Safety of antidepressants in a primary care cohort of adults with obesity and depression

Richard Morriss; Freya Tyrer; Francesco Zaccardi; Kamlesh Khunti

doi:10.1371/journal.pone.0245722

. 2021 Jan 29;16(1):e0245722. doi: 10.1371/journal.pone.0245722

Safety of antidepressants in a primary care cohort of adults with obesity and depression

Richard Morriss ^1,^*, Freya Tyrer ², Francesco Zaccardi ², Kamlesh Khunti ²

Editor: Nienke van Rein³

PMCID: PMC7846000 PMID: 33513174

Abstract

Background

Obesity, depressive disorders and antidepressant drugs are associated with increased mortality, cardiovascular disease, diabetes, fractures and falls. We explored outcomes associated with the most commonly prescribed antidepressants in overweight or obese people with depression.

Methods and findings

We identified a cohort of overweight or obese adults (≥18 years) in primary care from the UK Clinical Practice Research Datalink, linked with hospital and mortality data, between 1 January 2000 and 31 December 2016 who developed incident depression to January 2019. Cox proportional hazards models and 99% confidence intervals were used to estimate hazard ratios (HR) for mortality, cardiovascular disease, diabetes, and falls/fractures associated with exposure to selective serotonin reuptake inhibitors (SSRIs), tricyclic (TCA)/other, combination antidepressants, citalopram, fluoxetine, sertraline, amitriptyline and mirtazapine, adjusting for potential confounding variables. In 519,513 adults, 32,350 (9.2 per 1,000 years) displayed incident depression and 21,436 (66.3%) were prescribed ≥1 antidepressant. Compared with no antidepressants, all antidepressant classes were associated with increased relative risks of cardiovascular disorders [SSRI HR: 1.32 (1.14–1.53), TCA/Other HR: 1.26 (1.01–1.58)], and diabetes (any type) [SSRI HR: 1.28 (1.10–1.49), TCA/Other: 1.52 (1.19–1.94)]. All commonly prescribed antidepressants except citalopram were associated with increased mortality compared with no antidepressants. However, prescription ≥1 year of ≥40mg citalopram was associated with increased mortality and falls/fractures and ≥1 year 100mg sertraline with increased falls/fractures.

Conclusions

In overweight/obese people with depression, antidepressants may be overall and differentially associated with increased risks of some adverse outcomes. Further research is required to exclude indication bias and residual confounding.

Introduction

Obesity is a leading cause of death worldwide, accounting for 44% of cases of diabetes and 23% of cardiovascular disease [1,2]. The relationship between obesity and depression is bi-directional. Being overweight/obese is associated with an increased risk of depressive disorder (27% for overweight and 55% for obesity, respectively) [3], with a dose response effect seen for increasing BMI and depression [4] and for mortality [5]. Depressive disorder is also a risk for obesity, the risk varying by gender, ethnicity, severity of depression and whether they are taking antidepressants [6–8].

An area of uncertainty is whether the prescription of antidepressants in people who have both depression and obesity may be associated with increased rates of complications from these antidepressants over and above the risks of these complications in people with obesity and depression alone. For instance, antidepressants are associated with increased falls and fractures compared with no antidepressant drugs in people with depression [9] and further increased in older obese people [10]. However, both depression and selective serotonin re-uptake inhibitor (SSRI) antidepressants lower bone mineral density [11].

Antidepressants vary substantially in the degree to which they are associated with weight gain, with the greatest weight gain associated with mirtazapine and the least with paroxetine and dosulepin [12]. However, we do not know whether the use of antidepressants in people with obesity is associated with serious adverse cardiovascular events or incident diabetes mellitus [13]. Antidepressants may show important differences in absolute rates of overall mortality [14].

There is currently no guidance on the use of antidepressants in people who are overweight/obese, although there is specific guidance on the treatment of depression in the presence of physical disease [15]. There is, therefore, a gap in knowledge in relation to the prescribing of antidepressants to people who are overweight/obese who also have depressive disorders.

Using electronic health records, we aimed to explore the drug safety of antidepressants in terms of overall mortality, cardiovascular disease (CVD), diabetes (any type), and falls/fractures in relation to the prescribing of antidepressants by class and type.

Methods

Data sources

We used the Clinical Practice Research Datalink (CPRD GOLD), an electronic database of more than 11.3 million patients from 674 general practices in the UK, which is broadly representative of the national population in terms of age, gender and ethnicity [16]. Approximately 75% of practices in England participate in the CPRD linkage scheme, which allows person-level linkage to hospital episode statistics (HES), deaths registrations from the Office for National Statistics (ONS) and the 2015 index of multiple deprivation (IMD) used to estimate socioeconomic status. CPRD contains Read codes and product codes for diagnoses and prescriptions whereas HES and ONS mortality data use ICD-10 codes. All of the codes used in this study have been included in the supplementary material. Independent Scientific Advisory Committee (ISAC) for CPRD approved the study, approval number 18_311R.Written/oral consent was not obtained because the data was analysed anonymously from a national database.

Study design

This was a retrospective cohort study of patients aged 18 year or over who were overweight/obese between 1 January 2000 and 31 December 2016. Overweight/obesity was defined using either Read code for overweight/obese diagnosis (S1 Table) or BMI measurement (≥25kg/m²).

Inclusion criteria were meeting the “up to standard” patient and practice criteria set by the CPRD, with at least 12 months registration in the practice prior to their first overweight/obesity measurement/diagnosis in the study window, data linkage availability, and incident depression (defined using Read codes; S2 Table) during the study period.

Exclusion criteria were: antimania or antipsychotic medication (S3 Table) before date of incident depression; a diagnosis (ever) of psychotic disorder; bipolar disorder or dementia (S4 Table); anticholinesterase medication (ever) (S5 Table); or antidepressant (S6 Table), antipsychotic or antimania medication before incident depression date.

Patients were excluded if they had an overweight or obese diagnosis/measurement made after death (n = 10); of if they had an existing diagnosis of depression either: before the index date, date of registration with the practice, or before the age of 18 years (n = 11,854). They were also excluded if they had ever (either before or after the index date) a diagnosis of psychotic disorders, bipolar disorder or dementia (n = 33,643). Patients were also excluded if they were prescribed an antidepressant before the index date (n = 275,562), had ever taken anticholinesterase medication (n = 3,231), or had taken antimania or antipsychotic medication before the date of depression (n = 86,039).

Outcome measures

The safety outcomes of interest were: (i) all-cause mortality; (ii) cardiovascular disease (including cardiovascular-related mortality); (iii) diabetes (any type); and (iv) fractures/falls. Code sets for the outcome measures were determined a-priori using primary care Read codes from CPRD Gold and version 10 codes of the International Classification of Diseases (ICD-10) for hospital episodes (admitted patient care) and mortality data. We have listed all codes for the outcome measures in S7 Table.

Exposure measures

Antidepressant type (5 most common antidepressants only) and antidepressant drug class were defined using product codes from the CPRD and are defined in S6 Table. We included exposure of antidepressants from more than one drug or class owing to some concerns over potential adverse events.

