Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial
Open accessAbstract
BACKGROUND: Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. METHODS/DESIGN: The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n=102), test the findings in the second half, and then extend the analyses to the total sample. TRIAL REGISTRATION: International Study to Predict Optimized Treatment--in Depression (iSPOT-D). ClinicalTrials.gov, NCT00693849.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Previous data from this study support the concept that functional and white matter DTI structural deficits underlie the fronto-limbic dysfunction observed in MDD.
“We have recently presented data from this study supporting the concept that functional and white matter Diffusion Tensor Imaging (DTI) structural deficits underlie the fronto-limbic dysfunction observed in MDD (Grieve et al., 2013; Korgaonkar et al., 2011, 2012).”
From Widespread reductions in gray matter volume in depression (2013) · cites this paper as Grieve et al., 2013
Strong abnormal fMRI measures affecting the amygdala were observed in the current cohort, but the associated GM volume changes in the amygdala were weak and may not be as robust to observe for assessments made at the whole brain level.
“Although, we observe strong abnormal fMRI measures affecting the amygdala in the current cohort, the associated GM volume changes in the amygdala were weak (Grieve et al., 2013) and may not be as robust to observe for assessments made at the whole brain level.”
From Widespread reductions in gray matter volume in depression (2013) · cites this paper as Grieve et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630 · see citing works
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910 · see citing works
Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.021 · Cited by 9,526 · see citing works
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610 · see citing works
Network motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368 · see citing works
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09091379 · Cited by 7,067 · see citing works
Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework
Biomarkers Definitions Working Group (2001) · Clinical Pharmacology & Therapeutics · doi:10.1067/mcp.2001.113989 · Cited by 6,771 · see citing works
Cortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147 · see citing works
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C., Watkins, K., Ciccarelli, O., Cader, M., Matthews, P., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.024 · Cited by 6,035 · see citing works
Measuring the thickness of the human cerebral cortex from magnetic resonance images
Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,789 · see citing works
Maldjian, J. A., Laurienti, P. J., Kraft, R., & Burdette, J. H. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00169-1 · Cited by 5,066 · see citing works
Higgins, S. M. F., Macken, A. P., Cullen, W., Saunders, J., Dunne, C. P., & O’Gorman, C. S. (2013) · PubMed · doi:10.34961/9953 · Cited by 4,806 · see citing works
Automatically Parcellating the Human Cerebral Cortex
Fischl, B. R. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg087 · Cited by 4,208 · see citing works
Trivedi, M. H., Rush, A. J., Wisniewski, S. R., Nierenberg, A. A., Warden, D., Ritz, L., Norquist, G., Howland, R. H., Lebowitz, B., McGrath, P. J., et al. (2006) · American Journal of Psychiatry · doi:10.1176/appi.ajp.163.1.28 · Cited by 3,879 · see citing works
Self-citationLarge-scale automated synthesis of human functional neuroimaging data.
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011) · Nature Methods · doi:10.1038/nmeth.1635 · Cited by 3,686 · see citing works
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471 · see citing works
Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging
Behrens, T. E. J., Johansen-Berg, H., Woolrich, M. W., Smith, S. M., Wheeler-Kingshott, C. A. M., Boulby, P. A., Barker, G. J., Sillery, E. L., Sheehan, K., Ciccarelli, O., et al. (2003) · Nature Neuroscience · doi:10.1038/nn1075 · Cited by 2,330 · see citing works
A hybrid approach to the skull stripping problem in MRI
Ségonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D. H., Hahn, H., & Fischl, B. R. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.032 · Cited by 2,227 · see citing works
Sequence-independent segmentation of magnetic resonance images
