Personalized Medicine for Depression: Can We Match Patients With Treatments?

Simon, Gregory E.; Perlis, Roy H.

doi:10.1176/appi.ajp.2010.09111680

Cited by 369Treatment of Major DepressionPsychotherapy Techniques and ApplicationsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Personalized Medicine for Depression: Can We Match Patients With Treatments?

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Simon, Gregory E., Perlis, Roy H.·2010·American Journal of Psychiatry

DOI 10.1176/appi.ajp.2010.09111680PMC PMC3723328

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Abstract

OBJECTIVE: Response to specific depression treatments varies widely among individuals. Understanding and predicting that variation could have great benefits for people living with depression. METHOD: The authors describe a conceptual model for identifying and evaluating evidence relevant to personalizing treatment for depression. They review evidence related to three specific treatment decisions: choice between antidepressant medication and psychotherapy, selection of a specific antidepressant medication, and selection of a specific psychotherapy. They then discuss potential explanations for negative findings as well as implications for research and clinical practice. RESULTS: Many previous studies have examined general predictors of outcome, but few have examined true moderators (predictors of differential response to alternative treatments). The limited evidence indicates that some specific clinical characteristics may inform the choice between antidepressant medication and psychotherapy and the choice of specific antidepressant medication. Research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the choice between medication and psychotherapy, the selection of specific medication, or the selection of a specific psychotherapy. CONCLUSIONS: While individuals vary widely in response to specific depression treatments, the variability remains largely unpredictable. Future research should focus on identifying true moderator effects and should consider how response to treatments varies across episodes. At this time, our inability to match patients with treatments implies that systematic follow-up assessment and adjustment of treatment are more important than initial treatment selection.

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Psychological treatments benefit men and women to the same extent and are equally suitable for individuals of all ages, levels of education, and cultural and ethnic backgrounds.
“Psychological treatments benefit men and women to the same extent; psychological treatments are equally suitable for individuals of all ages, levels of education, and cultural and ethnic backgrounds.9”
From Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder (2016) · cites this paper as [9]
The Introduction says specific psychotherapies have success comparable to antidepressant medication as first-line treatment for moderate depression, supporting a general claim of benefit. It does not establish equal benefit for men and women or equal suitability across ages, education levels, and cultural or ethnic backgrounds; the sections on treatment selection instead discuss other patient characteristics. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Psychological treatments in general and CBT in particular appear to be equally effective for different subtypes of depression, including atypical, melancholic, and anxious depression.
“Psychological treatments in general and cognitive-behavioural therapy (CBT) in particular appear to be equally effective for different subtypes of depression, including atypical depression, melancholic depression, and anxious depression.9,10”
From Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder (2016) · cites this paper as [9]
The Selection of a Specific Psychotherapy section discusses whether clinical characteristics predict different responses to cognitive therapy and other psychotherapies, but does not compare effectiveness across atypical, melancholic, and anxious depression. The section on specific antidepressants discusses atypical symptoms and anxiety only in relation to medication response. Searches for these subtypes alongside psychotherapy and CBT found no passage supporting the cited claim; page numbers were not available in our copy. (LLM, conf=0.74)
Experimental — accuracy not yet measured
It has been estimated that only 12 to 34% of people in routine outpatient care are eligible for participation in a pharmacotherapy trial: others are ineligible because of comorbidities or failing to meet the minimum severity threshold.
“It has been estimated that only 12 to 34% of people in routine outpatient care are eligible for participation in a pharmacotherapy trial: others are ineligible because of comorbidities or failing to meet the minimum severity threshold. 588”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [588]

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Thase, M. E., Dubé, S., Bowler, K., Howland, R. H., Myers, J. E., Friedman, E. S., & Jarrett, D. B. (1996) · American Journal of Psychiatry · doi:10.1176/ajp.153.7.886 · Cited by 80 · see citing works
The G196A polymorphism of the brain-derived neurotrophic factor gene and the antidepressant effect of milnacipran and fluvoxamine
Yoshida, K., Higuchi, H., Kamata, M., Takahashi, H., Inoue, K., Suzuki, T., Itoh, K., & Ozaki, N. (2006) · Journal of Psychopharmacology · doi:10.1177/0269881106072192 · Cited by 80 · see citing works
Variation in Catechol-O-Methyltransferase Is Associated with Duloxetine Response in a Clinical Trial for Major Depressive Disorder
Perlis, R. H., Fijal, B. A., Adams, D. H., Sutton, V. K., Trivedi, M. H., & Houston, J. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.10.002 · Cited by 77 · see citing works
Self-citation
Clinical guidelines for the treatment of depressive disorders, I. Definitions, prevalence, and health burden.