Covariates

Covariates were decided a priori and included: age; gender; ethnicity (white, south Asian, other, not known); overweight/obesity status (overweight [clinical diagnosis or BMI 25–29.9 kg/m²], obese [clinical diagnosis or BMI 30–39.9 kg/m²], severely obese [clinical diagnosis or BMI 40+ kg/m²]); smoking status; alcohol status; socioeconomic status (quintile of multiple deprivation; ‘not known’ if missing); cancer or chronic kidney disease at baseline (i.e. depression diagnosis); glucose-lowering or statin therapy at baseline; and calendar year (2000–2004, 2005–2009, 2009–2014, 2015–2019). Read codes and ICD-10 codes for relevant covariates are described in S8 Table.

Statistical analyses

Patients were followed up for the outcomes of interest and associations were estimated using Cox proportional hazards models with age as the timescale until their date of event, date of death or when they were last known to be alive (date of transfer out of practice, last practice update or last database linkage [22 January 2019], whichever was earliest). Exposure variables and covariates included in the model were judged to be statistically significant if they met significance at the 1% level (p<0.01) because of the large number of variables under investigation. Therefore, 99% confidence intervals (CIs) are reported throughout. However, all covariates were left in the models even if they did not meet statistical significance because they were selected a priori as being related to both the exposures and outcome.

Antidepressant type (5 most common antidepressants only) and antidepressant drug class were included in two separate models (8 models in total for each outcome measure) as a time-dependent exposure measure to allow for changes in treatment during the follow-up period and control for immortal time bias. Adults who were not exposed to antidepressants were included as the reference category (i.e. no antidepressants [‘none’]). Adults were considered exposed to a drug throughout periods covered by the duration of the prescriptions if there were no gaps of more than 90 days between the end of one prescription and the start of the next prescription. If there were gaps of more than 90 days, the individual was counted as exposed to the antidepressant medication for the first 90 days of the gap and then unexposed for the remaining period.

The proportional hazards assumption was tested using Schoenfeld residuals. Where the assumption was violated, we included each of the relevant covariates as time-varying covariates (tvc) in the model using the ‘tvc’ option in Stata to allow the association between the covariate and mortality to change (relative to the reference category) during the follow-up period [17].

For each analysis, patients were excluded if they had an outcome of interest (cardiovascular disease, diabetes, or falls/fractures) before their first date of incident depression.

Analysis was conducted with Stata v15 [18].

Sensitivity analyses

To assess the effect of using a presumed 90-day exposure period, we also conducted a sensitivity analysis, assuming exposure to 30 and 60 days over end of last prescription respectively. The study design involved exclusion of antipsychotic and antimania medications prior to first depression diagnosis. An additional sensitivity analysis was conducted removing any prescriptions for antipsychotic or antimania medication from the analysis.

Results

Baseline characteristics

Between 2000 and 2016, 32,350 obese/overweight adults had incident depression and 21,436 (66.3%) were prescribed one or more antidepressants. Table 1 shows the baseline characteristics of the study population: median age was 46.2 years (range 18–106), just over half (57%) were male, and most (84%) were white. Median follow-up was 5 years (interquartile range 2.3–8.7) and total observation period 187,369 person-years (PY). The most common antidepressants to which patients were exposed during the period were citalopram (108.2 per 1000 PY), followed by fluoxetine (63.8 per 1000 PY), sertraline (45.0 per 1000 PY), amitriptyline (20.8 per 1000 PY) and mirtazapine (10.8 per 1000 PY).

Table 1. Baseline characteristics of study population included in all-cause mortality analysis.

Characteristic	Number/Median (N = 32,350^*)	(Percent/IQR)
Age	46.2	(34–59)
Gender^*:
Male	13,917	-43
Female	18,433	-57
Ethnicity:
White	27,099	-83.8
South Asian	650	-2
Black	375	-1.2
Mixed	178	-0.6
Other	324	-1
Not known	3,724	-11.5
BMI:
Overweight (diagnosis or 25–29 kg/m²)	20,524	-63.4
Obese (diagnosis or 30–39 kg/m²)	10,049	-31.1
Severely obese (diagnosis of 40+ kg/m²)	1,777	-5.5
Smoking
Yes	13,143	-40.6
No	14,952	-46.2
Ex-smoker	4,117	-12.7
Not known	138	-0.4
Drinks alcohol (n = 313,102 available)
Yes	5,117	-15.8
No	12,603	-39
Ex-alcohol drinker	904	-2.8
Not known	13,726	-42.4
Deaths	2,717	-8.4
Comorbidities at baseline^†
Chronic kidney disease (CKD)	2,235	-6.9
Cancer	2,957	-9.1
Baseline medication (on or before BMI date):
Glucose lowering therapies	3,055	-9.4
Statins	6,179	-19.1
Index of multiple deprivation (2015)
1 (least deprived)	6,573	-20.3
2	6,683	-20.7
3	6,852	-21.2
4	6,368	-19.7
5 (most deprived)	5,781	-17.9
Not known	93	-0.3
Years of follow up	5	(2.3–8.7)
Antidepressant class, median time exposed (years)
Selective serotonin reuptake inhibitors	0.8	(0.4–2.0)
TCA/Other antidepressants	0.6	(0.3–1.5)
None	3.8	(1.4–7.1)
SSRI combination (2+drugs)	0.3	(0.2–0.3)
TCA/Other combination (2+ drugs)	0.3	(0.2–0.4)
TCA/Other + SRRI combination (2+drugs	0.3	(0.2–0.5)
Type of antidepressants, median time exposed (years):
Citalopram	0.7	(0.3–1.7)
Fluoxetine	0.6	(0.3–1.4)
Sertraline	0.6	(0.3–1.4)
Escitalopram	0.6	(0.3–1.3)
Mirtazapine	0.4	(0.3–1.1)
Paroxetine	0.5	(0.3–1.2)
Dosulepin	0.4	(0.3–0.9)
Amitriptyline	0.4	(0.3–1.0)
Venlafaxine	0.7	(0.3–1.9)
Lofepramine	0.4	(0.2–0.8)
Trazodone	0.4	(0.2–1.2)
Duloxetine	0.5	(0.3–1.7)
Other	0.5	(0.3–1.1)
SSRI combination (2+drugs)	0.3	(0.2–0.3)
TCA/Other combination (2+ drugs)	0.3	(0.2–0.4)
TCA/Other + SRRI combination (2+drugs)	0.3	(0.2–0.5)

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IQR Interquartile range.

* 4 people with indeterminate gender excluded; 5 people excluded because their depression occurred on the same day as date of death.

^† CKD/cancer diagnosis within 10 years before depression or within 5 years post-depression.

Safety of antidepressants

Fig 1 shows the four individual models for the outcomes mortality, cardiovascular disease, diabetes and fractures/falls by drug class and Fig 2 by individual drug.

Model 1: All-cause mortality

There were 2,717 deaths during the observation period (14.5 per 1000 PY). Only 19 (0.7%) of these deaths were attributed to suicide. After adjustment for covariates, exposure to TCA/other antidepressants alone (HR: 1.64; 99% CI: 1.38–1.94) or to a combination of TCA/other or SSRI antidepressant or both SSRI and TCA/other antidepressants (HR: 2.97 [1.71–5.81] for ≥2 SSRIs; 2.18 [1.11–4.26] for ≥2 TCAs/other; and 2.98 [2.22–4.01] for SSRI and TCA/other combinations) were associated with increased all-cause mortality.

