Predicting Response to Brain Stimulation in Depression: a Roadmap for Biomarker Discovery

Overview

Journal Curr Behav Neurosci Rep

Specialty Social Sciences

Date 2021 Mar 12

PMID 33708470

Citations 3

Authors

Camilla L Nord

Affiliations

Soon will be listed here.

Abstract

Purpose Of Review: Clinical response to brain stimulation treatments for depression is highly variable. A major challenge for the field is predicting an individual patient's likelihood of response. This review synthesises recent developments in neural predictors of response to targeted brain stimulation in depression. It then proposes a framework to evaluate the clinical potential of putative 'biomarkers'.

Recent Findings: Largely, developments in identifying putative predictors emerge from two approaches: data-driven, including machine learning algorithms applied to resting state or structural neuroimaging data, and theory-driven, including task-based neuroimaging. Theory-driven approaches can also yield mechanistic insight into the cognitive processes altered by the intervention.

Summary: A pragmatic framework for discovery and testing of biomarkers of brain stimulation response in depression is proposed, involving (1) identification of a cognitive-neural phenotype; (2) confirming its validity as putative biomarker, including out-of-sample replicability and within-subject reliability; (3) establishing the association between this phenotype and treatment response and/or its modifiability with particular brain stimulation interventions via an early-phase randomised controlled trial RCT; and (4) multi-site RCTs of one or more treatment types measuring the generalisability of the biomarker and confirming the superiority of biomarker-selected patients over randomly allocated groups.

Citing Articles

Biomarkers: The Key to Enhancing Deep Brain Stimulation Treatment for Psychiatric Conditions.

Bazarra Castro G, Casitas V, Martinez Macho C, Madero Pohlen A, Alvarez-Salas A, Barbero Pablos E Brain Sci. 2024; 14(11).

PMID: 39595828 PMC: 11592218. DOI: 10.3390/brainsci14111065.

Biomarker development perspective: Exploring comorbid chronic pain in depression through deep transcranial magnetic stimulation.

Ju P, Zhao D, Ma L, Chen J J Transl Int Med. 2024; 12(2):123-128.

PMID: 38779118 PMC: 11107179. DOI: 10.2478/jtim-2023-0145.

The promise of machine learning in predicting treatment outcomes in psychiatry.

Chekroud A, Bondar J, Delgadillo J, Doherty G, Wasil A, Fokkema M World Psychiatry. 2021; 20(2):154-170.

PMID: 34002503 PMC: 8129866. DOI: 10.1002/wps.20882.

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