A TRANSDIAGNOSTIC PRODROME FOR SEVERE MENTAL DISORDERS: AN ELECTRONIC HEALTH RECORD STUDY

Abstract Background Effective prevention of severe mental disorders (SMD) rely on accurate knowledge of the duration and first presentation, time-course and transdiagnosticity of their prodromal stages. This has mostly been investigated in “look-back” studies which have limitations including the use of interviews that are not integrated into clinical practice, small sample sizes and substantial recall biases. Moreover, it is unclear to what extent SMD may display transdiagnostic prodromal symptoms. Aims & Objectives To address these limitations, we take advantage of Electronic Health Records (EHRs) routinely employed in secondary mental healthcare, constituting a pool of untapped real-world data. We aim to describe and compare the (1) incidence and duration of the first prodromal clusters, (2) mean number of occurrences of prodromal clusters between SMD diagnostic groups and prodromal years, and (3) total number of occurrences of prodromal features. Method Clinical register-based EHR cohort including all individuals accessing the South London and the Maudsley (SLaM) services (2008-2021) and receiving a primary (i.e. not comorbid) diagnosis of any ICD-10 mental disorder that falls under SMD. These diagnoses were clustered into diagnostic groups: non-psychotic unipolar mood disorders (UMD), psychotic bipolar mood disorders (BMD), and psychotic disorders (PSY). Natural language processing algorithms were used to extract monthly occurrences of 65 prodromal features (symptoms and substance use) from the index date of diagnosis until their first occurrence. Prodromal features were grouped into eight prodromal clusters (depressive, disorganised, catatonic, manic, negative, positive, substance use and other symptoms).For aim 1, the duration and incidence of the first prodromal clusters were compared between SMD groups with Cohen’ s F (f) and D (d) effect sizes derived from one-way ANOVA. For aim 2, the time-course (mean occurrences) of prodromal clusters was compared between SMD groups over 12 prodromal years using a linear mixed-effects model. For aim 3, the mean occurrence of each prodromal feature was compared with three-wise and pair-wise discriminability scores between SMD groups. Results 26,975 individuals were included (NBMD=13,422; BD=2,506; PSY=11,047; mean age 41.8 years [SD=17.4]; 55% female; 52% white ethnicity). Prodromal periods were shorter in NBMD (median[IQR]= 18[36] months) than BD (26[35], d=0.21) and PSY (24[38], d=0.18). Most individuals presented multiple first prodromal clusters, with the most common being non-specific (‘other’; 88% UMD, 85% BMD, 78% PSY). The only first prodromal cluster with a medium-sized difference between the SMD groups was positive symptoms (f=0.30). Time-course analysis showed an increase in prodromal cluster occurrences approaching SMD onset. Feature occurrence across the prodromal period showed small/negligible differences between SMD groups, suggesting that most features are transdiagnostic, except for positive symptoms (e.g. paranoia, f=0.40). Discussion & Conclusion Taken together, our findings show minimal differences in the duration and first presentation of SMD prodromes in secondary mental health care. All features intensified as individuals approached SMD onset, and other than positive symptoms, are transdiagnostic. These results support proposals to develop transdiagnostic preventive services for affective and psychotic disorders detected in secondary mental healthcare.

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Journal
The International Journal of Neuropsychopharmacology
Published
2025-02-01
DOI
https://doi.org/10.1093/ijnp/pyae059.400
Citations
1
Primary Topic
Chronic Disease Management Strategies
Type
article
Field-Weighted Citation Impact
1.35
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article

A TRANSDIAGNOSTIC PRODROME FOR SEVERE MENTAL DISORDERS: AN ELECTRONIC HEALTH RECORD STUDY

Dominic Oliver, Rashmi Patel, Daisy Kornblum, Umberto Provenzani et al.
1 citations
The International Journal of Neuropsychopharmacology
Chronic Disease Management Strategies
1.35
article

