Staging a protest!

Malhi, Gin S; Rosenberg, David; Gershon, Samuel

doi:10.1111/bdi.12254

Cited by 10 publications

(9 citation statements)

References 16 publications

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“…One of the core controversies about clinical staging is whether it is meaningful when understanding the underlying pathophysiology is limited and biomarkers are lacking . However, our study shows that application of a staging model based on the clinical course does provide new insights into illness progression thereby providing a valid framework in which the influence of different variables or biomarkers on the illness progression can be investigated.…”

Section: Discussionmentioning

confidence: 81%

Testing a clinical staging model for bipolar disorder using longitudinal life chart data

et al. 2018

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Objective Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages. Methods Using retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow‐up Study, the occurrence, duration and timely sequence of stages 2‐4 were determined per month. A multi‐state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi‐state model to determine their influence on the progression rates. Results Five years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression‐mania and the mania‐depression course and by male sex. Conclusions Staging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified.

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Section: Discussionmentioning

confidence: 81%

Testing a clinical staging model for bipolar disorder using longitudinal life chart data

et al. 2018

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“…It needs to be noted that biomarkers can reflect divergent yet overlapping clinical phenotypes, spanning risk, diagnosis or trait, state or acuity, stage or neuroprogression, treatment response, and prognosis . So far, no single biomarker with sufficient specificity and sensitivity for neuroprogression has been identified . However, the ones that have been shown to be altered inform important neurobiological aspects of illness progression, and ultimately allow us to propose a hypothesis for this process .…”

Section: Resultsmentioning

confidence: 99%

Areas of controversy in neuroprogression in bipolar disorder

Passos

Mwangi

Vieta

et al. 2016

Acta Psychiatr Scand

185

103

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Illness trajectories are largely variable, and illness progression is not a general rule in BD. The number of manic episodes seems to be the clinical marker more robustly associated with neuroprogression in BD. However, the majority of the evidence came from cross-sectional studies that are prone to bias. Longitudinal studies may help to identify signatures of neuroprogression and integrate findings from the field of neuroimaging, neurocognition, and biomarkers.

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“…Staging in the development and progression of BD is a popular point of discussion in the psychiatric literature today. Currently, in psychiatry, there are a number of uncertainties in proposed staging models . Staging models in BD suggest a progression from prodromal (at risk) to more severe, refractory presentations .…”

Section: Insulin Resistance and Relevance To Staging In Bdmentioning

confidence: 99%