Parikh, S. V., & Lam, R. W. M. (2001) · PubMed · Cited by 73 · see citing works
Urinary MHPG Levels and Tricyclic Antidepressant Drug Selection
Cobbin, D. M. (1979) · Archives of General Psychiatry · doi:10.1001/archpsyc.1979.01780100081007 · Cited by 69 · see citing works
Predictive Value of Symptoms of Atypical Depression
McGrath, P. J., Stewart, J. W., Harrison, W. M., Ocepek‐Welikson, K., Rabkin, J. G., NUNES, E. N., Wager, S., TRICAMO, E., Quitkin, F. M., & Klein, D. F. (1992) · Journal of Clinical Psychopharmacology · doi:10.1097/00004714-199206000-00009 · Cited by 63 · see citing works
Serotonin transporter polymorphisms and the occurrence of adverse events during treatment with selective serotonin reuptake inhibitors
Smits, K. M., Smits, L. J. M., Peeters, F. P. M. L., Schouten, J., Janssen, R. G. J. H., Smeets, H. J. M., van Os, J., & Prins, M. H. (2007) · International Clinical Psychopharmacology · doi:10.1097/yic.0b013e328014822a · Cited by 62 · see citing works
The MAOA T941G polymorphism and short‐term treatment response to mirtazapine and paroxetine in major depression
Tadić, A., Müller, M. J., Rujescu, D., Kohnen, R., Stassen, H. H., Dahmen, N., & Szegedi, A. (2006) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30462 · Cited by 62 · see citing works
Choosing a First-Line Antidepressant
Simon, G. (2001) · JAMA · doi:10.1001/jama.286.23.3003 · Cited by 60 · cited 1× · see citing works
“But the fact that treatments have similar effi cacy on average does not imply that treatment selection is unimportant (6, 7).”
BackgroundSelf-citation
Influence of the tyrosine hydroxylase val81met polymorphism and catechol‐O‐methyltransferase val158met polymorphism on the antidepressant effect of milnacipran
Yoshida, K., Higuchi, H., Takahashi, H., Kamata, M., Sato, K., Inoue, K., Suzuki, T., Itoh, K., & Ozaki, N. (2007) · Human Psychopharmacology Clinical and Experimental · doi:10.1002/hup.907 · Cited by 56 · see citing works
Pharmacogenetic Testing in the Clinical Management of Schizophrenia
Perlis, R. H., Ganz, D. A., Avorn, J., Schneeweiß, S., Glynn, R. J., Smoller, J. W., & Wang, P. S. (2005) · Journal of Clinical Psychopharmacology · doi:10.1097/01.jcp.0000177553.59455.24 · Cited by 52 · see citing works
Self-citation
Combined therapy of major depression with concomitant borderline personality disorder: comparison of interpersonal and cognitive psychotherapy
Bellino, S., Zizza, M., Rinaldi, C., & Bogetto, F. (2007) · The Canadian Journal of Psychiatry · doi:10.1177/070674370705201106 · Cited by 45 · cited 3× · see citing works
“(18) Borderline personality disorder Cognitive therapy (N=12) Interpersonal therapy (N=14) Mean HAM-D posttreatment score 13.”
Background
Clinical Guidelines for the Treatment of Depressive Disorders I. Definitions Prevalence Health Burden
Parikh, S. V., Lam, R. W. M., & the CANMAT Depression Work Group (2001) · The Canadian Journal of Psychiatry · doi:10.1177/070674372001460101001 · Cited by 43 · see citing works
Drug-Gene Interactions between Genetic Polymorphisms and Antihypertensive Therapy
Schelleman, H., Stricker, B. H. C., de Boer, A., Kroon, A. A., Verschuren, W. M. M., van Duijn, C. M., Psaty, B. M., & Klungel, O. H. (2004) · Drugs · doi:10.2165/00003495-200464160-00006 · Cited by 42 · see citing works
Psychobiological correlates of poor response to cognitive behavior therapy: potential indications for antidepressant pharmacotherapy.
Thase, M. E., Simons, A. D., & Reynolds, C. F. (1993) · PubMed · Cited by 42 · see citing works
Select comorbid personality disorders and the treatment of chronic depression with nefazodone, targeted psychotherapy, or their combination
Maddux, R. E., Riso, L. P., Klein, D. N., Markowitz, J. C., Rothbaum, B. O., Arnow, B. A., Manber, R., Blalock, J. A., Keitner, G. I., & Thase, M. E. (2009) · Journal of Affective Disorders · doi:10.1016/j.jad.2009.01.010 · Cited by 40 · see citing works
Clinically Responsible Genetic Testing in Neuropsychiatric Patients: A Bridge Too Far and Too Soon
BRAFF, D. L., & Freedman, R. (2008) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2008.08050717 · Cited by 37 · see citing works
The Alpha 2A-Adrenergic Receptor Gene Polymorphism Modifies Antidepressant Responses to Milnacipran
Wakeno, M., Kato, M., Okugawa, G., Fukuda, T., Hosoi, Y., Takekita, Y., Yamashita, M., Nonen, S., Azuma, J., & Kinoshita, T. (2008) · Journal of Clinical Psychopharmacology · doi:10.1097/jcp.0b013e31818455fc · Cited by 32 · see citing works
A monoamine oxidase B gene variant and short-term antidepressant treatment response
Tadić, A., Rujescu, D., Müller, M. J., Kohnen, R., Stassen, H. H., Dahmen, N., & Szegedi, A. (2007) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2007.05.015 · Cited by 24 · see citing works
Cytochrome P450 genotyping and antidepressants
Perlis, R. H. (2007) · BMJ · doi:10.1136/bmj.39169.547512.80 · Cited by 21 · see citing works
Self-citation
Rational antidepressant selection: applying evidence-based medicine to complex real-world patients.