For individual antidepressants, increased all-cause mortality was associated with fluoxetine (HR: 1.70; 1.39–2.09), sertraline (HR: 1.84; CI 1.44–2.35), amitriptyline (HR: 1.76; 1.36–2.27), mirtazapine (HR: 2.11; 1.59–2.79) and other SSRIs (HR: 1.67; 1.17–2.40).

The drug class model was used to report the effects of covariates, but was similar between models. Covariates associated with all-cause mortality were: female gender (HR: 0.65; 0.59–0.73); being severely obese compared with overweight (HR: 1.58; 1.26–1.97); smoking (HR: 1.33; 1.19–1.49); being in the fourth or fifth most deprived quintile areas compared with the least deprived (HR: 1.24; 1.05–1.45; and HR: 1.41; 1.20–1.66 respectively); CKD (HR: 1.13; 1.00–1.27); cancer (HR: 234.21; 125.93–435.60 at depression diagnosis, lessening by 6% each year [tvc HR: 0.94; 0.94–0.95]); glucose lowering therapies (HR: 1.60; 1.41–1.81); and more recent calendar year periods (HR: 0.68; 0.56–0.83 for 2010–2014 and HR: 0.55; 0.44–0.68 for 2015–2019).

Model 2: CVD

The model for CVD included 28,544 patients, after excluding 3,806 patients with a CVD event before their first incident depression date. 1,734 (10.7 per 1000 PY) individuals had a CVD event during the observation period (PY = 162,169). After adjustment, exposure to SSRI antidepressants (HR: 1.32; 1.14–1.53), TCA/other antidepressants (HR: 1.26; 1.01–1.58) and a combination of TCA/other and SSRI antidepressants (HR: 1.86; 1.23–2.82) were associated with increased risk of CVD. For individual antidepressant drug types, citalopram (HR: 1.30; 1.07–1.57), sertraline (HR = 1.44; 1.06–1.97), and amitriptyline (HR = 1.57; 1.15–2.15) were all associated with increased risk of CVD.

CVD was also associated with female gender (HR: 0.22; 0.11–0.41 at depression diagnosis, increasing by 1% per year relative to male gender [tvc HR 1.01; 1.00–1.03]), being obese or severely obese compared with overweight (HR: 1.23; 1.08–1.41; and HR: 1.75; 1.37–2.24 respectively), smoking (HR: 1.24; 1.08–1.43), living in the fourth or fifth most deprived quintile areas compared with the least deprived (HR: 1.22; 1.01–1.49; and HR: 1.32; 1.08–1.61 respectively), CKD (HR: 5.87; 1.87–1.843 at diagnosis, risk decreasing by 2% each year [tvd HR: 0.97–1.00]), glucose lowering therapies (p<0.001), statin therapies (p<0.001) and more recent calendar year periods (reduced risk; p<0.001).

Model 3: Diabetes

The model for diabetes included 28,152 patients, after excluding 4,198 patients with a diabetes event before their first incident depression date. 1,575 (10.0 per 1000 PY) individuals had a diabetes event during the observation period (PY = 157,691). After adjustment, exposure to SSRI antidepressants (HR: 1.28; 1.10–1.49), TCA/other antidepressants (HR: 1.52; 1.19–1.94), a combination of TCA/other antidepressants (HR: 2.73; 1.25–5.98) and a combination of TCA/other and SSRI antidepressants (HR: 1.76; 1.12–2.76) were associated with increased risk of diabetes. For individual antidepressant drug types, citalopram (p = 0.002), fluoxetine (p = 0.002), and mirtazapine (p = 0.003) were associated with increased risk of diabetes.

Covariates associated with diabetes were: female gender (HR: 0.57; 0.50–0.66; reduced risk); South Asian ethnicity compared with white (2.66; 1.81–3.91); being obese or severely obese compared with overweight (HR: 8.54; 4.42–16.48 for obese; HR: 45.89; 17.40–121.06 for severely obese at diagnosis, risk decreasing by 3% and 4% per year respectively [tvc HR: 0.98; 0.97–0.99] and 0.96; 0.94–0.98 respectively); smoking (p<0.001); living in the fifth most deprived quintile area compared with the least deprived (HR: 1.27; 1.03–1.57); CKD (HR: 1.35; 1.06–1.71); and statin therapies (HR: 1.32; 1.12–1.57).

Model 4: Falls/Fractures

The model for falls/fractures included 30,959 patients, after excluding 582 patients with a fall/fracture event before their first incident depression date. A total of 1,524 (8.6 per 1000 PY) individuals had a fall/fracture during the observation period (PY = 176,559). After adjustment for the covariates, TCA/other antidepressants (HR: 1.47; 1.15–1.18), SSRI combinations (HR 2.57; 1.21–5.45); TCA/other antidepressant combinations (HR: 2.52; 1.01–6.31); and SSRI and TCA/other combinations (HR: 2.07; 1.32–3.25) were associated with increased risk of falls/fractures. Of the individual antidepressants, fluoxetine (HR: 1.76; 1.35–2.30) and other TCA/other antidepressants (HR: 1.55; 1.06–2.25) were associated with increased risk of falls/fractures.

Other covariates associated with falls/fractures were female gender (HR: 0.16; 0.10–0.27, with a time-varying effect of HR 1.02; 1.02–1.03), living in the most deprived area quintile compared with the least (HR: 1.29; 1.04–1.60) and glucose lowering therapy at baseline (HR: 1.38; 1.14–1.67).

Effect of time-varying exposures on outcomes

The proportional hazards assumption in the models for mortality (Model 1) and fractures/falls (Model 4) were violated for both drug class and individual drug type. This effect was driven by the SSRI antidepressants citalopram (both models) and sertraline (Model 4 only). In the all-cause mortality model, the initial hazard of citalopram at baseline (i.e. first depression diagnosis) was 0.66 but increased disproportionately to the other antidepressants (in relation to the reference category no antidepressants) by 1% (HR: 1.01; 1.00–1.02) (Fig 3). Similarly, in the falls/fractures model, the initial hazard of citalopram was 1.18 and of sertraline was 0.44. Each year, these hazards increased disproportionately to the other antidepressants by 1% (HR: 1.01; 1.00–1.02) for citalopram and 2% (HR: 1.02; 1.00–1.04), respectively (Fig 3).

Sensitivity analyses

Sensitivity analyses are summarised in Table 2. The findings were relatively robust against all sensitivity analysis scenarios with the exception of combinations of two or more TCA/other antidepressants that did not reach statistical significance at the 1% level under the 60-day exposure assumption and on removal of either antipsychotic or antimania agents. The removal of antipsychotic agents appeared to have the greatest impact on the sensitivity analyses, such that the impact of TCA/other antidepressants (cardiovascular disease), SSRI combinations (falls/fractures), TCA/other combinations (mortality), SSRI + TCA/other combinations (falls/fractures) and mirtazapine (diabetes) no longer reached statistical significance. However, this may reflect smaller numbers in the sample (between 9.2–9.7% of patients were removed for the 4 models). We did not find an interaction between antidepressant use and overweight/obese/severely obese for any of the outcomes under investigation (p>0.01 for all).

Table 2. Summary of sensitivity analyses.

