Major Depressive DisorderNCT02934035
Early Improvement in Individual Symptoms and Response to Antidepressants in Patients With Major Depressive Disorder
An observational study of Major Depressive Disorder, run by University Medical Center Groningen.
Trial summary
Major depressive disorder (MDD) affects around 7% of the population yearly. Although effective treatments are available, only around half of all patients participating in clinical trials respond to 6 to 12 weeks of antidepressant treatment. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Major Depressive Disorder
- What is being tested?
- Antidepressant
- How many people
- 10,000 participants
- Where
- No sites listed yet
- Study dates
- Sep 2016to Sep 2017
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study population consists of participants in randomized controlled trials of FDA-approved antidepressants and of non-approved new chemical entities (if an FDA-approved antidepressant was used as an active comparator) for the treatment of major depressive disorder.
Who may be able to join
- Minimum duration of double-blind treatment of 6 weeks
- Participants must have a valid baseline, 2-week and 6 (±1)- or 12 (±1)-week Hamilton Depression Rating Scale score
- Aged 18 years or older
- Participants must have been assigned to either placebo or to an FDA-approved antidepressant
Who cannot join
- Inclusion criteria of the trial specify a specific subtype of MDD (e.g. MDD and anxiety; MDD and pain)
About this study
Major depressive disorder (MDD) affects around 7% of the population yearly. Although effective treatments are available, only around half of all patients participating in clinical trials respond to 6 to 12 weeks of antidepressant treatment. Given these high failure rates, the ability to predict as early as possible whether a patient is (un)likely to respond would be of great value, as it would enable physicians to change treatment strategies faster.
Early improvement has consistently been found to be a strong predictor of later response. However, misclassification is still quite common, with perhaps a third of those who do not show early improvement going on to respond. Conversely, a substantial proportion of those who do show early improvement do not go on to respond. One possibility for improving the predictive power of early improvement is to examine individual symptoms, rather than the total score on a depression rating scale. Some items, for example, could reflect antidepressant side effects (e.g. gastrointestinal symptoms) and may not be very predictive.
Read more
The proposed project aims to examine the relationship between early improvement in individual symptoms and response to antidepressants in a very large patient sample. This large sample size makes it possible to use more rigorous methods than previous studies, such as the use of cross-validation to confirm the findings. It also makes it possible to examine a large set of predictors, including possible interactions among early-improving symptoms and between symptoms and demographic factors like age and gender. The added value of individual symptoms over and above using the total symptom score alone will also be examined, as well as possible differences between different antidepressant classes.
The project will use penalized (lasso) regression, which is well-suited to analyzing data with a large number of (potentially highly correlated) predictors. In the primary analysis, response after 6 weeks of treatment will be predicted. In secondary analyses, remission at week 6 and response and remission at week 12 will also be predicted.
Read the detailed description
Study design
The proposed project is an individual patient data meta-analysis. Data will be collated from 31 trials of second-generation antidepressants for the treatment of major depressive disorder, using data from trial arms treated with placebo or Food and Drug Administration (FDA)-approved antidepressants. These trials include a total of approximately 7,800 antidepressant-treated and 3,000 placebo-treated participants. Penalized regression methods (specifically least absolute shrinkage and selection operator, 'lasso') will be used to examine the relationship between early improvement in specific depressive symptoms and response to treatment. Furthermore, the investigators will examine whether interactions among early-improving symptoms and between early-improving symptoms and demographic variables such as age and gender improve the prediction of treatment outcome. Finally, the investigators will also examine whether the prediction of response to treatment by early improvement in specific symptoms is dependent upon the type of treatment provided (placebo, selective serotonin reuptake inhibitors [SSRIs] or serotonin-norepinephrine reuptake inhibitors [SNRIs]), which would suggest a drug-specific mechanism.
Statistical Analysis Plan
Missing data: A complete cases approach will be taken, as it is of interest to predict response and remission in participants who have actually taken an antidepressant for the specified period of time. Therefore, only participants who have valid baseline, week 2 and week 6 (±1) HDRS scores will be selected for the main analyses (or valid week 12 data for the secondary analyses of week 12 outcomes).