Zetin, M., Hoepner, C. T., & Bjornson, L. (2006) · PubMed · Cited by 17 · see citing works
Failure of urinary MHPG levels to predict treatment response in patients with unipolar depression
Janicak, P. G., Davis, J. M., Chan, C. C. H., Altman, E., & Hedeker, D. (1986) · American Journal of Psychiatry · doi:10.1176/ajp.143.11.1398 · Cited by 15 · see citing works
Differential Responses to a Single Antidepressant in Recurrent Episodes of Major Depression
Rémillard, A. J., Blackshaw, S. L., & Dangor, A. (1994) · Psychiatric Services · doi:10.1176/ps.45.4.359 · Cited by 12 · see citing works
Biological predictors of treatment response in affective illness
Perlis, R. H., Iosifescu, D. V., & Renshaw, P. F. (2003) · Psychiatric Clinics of North America · doi:10.1016/s0193-953x(02)00112-0 · Cited by 10 · see citing works
Self-citation
Drs. Janicak and Davis Reply
Janicak, P. G., & Davis, J. M. (1986) · American Journal of Psychiatry · doi:10.1176/ajp.143.1.121-a · Cited by 7 · see citing works

Flagged first, then by citations

Sorted by citations

Childhood Maltreatment Predicts Unfavorable Course of Illness and Treatment Outcome in Depression: A Meta-Analysis
Nanni, V., Uher, R., & Danese, A. (2012) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.11020335 · Cited by 1,480 · see citing works
Time for united action on depression: a Lancet–World Psychiatric Association Commission
Herrman, H., Patel, V., Kieling, C., Berk, M., Buchweitz, C., Cuijpers, P., Furukawa, T. A., Kessler, R. C., Kohrt, B. A., Maj, M., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(21)02141-3 · Cited by 1,104 · see citing works
The Biological Effects of Childhood Trauma
De Bellis, M. D., & Zisk, A. (2014) · Child and Adolescent Psychiatric Clinics of North America · doi:10.1016/j.chc.2014.01.002 · Cited by 892 · see citing works
“important new tool for novel approaches to treatments, such as personalized medicine.(58) Several of these mediation and moderation mechanisms for the biological effects of trauma on the developing child can be found in a previously published critical review by De Bellis,(13) and 12 updated mechanisms are discussed la…”
Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders
Malhi, G. S., Bassett, D., Boyce, P., Bryant, R., Fitzgerald, P. B., Fritz, K., Hopwood, M., Lyndon, B., Mulder, R., Murray, G., et al. (2015) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867415617657 · Cited by 842 · see citing works
“…profile of the depressed patient, psychological treatment may be best administered after initiating pharmacotherapy, and in this context clinical features such as melancholic features that may predict better response to SSRIs than CBT should be taken into consideration (Simon and Perlis, 2010).”
Background
A Review of the Clinical, Economic, and Societal Burden of Treatment-Resistant Depression: 1996–2013
Mrazek, D. A., Hornberger, J. C., Altar, C. A., & Degtiar, I. (2014) · Psychiatric Services · doi:10.1176/appi.ps.201300059 · Cited by 580 · see citing works
Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder
Parikh, S. V., Quilty, L. C., Ravitz, P., Rosenbluth, M., Pavlova, B., Grigoriadis, S., Velyvis, V., Kennedy, S. H., Lam, R. W., MacQueen, G. M., et al. (2016) · The Canadian Journal of Psychiatry · doi:10.1177/0706743716659418 · Cited by 562 · see citing works
“Psychological treatments in general and cognitive-behavioural therapy (CBT) in particular appear to be equally effective for different subtypes of depression, including atypical depression, melancholic depression, and anxious depression.(9,10) In addition, a large individual-level meta-analysis confirmed that men and…”
Background
The personalized advantage index: translating research on prediction into individualized treatment recommendations. A demonstration
DeRubeis, R. J., Cohen, Z. D., Forand, N. R., Fournier, J. C., Gelfand, L. A., & Lorenzo-Luaces, L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0083875 · Cited by 509 · see citing works
“In mental health, this includes recent attempts to identify genetic [3–6] and neuroimaging [7–9] indices that predict differential response to pharmacological interventions.”
Background
Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety
Huckvale, K., Venkatesh, S., & Christensen, H. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0166-1 · Cited by 433 · see citing works
Treatment selection in depression.
Cohen, Z. D., & DeRubeis, R. J. (2018) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-050817-084746 · Cited by 435 · see citing works
“Given the observed heterogeneity in the presentation, history, and prognosis of depression, it is unlikely that any single variable in isolation will have clinically useful predictive utility (Simon & Perlis 2010).”