Fischl, B. R., Salat, D. H., van der Kouwe, A. J. W., Makris, N., Ségonne, F., Quinn, B. T., & Dale, A. M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.016 · Cited by 2,117 · see citing works
Dale, A. M., & Sereno, M. I. (1993) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1993.5.2.162 · Cited by 2,003 · see citing works
Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template
Mori, S., Oishi, K., Jiang, H., Jiang, L., Li, X., Akhter, K., Hua, K., Faria, A. V., Mahmood, A., Woods, R. P., et al. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.12.035 · Cited by 1,832 · see citing works
OsiriX: An Open-Source Software for Navigating in Multidimensional DICOM Images
Rosset, A., Spadola, L., & Ratib, O. M. (2004) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-004-1014-6 · Cited by 1,771 · see citing works
Fischl, B. R., Liu, A., & Dale, A. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906426 · Cited by 1,755 · see citing works
Frackowiak, R. S. J. (1997) · Cited by 1,713 · see citing works
Han, X., Jovicich, J., Salat, D., van der Kouwe, A., Quinn, B., Czanner, S., Busa, E., Pacheco, J., Albert, M., Killiany, R., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.051 · Cited by 1,508 · see citing works
Jovicich, J., Czanner, S., Greve, D. N., Haley, E., van der Kouwe, A. J. W., Gollub, R. L., Kennedy, D. N., Schmitt, F., Brown, G. G., MacFall, J. R., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.09.046 · Cited by 1,269 · see citing works
Mathers, C. D. (2008) · Elsevier eBooks · doi:10.1016/b978-012373960-5.00335-x · Cited by 1,125 · see citing works
Sequenced treatment alternatives to relieve depression (STAR*D): Rationale and design
Rush, A. J., Fava, M., Wisniewski, S. R., Lavori, P. W., Trivedi, M. H., Sackeim, H. A., Thase, M. E., Nierenberg, A. A., Quitkin, F. M., Kashner, T. M., et al. (2004) · Controlled Clinical Trials · doi:10.1016/s0197-2456(03)00112-0 · Cited by 1,076 · see citing works
Self-citationScheltens, P., Barkhof, F., Leys, D., Pruvo, J., Nauta, J. J. P., Vermersch, P., Steinling, M., & Valk, J. (1993) · Journal of the Neurological Sciences · doi:10.1016/0022-510x(93)90041-v · Cited by 920 · see citing works
Gur, R. C., Šára, R., Hagendoorn, M., Marom, O., Hughett, P., Macy, L., Turner, T. H., Bajcsy, R., Posner, A., & Gur, R. E. (2002) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00006-7 · Cited by 647 · see citing works
Fair, D. A., Schlaggar, B. L., Cohen, A. L., Miezin, F. M., Dosenbach, N. U. F., Wenger, K. K., Fox, M., Snyder, A. Z., Raichle, M. E., & Petersen, S. E. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.11.051 · Cited by 600 · see citing works
(2002) · Cited by 479 · see citing works
Wang, J.-H., Zuo, X.-N., Gohel, S., Milham, M. P., Biswal, B. B., & He, Y. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021976 · Cited by 416 · see citing works
Cognitive aging, executive function, and fractional anisotropy: a diffusion tensor MR imaging study.
Grieve, S. M., Williams, L. M., Paul, R. H., Clark, C. R., & Gordon, E. (2007) · PubMed Central · Cited by 350 · see citing works
Self-citationPreservation of limbic and paralimbic structures in aging
Grieve, S. M., Clark, C. R., Williams, L. M., Peduto, A. J., & Gordon, E. (2005) · Human Brain Mapping · doi:10.1002/hbm.20115 · Cited by 293 · see citing works
Self-citationThe ‘when’ and ‘where’ of perceiving signals of threat versus non-threat
Williams, L. M., Palmer, D. M., Liddell, B. J., Song, L., & Gordon, E. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.009 · Cited by 257 · see citing works
Self-citationDixon, L. C. W., & Maine, R. E. (1975) · Journal of Dynamic Systems Measurement and Control · doi:10.1115/1.3426911 · Cited by 243 · see citing works
Liddell, B. J., Williams, L. M., Rathjen, J., Shevrin, H., & Gordon, E. (2004) · Journal of Cognitive Neuroscience · doi:10.1162/089892904322926809 · Cited by 229 · see citing works
Self-citationDisrupted Small-World Brain Networks in Moderate Alzheimer's Disease: A Resting-State fMRI Study
Zhao, X., Liu, Y., Wang, X., Liu, B., Xi, Q., Guo, Q., Jiang, H., Jiang, T., & Wang, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033540 · Cited by 215 · see citing works
Korgaonkar, M. S., Grieve, S. M., Koslow, S. H., Gabrieli, J. D. E., Gordon, E., & Williams, L. M. (2011) · Human Brain Mapping · doi:10.1002/hbm.21178 · Cited by 205 · see citing works
Self-citationWilliams, L. M., Rush, A. J., Koslow, S. H., Wisniewski, S. R., Cooper, N. J., Nemeroff, C. B., Schatzberg, A. F., & Gordon, E. (2011) · Trials · doi:10.1186/1745-6215-12-4 · Cited by 193 · see citing works
