Rate of diagnostic conversion to bipolar disorder in adults with unipolar depression and psychopharmacological treatment in the republic of Korea: A nationwide register-based study

Kim, Eun Young; Kim, Nam Woo; Kim, Min Ji; Yang, Bo; Rhee, Sang Jin; Park, C. Hyung Keun; Lee, Hyun Jeong; Kim, Se Hyun; Ahn, Yong Min

doi:10.1016/j.jad.2020.03.159

Cited by 8 publications

(8 citation statements)

References 24 publications

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“…A recent meta-analysis failed to identify factors that were consistently confirmed to predict MDD to BD conversion across studies [ 10 ]. Among the reported predictors of diagnosis conversion were younger patient age, treatment resistance, early depression onset, higher depression severity, multiple depressive episodes, family history of mood disorders, co-existing alcohol/substance abuse, attention-deficit/hyperactivity disorder, anxiety disorders, psychoses, suicide attempts, personality disorders, hospitalization, as well as rapid mood cycling, psychotherapy, living alone, prior use of psychotropic drugs, and others [ 8 , 14 – 18 ]. Contradicting data are reported across the literature on the role of sex, age, depression onset, and severity in MDD-BD diagnostic transition.…”

Section: Introductionmentioning

confidence: 99%

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

et al. 2021

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Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD’s timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five “training” US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model’s area under the curve (AUC) varied 0.633–0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570–0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.

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Section: Introductionmentioning

confidence: 99%

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

et al. 2021

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“…In the previously mentioned 5-year prospective study, age at onset was not significantly associated with conversion to BD; in particular, LOD (> 60 years) failed to confer a higher risk of conversion compared with midlife onset (30-60 years) and early-onset depression (<30 years) (Bukh et al, 2016) et al, 2017). Notably, in another study, the conversion rate was found to vary with age: conversion was, indeed, the highest in patients aged between 18 and 29 years and gradually decreased with increasing age (Kim et al, 2020). Nevertheless, a slight increase in conversion to BD was observable for patients aged 70 years or more (Kim et al, 2020), which could be putatively mediated by the effect of LOD.…”

Section: Discussionmentioning

confidence: 86%

“…recruitment setting, source dataset and length of follow-up) (Kessing et al , 2017). Notably, in another study, the conversion rate was found to vary with age: conversion was, indeed, the highest in patients aged between 18 and 29 years and gradually decreased with increasing age (Kim et al , 2020). Nevertheless, a slight increase in conversion to BD was observable for patients aged 70 years or more (Kim et al , 2020), which could be putatively mediated by the effect of LOD.…”

Section: Discussionmentioning

confidence: 94%

Risk of conversion to bipolar disorder in patients with late-onset major depression

Elefante

Brancati

Petrücci

et al. 2022

International Clinical Psychopharmacology

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To evaluate the impact of age at onset on late-life depression course and on risk of conversion to bipolar disorder (BD). A retrospective chart review of 100 elderly patients (age ≥ 65 years) diagnosed with a moderate-tosevere depressive episode and followed up for at least 18 months was conducted. Among patients affected by major depressive disorder (N = 57), follow-up morbidity differences between those with typical onset depression (TOD) (<60 years) and those with late-onset depression (LOD) (≥60 years) were investigated using Wilcoxon ranksum test and Cox proportional hazard model. Patients belonging to the LOD group had a significantly lower percentage of follow-up time spent with depressive symptoms compared with patients with TOD (r = 0.36; P = 0.006), but significantly more time spent with (hypo) manic episodes (r = −0.31; P = 0.021). Moreover, LOD was significantly associated with a faster conversion to BD (hazard ratio = 3.05; P = 0.037). Depression first emerging in late life may represent an unstable condition with a high risk to convert to BD. Given the potential clinical implications, further studies on the course of LOD are required.

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“…However, those studies also found that higher hyperthymic temperament scores differentiated subjects diagnosed with BD-1 versus BD-2, which we did not find ( Table 1 ). The studies by Morishita et al [ 29 , 30 ] were based on a cross-sectional design and so may have missed some patients considered to have MDD who might later have met diagnostic criteria for BD [ 5 , 37 , 38 ]. Moreover, not all of their patients were currently in remission or euthymic, and some responses to temperament categorizing questions may have been influenced by current mood states [ 34 , 39 ].…”

Section: Discussionmentioning

confidence: 99%

Relationships of affective temperament ratings to diagnosis and morbidity measures in major affective disorders

Miola

Baldessarini

Pinna³

et al. 2021

Eur. Psychiatr.

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Background. Ratings of affective temperament types show promise in helping to differentiate diagnostic groups among major affective disorders as well as to predict associations with important aspects of morbidity including suicidal risk. Methods. The Temperament Evaluation of Memphis, Pisa, Paris, and San Diego auto-rating (TEMPS-A) questionnaire was completed by 858 unselected, consecutive, consenting adults diagnosed with a DSM-5 major affective disorder (173 bipolar-1 [BD-1]), 250 BD-2, 435 major depressive disorder [MDD]) to score for anxious (anx), cyclothymic (cyc), dysthymic (dys), hyperthymic (hyp), and irritable (irr) affective temperaments. We tested their associations with diagnosis and selected clinical factors, including diagnosis, depression scores, suicidal ideation or acts, substance abuse, episodes/year, and %-time ill. Results. Scores for cyc ranked: BD-2 > BD-1 > MDD; anx ranked: MDD > BD-2 > BD-1; irr was greater in BD than MDD; dys was greater in MDD than BD; hyp did not differ by diagnosis. We confirmed associations of suicidal risk with higher scores of all temperament types except lower hyp scores. Higher cyc and irr scores and lower anx scores were associated with substance abuse. Several scores were higher with measures of greater affective morbidity: cyc with current depression, episodes/year, and %-time ill; irr with more episodes and depressions/year and greater %-time manic. Some of these associations were selective for BD or MDD. Conclusions. The findings indicate that TEMPS-A ratings of affective temperament types can contribute to differential diagnoses and predict types and amounts of affective morbidity, as well as detecting suicidal risks.

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Rate of diagnostic conversion to bipolar disorder in adults with unipolar depression and psychopharmacological treatment in the republic of Korea: A nationwide register-based study

Cited by 8 publications

References 24 publications

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

Risk of conversion to bipolar disorder in patients with late-onset major depression

Relationships of affective temperament ratings to diagnosis and morbidity measures in major affective disorders

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