Background
The clinical characterization of the adult patient with depression aimed at personalization of management
Maj, M., Stein, D. J., Parker, G., Zimmerman, M., Fava, G. A., De Hert, M., Demyttenaere, K., McIntyre, R. S., Widiger, T., & Wittchen, H. (2020) · World Psychiatry · doi:10.1002/wps.20771 · Cited by 435 · see citing works
An Inflammatory Biomarker as a Differential Predictor of Outcome of Depression Treatment With Escitalopram and Nortriptyline
Uher, R., Tansey, K. E., Dew, T., Maier, W., Mors, O., Hauser, J., Dernovsek, M. Z., Henigsberg, N., Souery, D., Farmer, A., et al. (2014) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2014.14010094 · Cited by 418 · see citing works
Chemotherapy in Psychiatry
Baldessarini, R. J. (2013) · doi:10.1007/978-1-4614-3710-9 · Cited by 365 · see citing works
Machine learning, statistical learning and the future of biological research in psychiatry
Iniesta, R., Stahl, D. R., & McGuffin, P. (2016) · Psychological Medicine · doi:10.1017/s0033291716001367 · Cited by 329 · see citing works
“Major depressive disorder is a prime example of a common disorder where there are many available drugs but where there is no straightforward way of deciding which treatment is likely to work for a given individual (Simon & Perlis, 2010).”
Background
Annual Research Review: Building a science of personalized intervention for youth mental health
Ng, M. Y., & Weisz, J. R. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12470 · Cited by 291 · see citing works
“In mental health, there is currently insufficient empirical basis for the subgroup approach defined by underlying genetic or biological mechanisms, which predominates in personalized medicine (Insel & Cuthbert, 2015; Mitchell et al., 2010; Simon & Perlis, 2010).”
Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports
Kessler, R., van Loo, H. V., Wardenaar, K., Bossarte, R., Brenner, L., Cai, T., Ebert, D., Hwang, I., Li, J.-L., de Jonge, P., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.198 · Cited by 247 · see citing works
Is low positive emotionality a specific risk factor for depression? A meta-analysis of longitudinal studies.
Khazanov, G. K., & Ruscio, A. M. (2016) · Psychological Bulletin · doi:10.1037/bul0000059 · Cited by 240 · see citing works
“Patient outcomes could improve if treatment choices were made based on characteristics that predict treatment response (DeRubeis et al., 2014), and personality traits have been found to predict response to particular types of treatments (Simon & Perlis, 2010).”
Background
Data-driven biological subtypes of depression: Systematic review of biological approaches to depression subtyping
Beijers, L., Wardenaar, K. J., van Loo, H. M., & Schoevers, R. A. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0385-5 · Cited by 240 · see citing works
Meta-analysis: 13-year follow-up of psychotherapy effects on youth depression
Eckshtain, D., Kuppens, S., Ugueto, A., Ng, M. Y., Vaughn-Coaxum, R., Corteselli, K., & Weisz, J. R. (2020) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2019.04.002 · Cited by 224 · see citing works
Management of Depression in Adults: A Review
Simon, G. E., Moise, N., & Mohr, D. C. (2024) · JAMA · doi:10.1001/jama.2024.5756 · Cited by 234 · see citing works
Self-citation
Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions
Webb, C. A., Rosso, I. M., & Rauch, S. L. (2017) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000139 · Cited by 217 · see citing works
Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting
Hall‐Flavin, D. K., Winner, J. G., Allen, J. D., Carhart, J. M., Proctor, B. D., Snyder, K. A., Drews, M. S., Eisterhold, L. L., Geske, J. R., & Mrazek, D. A. (2013) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0b013e3283649b9a · Cited by 208 · see citing works
The compensation and capitalization models: a test of two approaches to individualizing the treatment of depression
Cheavens, J. S., Strunk, D. R., Lazarus, S. A., & Goldstein, L. A. (2012) · Behaviour Research and Therapy · doi:10.1016/j.brat.2012.08.002 · Cited by 191 · see citing works
“…capitalization and compensation models Most of the evidence relevant to evaluating the capitalization and compensation models has come from examining pretreatment characteristics as predictors of differential response to treatments in randomized trials (for a review, see Simon & Perlis, 2010).”
Strategies to Improve the Management of Depression in Primary Care
Unützer, J., & Park, M. (2012) · Primary Care Clinics in Office Practice · doi:10.1016/j.pop.2012.03.010 · Cited by 197 · see citing works
Neurophysiological predictors of non-response to rTMS in depression
Arns, M., Drinkenburg, W. H. I. M., Fitzgerald, P. B., & Kenemans, J. L. (2012) · Brain stimulation · doi:10.1016/j.brs.2011.12.003 · Cited by 196 · see citing works
“The value of clinical factors in predicting treatment outcome inMDD is very limited [17,18] and a shift towards biomarkers is noticeable.”
Background
Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder
Kessler, R. C., van Loo, H. M., Wardenaar, K. J., Bossarte, R. M., Brenner, L. A., Ebert, D. D., de Jonge, P., Nierenberg, A. A., Rosellini, A. J., Sampson, N. A., et al. (2016) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796016000020 · Cited by 193 · see citing works
“Analyses considering only a small number of modifiers are unlikely to provide reliable clinical guidance due to the existence of many HTE predictors, while more complex subgroup analyses are precluded by the small size of MDD treatment trials (Simon & Perlis, 2010; Cuijpers et al. 2012).”
