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Therapy and prevention for mental health: What if mental diseases are mostly not brain disorders?

Published online by Cambridge University Press:  06 March 2019

John P. A. Ioannidis
John P. A. Ioannidis*
Affiliation:
Departments of Medicine, Health Research and Policy, and Biomedical Data Science, Stanford University School of Medicine; and Department of Statistics, Stanford University School of Humanities and Sciences; and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA 94305. [email protected]://profiles.stanford.edu/john-ioannidis
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Abstract

Neurobiology-based interventions for mental diseases and searches for useful biomarkers of treatment response have largely failed. Clinical trials should assess interventions related to environmental and social stressors, with long-term follow-up; social rather than biological endpoints; personalized outcomes; and suitable cluster, adaptive, and n-of-1 designs. Labor, education, financial, and other social/political decisions should be evaluated for their impacts on mental disease.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e13
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Copyright
Copyright © Cambridge University Press 2019 

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References

Alves, P., Sales, C. & Ashworth, M. (2017) Does outcome measurement of treatment for substance use disorder reflect the personal concerns of patients? A scoping review of measures recommended in Europe. Drug and Alcohol Dependence 179:299–308.Google Scholar
Braid, F., Baiardini, I., Molinengo, G., Garuti, S., Ferrari, M., Mantero, M., Blasi, F. & Canonica, G. W. (2016) Choose your outcomes: From the mean to the personalized assessment of outcomes in COPD. An exploratory pragmatic survey. European Journal of Internal Medicine 34:85–88.Google Scholar
Chandler, D. J. (2013) Something's got to give: Psychiatric disease on the rise and novel drug development on the decline. Drug Discovery Today 18:202–206.Google Scholar
Cipriani, A., Furukawa, T. A., Salanti, G., Chaimani, A., Atkinson, L. Z., Ogawa, Y., Leucht, S., Ruhe, H. G., Turner, E. H., Higgins, J. P. T., Egger, M., Takeshima, N., Hayasaka, Y., Imai, H., Shinohara, K., Tajika, A., Ioannidis, J. P. A. & Geddes, J. R. (2018) Comparative efficacy and acceptability of first- and second-generation antidepressants in the acute treatment of major depressive disorder: A network meta-analysis. The Lancet 391:1357–66.Google Scholar
Gotzsche, P. C. (2013) Deadly medicines and organized crime. CRC Press.Google Scholar
Huhn, M., Tardy, M., Spineli, L.-M., Kissling, W., Förstl, H., Pitschel-Walz, G., Leucht, C., Samara, M., Dold, M., Davis, J. M. & Leucht, S. (2014) Efficacy of pharmacotherapy and psychotherapy for adult psychiatric disorders: A systematic overview of meta-analyses. JAMA Psychiatry 71:706–15.Google Scholar
Ioannidis, J. P. (2008) Effectiveness of antidepressants: An evidence myth constructed of a thousand clinical trials? Philosophy, Ethics, and Humanities in Medicine 3:14. doi: 10.1186/1747-5341-3-14. Available at: https://peh-med.biomedcentral.com/articles/10.1186/1747-5341-3-14.Google Scholar
Kendrick, T., El-Gohary, M., Stuart, B., Gilbody, S., Churchill, R., Aiken, L., Bhattacharya, A., Gimson, A., Brütt, A. L., de Jong, K. & Moore, M. (2016) Routine use of patient reported outcome measures (PROMs) for improving treatment of common mental health disorders in adults. Cochrane Database of Systematic Reviews 7: article CD011119. Available at: https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD011119.pub2/media/CDSR/CD011119/CD011119_standard.pdf.Google Scholar
Leucht, S., Leucht, C., Huhn, M., Chaimani, A., Mavridis, D., Helfer, B., Samara, M., Rabaioli, M., Bächer, S., Cipriani, A., Geddes, J. R., Salanti, G. & Davis, J. M. (2017) Sixty years of placebo-controlled antipsychotic drug trials in acute schizophrenia: systematic review, Bayesian meta-analysis, and meta-regression of efficacy predictors. American Journal of Psychiatry 174:927–42.Google Scholar
Macefield, R. C., Jacobs, M., Korfage, I. J., Nicklin, J., Whistance, R. N., Brookes, S. T., Sprangers, M. A. & Blazeby, J. M. (2014) Developing core outcomes sets: Methods for identifying and including patient-reported outcomes (PROs). Trials 15:49. doi: 10.1186/1745-6215-15-49.Google Scholar
Radua, J., Ramella-Cravaro, V., Ioannidis, J. P. A., Reichenberg, A., Phiphopthatsanee, N., Amir, T., Yenn Thoo, H., Oliver, D., Davies, C., Morgan, C., McGuire, P., Murray, R. M. & Fusar-Poli, P. (2018) What causes psychosis? An umbrella review of risk and protective factors. World Psychiatry 17:49–66.Google Scholar
Thase, M. E. (2014) Using biomarkers to predict treatment response in major depressive disorder: Evidence from past and present studies. Dialogues in Clinical Neuroscience 16:539–44.Google Scholar