Risk factors for depression relapse while on long-term maintenance antidepressant treatment

Within primary care, people with a history of depression often choose to take maintenance antidepressant medication; the National Institute for Health and Care Excellence (NICE) guidance recommends antidepressant medication for those at risk of depression relapse for up to 2 years (NICE, 2022).

When someone gets to a point of wanting to stop taking maintenance antidepressant medication, a natural consideration is to think about the risk of depression relapse (Maund et al., 2019). However, there is a limited understanding of the clinical risk factors that might make someone in primary care vulnerable to relapse.

Currently, there is some evidence to suggest that the number of previous depression episodes (Conradi et al., 2008), residual depression symptoms, and comorbid anxiety (Gopinath et al., 2007) are all associated with an increased risk of relapse in this group. By understanding these individual factors further, clinicians may be able to provide more informed clinical advice to those looking to stop taking maintenance antidepressants.

In the current study, Duffy and colleagues (2023) aimed to address this knowledge gap by assessing clinical factors that might be associated with a risk of depression relapse for people who feel better and are considering discontinuing maintenance antidepressant treatment.

Little is known about the clinical risk factors that are associated with depression relapse in primary care patients on long-term maintenance antidepressants.

Methods

Data was used from a double blind, randomised group-controlled trial (ANTLER) of people randomised to either continue or gradually taper their antidepressant use over 2 months.

Cox proportional hazards modelling was used, which examines how long it takes to reach a fixed event – in this case time to relapse (measured using a modified Clinical Interview Schedule- Revised [CIS-R] at 12, 16, 39 and 52 weeks). It’s often difficult to untangle ‘relapse’ (re-experience current episode) and ‘recurrence’ (new episode, after recovery) so the authors defined relapse as “any new reappearance of depressive symptoms”.

Clinical factors (age of depression onset, number of episodes, residual depression [PHQ-9] and anxiety [GAD-7] symptoms) were examined as predictors of time to relapse, adjusting for baseline sociodemographic confounders (age, gender, ethnicity, education, marital status, employment status, and housing) and alcohol consumption, financial difficulties and whether someone was receiving psychological therapy.

Results

The sample included 477 individuals who were predominately female (73%) and White British (94%). There was little difference between those who relapsed (n = 204) compared to those who did not relapse (n = 273) in relation to baseline sociodemographic and clinical characteristics, except people with higher educational attainment were more likely to relapse.

The authors conducted 3 separate models adjusting for (1) randomised treatment group allocation, (2) clinical factors, or (3) sociodemographic factors, group allocation, therapy status, and clinical factors.

In model 3, there was strong evidence that the number of previous depressive episodes and residual depression increased the risk of relapse. If someone had experienced more than 5 episodes of depression, they had a 57% increased risk of depression relapse (HR = 1.57, 95% CI [1.01 to 2.43], p = .025) compared to people who had up to 2 depressive episodes. For depression scores, with 1-point unit change on the PHQ-9, individuals had a 6% greater chance of relapse (HR = 1.06, 95% CI [1.01 to 1.12], p = .023).

However, as the authors acknowledge, a clinician cannot ‘adjust’ for these factors when making clinical decisions, so it makes sense to also look at a model without adjusted factors (model 1). Here, in addition to the greater number of previous depressive episodes (>5 episodes, HR = 1.84, 95% CI [1.23 to 2.75], p = .002) and residual depression (HR = 1.05, 95% CI [1.01 to 1.09], p = .010), age of depression onset was also a risk factor for relapsing (p = .024). Compared to older age (40–75-year-olds), there was a 62% increased risk of relapse if age of depression onset was between the ages of 23-39 years (HR = 1.62, 95% CI [1.13 to 2.43), and a 37% increased risk of relapse if onset was between 18-22 years (HR = 1.37, 95% CI [0.90 to 1.97]).

There was no statistical evidence that the duration of the current depressive episode (p = 0.172) or residual anxiety symptoms (p = 0.547) were associated with the risk of depression relapse in this sample.

Greater number of previous depressive episodes, higher residual depressive symptoms, and younger age were all identified as risk factors for depression relapse whilst on long-term maintenance antidepressants.

Conclusions

This secondary analysis of the ANTLER trial data highlighted three clinical factors that may contribute to an increased risk of depression relapse following long-term use of maintenance antidepressants:

• Greater number (>5) of previous depression episodes;
• More residual depression symptoms;
• Younger age of depression onset (under 40 compared to over 40).