Predicting early psychiatric readmission with natural language processing of narrative discharge summaries
Rumshisky, A., Ghassemi, M., Naumann, T., Peter Szolovits, B., Castro, V. M., McCoy, T. H., & Perlis, R. H. (2016) · Translational Psychiatry · doi:10.1038/tp.2015.182 · Cited by 190 · see citing works
“25 Another valuable comparison would consider clinician estimates of risk at time of hospital discharge, and the extent to which the variance explained by the present model overlaps with or complements clinician estimate.”
BackgroundSelf-citation
Moderators and non-specific predictors of treatment outcome for anxiety disorders: A comparison of cognitive behavioral therapy to acceptance and commitment therapy
Wolitzky-Taylor, K. B., Arch, J. J., Rosenfield, D., & Craske, M. G. (2012) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0029418 · Cited by 185 · see citing works
Using a pharmacogenomic algorithm to guide the treatment of depression
Hall‐Flavin, D. K., Winner, J. G., Allen, J. D., Jordan, J. J., Nesheim, R. S., Snyder, K. A., Drews, M. S., Eisterhold, L. L., Biernacka, J. M., & Mrazek, D. A. (2012) · Translational Psychiatry · doi:10.1038/tp.2012.99 · Cited by 185 · see citing works
A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder
Perlman, K., Benrimoh, D. A., Israel, S. A., Rollins, C. P. E., Brown, E. H., Tunteng, J.-F., You, R., You, E. L., Tanguay-Sela, M., Snook, E., et al. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2018.09.067 · Cited by 185 · see citing works
Combining clinical variables to optimize prediction of antidepressant treatment outcomes
Iniesta, R., Malki, K., Maier, W., Rietschel, M., Mors, O. N., Hauser, J., Henigsberg, N., Dernovšek, M. Z., Souery, D., Stahl, D. R., et al. (2016) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2016.03.016 · Cited by 182 · see citing works
“There is little evidence to guide clinicians in selecting a treatment for a given individual (Simon and Perlis, 2010).”
Background
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens
Jacobs, M., He, J., F. Pradier, M., Lam, B., Ahn, A. C., McCoy, T. H., Perlis, R. H., Doshi-Velez, F., & Gajos, K. Z. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445385 · Cited by 177 · see citing works
“The frequency of ineffective drug trials has resulted in the psychiatry community calling for more information on which treatments will be most effective for an individual patient [58].”
BackgroundSelf-citation
Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model
Perlis, R. H., Iosifescu, D. V., Castro, V. M., Murphy, S. N., Gainer, V. S., Minnier, J., Cai, T., Goryachev, S., Zeng, Q., Gallagher, P. J., et al. (2012) · Psychological Medicine · doi:10.1017/s0033291711000997 · Cited by 193 · see citing works
“…in psychiatry: treatment resistant depression as a model R. H. Perlis1,2*, D. V. Iosifescu1,3, V. M. Castro4, S. N. Murphy5, V. S. Gainer4, J. Minnier6, T. Cai6, S. Goryachev4, Q. Zeng7, P. J. Gallagher2, M. Fava1, J. B. Weilburg1, S. E. Churchill8, I. S. Kohane9 and J. W. Smoller2 1…”
MethodSelf-citation
Time to get personal? The impact of researchers’ choices on the selection of treatment targets using the experience sampling methodology
Bastiaansen, J. A., Kunkels, Y. K., Blaauw, F., Boker, S. M., Ceulemans, E., Chen, M., Chow, S.-M., de Jonge, P., Emerencia, A. C., Epskamp, S., et al. (2019) · doi:10.31234/osf.io/c8vp7 · Cited by 158 · see citing works
“By identifying individual characteristics that determine disease susceptibility as well as treatment response [6], personalized medicine promises to move from treatments that are effective on average towards identifying the best evidence-based treatment for any individual [7,8].”
PERSONALIZED TREATMENT OF ADULT DEPRESSION: MEDICATION, PSYCHOTHERAPY, OR BOTH? A SYSTEMATIC REVIEW
Cuijpers, P. J., Reynolds, C. F., Donker, T., Li, J., Andersson, G., & Beekman, A. T. F. (2012) · Depression and Anxiety · doi:10.1002/da.21985 · Cited by 166 · see citing works
“[15, 16] Personalized medicine aims at identifying which characteristics of an individual predict the outcome of a specific treatment in order to get a better match between the individual and treatment received.[17] These characteristics may include sociodemographic characteristics and clinical characteristics of the…”
BackgroundInfluential
Clinical Predictors of Ketamine Response in Treatment-Resistant Major Depression
Niciu, M. J., Luckenbaugh, D. A., Ionescu, D. F., Guevara, S., Machado-Vieira, R., Richards, E. M., Brutsche, N. E., Nolan, N. M., & Zarate, C. A. (2014) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.13m08698 · Cited by 165 · see citing works
Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns
Liao, S., Wu, C., Huang, H.-C., Cheng, W.-T., & Liu, Y. (2017) · Sensors · doi:10.3390/s17061385 · Cited by 165 · see citing works
“Therefore, measuring brain activity is a reasonable approach to explore the endophenotype of MDD. Measurement of brain activity may help us reﬁne MDD into several more homogeneous subgroups and to match an effective treatment [13,14].”