Self-citationArnone, D., McKie, S., Elliott, R., Thomas, E. J., Downey, D., Juhasz, G., Williams, S. R., Deakin, J. F. W., & Anderson, I. M. (2012) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2012.11121774 · Cited by 192 · cited 3× · see citing works
“The rationale behind the use of three treatment arms in iSPOT-D is to identify what are the unique and common brain circuits that modulate response and remission to different types of anti-depressant medications, that is, selective serotonin reuptake inhibitors (SSRIs) versus selective norepinephrine reuptake inhibito…”
BackgroundSoriano‐Mas, C., Hernández‐Ribas, R., Pujol, J., Urretavizcaya, M., Deus, J., Harrison, B. J., Ortiz, H., López‐Solà, M., Menchón, J. M., & Cardoner, N. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.07.029 · Cited by 152 · see citing works
Korgaonkar, M. S., Grieve, S. M., Etkin, A., Koslow, S. H., & Williams, L. M. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2012.252 · Cited by 135 · see citing works
Self-citationChronic, treatment-resistant depression and right fronto-striatal atrophy
Shah, P. J., Glabus, M. F., Goodwin, G. M., & Ebmeier, K. P. (2002) · The British Journal of Psychiatry · doi:10.1192/bjp.180.5.434 · Cited by 134 · see citing works
Phan, K. L., Coccaro, E. F., Angstadt, M., Kreger, K. J., Mayberg, H. S., Liberzon, I., & Stein, M. B. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.10.003 · Cited by 114 · see citing works
Economic implications of treatment-resistant depression among employees
Greenberg, P., Corey-Lisle, P. K., Birnbaum, H., Marynchenko, M., & Claxton, A. (2004) · PharmacoEconomics · doi:10.2165/00019053-200422060-00003 · Cited by 113 · see citing works
A hybrid approach to the skull stripping problem in MRI
Ségonne, F. (2004) · NeuroImage · doi:10.1016/s1053-8119(04)00188-0 · Cited by 102 · see citing works
Paul, R., Henry, L., Grieve, S., Guilmette, T., Niaura, R., Bryant, R., Bruce, S., Williams, L., Richard, C. C., Cohen, R., et al. (2008) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s1549 · Cited by 97 · see citing works
Self-citationAltered Small-World Brain Networks in Schizophrenia Patients during Working Memory Performance
He, H., Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Yu, Q., Turner, J. A., Ho, B., Sponheim, S. R., Manoach, D. S., Clark, V. P., & Calhoun, V. D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0038195 · Cited by 82 · see citing works
Riedel, W. J., Eikmans, K., Heldens, A., & Schmitt, J. A. J. (2005) · Journal of Psychopharmacology · doi:10.1177/0269881105048887 · Cited by 73 · see citing works
Grieve, S. M., Korgaonkar, M. S., Clark, C. R., & Williams, L. M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.087 · Cited by 64 · see citing works
Self-citationExner, C., Lange, C., & Irle, E. (2009) · Journal of Affective Disorders · doi:10.1016/j.jad.2009.03.015 · Cited by 61 · see citing works
Mapping inter-regional connectivity of the entire cortex to characterize major depressive disorder
Korgaonkar, M. S., Cooper, N. J., Williams, L. M., & Grieve, S. M. (2012) · Neuroreport · doi:10.1097/wnr.0b013e3283546264 · Cited by 57 · see citing works
Self-citationEarly Life Stress on Brain Structure and Function Across the Lifespan: A Preliminary Study
Seckfort, D. L., Paul, R., Grieve, S. M., Vandenberg, B., Bryant, R., Williams, L. M., Clark, C., Cohen, R. A., Bruce, S., & Gordon, E. (2008) · Brain Imaging and Behavior · doi:10.1007/s11682-007-9015-y · Cited by 48 · see citing works
Self-citationGatt, J. M., Korgaonkar, M. S., Schofield, P. R., Harris, A. W. F., Clark, C. R., Oakley, K. L., Ram, K., Michaelson, H., Yap, S., Stanners, M. N., et al. (2012) · Twin Research and Human Genetics · doi:10.1017/thg.2012.12 · Cited by 47 · see citing works
Self-citationGavrilescu, M. C., Stuart, G. W., Rossell, S. L., Henshall, K. R., McKay, C. M., Sergejew, A. A., Copolov, D., & Egan, G. F. (2007) · Human Brain Mapping · doi:10.1002/hbm.20446 · Cited by 45 · see citing works
Victor, T. A., Furey, M. L., Fromm, S. J., Bellgowan, P. S. F., Öhman, A., & Drevets, W. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046439 · Cited by 41 · see citing works
Inhibition of hippocampal excitability by citalopram
Igelström, K. M., & Heyward, P. M. (2012) · Epilepsia · doi:10.1111/j.1528-1167.2012.03660.x · Cited by 16 · see citing works
Department of Health and Ageing Therapeutic Goods Administration