Exposure	Outcome	Sensitivity analyses
Exposure	Outcome	Assumed exposure for 30 days after end of prescription HR (99% CI)	Assumed exposure for 60 days after end of prescription HR (99% CI)	Antipsychotic agents removed (9.2%–9.7% of total) HR (99% CI)	Antimania drugs removed (0.7% of total)HR (99% CI)
Drug Class
SSRI	Mortality	-	-	-	-
	CVD	1.29 (1.11–1.51)	1.33 (1.15–1.55)	1.35 (1.15–1.58)	1.32 (1.14–1.53)
	Diabetes	1.27 (1.08–1.48)	1.28 (1.10–1.50)	1.25 (1.06–1.48)	1.28 (1.09–1.49)
	Falls/fractures	-	-	-	-
TCA/Other	Mortality	1.63 (1.38–1.93)	1.63 (1.38–1.94)	1.49 (1.22–1.82)	1.68 (1.42–2.00)
	CVD	1.30 (1.03–1.64)	1.29 (1.03–1.62)	1.22 (0.94–1.59)	1.29 (1.02–1.62)
	Diabetes	1.61 (1.26–2.06)	1.56 (1.22–1.99)	1.43 (1.08–1.90)	1.52 (1.19–1.94)
	Falls/fractures	1.48 (1.22–1.79)	1.47 (1.15–1.89)	1.48 (1.12–1.96)	1.46 (1.13–1.87)
SSRI combination	Mortality	2.96 (1.54–5.66)	2.96 (1.54–5.66)	3.56 (1.99–6.38)	3.07 (1.76–5.35)
	CVD	0.44 (0.03–5.75)	0.80 (0.18–3.54)	0.72 (0.16–3.20)	1.19 (0.41–3.41)
	Diabetes	1.25 (0.28–5.57)	1.22 (0.38–3.88)	0.85 (0.23–3.08)	0.87 (0.27–2.75)
	Falls/fractures	3.52 (1.67–7.42)	3.03 (1.33–6.88)	2.10 (0.84–5.26)	2.41 (1.10–5.29)
TCA/Other combination	Mortality	2.25 (1.12–4.51)	2.25 (1.12–4.51)	2.35 (0.99–5.58)	2.42 (1.18–4.97)
	CVD	1.35 (0.37–4.91)	2.00 (0.75–5.32)	2.29 (0.79–6.58)	1.93 (0.73–5.13)
	Diabetes	3.21 (1.41–7.29)	2.79 (1.23–6.35)	3.37 (1.42–8.02)	2.70 (1.19–6.14)
	Falls/fractures	2.43 (1.08–5.42)	2.45 (0.92–6.53)	2.31 (0.72–7.35)	2.42 (0.84–6.97)
SSRI + TCA/Other combination	Mortality	2.78 (1.99–3.87)	2.78 (1.99–3.87)	3.04 (2.14–4.32)	3.30 (2.45–4.45)
	CVD	2.09 (1.30–3.38)	1.84 (1.17–2.91)	2.14 (1.35–3.40)	1.96 (1.29–2.99)
	Diabetes	2.14 (1.30–3.55)	1.81 (1.11–2.94)	1.63 (0.96–2.79)	1.76 (1.11–2.78)
	Falls/fractures	1.99 (1.30–3.05)	2.18 (1.35–3.51)	1.72 (0.96–3.09)	2.27 (1.44–3.56)
Drug Type
Citalopram	Mortality	-	-	-	-
	CVD	1.29 (1.06–1.57)	1.32 (1.09–1.60)	1.28 (1.04–1.58)	1.30 (1.07–1.57)
	Diabetes	1.25 (1.01–1.54)	1.26 (1.03–1.55)	1.25 (1.01–1.56)	1.26 (1.03–1.54)
	Falls/fractures	-	-	-	-
Fluoxetine	Mortality	1.74 (1.42–2.14)	1.74 (1.41–2.14)	1.78 (1.41–2.20)	1.76 (1.43–2.16)
	CVD	1.26 (0.96–1.66)	1.26 (0.97–1.65)	1.39 (1.05–1.83)	1.27 (0.97–1.65)
	Diabetes	1.33 (1.02–1.75)	1.39 (1.07–179)	1.37 (1.04–1.80)	1.36 (1.05–1.76)
	Falls/fractures	1.73 (1.40–2.14)	1.75 (1.33–2.29)	1.93 (1.46–2.55)	1.79 (1.38–2.34)
Sertraline	Mortality	1.83 (1.43–2.34)	1.83 (1.43–2.34)	1.83 (1.39–2.41)	1.85 (1.45–2.36)
	CVD	1.33 (0.96–1.85)	1.45 (1.06–1.97)	1.42 (1.01–2.00)	1.47 (1.08–2.00)
	Diabetes	1.30 (0.92–1.82)	1.28 (0.92–1.79)	1.19 (0.82–1.72)	1.25 (0.90–1.75)
	Falls/fractures	-	-	-
Amitriptyline	Mortality	1.77 (1.37–2.30)	1.77 (1.37–2.30)	1.61 (1.19–2.18)	1.80 (1.39–2.33)
	CVD	1.61 (1.15–2.24)	1.61 (1.16–2.21)	1.59 (1.12–2.27)	1.57 (1.14–2.15)
	Diabetes	1.35 (0.87–2.09)	1.25 (0.81–1.92)	1.19 (0.74–1.92)	1.23 (0.81–1.87)
	Falls/fractures	1.25 (0.90–1.75)	1.36 (0.90–2.04)	1.54 (1.01–2.36)	1.34 (0.90–2.01)
Mirtazapine	Mortality	2.08 (1.57–2.76)	2.08 (1.57–2.76)	1.78 (1.26–2.52)	2.26 (1.70–3.01)
	CVD	0.97 (0.57–1.63)	0.95 (0.57–1.61)	1.87 (0.47–1.61)	1.01 (0.60–1.71)
	Diabetes	1.80 (1.14–2.84)	1.79 (1.14–2.81)	1.63 (0.96–2.75)	1.75 (1.11–2.77)
	Falls/fractures	1.54 (1.08–2.19)	1.56 (0.98–2.47)	1.41 (0.82–2.45)	1.45 (0.89–2.36)

Open in a new tab

CVD Cardiovascular disease.

Discussion

Compared to a large UK primary care record study including people of any weight that was carried out over a similar time period [14], only 66% of people with depression who are overweight or obese were prescribed antidepressants compared with 88% of the general population with depression, although the duration of treatment appears similar. The five most commonly prescribed antidepressants in this database in people who were obese or overweight are the same as the general population in England, namely citalopram, fluoxetine, sertraline, amitriptyline and mirtazapine [19].

There were class effects on outcomes in obese/overweight people with incident depression, additional risks in people on combinations of antidepressants, and sometimes differing risks of antidepressants within the same class. Hence, compared with no antidepressants, SSRI or TCA/other antidepressants were associated with 26% relative increased risk of cardiovascular disease and 28% increased risk of diabetes. Exposure to combinations of SSRI and TCA/other antidepressants was associated with a significantly higher risk than single drugs for all outcomes including all-cause mortality. These findings mirror those in the general population [9,20], possibly due to indication bias in more severe and treatment resistant depression [21]. An exception was the prescription of two or more SSRIs, which were not associated with an increased risk of new cardiovascular events or diabetes. Prescribers may have been careful not to prescribe two or more SSRIs in this at risk group for cardiovascular disease and diabetes mellitus. Mirtazapine was also found to have a higher risk (70%) of diabetes than the other four antidepressants but no increased risk of cardiovascular disease compared to no antidepressants, reflecting possibly increased weight gain [12,22] but little effect on glucose or lipid homeostasis [23].