Background
Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis
Sajjadian, M., Lam, R. W. M., Milev, R. V., Rotzinger, S., Frey, B. N., Soares, C. N., Parikh, S. V., Foster, J. A., Turecki, G., Müller, D. J., et al. (2021) · Psychological Medicine · doi:10.1017/s0033291721003871 · Cited by 159 · see citing works
“Reasons for the lack of adoption may be that no single characteristic provides a prediction that is accurate enough to be clinically meaningful or differential prediction of outcomes with alternative treatments (Simon & Perlis, 2010).”
Background
Predicting Optimal Outcomes in Cognitive Therapy or Interpersonal Psychotherapy for Depressed Individuals Using the Personalized Advantage Index Approach
Huibers, M. J. H., Cohen, Z. D., Lemmens, L. H. J. M., Arntz, A., Peeters, F. P. M. L., Cuijpers, P., & DeRubeis, R. J. (2015) · PLOS ONE · doi:10.1371/journal.pone.0140771 · Cited by 215 · see citing works
An adaptationist perspective on the etiology of depression
Durisko, Z., Mulsant, B. H., & Andrews, P. W. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.09.032 · Cited by 140 · see citing works
“Indeed, despite its intuitive appeal, there is little support for the notion that a treatment that has been effective during a prior episode will be effective in subsequent depressive episodes (Remillard et al., 1994; Simon and Perlis, 2010).”
BackgroundInfluential
Predictors of remission in depression to individual and combined treatments (PReDICT): study protocol for a randomized controlled trial
Dunlop, B. W., Binder, E. B., Cubells, J. F., Goodman, M. M., Kelley, M. E., Kinkead, B., Kutner, M., Nemeroff, C. B., Newport, D. J., Owens, M. J., et al. (2012) · Trials · doi:10.1186/1745-6215-13-106 · Cited by 136 · see citing works
“Previous efforts attempting to identify predictors of treatment response have typically been post-hoc analyses of datasets designed to test other hypotheses [18].”
Neurocognitive Effects of Ketamine and Association with Antidepressant Response in Individuals with Treatment-Resistant Depression: A Randomized Controlled Trial
Murrough, J. W., Burdick, K. E., Levitch, C. F., Perez, A. M., Brallier, J. W., Chang, L. C., Foulkes, A., Charney, D. S., Mathew, S. J., & Iosifescu, D. V. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2014.298 · Cited by 142 · see citing works
“Prior studies have found associations between clinical and demographic factors and therapeutic response to conventional antidepressants (Perlis, 2013), however, a quantitative laboratory-based behavioral or biological predictor of treatment response has remained elusive (Kapur et al, 2012; Simon and Perlis, 2010; Triv…”
Background
The state of personalized treatment for anxiety disorders: A systematic review of treatment moderators
Schneider, R. L., Arch, J. J., & Wolitzky-Taylor, K. B. (2015) · Clinical Psychology Review · doi:10.1016/j.cpr.2015.02.004 · Cited by 135 · see citing works
“Distinguishing treatment and childhood depression and childhood anxiety disorder literatures have been synthesized in reviews (Nilsen, Eisemann, & Kvernmo, 2013; Simon & Perlis, 2010).”
Background
Translating biomarkers to clinical practice
Perlis, R. H. (2011) · Molecular Psychiatry · doi:10.1038/mp.2011.63 · Cited by 134 · see citing works
Self-citation
Genetic Predictors of Response to Serotonergic and Noradrenergic Antidepressants in Major Depressive Disorder: A Genome-Wide Analysis of Individual-Level Data and a Meta-Analysis
Tansey, K. E., Guipponi, M., Perroud, N. A., Bondolfi, G., Domenici, E., Evans, D. M., Hall, S. K., Hauser, J., Henigsberg, N., Hu, X., et al. (2012) · PLoS Medicine · doi:10.1371/journal.pmed.1001326 · Cited by 131 · see citing works
“Currently, no clinically significant predictor is available [10].”
Background
Personalized Psychotherapy for Adult Depression: A Meta-Analytic Review
Cuijpers, P., Ebert, D. D., Acarturk, C., Andersson, G., & Cristea, I. A. (2016) · Behavior Therapy · doi:10.1016/j.beth.2016.04.007 · Cited by 128 · see citing works
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Predictors and Moderators of Response to Internet-Delivered Interpersonal Psychotherapy and Cognitive Behavior Therapy for Depression
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“By identifying which characteristics of an individual predict the outcome of a specific treatment, a better match of treatment to the individual characteristics is achievable (Cuijpers et al., 2012; Simon and Perlis, 2010).”
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Regulation of neural responses to emotion perception by ketamine in individuals with treatment-resistant major depressive disorder
Murrough, J. W., Collins, K. A., Fields, J., DeWilde, K. E., Phillips, M. L., Mathew, S. J., Wong, E., Tang, C. Y., Charney, D. S., & Iosifescu, D. V. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.10 · Cited by 109 · see citing works
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“or contradict thewisdomof heeding a depressedpatient’s preference for a specific treatment, or of favoring an antidepressant to which a patient has responded in the past.(40)”
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Translational applications of personality science for the conceptualization and treatment of psychopathology.