Hawthorn, E. (2013) · Cited by 10 · see citing works
Personalized medicine for the brain: a call for action
Koslow, S. H., Williams, L. M., & Gordon, E. (2010) · Molecular Psychiatry · doi:10.1038/mp.2009.147 · Cited by 8 · see citing works
Self-citationRuhé, H. G., Booij, J., van Weert, H. C. P. M., et al. (2010) · PubMed · Cited by 5 · see citing works
High-resolution intersubject averaging and a coordinate system for the cortical surface
Fischl, B., Sereno, M. I., Tootell, R. B. H., & Dale, A. M. (1999) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(1999)8:4
Flagged first, then by citations
Cited by
Sorted by citations
Widespread reductions in gray matter volume in depression
Grieve, S. M., Korgaonkar, M. S., Koslow, S. H., Gordon, E., & Williams, L. M. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.08.016 · Cited by 388 · see citing works
Self-citationWilliams, L. M., Korgaonkar, M. S., Song, Y. C., Paton, R., Eagles, S., Goldstein-Piekarski, A., Grieve, S. M., Harris, A. W. F., Usherwood, T., & Etkin, A. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.89 · Cited by 195 · see citing works
Self-citationIntrinsic connectomes are a predictive biomarker of remission in major depressive disorder
Korgaonkar, M. S., Goldstein-Piekarski, A. N., Fornito, A., & Williams, L. M. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0574-2 · Cited by 163 · see citing works
Gyurak, A., Patenaude, B., Korgaonkar, M. S., Grieve, S. M., Williams, L. M., & Etkin, A. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.02.037 · Cited by 149 · see citing works
Self-citationGoldstein-Piekarski, A. N., Staveland, B. R., Ball, T. M., Yesavage, J., Korgaonkar, M. S., & Williams, L. M. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0100-3 · Cited by 108 · see citing works
Self-citationMaller, J. J., Broadhouse, K., Rush, A. J., Gordon, E., Koslow, S., & Grieve, S. M. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.224 · Cited by 87 · see citing works
Self-citationMiller, S., McTeague, L. M., Gyurak, A., Patenaude, B., Williams, L. M., Grieve, S. M., Korgaonkar, M. S., & Etkin, A. (2015) · Depression and Anxiety · doi:10.1002/da.22368 · Cited by 74 · see citing works
Self-citationMacQueen, G. M., Hassel, S., Arnott, S. R., Addington, J., Bowie, C. R., Bray, S. L., Davis, A. D., Downar, J., Foster, J. A., Frey, B. N., et al. (2019) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.180036 · Cited by 57 · see citing works
Deep phenotyping of attention impairments and the ‘Inattention Biotype’ in Major Depressive Disorder
Keller, A. S., Ball, T. M., & Williams, L. M. (2020) · Psychological Medicine · doi:10.1017/s0033291719002290 · Cited by 52 · see citing works
Self-citationFischer, A. S., Holt-Gosselin, B., Fleming, S. L., Hack, L. M., Ball, T. M., Schatzberg, A. F., & Williams, L. M. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-00905-3 · Cited by 30 · see citing works
Self-citation
- Authors
- Grieve, S. M., Korgaonkar, M. S., Etkin, A., Harris, A., Koslow, S. H., Wisniewski, S., Schatzberg, A. F., Nemeroff, C. B., Gordon, E., & Williams, L. M.
- Affiliations
- The University of Sydney (AU)
- VA Palo Alto Health Care System (US)
- University of Miami (US)
- Stanford University (US)
- Corresponding author
- Grieve, Stuart M
- ORCID
- Venue
- Trials
- Published
- 2013
- Volume
- 14
- Issue
- 1
- Pages
- 224
- ISSN
- 1745-6215 (ISSN-L)
- PMC
- PMC3729660
- OpenAlex
- W2099704444
- Cited by
- 44
- References
- 63
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 9 · 2018: 2 · 2017: 2 · 2016: 2 · 2015: 6 · 2014: 8 · 2013: 2
- FWCI
- 4.41
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Trials (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- major depressive disorder, treatment response prediction, antidepressant treatment, neuroimaging, escitalopram, sertraline, venlafaxine, structural MRI, diffusion tensor imaging, functional MRI, emotional processing, cognitive tasks, EEG, genetic markers, treatment-resistant depression
- MeSH terms
- Venlafaxine Hydrochloride, Adolescent, Adult, Aged, Antidepressive Agents, Brain, California, Clinical Protocols, Cognition, Cyclohexanols, Depressive Disorder, Major, Major Depressive Disorder, Emotions, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, New South Wales, Predictive Value of Tests, Prospective Studies, Psychiatric Status Rating Scales, Research Design, Citalopram, Treatment Outcome, Sertraline, Young Adult, Diffusion Tensor Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