The proportional hazards assumption for survival analysis was violated for SSRIs for both all-cause mortality and falls/fractures, with longer exposure to the drugs lessening the risk difference between SSRIs and other TCA/other antidepressants. Further investigation of prescriptions for citalopram and sertraline suggested that dosage increased over time (Fig 3) with a combination of higher doses and longer exposure increasing the risk of falls and fractures. Our findings in at risk groups for cardiovascular mortality and falls/fractures support the US Food and Drug Administration warning of sudden cardiac death concerning doses of citalopram ≥40mg [24] and findings in relation to lower bone density with SSRI prescription [14,25].

The main strength of the study is that we interrogated a large primary care database typical of where most of the treatment for both depression and obesity is practised. Therefore, it has considerable statistical power and generalisability to clinical practice. Randomised controlled trials of antidepressants in obese and overweight people with depression are rarely performed, are of short duration (usually 6–12 weeks) and underpowered for the detection of serious adverse effects. We included outcomes where additional serious risks might be expected in an obese population with depression. Unlike previous observational studies, we considered only incident cases of unipolar depression. The sample was representative of obese populations in terms of deprivation and ethnicity except fewer than expected people were from a South Asian population known to be at additional risk of obesity related cardiovascular disease, diabetes and death [26]. We controlled for a number of baseline confounders that might have been independently associated with the exposure and outcomes of interest including cancer and chronic kidney disease, smoking, drinking alcohol, demographic factors, deprivation and medication. We considered time, medication and length of exposure after stopping medication as sensitivity analyses.

There are important limitations to observational studies such as this. Firstly, there is confounding by indication, i.e. selective prescribing of certain types of antidepressants because of severity or chronicity of depression, associated comorbidities or symptom presentation. Confounding by indication with antidepressants may be particularly complex in relation to mortality since some antidepressants singly or in combination may be preferentially prescribed in severe and more treatment resistant depression. However in this sample and in other studies mortality from suicide was a small proportion of overall mortality in people with depression and obesity even if some suicides were not recorded as suicide but as other causes of mortality [27]. We did not have disaggregated data for other causes of mortality in this sample. It would be important to know in future research whether increased risk of diabetes and cardiovascular disease with the prescription of antidepressants for incident depression is reflected in increased mortality from cardiovascular disease overall, by different antidepressant agent and by time or dose.

Secondly our results apply only to people who are overweight or obese and do not apply to people who are underweight or normal weight. We included people with known BMI measurements/clinical diagnoses only. Whilst complete BMI reporting in UK GP surgeries has improved over time, BMI is known to be more commonly reported in older patients, females, those with higher BMIs, people with lower socioeconomic status and people with coexisting chronic conditions [28,29]. Similarly, we have access only to primary care prescribing and not secondary care prescribing although there are no specific secondary care services for people with obesity and depression. We have no information on the severity of depression, and variation in the recognition, recording and management of patients with depression in primary care. We also did not include comparisons with the general population without overweight/obesity and recommend this for future research.

We did not explore the adequacy of depression treatment with antidepressants, adherence to medication, and control all confounders e.g. sleep apnoea, diet, exercise, personality or other mental disorder owing to lack of available data. Some of our outcomes were aggregated and may have obscured differential effects of SSRIs and TCAs that have been found in other groups, such as on haemorrhagic and ischaemic strokes in the elderly [12,30]. Weight and BMI index are also variably recorded, especially in those who do not receive NHS Health checks [31] reducing the chances of finding real associations.

Conclusions

When depression is recognised in obese and overweight people in primary care, GPs may be more reluctant to start antidepressant medication. There were broad class effects of antidepressants on adverse outcomes, additional risks from their combination, and some important differences among the five most commonly prescribed antidepressants, especially when prescribed at higher dosages for 12 months or more. However, some of these results need to be considered cautiously as there was likely to be indication bias and residual confounding. The results indicate the complexity of treatment of depression in people who are overweight and obese. Given the risks of both depression and continuing treatment with antidepressants for 12 months or more, especially combinations of antidepressants, a clinical review should be conducted in people who are also overweight or obese at 12 months after the last episode of depression to consider the balance of risks and benefits of continuing their current medication regime and the risks from depression. Consideration might be given to alternative effective treatments for depression such as psychological treatments should these be clinically available.

Supporting information

S1 Checklist. STROBE statement—Checklist of items that should be included in reports of cohort studies.

(DOC)

Click here for additional data file.^{(84.5KB, doc)}

S1 Fig. Proportion of people on higher dose (40mg+) citalopram by length of exposure.

(DOCX)

Click here for additional data file.^{(58.2KB, docx)}

S2 Fig. Proportion of people on higher dose (100mg+) sertraline by length of exposure.

(DOCX)

Click here for additional data file.^{(59.1KB, docx)}

S1 Table. RECORD* checklist.

(DOCX)

Click here for additional data file.^{(30.7KB, docx)}

S2 Table. BMI measurements and Read codes for definitions of overweight, obesity and severely obese.

(DOCX)

Click here for additional data file.^{(14.9KB, docx)}

S3 Table. Read codes for depression.

(DOCX)

Click here for additional data file.^{(19KB, docx)}

S4 Table. Product codes for antipsychotic and antimania medications.

(DOCX)

Click here for additional data file.^{(66.5KB, docx)}

S5 Table. Read code diagnoses of bipolar disorders, psychotic disorder or dementia.

(DOCX)

Click here for additional data file.^{(41.8KB, docx)}

S6 Table. Product codes for anticholinesterase medication.

(DOCX)

Click here for additional data file.^{(20.1KB, docx)}

S7 Table. Product codes for antidepressant medication.

(DOCX)

Click here for additional data file.^{(70.5KB, docx)}

S8 Table. Outcome measures (Read codes and ICD-10 codes from secondary care/mortality data).

(DOCX)

Click here for additional data file.^{(286.1KB, docx)}

Acknowledgments

This study is based in part on data from the Clinical Practice Research Datalink GOLD database obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. However, the interpretation and conclusions contained in this report/article are those of the author/s alone and not necessarily those of the NHS, the NIHR or the Department of Health.

Data Availability

Data cannot be shared publicly because it is owned by the NIHR CPRD on behalf of the National Health Service in England and can only be accessed by researchers making a scientific case to have access to it. Data are available from the Independent Scientific Advisory Committee of CPRD if researchers meet the criteria for access to confidential data. The process for obtaining such access is outlined at https://www.cprd.com/research-application. Researchers should contact the ISAC Secretariat at isac@cprd.com for further details.