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“With regard to affective disorders, Simon and Perlis (2010) argued that personalized medicine for depression would be better served by monitoring outcomes and adjusting treatment over time than by attempting to personalize via information collected before treatment is initiated.”
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Pharmacogenetics in psychiatry: translating research into clinical practice
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BackgroundResult
Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: cognitive therapy or interpersonal psychotherapy?
van Bronswijk, S. C., DeRubeis, R. J., Lemmens, L. H. J. M., Peeters, F. P. M. L., Keefe, J. R., Cohen, Z. D., & Huibers, M. J. H. (2021) · Psychological Medicine · doi:10.1017/s0033291719003192 · Cited by 75 · see citing works
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“…moderators of treatment outcomes (Kraemer, Frank, & Kupfer, 2006; Kraemer, Wilson, Fairburn, & Agras, 2002) in an effort to personalise treatments (Simon & Perlis, 2010) for PTSD. Dissociation has been suggested by a number of researchers and trauma therapists as an important moderator of…”
Background
Transdiagnostic Treatment Personalization: The Feasibility of Ordering Unified Protocol Modules According to Patient Strengths and Weaknesses
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“…evidence cited to support these personalization strategies has come from post hoc examinations of pretreatment characteristics that predict differential response to interventions in randomized trials and the literature is mixed with regard to the most advantageous approach (Simon & Perlis, 2010).”
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RETRACTED: Individual Differences in Response to Antidepressants
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EEG-Based Personalized Medicine in ADHD: Individual Alpha Peak Frequency as an Endophenotype Associated with Nonresponse
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“Therefore, a move beyond data regarding the average effectiveness of treatment, to identify the best treatment for any individual (Simon & Perlis, 2010) or personalized medicine, is crucial.”
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Reinforcement learning for personalization: A systematic literature review
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Individual Differences in Response to Antidepressants
Maslej, M. M., Furukawa, T. A., Cipriani, A., Andrews, P. W., Sanches, M., Tomlinson, A., Volkmann, C., McCutcheon, R. A., Howes, O. D., Guo, X., et al. (2021) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.4564 · Cited by 55 · see citing works
Is it worth it to personalize the treatment of PTSD? – A variance-ratio meta-analysis and estimation of treatment effect heterogeneity in RCTs of PTSD
Herzog, P., & Kaiser, T. (2022) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2022.102611 · Cited by 60 · see citing works
Single-subject research in psychiatry: facts and fictions
Zuidersma, M., Riese, H., Snippe, E., Booij, S. H., Wichers, M., & Bos, E. H. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.539777 · Cited by 54 · see citing works
Older Adults With Severe, Treatment-Resistant Depression
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A narrative review of emotion regulation process in stress and recovery phases
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Non-linear EEG analyses predict non-response to rTMS treatment in major depressive disorder
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Blue genes? Understanding and mitigating negative consequences of personalized information about genetic risk for depression
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“In particular, there has been significant interest in using genetic information and other biomarkers to find the best antidepressant medication for individual patients (Simon and Perlis 2010; Uher et al. 2010; Williams et al. 2011).”
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Predicting Barriers to Treatment for Depression in a U.S. National Sample: A Cross-Sectional, Proof-of-Concept Study
Chekroud, A. M., Foster, D. F., Zheutlin, A. B., Gerhard, D. M., Roy, B., Koutsouleris, N., Chandra, A., Esposti, M. D., Subramanyan, G., Gueorguieva, R. V., et al. (2018) · Psychiatric Services · doi:10.1176/appi.ps.201800094 · Cited by 51 · see citing works
“Because low motivation, hypersomnia, and low energy are cardinal symptoms of depression, aggressive outreach may be required to encourage some individuals to begin and remain in care (46,49), and thus better targeting of patients in need of encouragement may make outreach cost-effective.”
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Inflammatory Biomarker and Response to Antidepressant in Major Depressive Disorder: a Systematic Review and Meta-Analysis
Gasparini, A., Callegari, C., Lucca, G., Bellini, A., Caselli, I., & Ielmini, M. (2025) · Psychopharmacology Bulletin · doi:10.64719/pb.4425 · Cited by 49 · see citing works
Robust symptom networks in recurrent major depression across different levels of genetic and environmental risk
van Loo, H. M., van Borkulo, C. D., Peterson, R. E., Fried, E. I., Aggen, S. H., Borsboom, D., & Kendler, K. S. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.10.038 · Cited by 49 · see citing works
“Major depression (MD) is a heterogeneous disorder in terms of presentation, course of illness and treatment response (Cuijpers et al., 2012; Eaton et al., 2008; Hardeveld et al., 2013; Holma et al., 2008; Oquendo et al., 2004; Simon and Perlis, 2010).”
