Evidence map›Paper›PMID 26137532›Full record

ArticleEBioMedicine2015

Magnetic Resonance Imaging Measures of Brain Structure to Predict Antidepressant Treatment Outcome in Major Depressive Disorder.

Mayuresh S Korgaonkar, William Rekshan, Evian Gordon, A John Rush, Leanne M Williams, Christine Blasey, Stuart M Grieve

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EBioMedicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00693849 (International Study to Predict Optimised Treatment - in Depression), which is not on this map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT00693849 phase4unknown statusnot on this map

International Study to Predict Optimised Treatment - in Depression

TypeinterventionalSponsorBRC Operations Pty. Ltd.Ran2008 to 2019Enrolled2,688ConditionsMajor Depressive DisorderArmsEscitalopram, Sertraline, Venlafaxine-XR
3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  5. Review
  6. A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
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  17. Hippocampal tail volume as a predictive biomarker of antidepressant treatment outcomes in patients with major depressive disorder: a CAN-BIND report.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mayuresh S KorgaonkarThe Brain Dynamics Centre, Westmead Millennium Institute, Sydney Medical School, Sydney, NSW, Australia ; Discipline of Psychiatry, Sydney Medical School, The University of Sydney, Westmead Hospital, Sydney, NSW, Australia.
William RekshanBrain Resource Ltd, Sydney, NSW, Australia ; Brain Resource Ltd, San Francisco, CA, USA.
Evian GordonThe Brain Dynamics Centre, Westmead Millennium Institute, Sydney Medical School, Sydney, NSW, Australia ; Brain Resource Ltd, Sydney, NSW, Australia ; Brain Resource Ltd, San Francisco, CA, USA.
A John RushDuke-National University of Singapore, Singapore.
Leanne M WilliamsThe Brain Dynamics Centre, Westmead Millennium Institute, Sydney Medical School, Sydney, NSW, Australia ; Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA 94305, USA ; Sierra-Pacific Mental Illness Research, Education, Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA.
Christine BlaseyPGSP-Stanford University Consortium, Palo Alto, CA, USA.
Stuart M GrieveThe Brain Dynamics Centre, Westmead Millennium Institute, Sydney Medical School, Sydney, NSW, Australia ; Sydney Translational Imaging Laboratory, Charles Perkins Centre and Sydney Medical School, University of Sydney, NSW 2006, Australia ; Department of Radiology, Royal Prince Alfred Hospital, Camperdown, Sydney, NSW 2006, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLess than 50% of patients with Major Depressive Disorder (MDD) reach symptomatic remission with their initial antidepressant medication (ADM). There are currently no objective measures with which to reliably predict which individuals will achieve remission to ADMs.

methods157 participants with MDD from the International Study to Predict Optimized Treatment in Depression (iSPOT-D) underwent baseline MRIs and completed eight weeks of treatment with escitalopram, sertraline or venlafaxine-ER. A score at week 8 of 7 or less on the 17 item Hamilton Rating Scale for Depression defined remission. Receiver Operator Characteristics (ROC) analysis using the first 50% participants was performed to define decision trees of baseline MRI volumetric and connectivity (fractional anisotropy) measures that differentiated non-remitters from remitters with maximal sensitivity and specificity. These decision trees were tested for replication in the remaining participants.

findingsOverall, 35% of all participants achieved remission. ROC analyses identified two decision trees that predicted a high probability of non-remission and that were replicated: 1. Left middle frontal volume < 14 · 8 mL & right angular gyrus volume > 6 · 3 mL identified 55% of non-remitters with 85% accuracy; and 2. Fractional anisotropy values in the left cingulum bundle < 0 · 63, right superior fronto-occipital fasciculus < 0 · 54 and right superior longitudinal fasciculus < 0 · 50 identified 15% of the non-remitters with 84% accuracy. All participants who met criteria for both decision trees were correctly identified as non-remitters.

interpretationPretreatment MRI measures seem to reliably identify a subset of patients who do not remit with a first step medication that includes one of these commonly used medications. Findings are consistent with a neuroanatomical basis for non-remission in depressed patients.

fundingBrain Resource Ltd is the sponsor for the iSPOT-D study (NCT00693849).

Indexed as

Magnetic Resonance ImagingAdultAntidepressive AgentsBrainCohort StudiesDecision TreesDemographyDiffusion Tensor ImagingFemaleGray MatterHumansMajor Depressive DisorderMaleRemission InductionReproducibility of ResultsTreatment OutcomeAntidepressive AgentsBiomarker predictorsDecision treesDiffusion tensor imagingiSPOT-DMagnetic resonance imagingMajor depressive disorderRemissionReplication

Identifiers

PMID26137532
PMCPMC4484820

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.