2026 ECNP Congress

PS04-4192

Beyond pharmacological staging: biopsychosocial complexity in esketamine-referred treatment-resistant depression

Diogo Santos — I. Gomes, G. Lima · Unidade Local de Saúde Arco Ribeirinho, Departamento de Psiquiatria e Saúde Mental, Barreiro, Portugal

2026 ECNP Congress

Background

Treatment-resistant depression (TRD) affects up to 40% of patients with major depressive disorder, carrying individual and societal burden [1]. Staging models have been centered on pharmacological non-response; however TRD is increasingly recognised as a multidimensional condition encompassing severe psychiatric and somatic comorbidity, personality traits, psychosocial adversity and functional impairment [2]. The expansion of novel interventions - including intranasal esketamine - into tertiary care brought into focus a subset of patients whose complexity extends well beyond treatment failure [3]. Structured complexity instruments, including the Dutch Measure for Quantification of Treatment Resistance in Depression (DM-TRD), identified in systematic reviews of clinical prediction tools [4], and the INTERMED, validated across complex medical-psychiatric populations[5], offer plausible frameworks to characterise this burden; however their combined application in esketamine-referred cohorts has yet to be explored.

Objectives

To characterise the biopsychosocial complexity profile of patients referred for esketamine using INTERMED as a structured complexity measure and DM-TRD as a disorder-specific staging tool.

Methods

This cross-sectional pilot study retrospectively analysed 15 consecutive adult patients with TRD referred for intranasal esketamine in a tertiary Psychiatry department. INTERMED and DM-TRD were scored from clinical records. Somatic comorbidity was quantified using the Cumulative Illness Rating Scale (CIRS). Associations between instruments/subscales and clinical variables were examined using Spearman correlations; analyses were exploratory/ hypothesis-generating. Three representative cases were selected to illustrate contrasting profiles across the DM-TRD/INTERMED space.

Results

About three-quarters of patients had a chronic course (median 8 years, IQR 4–8), two-thirds had at least one psychiatric comorbidity and 40% had history of suicide attempts. At referral, 60% were experiencing a depressive episode lasting >2 years and approximately half presented with severe-to-extreme illness. Psychopharmacological burden was high: median fluoxetine-equivalent dose 60.2mg (IQR 43.7–88.8), 86.7% were on antipsychotics and 86.7% exceeding 8mg diazepam-equivalents/daily. Retrospective INTERMED scoring was feasible across all records. The majority met case complexity criteria (INTERMED>20: 86.7%; median 32, IQR 25–45), suggesting limited discriminatory capacity of the standard threshold in this population. Median DM-TRD score was 19.5 (IQR 17–21). INTERMED total correlated moderately with DM-TRD (rho=.518, p=.048), driven by the Psychological (rho=.607,p=.016) and Social (rho=.637, p=.011) axes; Biological and Health Care axes showed no significant association. The Biological axis correlated strongly with somatic comorbidity (CIRS: rho=.767,p<.001). Both somatic burden and the Health Care axis inversely correlated with prior psychotherapy trials (rho=−.604, p=.017 and rho=−.682, p=.005, respectively), suggesting that patients with greater somatic and healthcare complexity may be less likely to access structured psychological interventions. Scatter plot inspection revealed variability in INTERMED scores at comparable DM-TRD levels, indicating heterogeneity beyond pharmacological staging. Three vignettes illustrate contrasting complexity-resistance profiles.

Conclusions

Esketamine-referred TRD patients exhibited multidimensional burden beyond pharmacocentric staging. Dissociation between DM-TRD and INTERMED Biological and Health Care domains suggests somatic comorbidity and healthcare-related factors as under-recognised drivers of complexity. Marked within-group heterogeneity indicates that some highly complex patients may not be adequately captured by formal TRD definitions, potentially falling outside conventional treatment pathways. Retrospective INTERMED scoring was feasible, supporting prospective data-driven approaches (e.g., cluster analysis) to identify clinically meaningful subgroups and optimise screening and treatment allocation.

References

  1. Fiorillo, A., Demyttenaere, K., Martiadis, V., Martinotti, G., 2025. Treatment resistant depression (TRD): Epidemiology, clinic, burden and treatment. Front. Psychiatry 16:1588902. doi:10.3389/fpsyt.2025.1588902
  2. Paganin, W., 2026. Treatment-resistant depression: Time to rethink current definitions and clinical practice. Front. Psychiatry 16:1733678. doi:10.3389/fpsyt.2025.1733678
  3. Rost, F., Fonagy, P., Booker, T., Gonsard, A., de Felice, G., Asseburg, L., et al., 2024. The complexity of treatment-resistant depression: A data-driven approach. J. Affect. Disord. 358:292–301. doi:10.1016/j.jad.2024.04.093
  4. van Dijk, DA., Stoel, NG., Meijer, RJ., Repko, RJE., van den Boogaard, ThM., Ruhé, HG., et al., 2025. Clinical prediction instruments available for clinicians treating major depressive disorder: A systematic review. J. Affect. Disord. 382:68–84. doi:10.1016/j.jad.2025.04.050
  5. Meller, W., Specker, S., Schultz, P., Kishi, Y., Thurber, S., Kathol, R., 2015. Using the INTERMED complexity instrument for a retrospective analysis of patients presenting with medical illness, substance use disorder, and other psychiatric illnesses. Ann. Clin. Psychiatry 27(1):39–43. doi:10.1177/104012371502700107