Training and validation sample: The data will be randomly divided into an 80% training sample and a 20% validation sample (stratified by treatment group). Model discovery will be done in the training sample, while the predictive performance of the models will be assessed in the validation sample.
Predictors: Improvement in individual symptoms will be derived from the HDRS items at baseline and week 2. The answer choices for these items range from 0 - 2 for 7 items and 0 - 4 for 10 items. Early improvement will be dichotomized into "no improvement" and "improvement". "No improvement" is indicated by worsening of the item score (e.g. from 1 at baseline to 2 at week 2) or no change in the item score. "Improvement" is indicated by an improvement in the item score of ≥1. Cross-tables will be used to check whether any variables are very highly correlated and if so, one of the items will be removed. Baseline scores on the HDRS items will also be included in the model in order to investigate the added value of improvement of individual items over and above the baseline item scores.
For the total HDRS-17 score, early improvement will also be dichotomized into no/minor improvement (<20% improvement) or improvement (≥20% improvement). The baseline HDRS-17 score will be standardized and included in the model as a covariate.
With regard to the demographic factors, gender is already a dichotomous variable and age will be standardized.
Lasso regression: Lasso regression will be applied to the following models:
Primary analysis (in the antidepressant-treated group only)
- A model containing variables for early improvement at week 2 in all 17 HDRS items, age, gender, and all two-way interactions between these variables; baseline HDRS item scores; and additionally total HDRS score at baseline and early improvement (≥20% improvement in score) in total HDRS score at week 2. Exploratory analysis (in all participants, including those treated with placebo)
- As model 1 above, but including treatment group (placebo, SSRI, SNRI) and all two- and three-way interactions with treatment group.
The tuning parameter (lambda) resulting in minimal prediction error (based on deviance) will be selected with the help of 10-fold cross-validation. The GLMMLasso package for multilevel data will be used to fit the lasso model, which will subsequently be refit with mixed-effects logistic regression using only the variables selected by lasso regression.
Model performance: Prediction accuracy will be assessed by applying the mixed-effects logistic regression model to the independent validation sample. The area under the curve (AUC) for the receiver-operating characteristic (ROC) curve in predicting response/remission at 6 or 12 weeks will be used to assess prediction accuracy. Sensitivity, specificity, and accuracy (percentage of correct predictions) will also be determined.
Secondary analyses: Secondary analyses will examine 12-week outcomes within the subgroup of trials with a double-blind treatment duration of at least 12 weeks.
- Conditions
- Major Depressive Disorder
- Being tested
- Antidepressant
- Medical subject headings
- Depressive Disorder, Major
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AntidepressantDrug
Also called Duloxetine, Paroxetine, Escitalopram, Fluoxetine
| Study group | Role | What they receive |
|---|---|---|
| Placebo | The placebo group includes participants in eligible clinical trials who have been assigned to placebo medication. | |
| Antidepressant | The antidepressant group includes participants in eligible clinical trials who have been assigned to antidepressant medication. Receives: Drug: Antidepressant |
What is being measured
The primary outcome is the main question the study is designed to answer.
Response
Response is defined as a change of >=50% on the Hamilton Depression Rating Scale (HDRS, 17-item version) from baseline to week 6 (±1) of the trial.
Measured: Week 6
Secondary outcomes (3)
Remission
Remission is defined as attaining a score of <=7 on the Hamilton Depression Rating Scale (HDRS-17) at week 6 (±1).
Measured: Week 6
Response
Response is defined as a change of >=50% on the Hamilton Depression Rating Scale (HDRS, 17-item version) from baseline to week 12 (±1) of the trial.
Measured: Week 12
Remission
Remission is defined as attaining a score of <=7 on the Hamilton Depression Rating Scale (HDRS-17) at week 12 (±1).