Funding Statement

The funding for the study came from the National Institute for Health Research (https://www.nihr.ac.uk) Collaboration for Leadership in Applied Research and Health Care East Midlands. The authors gratefully acknowledge Leicester Real-World Evidence (LRWE) Unit for providing CPRD data. LRWE Unit is funded by University of Leicester, National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) East Midlands and Leicester NIHR Biomedical Research Centre. The interpretation and conclusions contained in this report/article do not necessarily reflect those of the LRWE Unit. RM is also funded by the Nottingham NIHR Biomedical Research Centre and NIHR MindTech MedTech and in-Vitro Centre. KK is supported by the NIHR Leicester Lifestyle Biomedical Research Centre (BRC) and NIHR Applied Research Collaboration (ARC-EM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0245722.r001

Decision Letter 0

Christine Leong

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

29 Apr 2020

PONE-D-20-03344

Safety of antidepressants in a primary care cohort of adults with obesity and depression

PLOS ONE

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Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Of note, this paper could be improved if strategies for minimizing confounding by indication/severity as the reviewers have described have been implemented. Please also address obesity grouping and immortal time bias. The last sentence of the conclusion should be re-phrased to consider re-evaluating the continued use of antidepressant at 12 months rather than discontinue at 12 months. The Discussion section could include more description of how findings compare and add to previous studies.

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Reviewer #1: This is a study of the safety of antidepressants in a primary care cohort of adults with obesity and depression. It is set in the high quality CPRD and looks at an important and high risk population. However, despite these strengths, the study has two major areas of concern, one in its design and one in its methods, which impact the validity of its results and conclusions.

First, the design of the study, only including people who are obese and categorizing them as a single group, severely limits the authors’ ability to interpret their results and compare to the risk of mortality due to antidepressant use in the general population. The risks presented in this study are not contextualized to suggest if this population is at an elevated risk of mortality when using these medications, as is suggested in the conclusion. The empirical risk in this population is not incorrect, however, interpreting these results as a comparison relative to other populations is complicated by the lack of a direct comparison group.

- Keeping their population the same, the authors could redesign the study to understand the association between antidepressant use and the outcomes incorporating obesity as a dose-response of BMI. This would allow them to directly evaluate the interaction between antidepressant use and obesity on mortality.

Second, Model 1 (all-cause mortality) and Model 4 (suicidality) are subject to confounding by indication bias. Suicidal ideation is an indication for antidepressant use. The authors are not able to determine, with this study design, whether the risk of these outcomes affects the prescribing of antidepressants or if they are actually a consequence of antidepressant use. This leads to biased results, complicating their interpretation, and the authors mention this but are unable to estimate the magnitude of the possible error. Furthermore, if the participants in this study are at a very high risk of suicide, antidepressants could possibly lower their risk, so the residual risk remains high, but is not in fact due to their use of antidepressants, rather was underlying and a biased estimate was made apparent then interpreted as an outcome of antidepressant use. Without being able to estimate these associations, it is impossible to determine if the drugs are protective or harmful, greatly reducing the benefit of these associations to guiding care.

- The authors could consider dropping suicidality as an outcome or mentioning these results as a secondary outcome with unknown causality. Similarly, without understanding whether all cause mortality could be driven by an indication for the medication use, it is hard to interpret.

- Alternatively, they could incorporate a systematically measured index of severity of depression or suicide ideation at baseline and follow-up to contextualize if there is actually a change relative to taking antidepressants.

Additionally, in their conclusion, the authors recommend discontinuation of antidepressants after 12 months, which could undermine the effect of antidepressants if they need to be restarted. Evidence of an increased risk of suicide in the short term following initiation of antidepressants guides limiting initiation of medications as much as possible, and encouraging discontinuation could prove harmful if it leads to increased initiation. It does not appear that the authors directly evaluate this strategy (such as with dynamic treatment regimens) to improve this recommendation nor due they present a formal risk/benefit analysis for discontinuation. This remains conjectural until more careful analysis is done and should be noted as such.

Overall, this is a good paper and provides some important evidence on CVD and fracture outcomes. There remain some crucial concerns in this paper that need to be addressed to improve the validity and utility of this study, or a need to focus it more directly on the outcomes less susceptible to confounding by indication.

Reviewer #2: Major comments:

1. I would like to get a clearer picture on how the authors accounted for immortal time bias. It is not clear from the manuscript as it is written if it was appropriately considered.

2. The use of forward selection strategy to adjust for confounders is not recommended and not reasonable given the sample size. A directed acyclic graph will be a more robust approach, or PS analysis.

3.There was no attempt to minimize confounding by severity, for example adjusting for number of visits in the prior year or number of switches

4. Table 1 should be divided to include comparison group.

other:

how Weight and BMI index are also variably recorded?? this could be a major issue

The conclusion should be rewritten to account for the major limitation, indication bias

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Jan 29;16(1):e0245722. doi: 10.1371/journal.pone.0245722.r002

Author response to Decision Letter 0

5 Jun 2020

RESPONSE TO REVIEWER 1

The risks presented in this study are not contextualized to suggest if this population is at an elevated risk of mortality when using these medications, as is suggested in the conclusion. The empirical risk in this population is not incorrect, however, interpreting these results as a comparison relative to other populations is complicated by the lack of a direct comparison group.

We thank the reviewer for this comment. We have now added in a statement and corresponding references to the Introduction (first paragraph, line 50) to highlight that there is a dose-response relationship between BMI and depression, and also between BMI and mortality. We hope that this contextualises more fully that depression is a particular challenge in this population and that treatment approaches need to consider potential risks associated with depression and obesity.

In terms of comparisons with the general population, we agree that it is a limitation that we were unable to make comparisons with the general population in the ‘normal’ (and underweight) BMI category. We have now highlighted this in the Discussion (please see limitations section, lines 390-391).

We did not find an interaction between antidepressant use and overweight/obese/severely obese for any of the outcomes under investigation (p>0.01 for all) – see results line 312. We can confirm that we adjusted for the relationship between BMI (categorised as overweight, obese and severely obese) in this analysis. We have now made this clearer (see covariates sub-heading / Methods, line 152).

We have discussed this issue more thoroughly in the limitation section of the Discussion (lines 374-386). Confounding by indication with antidepressants in relation to suicidality and mortality is complex. On the one hand an obese person with depression at high suicide risk is more likely to be prescribed antidepressants. However a person who self-harms by overdose with little intent to end their life is less likely to be prescribed antidepressants in case they took the antidepressants as an overdose. Given that the risk of self-harm is 40 times greater than suicide in people who are obese (reference 28 in the paper), then there is likely to be confounding by indication but the confounding is operating to both increase and decrease the likelihood of antidepressant prescribing.

In relation to mortality, suicide is a rare outcome compared to deaths from other causes such as cardiovascular disease and cancer. While a high risk of death by suicide would certainly increase the likelihood that antidepressants would be prescribed, a risk of mortality due to other possible causes would deter the prescription of antidepressants e.g. people with obesity who are prescribed opiate drugs, antidepressant prescribing would be discouraged because of the risk of mortality from respiratory depression.

We agree that that results of the analysis in relation to suicide and mortality is not straight forward because of confounding by indication that may be operating to both increase and decrease these risks. We have outlined these in the Discussion (lines 374 to 386). We describe these sources of confounding and what impact they may have in the discussion.

We agree that ideally we would include a measure of severity of depression but we have not have not found a suitable proxy measure for this. The reviewer suggested number of switches of antidepressants (which would be subject to immortal time bias given that the patient has to have survived long enough in order to have a switch) or number of consultations prior to the depression diagnosis (which would interact with the adjustments for glucose-lowering therapies, statins, CKD and cancer diagnosis). We have acknowledged that inability to account for depression severity is a significant limitation of our study (lines 374-386).

We agree that the conclusion should be changed to a recommendation to clinically review each patient after being on antidepressants for 12 months. The clinical consideration is the need to manage depression and its risks by remaining on antidepressants or start an alternative treatment for depression e.g. psychological treatment and the risk of harm from antidepressants. We have altered our conclusion accordingly (lines 409-412).