These factors can be taken into consideration by clinicians when assessing the risks of relapse for adults who have been on long-term antidepressant medication, but are feeling well and considering stopping them.

This study lays the foundation for future research to explore other factors that could be taken into consideration when thinking of discontinuing maintenance antidepressant medication.

Strengths and limitations

Strengths

The main strength of this study was the ANTLER trial data, which was a high quality randomised controlled trial. As the authors acknowledge, there is little research in this area and this study adds to the evidence base using a large, primary care sample from England.

Limitations

The authors acknowledge that the final sample was a subset of a much larger sample who were approached (N = 23,553) and screened for the trial, and the representativeness of the sample is limited because of this.

Within the analyses the authors adjust for sociodemographic factors, but what really stands out is the lack of diversity in the sample; out of 477 individuals included in the trial 447 (94%) were White British. The ANTLER trial is not alone in its lack of representation, with a review of randomised controlled trials for depression across 36 years finding few trials that included a range of people from ethnic minority backgrounds (amongst other groups, including those from low socioeconomic backgrounds and under 18’s; Polo et al., 2019). The factors the authors found to be associated with depression relapse in this sample may not be the same as for those who are from different sociodemographic backgrounds and caution is needed as these findings are not generalisable. The sample size did not allow the authors to conduct analyses to see whether sociodemographic factors interact with clinical factors to influence time to recovery, and future research is needed to further understand risk of relapse in this group of people.

It is also of note that participants with residual depression symptoms in the sample were in the moderate-severe range (the highest PHQ-9 depression score was 19, out of a possible 27). So, the hazard of relapse for those with greater residual depression symptoms still needs to be investigated.

Greater diversity in trials is needed to fully understand how sociodemographic factors might influence risk of depression relapse.

Implications for practice

Until now, there has been little guidance for clinicians as to who may be at risk of depression relapse when on maintenance antidepressants, therefore making it difficult to make informed decisions regarding discontinuation. This paper contributes to the limited available evidence in this field.

As the authors note, clinicians can ask patients about previous depression episodes, assess residual depression symptoms, and consider age during consultations where discontinuation of maintenance antidepressants are being discussed.

However, there is a still a long way to go in fully understanding the clinical factors associated with relapse in this population before this can be fully embedded into practice. Future research should build on this work to understand how other different clinical (e.g., co-morbid physical and mental health conditions, previous number of psychological therapies received), sociodemographic (e.g., ethnic diversity, employment, housing, and income), and interpersonal factors may influence risk of relapse in this population.

Clinicians can use this research to help advise about discontinuing antidepressant medication, but future research is needed to explore other factors (e.g., clinical, sociodemographic, interpersonal) related to risk of depression relapse.

Statement of interests

None.

Links

Primary paper

Duffy, L., Lewis, G., Marston, L., et al. (2023). Clinical factors associated with relapse in depression in a sample of UK primary care patients who have been on long-term antidepressant treatment. Psychological Medicine, 1-11.

Other references

Conradi, H. J., de Jonge, P., & Ormel, J. (2008). Prediction of the three-year course of recurrent depression in primary care patients: Different risk factors for different outcomes. Journal of Affective Disorders, 105(1–3), 267–271.

Gopinath, S., Katon, W. J., Russo, J. E., & Ludman, E. J. (2007). Clinical factors associated with relapse in primary care patients with chronic or recurrent depression. Journal of Affective Disorders, 101(1–3), 57–63.

Katsampa, D., & Nguyen, T. (2020). Stopping antidepressants: patient perspectives on barriers and facilitators. The Mental Elf.

Maund, E., Dewar-Haggart, R., Williams, S., Bowers, H., Geraghty, A. W., Leydon, G., … & Kendrick, T. (2019). Barriers and facilitators to discontinuing antidepressant use: a systematic review and thematic synthesis. Journal of Affective Disorders, 245, 38-62.

National Institute for Health Care and Excellence. (2022). Depression in adults: Treatment and management full guideline. London: NICE. www.nice.org.uk/guidance/ng222 (April).

Polo, A. J., Makol, B. A., Castro, A. S., Colón-Quintana, N., Wagstaff, A. E., & Guo, S. (2019). Diversity in randomized clinical trials of depression: A 36-year review. Clinical Psychology Review, 67, 22-35.

Rifkin-Zybutz, R., & Jauharm S. (2021). Maintenance or discontinuation of antidepressants for depression? Findings from the ANTLER trial. The Mental Elf.

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