A TRANSDIAGNOSTIC PRODROME FOR SEVERE MENTAL DISORDERS: AN ELECTRONIC HEALTH RECORD STUDY

Dominic Oliver, Rashmi Patel, Daisy Kornblum, Umberto Provenzani, Kamil Krakowski, Paolo Fusar‐Poli, Stefano Damiani, Maite Arribas, Hitesh Shetty, Daniel Ståhl, Philip K. McGuire, Nikolaos Koutsouleris
article en
1 citations

Abstract

Abstract Background Effective prevention of severe mental disorders (SMD) rely on accurate knowledge of the duration and first presentation, time-course and transdiagnosticity of their prodromal stages. This has mostly been investigated in “look-back” studies which have limitations including the use of interviews that are not integrated into clinical practice, small sample sizes and substantial recall biases. Moreover, it is unclear to what extent SMD may display transdiagnostic prodromal symptoms. Aims & Objectives To address these limitations, we take advantage of Electronic Health Records (EHRs) routinely employed in secondary mental healthcare, constituting a pool of untapped real-world data. We aim to describe and compare the (1) incidence and duration of the first prodromal clusters, (2) mean number of occurrences of prodromal clusters between SMD diagnostic groups and prodromal years, and (3) total number of occurrences of prodromal features. Method Clinical register-based EHR cohort including all individuals accessing the South London and the Maudsley (SLaM) services (2008-2021) and receiving a primary (i.e. not comorbid) diagnosis of any ICD-10 mental disorder that falls under SMD. These diagnoses were clustered into diagnostic groups: non-psychotic unipolar mood disorders (UMD), psychotic bipolar mood disorders (BMD), and psychotic disorders (PSY). Natural language processing algorithms were used to extract monthly occurrences of 65 prodromal features (symptoms and substance use) from the index date of diagnosis until their first occurrence. Prodromal features were grouped into eight prodromal clusters (depressive, disorganised, catatonic, manic, negative, positive, substance use and other symptoms).For aim 1, the duration and incidence of the first prodromal clusters were compared between SMD groups with Cohen’ s F (f) and D (d) effect sizes derived from one-way ANOVA. For aim 2, the time-course (mean occurrences) of prodromal clusters was compared between SMD groups over 12 prodromal years using a linear mixed-effects model. For aim 3, the mean occurrence of each prodromal feature was compared with three-wise and pair-wise discriminability scores between SMD groups. Results 26,975 individuals were included (NBMD=13,422; BD=2,506; PSY=11,047; mean age 41.8 years [SD=17.4]; 55% female; 52% white ethnicity). Prodromal periods were shorter in NBMD (median[IQR]= 18[36] months) than BD (26[35], d=0.21) and PSY (24[38], d=0.18). Most individuals presented multiple first prodromal clusters, with the most common being non-specific (‘other’; 88% UMD, 85% BMD, 78% PSY). The only first prodromal cluster with a medium-sized difference between the SMD groups was positive symptoms (f=0.30). Time-course analysis showed an increase in prodromal cluster occurrences approaching SMD onset. Feature occurrence across the prodromal period showed small/negligible differences between SMD groups, suggesting that most features are transdiagnostic, except for positive symptoms (e.g. paranoia, f=0.40). Discussion & Conclusion Taken together, our findings show minimal differences in the duration and first presentation of SMD prodromes in secondary mental health care. All features intensified as individuals approached SMD onset, and other than positive symptoms, are transdiagnostic. These results support proposals to develop transdiagnostic preventive services for affective and psychotic disorders detected in secondary mental healthcare.

The International Journal of NeuropsychopharmacologyVol. 28(Supplement_1)
King's College London (GB), South London and Maudsley NHS Foundation Trust (GB), University of Pavia (IT), Oxford Health NHS Foundation Trust (GB), University of Oxford (GB), NIHR Maudsley Dementia Biomedical Research Unit (GB), Max Planck Institute of Psychiatry (DE), Oxford BioMedica (United Kingdom) (GB), NIHR Maudsley Biomedical Research Centre (GB), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 23%
Chronic Disease Management Strategies
1.35
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