We thank the reviewer for these comments.

RESPONSE TO REVIEWER 2

Major comments:

1. I would like to get a clearer picture on how the authors accounted for immortal time bias. It is not clear from the manuscript as it is written if it was appropriately considered.

We used a time-dependent approach (for our exposure measure, antidepressant use) to control for immortal time bias (see papers [1] and [2] below for justification of this approach). This choice means that a patient who is not exposed to an antidepressant is treated as ‘unexposed’ (i.e. no antidepressant at that time period – our reference category ‘none’). We have now clarified this more fully in the statistical analyses section [Methods, lines 152-154].

[1] Zhou et al. (2005) https://academic.oup.com/aje/article/162/10/1016/65057

[2] Suissa (2007). https://academic.oup.com/aje/article/167/4/492/233064

We would like to reassure the reviewer that the confounders/covariates were selected a priori as being conceptually related to the outcome of interest and not through forward selection. We did not draw a DAG specifically, but a similar approach was adopted. A PS analysis may have been possible, but would have been complex, given the different number of antidepressants under investigation. We would have needed to define the probability of being prescribed each individual antidepressant, and censoring on switch date, thereby compromising length of follow up. We are confident that our approach is sufficiently robust.

3.There was no attempt to minimize confounding by severity, for example adjusting for number of visits in the prior year or number of switches

We acknowledge that controlling for severity of depression is a limitation of our study. However, adding in number of switches would introduce immortal time bias (given that a person has to have survived/be event-free in order to have a switch). Similarly, there will be an interaction between number of consultations and glucose-lowering therapies, cancer, CKD and statins. We are reluctant to add in additional covariates at this stage as this was neither an a priori hypothesis nor in the approved ISAC protocol. However, we have acknowledged in the discussion that severity of depression was not possible as a limitation of the study (lines 374 to 386).

4. Table 1 should be divided to include comparison group.

Given that antidepressant exposure was treated as a time-dependent measure, there is no comparison group – only those who are not exposed during the time period. For example, a patient who enters the study at age 30 (i.e. first date of depression diagnosis) and who is initially prescribed no antidepressants for 1 year followed by sertraline for 1 year before leaving the practice contributes 1 year (age 30) to the “none” category (i.e. non-exposed) and 1 year (age 31) to the sertraline category. Therefore, the same patients contribute to both the reference and exposure category. We hope that this is now clearer with the new narrative added (Statistical analysis section lines 152-154).

other:

how Weight and BMI index are also variably recorded?? this could be a major issue

We agree that this is a limitation of the study, given that weight is variably recorded on the CPRD and is not missing at random. We have now added this to the limitations section (please see Discussion, lines 382-386) and have added in two new references to support this.

Of particular note, we included only�people with known

BMI measurement. Complete BMI reporting in UK GP surgeries,

which has improved over time, is known to be more common in older

individuals, females, people with lower socioeconomic status� and

higher BMIs, and people with coexisting chronic conditions (43,44

The conclusion should be rewritten to account for the major limitation, indication bias

We agree. We have added the statement “However some of these results need to be considered cautiously as there was likely to be indication bias and residual confounding (lines406-407)” to our conclusion.

EDITORIAL TEAM

We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

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We will update your Data Availability statement on your behalf to reflect the information you provide.

There is a legal restriction on the authors sharing a de-identified data set from CPRD. There is on-going data collection of psuedoanonymised data from primary care practices, hospitals and public health as a national resource by CPRD on behalf of the National Institute for Health Research in England. The authors of the manuscript applied for, paid and were loaned the data for a set period of time after which they do not have legal access to the data. This has been set legally for the data protection of the participants and staff who collect the data because the information that is kept is very detailed, personal and sensitive including detailed patterned activity that over time might identify participants. There are also such safeguards in place because participants have their data entered into the database without formal consent; participants are only allowed to opt out so there are additional safeguards on access to the data in line with the United Kingdom Data Protection Act and GPDR. The data operates on this basis to maximise population coverage and data completeness to minimise selection, non-responder and attrition bias, thereby enhancing the generalizability of findings to clinical practice. Access to the database requires the development of a suitable protocol that is peer reviewed and approved by a board. A key principle is that there has to be a strong scientific case for the use of the data and that only the data is released to researchers with the expertise to utilise it to answer the research. The researchers also need to provide adequate assurances around data protection and data security.

However, researchers internationally can apply for access to any data including the same data that we used. The process for obtaining such access is outlined at https://www.cprd.com/research-applications (accessed 05/28/2020).

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PLoS One. doi: 10.1371/journal.pone.0245722.r003

Decision Letter 1

Nienke van Rein

11 Nov 2020

PONE-D-20-03344R1

Safety of antidepressants in a primary care cohort of adults with obesity and depression

PLOS ONE

Dear Dr. Morriss,

I would like to apologize that this took a bit longer than expected (mainly due to the COVID care that has to be provided at this moment). One of the two reviewers has addressed some methodological points that need to be addressed before considering the manuscript for publication.

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We look forward to receiving your revised manuscript.

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Nienke van Rein

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: This paper investigates adverse outcomes associated with anti-depressant use in a large cohort of overweight and obese adults. While there are some useful results from the study, there continue to be serious issues with the authors’ approach and conclusions.

The context of this paper, as a study among people with overweight or obese BMI, is overreached to suggest that the observed associations may exist among the general population (a group including people with underweight or normal weight BMI measures). The authors should make it much clearer that their results are observed in a population only including overweight and obese individuals. If the authors suggest that their study sample is representative, then their results are dissimilar from the literature exploring similar questions, which includes RCTs (PMID: 27367876, PMID: 32617669), and potential sources of confounding and bias should be further investigated. Even the randomized studies and meta-analyses of randomized studies that find short term risk, show much lower risk levels – which suggests that this estimate is only sensible if there is no increase in suicide among participants who are not overweight. This would be a major finding, if true, but more likely there is confounding by indication.

This paper would be stronger (and not subject to the bias it currently is) if the authors only included CVD, diabetes, and falls/fractures outcomes in their analyses/results. Suicide and all-cause mortality are subject to serious confounding by indication, which the authors agree with, and it is unclear what the value of giving a biased estimate is to the literature. Given that the study cohort is relatively young (mean age: 46, 25% under 34 years) and less likely to experience some of the outcomes related to age, premature death, such as due to suicide, should be a consideration in the methods and particular attention should be made to limit confounding in these analyses. The authors’ inability to account for severity of depression prevents them from attaining unbiased results from models that are subject to confounding related to this measure. Additionally, the inclusion of individuals taking multiple antidepressants (e.g. 2+ SSRIs) exacerbates the confounding by indication since individuals are requiring a second medication, potentially an indicator for severe depression and suicide ideation. The authors report very high hazard ratios for the risk of suicide among these individuals, which are likely severely confounded. All-cause mortality encompasses suicide, thus is subject to the same issues.

The authors slightly modified their conclusion; however, their recommendation for possible discontinuation of antidepressants is an unsubstantiated claim based off their study. An interesting study could have been designed on the benefits or risk of discontinuing medication, where there is an absence of randomized evidence. This conclusion could even prove to be harmful, as there is evidence of adverse impact on risk of suicide in the short-term following antidepressant initiation and current recommendations suggest minimizing the amount of times initiating antidepressants. The conclusion should be further adjusted to not suggest discontinuation of antidepressants.

