Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data

Abstract Background Threshold regression, in which time to remission is modelled as a stochastic drift towards a boundary, is an alternative to the proportional hazards survival model and has a clear conceptual mechanism for examining the effects of drug dose. However, for both threshold regression...

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Main Authors: Jennifer Hellier, Richard Emsley, Andrew Pickles
Format: Article
Language:English
Published: BMC 2020-01-01
Series:Trials
Subjects:
Online Access:https://doi.org/10.1186/s13063-019-3810-9
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spelling doaj-94ecf7c956414e52aed1b99bb5791dc92021-01-03T12:14:25ZengBMCTrials1745-62152020-01-0121111110.1186/s13063-019-3810-9Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial dataJennifer Hellier0Richard Emsley1Andrew Pickles2Biostatistics and Health Informatics Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College LondonBiostatistics and Health Informatics Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College LondonBiostatistics and Health Informatics Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College LondonAbstract Background Threshold regression, in which time to remission is modelled as a stochastic drift towards a boundary, is an alternative to the proportional hazards survival model and has a clear conceptual mechanism for examining the effects of drug dose. However, for both threshold regression and proportional hazard models, when dose titration occurs during treatment, the estimated causal effect of dose can be biased by confounding. An instrumental variable analysis can be used to minimise such bias. Method Weekly antidepressant dose was measured in 380 men and women with major depression treated with escitalopram or nortriptyline for 12 weeks as part of the Genome Based Therapeutic Drugs for Depression (GENDEP) study. The averaged dose relative to maximum prescribing dose was calculated from the 12 trial weeks and tested for association with time to depression remission. We combined the instrumental variable approach, utilising randomised treatment as an instrument, with threshold regression and proportional hazard survival models. Results The threshold model was constructed with two linear predictors. In the naïve models, averaged daily dose was not associated with reduced time to remission. By contrast, the instrumental variable analyses showed a clear and significant relationship between increased dose and faster time to remission, threshold regression (velocity estimate: 0.878, 95% confidence interval [CI]: 0.152–1.603) and proportional hazards (log hazards ratio: 3.012, 95% CI: 0.086–5.938). Conclusions We demonstrate, using the GENDEP trial, the benefits of these analyses to estimate causal parameters rather than those that estimate associations. The results for the trial dataset show the link between antidepressant dose and time to depression remission. The threshold regression model more clearly distinguishes the factors associated with initial severity from those influencing treatment effect. Additionally, applying the instrumental variable estimator provides a more plausible causal estimate of drug dose on treatment effect. This validity of these results is subject to meeting the assumptions of instrumental variable analyses. Trial registration EudraCT, 2004–001723-38; ISRCTN, 03693000. Registered on 27 September 2007.https://doi.org/10.1186/s13063-019-3810-9DepressionDose responseInstrumental variablesSurvival analysisThreshold regressionTime to remission
collection DOAJ
language English
format Article
sources DOAJ
author Jennifer Hellier
Richard Emsley
Andrew Pickles
spellingShingle Jennifer Hellier
Richard Emsley
Andrew Pickles
Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data
Trials
Depression
Dose response
Instrumental variables
Survival analysis
Threshold regression
Time to remission
author_facet Jennifer Hellier
Richard Emsley
Andrew Pickles
author_sort Jennifer Hellier
title Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data
title_short Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data
title_full Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data
title_fullStr Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data
title_full_unstemmed Estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in Genome Based Therapeutic Drugs for Depression Trial (GENDEP): clinical trial data
title_sort estimating dose-response for time to remission with instrumental variable adjustment: the obscuring effects of drug titration in genome based therapeutic drugs for depression trial (gendep): clinical trial data
publisher BMC
series Trials
issn 1745-6215
publishDate 2020-01-01
description Abstract Background Threshold regression, in which time to remission is modelled as a stochastic drift towards a boundary, is an alternative to the proportional hazards survival model and has a clear conceptual mechanism for examining the effects of drug dose. However, for both threshold regression and proportional hazard models, when dose titration occurs during treatment, the estimated causal effect of dose can be biased by confounding. An instrumental variable analysis can be used to minimise such bias. Method Weekly antidepressant dose was measured in 380 men and women with major depression treated with escitalopram or nortriptyline for 12 weeks as part of the Genome Based Therapeutic Drugs for Depression (GENDEP) study. The averaged dose relative to maximum prescribing dose was calculated from the 12 trial weeks and tested for association with time to depression remission. We combined the instrumental variable approach, utilising randomised treatment as an instrument, with threshold regression and proportional hazard survival models. Results The threshold model was constructed with two linear predictors. In the naïve models, averaged daily dose was not associated with reduced time to remission. By contrast, the instrumental variable analyses showed a clear and significant relationship between increased dose and faster time to remission, threshold regression (velocity estimate: 0.878, 95% confidence interval [CI]: 0.152–1.603) and proportional hazards (log hazards ratio: 3.012, 95% CI: 0.086–5.938). Conclusions We demonstrate, using the GENDEP trial, the benefits of these analyses to estimate causal parameters rather than those that estimate associations. The results for the trial dataset show the link between antidepressant dose and time to depression remission. The threshold regression model more clearly distinguishes the factors associated with initial severity from those influencing treatment effect. Additionally, applying the instrumental variable estimator provides a more plausible causal estimate of drug dose on treatment effect. This validity of these results is subject to meeting the assumptions of instrumental variable analyses. Trial registration EudraCT, 2004–001723-38; ISRCTN, 03693000. Registered on 27 September 2007.
topic Depression
Dose response
Instrumental variables
Survival analysis
Threshold regression
Time to remission
url https://doi.org/10.1186/s13063-019-3810-9
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