A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC)

Dore Loef; Adriaan W Hoogendoorn; Metten Somers; Roel J T Mocking; Dominique S Scheepens; Karel W F Scheepstra; Maaike Blijleven; Johanna M Hegeman; Karen S van den Berg; Bart Schut; Tom K Birkenhager; Willemijn Heijnen; Didi Rhebergen; Mardien L Oudega; Sigfried N T M Schouws; Eric van Exel; Bart P F Rutten; Birit F P Broekman; Anton C M Vergouwen; Thomas J C Zoon; Rob M Kok; Karina Somers; Esmée Verwijk; Jordy J E Rovers; Gijsbert Schuur; Jeroen A van Waarde; Joey P A J Verdijk; Dieneke Bloemkolk; Frank L Gerritse; Hanneke van Welie; Bartholomeus C M Haarman; Sjoerd M van Belkum; Maurice Vischjager; Karin Hagoort; Edwin van Dellen; Indira Tendolkar; Philip F P van Eijndhoven; Annemiek Dols

doi:10.1038/s41380-024-02803-2

A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC)

Dore Loef, Adriaan W Hoogendoorn, Metten Somers, Roel J T Mocking, Dominique S Scheepens, Karel W F Scheepstra, Maaike Blijleven, Johanna M Hegeman, Karen S van den Berg, Bart Schut, Tom K Birkenhager, Willemijn Heijnen, Didi Rhebergen, Mardien L Oudega, Sigfried N T M Schouws, Eric van Exel, Bart P F Rutten, Birit F P Broekman, Anton C M Vergouwen, Thomas J C ZoonRob M Kok, Karina Somers, Esmée Verwijk, Jordy J E Rovers, Gijsbert Schuur, Jeroen A van Waarde, Joey P A J Verdijk, Dieneke Bloemkolk, Frank L Gerritse, Hanneke van Welie, Bartholomeus C M Haarman, Sjoerd M van Belkum, Maurice Vischjager, Karin Hagoort, Edwin van Dellen, Indira Tendolkar, Philip F P van Eijndhoven, Annemiek Dols

Research output: Contribution to journal/periodical › Article › Scientific › peer-review

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Abstract

Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.

Original language	English
Journal	Molecular Psychiatry
DOIs	https://doi.org/10.1038/s41380-024-02803-2
Publication status	E-pub ahead of print - Jan 2025

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10.1038/s41380-024-02803-2

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Loef, D., Hoogendoorn, A. W., Somers, M., Mocking, R. J. T., Scheepens, D. S., Scheepstra, K. W. F., Blijleven, M., Hegeman, J. M., van den Berg, K. S., Schut, B., Birkenhager, T. K., Heijnen, W., Rhebergen, D., Oudega, M. L., Schouws, S. N. T. M., van Exel, E., Rutten, B. P. F., Broekman, B. F. P., Vergouwen, A. C. M., ... Dols, A. (2025). A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC). Molecular Psychiatry. Advance online publication. https://doi.org/10.1038/s41380-024-02803-2

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title = "A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC)",

abstract = "Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.",

author = "Dore Loef and Hoogendoorn, {Adriaan W} and Metten Somers and Mocking, {Roel J T} and Scheepens, {Dominique S} and Scheepstra, {Karel W F} and Maaike Blijleven and Hegeman, {Johanna M} and {van den Berg}, {Karen S} and Bart Schut and Birkenhager, {Tom K} and Willemijn Heijnen and Didi Rhebergen and Oudega, {Mardien L} and Schouws, {Sigfried N T M} and {van Exel}, Eric and Rutten, {Bart P F} and Broekman, {Birit F P} and Vergouwen, {Anton C M} and Zoon, {Thomas J C} and Kok, {Rob M} and Karina Somers and Esm{\'e}e Verwijk and Rovers, {Jordy J E} and Gijsbert Schuur and {van Waarde}, {Jeroen A} and Verdijk, {Joey P A J} and Dieneke Bloemkolk and Gerritse, {Frank L} and {van Welie}, Hanneke and Haarman, {Bartholomeus C M} and {van Belkum}, {Sjoerd M} and Maurice Vischjager and Karin Hagoort and {van Dellen}, Edwin and Indira Tendolkar and {van Eijndhoven}, {Philip F P} and Annemiek Dols",

note = "{\textcopyright} 2024. The Author(s), under exclusive licence to Springer Nature Limited.",

year = "2025",

month = jan,

doi = "10.1038/s41380-024-02803-2",

language = "English",

journal = "Molecular Psychiatry",

issn = "1359-4184",

publisher = "Nature Publishing Group",

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Loef, D, Hoogendoorn, AW, Somers, M, Mocking, RJT, Scheepens, DS, Scheepstra, KWF, Blijleven, M, Hegeman, JM, van den Berg, KS, Schut, B, Birkenhager, TK, Heijnen, W, Rhebergen, D, Oudega, ML, Schouws, SNTM, van Exel, E, Rutten, BPF, Broekman, BFP, Vergouwen, ACM, Zoon, TJC, Kok, RM, Somers, K, Verwijk, E, Rovers, JJE, Schuur, G, van Waarde, JA, Verdijk, JPAJ, Bloemkolk, D, Gerritse, FL, van Welie, H, Haarman, BCM, van Belkum, SM, Vischjager, M, Hagoort, K, van Dellen, E, Tendolkar, I, van Eijndhoven, PFP & Dols, A 2025, 'A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC)', Molecular Psychiatry. https://doi.org/10.1038/s41380-024-02803-2

TY - JOUR

T1 - A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC)

AU - Loef, Dore

AU - Hoogendoorn, Adriaan W

AU - Somers, Metten

AU - Mocking, Roel J T

AU - Scheepens, Dominique S

AU - Scheepstra, Karel W F

AU - Blijleven, Maaike

AU - Hegeman, Johanna M

AU - van den Berg, Karen S

AU - Schut, Bart

AU - Birkenhager, Tom K

AU - Heijnen, Willemijn

AU - Rhebergen, Didi

AU - Oudega, Mardien L

AU - Schouws, Sigfried N T M

AU - van Exel, Eric

AU - Rutten, Bart P F

AU - Broekman, Birit F P

AU - Vergouwen, Anton C M

AU - Zoon, Thomas J C

AU - Kok, Rob M

AU - Somers, Karina

AU - Verwijk, Esmée

AU - Rovers, Jordy J E

AU - Schuur, Gijsbert

AU - van Waarde, Jeroen A

AU - Verdijk, Joey P A J

AU - Bloemkolk, Dieneke

AU - Gerritse, Frank L

AU - van Welie, Hanneke

AU - Haarman, Bartholomeus C M

AU - van Belkum, Sjoerd M

AU - Vischjager, Maurice

AU - Hagoort, Karin

AU - van Dellen, Edwin

AU - Tendolkar, Indira

AU - van Eijndhoven, Philip F P

AU - Dols, Annemiek

PY - 2025/1

Y1 - 2025/1

N2 - Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.

AB - Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.

U2 - 10.1038/s41380-024-02803-2

DO - 10.1038/s41380-024-02803-2

M3 - Article

C2 - 39448805

SN - 1359-4184

JO - Molecular Psychiatry

JF - Molecular Psychiatry

ER -