Overall, this paper contains important content related to antidepressants and CVD, diabetes, and falls/fractures, but the authors present biased estimates that need to be addressed before this paper provides a beneficial contribution to the literature

Reviewer #2: If confounders were selected as a priori and adjusted for in full models and not using forward selection, then this should be stated and considered the superior method.

No additional comments

**********

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Reviewer #2: No

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PLoS One. 2021 Jan 29;16(1):e0245722. doi: 10.1371/journal.pone.0245722.r004

Author response to Decision Letter 1

19 Nov 2020

Response to Reviewers

Reply. We have added some text to the discussion and conclusion that further explains that the findings apply to obese and overweight people by:

1. Line 373 removing the reference to the representativeness of the sample to the general population.

2. Lines 401-402. Adding a statement that the results apply only to obese and overweight people not normal or underweight people.

3. Line 430. State that the clinical review at 12 months should be conducted in obese/overweight people.

The abstract makes no reference to the general population and its conclusion only mentions people who are obese or overweight.

Reply. We have removed all data for suicide/self-harm from the paper because we agree that there may be serious confounding by indication so there are now four outcomes. However, we think that all cause morality is extremely unlikely to be seriously confounded by indication because only 19 (0.7%) of 2717 deaths were attributed to suicide taking all sources of information available to us from the database. Even if there were a substantial number of other deaths due to suicide that were attributed to other causes, then it is still unlikely that there would be serious confounding. Another database study cited in the paper also founds that suicide is a relatively uncommon cause of death in overweight or obese with depression. Unfortunately apart from suicide we cannot say what the specific causes of death were. Given that the SMR for cardiovascular death in depression is approximately 2, obesity is also a risk factor for cardiovascular death and trials of antidepressants have not reduced cardiovascular events, then it is plausible that many of these young deaths might be due to cardiovascular causes.

In summary we have removed references to suicide and self-harm from the abstract, introduction, aims, method, results, Figures 1 and 2, Table 2 and discussion. Under all-cause mortality results we have added the data that there were 19 suicides out of 2717 deaths (lines 212-213). We have acknowledged the possibility that there may be more deaths from suicide than are reported but have also stated that since suicide is a rare outcome in this and other database studies of overweight and obese people with depression (reference number 27), then we consider the risk of serious confounding by indication to be low (lines 386-398). We acknowledge that we do not know the cause of death other than suicide in the participants of this study and this would be important to study.

Reply. We have further modified our conclusion (lines 430-434) that people who are overweight or obese with depression who are taking antidepressants should be clinically reviewed to consider the balance of risks and benefits of continuing antidepressants in view of the risks from both the antidepressants and depression. We have also added that alternative effective treatments for depression such as psychological treatments should be considered if they are available. We think our data support such a conclusion and we are not advocating that on the basis of this data that everyone should stop taking antidepressants after one year. Furthermore in many countries, including the UK, these conclusions would not be controversial as they are recommended practice for people with mental disorder whatever their weight. Access to psychological treatments is readily available. However we know that this is not the case in many countries so we hope that we have now struck the correct clinical balance in our conclusion.

Reply. We hope the above addresses these concerns.

Reviewer #2: If confounders were selected as a priori and adjusted for in full models and not using forward selection, then this should be stated and considered the superior method.

Reply. We thank the reviewer for pointing this out. We can confirm that we adjusted for the covariates selected a priori in all models and retained the covariates even if they were not statistically significant in line with the a priori selection. We have now clarified this (Line 153–155).

Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reply. We have already explained that there are restrictions on publicly sharing data because the data is owned by a third party and licensed for a period of time for a fee to complete a defined protocol of work that is peer reviewed and agreed between the guardians of this publicly owned data and the research team. Anyone who wishes to check or use the data in this study would need to apply to the guardians of the data and go through a similar process and pay an appropriate fee to obtain access to such data. We have outlined these procedures in our last revision. Unfortunately we are unable to modify these procedures or provide greater access.

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PLoS One. doi: 10.1371/journal.pone.0245722.r005

Decision Letter 2

Nienke van Rein

7 Jan 2021

Safety of antidepressants in a primary care cohort of adults with obesity and depression

PONE-D-20-03344R2

Dear Dr. Morriss,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Nienke van Rein

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

PLoS One. doi: 10.1371/journal.pone.0245722.r006

Acceptance letter

Nienke van Rein

14 Jan 2021

PONE-D-20-03344R2

Safety of antidepressants in a primary care cohort of adults with obesity and depression

Dear Dr. Morriss:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Nienke van Rein

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. STROBE statement—Checklist of items that should be included in reports of cohort studies.

(DOC)

Click here for additional data file.^{(84.5KB, doc)}

S1 Fig. Proportion of people on higher dose (40mg+) citalopram by length of exposure.

(DOCX)

Click here for additional data file.^{(58.2KB, docx)}

S2 Fig. Proportion of people on higher dose (100mg+) sertraline by length of exposure.

(DOCX)

Click here for additional data file.^{(59.1KB, docx)}

S1 Table. RECORD* checklist.

(DOCX)

Click here for additional data file.^{(30.7KB, docx)}

S2 Table. BMI measurements and Read codes for definitions of overweight, obesity and severely obese.

(DOCX)

Click here for additional data file.^{(14.9KB, docx)}

S3 Table. Read codes for depression.

(DOCX)

Click here for additional data file.^{(19KB, docx)}

S4 Table. Product codes for antipsychotic and antimania medications.

(DOCX)

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S5 Table. Read code diagnoses of bipolar disorders, psychotic disorder or dementia.

(DOCX)

Click here for additional data file.^{(41.8KB, docx)}

S6 Table. Product codes for anticholinesterase medication.

(DOCX)

Click here for additional data file.^{(20.1KB, docx)}

S7 Table. Product codes for antidepressant medication.

(DOCX)

Click here for additional data file.^{(70.5KB, docx)}

S8 Table. Outcome measures (Read codes and ICD-10 codes from secondary care/mortality data).

(DOCX)

Click here for additional data file.^{(286.1KB, docx)}

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Data Availability Statement

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PERMALINK

Safety of antidepressants in a primary care cohort of adults with obesity and depression

Richard Morriss

Freya Tyrer

Francesco Zaccardi

Kamlesh Khunti

Roles

Abstract

Background

Methods and findings

Conclusions

Introduction

Methods

Data sources

Study design

Outcome measures

Exposure measures

Covariates

Statistical analyses

Sensitivity analyses

Results

Baseline characteristics

Table 1. Baseline characteristics of study population included in all-cause mortality analysis.

Safety of antidepressants

Fig 1.

Fig 2.

Model 1: All-cause mortality

Model 2: CVD

Model 3: Diabetes

Model 4: Falls/Fractures

Effect of time-varying exposures on outcomes

Fig 3.

Sensitivity analyses

Table 2. Summary of sensitivity analyses.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Christine Leong

Roles

Transfer Alert

Author response to Decision Letter 0

Decision Letter 1

Nienke van Rein

Roles

Author response to Decision Letter 1

Decision Letter 2

Nienke van Rein

Roles

Acceptance letter

Nienke van Rein

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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