneo A et al. Neuropsychopharmacology 2013;38:377-85

11. Chamberlain SR et al. Br J Psychiatry 2019; 214: 11-19

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