Measured: Week 12
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Oct 2016 (estimated)
- Study startSep 2016
- Primary completionSep 2017 (estimated)
- Study completionSep 2017 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Major Depressive DisorderStudies of the same condition, open and under way.
- More trials run by University Medical Center GroningenThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Time perspective
- Prospective
- Enrolment
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Medical Center Groningen
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, prof. Peter de Jonge, University Medical Center Groningen
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02934035
- Sponsor's protocol ID
- 1575
- Status last verified
- Oct 2016
- First submitted
- 13 Oct 2016
- Last updated
- 17 Oct 2016
- Results posted
- No
- Data monitoring committee
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 Oct 2016. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Early Improvement in Individual Symptoms and Response to Antidepressants in Patients With Major Depressive Disorder
- ClinicalTrials.gov ID
- NCT02934035
- Acronym / sponsor ID
- 1575
- Conditions
- Major Depressive Disorder
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- University Medical Center GroningenUniversity, hospital or other
- Study start
- Sep 2016
- Primary completion
- Sep 2017 (estimated)
- Study completion
- Sep 2017 (estimated)
- First posted
- 14 Oct 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Major depressive disorder (MDD) affects around 7% of the population yearly. Although effective treatments are available, only around half of all patients participating in clinical trials respond to 6 to 12 weeks of antidepressant treatment. Given these high failure rates, the ability to predict as early as possible whether a patient is (un)likely to respond would be of great value, as it would enable physicians to change treatment strategies faster.
Early improvement has consistently been found to be a strong predictor of later response. However, misclassification is still quite common, with perhaps a third of those who do not show early improvement going on to respond. Conversely, a substantial proportion of those who do show early improvement do not go on to respond. One possibility for improving the predictive power of early improvement is to examine individual symptoms, rather than the total score on a depression rating scale. Some items, for example, could reflect antidepressant side effects (e.g. gastrointestinal symptoms) and may not be very predictive.
The proposed project aims to examine the relationship between early improvement in individual symptoms and response to antidepressants in a very large patient sample. This large sample size makes it possible to use more rigorous methods than previous studies, such as the use of cross-validation to confirm the findings. It also makes it possible to examine a large set of predictors, including possible interactions among early-improving symptoms and between symptoms and demographic factors like age and gender. The added value of individual symptoms over and above using the total symptom score alone will also be examined, as well as possible differences between different antidepressant classes.
The project will use penalized (lasso) regression, which is well-suited to analyzing data with a large number of (potentially highly correlated) predictors. In the primary analysis, response after 6 weeks of treatment will be predicted. In secondary analyses, remission at week 6 and response and remission at week 12 will also be predicted.
Detailed description
Study design
The proposed project is an individual patient data meta-analysis. Data will be collated from 31 trials of second-generation antidepressants for the treatment of major depressive disorder, using data from trial arms treated with placebo or Food and Drug Administration (FDA)-approved antidepressants. These trials include a total of approximately 7,800 antidepressant-treated and 3,000 placebo-treated participants. Penalized regression methods (specifically least absolute shrinkage and selection operator, 'lasso') will be used to examine the relationship between early improvement in specific depressive symptoms and response to treatment. Furthermore, the investigators will examine whether interactions among early-improving symptoms and between early-improving symptoms and demographic variables such as age and gender improve the prediction of treatment outcome. Finally, the investigators will also examine whether the prediction of response to treatment by early improvement in specific symptoms is dependent upon the type of treatment provided (placebo, selective serotonin reuptake inhibitors [SSRIs] or serotonin-norepinephrine reuptake inhibitors [SNRIs]), which would suggest a drug-specific mechanism.
Statistical Analysis Plan
Missing data: A complete cases approach will be taken, as it is of interest to predict response and remission in participants who have actually taken an antidepressant for the specified period of time. Therefore, only participants who have valid baseline, week 2 and week 6 (±1) HDRS scores will be selected for the main analyses (or valid week 12 data for the secondary analyses of week 12 outcomes).