What are the chances for personalised treatment with antidepressants? Detection of patient-by-treatment interaction with a variance ratio meta-analysis
Plöderl, M., & Hengartner, M. P. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-034816 · Cited by 50 · see citing works
How and for whom does web-based acceptance and commitment therapy work? Mediation and moderation analyses of web-based ACT for depressive symptoms
Pots, W. T. M., Trompetter, H. R., Schreurs, K. M. G., & Bohlmeijer, E. T. (2016) · BMC Psychiatry · doi:10.1186/s12888-016-0841-6 · Cited by 46 · see citing works
“Since the analyses were exploratory and post-hoc, the absence of significant moderators could well be a result of inadequate statistical power [67].”
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Customizing Emotional Support: How Do Individuals Construct and Interact With LLM-Powered Chatbots
Zheng, X., Li, Z., Gui, X., & Luo, Y. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713453 · Cited by 50 · see citing works
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The importance of transdiagnostic symptom level assessment to understanding prognosis for depressed adults: analysis of data from six randomised control trials
O’Driscoll, C., Buckman, J. E. J., Fried, E. I., Saunders, R., Cohen, Z. D., Ambler, G., DeRubeis, R. J., Gilbody, S. M., Hollon, S. D., Kendrick, T., et al. (2021) · BMC Medicine · doi:10.1186/s12916-021-01971-0 · Cited by 46 · see citing works
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“…greater understanding of who, when, and how individuals are at most risk for maladaptive outcomes, or who, when, and how some individuals are resilient, studies can push forward more targeted and personalized prevention and intervention strategies (Simon & Perlis, 2010; Willard & Ginsburg, 2009).”
Background
Biomarkers Predicting Treatment Outcome in Depression: What is Clinically Significant?
Uher, R., Tansey, K. E., Malki, K., & Perlis, R. H. (2012) · Pharmacogenomics · doi:10.2217/pgs.11.161 · Cited by 44 · see citing works
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“Keywords: GAD; interpersonal problems; CBT; cognitive therapy; behavioral therapy AN IMPORTANT FOCUS OF PSYCHOTHERAPY research has been which treatments work for whom (Paul, 1967), which is the core theme of “personalized medicine” (Simon & Perlis, 2010).”
Novel drug-regulated transcriptional networks in brain reveal pharmacological properties of psychotropic drugs
Korostyński, M., Piechota, M., Dzbek, J., Młynarski, W. F., Szklarczyk, K., Ziółkowska, B., & Przewłocki, R. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-606 · Cited by 41 · see citing works
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“In depression, it has been suggested that it will be necessary to consider a range of factors including sociodemographic factors, biological markers (for example neural changes and genetic variation) and differences in clinical presentation (Simon and Perlis, 2010).”
Background
Symptom networks in acute depression across bipolar and major depressive disorders: A network analysis on a large, international, observational study
Corponi, F., Anmella, G., Verdolini, N., Pacchiarotti, I., Samalin, L., Popović, D., Azorin, J., Angst, J., Bowden, C. L., Mosolov, S. N., et al. (2020) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2020.03.017 · Cited by 39 · see citing works
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“This limits their opportunity for treatment with a different agent or the addition of a second drug; both strategies are used in non-responders and can be effective [19].”
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Neuroimaging for precision medicine in psychiatry
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Advancing Personalized Medicine: Application of a Novel Statistical Method to Identify Treatment Moderators in the Coordinated Anxiety Learning and Management Study
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A quantitative review on outcome-to-antidepressants in melancholic unipolar depression
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Abandoning personalization to get to precision in the pharmacotherapy of depression
Perlis, R. H. (2016) · World Psychiatry · doi:10.1002/wps.20345 · Cited by 78 · see citing works
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Authors: Simon, G. E., & Perlis, R. H.
Affiliations: Kaiser Permanente Washington Health Research Institute (US)
ORCID: Simon, Gregory E.
Perlis, Roy H.
Venue: American Journal of Psychiatry
Publisher: American Psychiatric Association Publishing
Published: 2010-12
Volume: 167
Issue: 12
Pages: 1445-1455
ISSN: 0002-953X (ISSN-L)
1535-7228
DOI: 10.1176/appi.ajp.2010.09111680
PMC: PMC3723328
OpenAlex: W2148933229
Semantic Scholar: ca7063c77ba1833df2d5629f27cb2392af0da971
Cited by: 365
References: 89
Citations by year: 2026: 17 · 2025: 16 · 2024: 34 · 2023: 21 · 2022: 29 · 2021: 29 · 2020: 30 · 2019: 24 · 2018: 21 · 2017: 17 · 2016: 25 · 2015: 24 · 2014: 25 · 2013: 17 · 2012: 26
FWCI: 1.87
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: American Journal of Psychiatry (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: Eli Lilly and Company
National Institute of Mental Health (P20MH068572, R01MH085930, R01MH086026)
Topics: Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Keywords: depression, personalized medicine, treatment response variability, antidepressants, psychotherapy, treatment selection, treatment moderators, predictors of treatment outcome, genetic predictors, treatment modification
MeSH terms: Antidepressive Agents, Clinical Trials as Topic, Decision Support Techniques, Depression, Humans, Psychotherapy, Precision Medicine

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Personalized Medicine for Depression: Can We Match Patients With Treatments?

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