Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

Chiara Fabbri; Siegfried Kasper; Joseph Zohar; Daniel Souery; Stuart Montgomery; Diego Albani; Gianluigi Forloni; Panagiotis Ferentinos; Dan Rujescu; Julien Mendlewicz; Alessandro Serretti; Cathryn M. Lewis

doi:10.1016/j.jad.2020.10.049

Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

Chiara Fabbri^*, Siegfried Kasper, Joseph Zohar, Daniel Souery, Stuart Montgomery, Diego Albani, Gianluigi Forloni, Panagiotis Ferentinos, Dan Rujescu, Julien Mendlewicz, Alessandro Serretti, Cathryn M. Lewis

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

Background:: Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment. Methods:: We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health). Results:: CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples. Limitations:: lack of validation in large samples from the general population. Conclusions:: Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.

Original language	English
Pages (from-to)	722-729
Number of pages	8
Journal	Journal of Affective Disorders
Volume	279
DOIs	https://doi.org/10.1016/j.jad.2020.10.049
Publication status	Published - 15 Jan 2021

Keywords

Antidepressants
Cost-Effectiveness
Genetics
Psychotherapy
Treatment-Resistant Depression

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10.1016/j.jad.2020.10.049

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Fabbri, C., Kasper, S., Zohar, J., Souery, D., Montgomery, S., Albani, D., Forloni, G., Ferentinos, P., Rujescu, D., Mendlewicz, J., Serretti, A., & Lewis, C. M. (2021). Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression. Journal of Affective Disorders, 279, 722-729. https://doi.org/10.1016/j.jad.2020.10.049

@article{63ac02a387204a72993866c19bf9181b,

title = "Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression",

abstract = "Background:: Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment. Methods:: We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health). Results:: CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples. Limitations:: lack of validation in large samples from the general population. Conclusions:: Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.",

keywords = "Antidepressants, Cost-Effectiveness, Genetics, Psychotherapy, Treatment-Resistant Depression",

author = "Chiara Fabbri and Siegfried Kasper and Joseph Zohar and Daniel Souery and Stuart Montgomery and Diego Albani and Gianluigi Forloni and Panagiotis Ferentinos and Dan Rujescu and Julien Mendlewicz and Alessandro Serretti and Lewis, {Cathryn M.}",

note = "Funding Information: The collection of the main sample included in this study and TRD2 sample was supported by an unrestricted grant from Lundbeck for the Group for the Study of Resistant Depression (GSRD). Lundbeck had no further role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. All authors were actively involved in the design of the study, the analytical method of the study, the selection and review of all scientific content. All authors had full editorial control during the writing of the manuscript and approved it. Funding Information: The GENDEP project was supported by a European Commission Framework 6 grant (contract reference: LSHB-CT-2003-503428). The Medical Research Council, United Kingdom, and GlaxoSmithKline (G0701420) provided support for genotyping. This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. High performance computing facilities were funded with capital equipment grants from the GSTT Charity (TR130505) and Maudsley Charity (980). Funding Information: Chiara Fabbri was supported by a Marie Sk{\l}odowska-Curie Actions Individual Fellowship funded by the European Community (EC Grant agreement number: 793526; project title: Exome Sequencing in stages of Treatment Resistance to Antidepressants - ESTREA). Publisher Copyright: {\textcopyright} 2020 Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

month = jan,

day = "15",

doi = "10.1016/j.jad.2020.10.049",

language = "English",

volume = "279",

pages = "722--729",

journal = "Journal of Affective Disorders",

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Fabbri, C, Kasper, S, Zohar, J, Souery, D, Montgomery, S, Albani, D, Forloni, G, Ferentinos, P, Rujescu, D, Mendlewicz, J, Serretti, A & Lewis, CM 2021, 'Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression', Journal of Affective Disorders, vol. 279, pp. 722-729. https://doi.org/10.1016/j.jad.2020.10.049

TY - JOUR

T1 - Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

AU - Fabbri, Chiara

AU - Kasper, Siegfried

AU - Zohar, Joseph

AU - Souery, Daniel

AU - Montgomery, Stuart

AU - Albani, Diego

AU - Forloni, Gianluigi

AU - Ferentinos, Panagiotis

AU - Rujescu, Dan

AU - Mendlewicz, Julien

AU - Serretti, Alessandro

AU - Lewis, Cathryn M.

N1 - Funding Information: The collection of the main sample included in this study and TRD2 sample was supported by an unrestricted grant from Lundbeck for the Group for the Study of Resistant Depression (GSRD). Lundbeck had no further role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. All authors were actively involved in the design of the study, the analytical method of the study, the selection and review of all scientific content. All authors had full editorial control during the writing of the manuscript and approved it. Funding Information: The GENDEP project was supported by a European Commission Framework 6 grant (contract reference: LSHB-CT-2003-503428). The Medical Research Council, United Kingdom, and GlaxoSmithKline (G0701420) provided support for genotyping. This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. High performance computing facilities were funded with capital equipment grants from the GSTT Charity (TR130505) and Maudsley Charity (980). Funding Information: Chiara Fabbri was supported by a Marie Skłodowska-Curie Actions Individual Fellowship funded by the European Community (EC Grant agreement number: 793526; project title: Exome Sequencing in stages of Treatment Resistance to Antidepressants - ESTREA). Publisher Copyright: © 2020 Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/1/15

Y1 - 2021/1/15

N2 - Background:: Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment. Methods:: We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health). Results:: CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples. Limitations:: lack of validation in large samples from the general population. Conclusions:: Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.

AB - Background:: Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment. Methods:: We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health). Results:: CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples. Limitations:: lack of validation in large samples from the general population. Conclusions:: Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.

KW - Antidepressants

KW - Cost-Effectiveness

KW - Genetics

KW - Psychotherapy

KW - Treatment-Resistant Depression

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DO - 10.1016/j.jad.2020.10.049

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AN - SCOPUS:85096175899

SN - 0165-0327

VL - 279

SP - 722

EP - 729

JO - Journal of Affective Disorders

JF - Journal of Affective Disorders

ER -

Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

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Keywords

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