Training and validation sample: The data will be randomly divided into an 80% training sample and a 20% validation sample (stratified by treatment group). Model discovery will be done in the training sample, while the predictive performance of the models will be assessed in the validation sample.
Predictors: Improvement in individual symptoms will be derived from the HDRS items at baseline and week 2. The answer choices for these items range from 0 - 2 for 7 items and 0 - 4 for 10 items. Early improvement will be dichotomized into "no improvement" and "improvement". "No improvement" is indicated by worsening of the item score (e.g. from 1 at baseline to 2 at week 2) or no change in the item score. "Improvement" is indicated by an improvement in the item score of ≥1. Cross-tables will be used to check whether any variables are very highly correlated and if so, one of the items will be removed. Baseline scores on the HDRS items will also be included in the model in order to investigate the added value of improvement of individual items over and above the baseline item scores.
For the total HDRS-17 score, early improvement will also be dichotomized into no/minor improvement (<20% improvement) or improvement (≥20% improvement). The baseline HDRS-17 score will be standardized and included in the model as a covariate.
With regard to the demographic factors, gender is already a dichotomous variable and age will be standardized.
Lasso regression: Lasso regression will be applied to the following models:
Primary analysis (in the antidepressant-treated group only)
- A model containing variables for early improvement at week 2 in all 17 HDRS items, age, gender, and all two-way interactions between these variables; baseline HDRS item scores; and additionally total HDRS score at baseline and early improvement (≥20% improvement in score) in total HDRS score at week 2. Exploratory analysis (in all participants, including those treated with placebo)
- As model 1 above, but including treatment group (placebo, SSRI, SNRI) and all two- and three-way interactions with treatment group.
The tuning parameter (lambda) resulting in minimal prediction error (based on deviance) will be selected with the help of 10-fold cross-validation. The GLMMLasso package for multilevel data will be used to fit the lasso model, which will subsequently be refit with mixed-effects logistic regression using only the variables selected by lasso regression.
Model performance: Prediction accuracy will be assessed by applying the mixed-effects logistic regression model to the independent validation sample. The area under the curve (AUC) for the receiver-operating characteristic (ROC) curve in predicting response/remission at 6 or 12 weeks will be used to assess prediction accuracy. Sensitivity, specificity, and accuracy (percentage of correct predictions) will also be determined.
Secondary analyses: Secondary analyses will examine 12-week outcomes within the subgroup of trials with a double-blind treatment duration of at least 12 weeks.
Study design
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Placebo | – | –The placebo group includes participants in eligible clinical trials who have been assigned to placebo medication. |
| Antidepressant | – | Drug: AntidepressantThe antidepressant group includes participants in eligible clinical trials who have been assigned to antidepressant medication. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of participants in randomized controlled trials of FDA-approved antidepressants and of non-approved new chemical entities (if an FDA-approved antidepressant was used as an active comparator) for the treatment of major depressive disorder.
Key inclusion criteria (4 listed)
- Minimum duration of double-blind treatment of 6 weeks
- Participants must have a valid baseline, 2-week and 6 (±1)- or 12 (±1)-week Hamilton Depression Rating Scale score
- Aged 18 years or older
- Participants must have been assigned to either placebo or to an FDA-approved antidepressant
Key exclusion criteria (1 listed)
- Inclusion criteria of the trial specify a specific subtype of MDD (e.g. MDD and anxiety; MDD and pain)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AntidepressantAlso: Duloxetine, Paroxetine, Escitalopram, Fluoxetine | Drug | Antidepressant |
Primary outcome
Response
Time frame: Week 6
Response is defined as a change of >=50% on the Hamilton Depression Rating Scale (HDRS, 17-item version) from baseline to week 6 (±1) of the trial.
3 secondary outcomes
Remission
Time frame: Week 6
Response
Time frame: Week 12
Remission
Time frame: Week 12
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Oct 2016.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Major Depressive Disorder, run by University Medical Center Groningen.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 17 Oct 2016. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Response (time frame: Week 6). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Oct 2016.