CLINICAL EPIDEMIOLOGY www.jasn.org

Comparative Cardiac Safety of Selective Serotonin Reuptake Inhibitors among Individuals Receiving Maintenance Hemodialysis

Magdalene M. Assimon,1 M. Alan Brookhart,2 and Jennifer E. Flythe1,3

1Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina Kidney Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina; 2Department of Epidemiology, University of North Carolina Gillings School of Global Public Heath, Chapel Hill, North Carolina; and 3Cecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, North Carolina

ABSTRACT Background Individuals receiving maintenance hemodialysis may be particularly susceptible to the lethal cardiac consequences of drug-induced QT prolongation because they have a substantial cardiovascular disease burden and high level of polypharmacy, as well as recurrent exposure to electrolyte shifts during dialysis. Electrophysiologic data indicate that among the selective serotonin reuptake inhibitors (SSRIs), citalopram and escitalopram prolong the QT interval to the greatest extent. However, the relative cardiac safety of SSRIs in the hemodialysis population is unknown. Methods In this retrospective cohort study, we used data from a cohort of Medicare beneficiaries re- ceiving hemodialysis included in the US Renal Data System registry (2007–2014). We used a new-user design to compare the 1-year risk of sudden cardiac death among hemodialysis patients initiating SSRIs with a higher potential for prolonging the QT interval (citalopram, escitalopram) versus the risk among those initiating SSRIs with lower QT-prolonging potential (fluoxetine, fluvoxamine, paroxetine, sertraline). We estimated adjusted hazard ratios using inverse probability of treatment weighted survival models. Nonsudden cardiac death was treated as a competing event. Results The study included 30,932 (47.1%) hemodialysis patients who initiated SSRIs with higher QT- prolonging potential and 34,722 (52.9%) who initiated SSRIs with lower QT-prolonging potential. Initiation of an SSRI with higher versus lower QT-prolonging potential was associated with higher risk of sudden CLINICAL EPIDEMIOLOGY cardiac death (adjusted hazard ratio, 1.18; 95% confidence interval, 1.05 to 1.31). This association was more pronounced among elderly individuals, females, patients with conduction disorders, and those treated with other non-SSRI QT-prolonging medications. Conclusions The heterogeneous QT-prolonging potential of SSRIs may differentially affect cardiac out- comes in the hemodialysis population.

J Am Soc Nephrol 30: 611–623, 2019. doi: https://doi.org/10.1681/ASN.2018101032

– Depression affects 25% 40% of the hemodialysis Received October 18, 2018. Accepted January 19, 2019. population1 and associates with a range of adverse Published online ahead of print. Publication date available at health outcomes, including treatment nonadher- www.jasn.org. ence, lower quality of life, higher hospitalization rates, and increased mortality.2 With the inclusion Correspondence: Dr. Magdalene M. Assimon, Division of Ne- phrology and Hypertension, Department of Medicine, University of the Clinical Depression Screening and Follow- of North Carolina Kidney Center, 7024 Burnett-Womack CB Up Reporting Measure in the 2018 ESRD Quality #7155, Chapel Hill, NC 27599-7155. Email: [email protected]. Incentive Program,3 the diagnosis and treatment of edu depression among United States hemodialysis Copyright © 2019 by the American Society of Nephrology

J Am Soc Nephrol 30: 611–623, 2019 ISSN : 1046-6673/3004-611 611 CLINICAL EPIDEMIOLOGY www.jasn.org patients may increase in the coming years. Selective seroto- Significance Statement nin reuptake inhibitors (SSRIs) are recommended as first- line agents for the pharmacologic management of depressive Patients on hemodialysis may be particularly susceptible to the lethal disorders,4 and in 2015, .20% of United States hemodialy- cardiac consequences of drug-induced QT prolongation because sis patients filled a prescription for an SSRI.5 Even though they generally have a substantial cardiovascular disease burden and fi high level of polypharmacy, and are recurrently exposed to elec- clinical trials have demonstrated that SSRIs are ef cacious trolyte shifts during dialysis. Electrophysiologic data indicate that antidepressants in the hemodialysis population, their small among selective serotonin reuptake inhibitors (SSRIs), citalopram sample sizes and limited follow-up time precluded adequate and escitalopram prolong the QT interval to the greatest extent. In a safety assessments.6215 cohort of 65,654 hemodialysis patients, individuals receiving SSRIs fl Electrophysiologic data indicate that all six SSRIs have with higher (citalopram, escitalopram) versus lower ( uoxetine, fluvoxamine, paroxetine, sertraline) potential to prolong the QT 16218 QT-prolonging capabilities. However, citalopram and interval had a higher risk of sudden cardiac death. This risk was more escitalopram prolong the QT interval to the greatest extent pronounced among elderly individuals, females, those with con- at therapeutic doses,16218 and currently carry pharmaceutic reg- duction disorders, and those taking other non-SSRI QT-prolonging ulatory agency–issued warnings related to their proarrhythmic medications. When prescribing SSRIs to patients on hemodialysis, potential.19224 Although these cardiac safety warnings highlight clinicians should consider the QT-prolonging potential of these agents. patient populations at increased risk for QT prolongation and subsequent torsades de pointes (e.g., individuals with hypokale- mia or hypomagnesemia), there is no specific mention of Study Design and Population hemodialysis patients. Individuals receiving maintenance We conducted a retrospective cohort study using an active hemodialysis may be particularly susceptible to the lethal comparator new-user design25 (Figure 1) to investigate the cardiac consequences of citalopram- and escitalopram-induced association between the initiation of higher (citalopram or QT prolongation due to their substantial cardiovascular dis- escitalopram)versuslower(fluoxetine, fluvoxamine, paroxe- ease burden, recurrent exposure to electrolyte shifts during tine, or sertraline) QT-prolonging–potential SSRIs and the dialysis treatments, and extensive use of medications that 1-year risk of sudden cardiac death among individuals receiv- can enhance the proarrhythmic effects of citalopram and ing maintenance hemodialysis. First, we identified hemodial- escitalopram via pharmacokinetic and/or pharmacody- ysis patients with Medicare coverage (Parts A, B, and D) who namic drug interactions. newly initiated SSRI therapy from January 1, 2007 to December 30, In the proarrhythmic ESRD environment, the differential 2014 after a 180-day washout period free of documented SSRI QT-prolonging nature of SSRIs may render certain SSRIs use. Tobe included in the study, SSRI new-users had to receive safer than others. We undertook this study to investigate the in-center hemodialysis during the 180 days before SSRI ini- comparative cardiac safety of SSRIs in a cohort of .65,000 tiation (i.e., baseline period) and also have continuous Medi- United States hemodialysis patients. We hypothesized that care Part A, B, and D coverage during this period. We then individuals initiating higher (citalopram or escitalopram) ver- applied the following exclusion criteria: (1)age,18 years at sus lower (fluoxetine, fluvoxamine, paroxetine or sertraline) the start of the baseline period, (2) dialysis vintage #90 days at QT-prolonging–potential SSRIs would have a higher risk of the start of the baseline period, (3) presence of an implantable sudden cardiac death. automatic cardiac defibrillator, (4)receiptofhospicecare during the baseline period, and (5) missing demographic data. Thus, the study cohort consisted of prevalent, center- METHODS based hemodialysis patients who were SSRI new-users.

This study was approved by the University of North Carolina at Study Exposure, Outcomes, and Baseline Covariates Chapel Hill Institutional Review Board (#17–0011). A waiver We used Medicare Part D prescription claims to identify SSRI of consent was granted due to the study’s large size, data an- new-users. The index date was the date of the first SSRI onymity, and retrospective nature. prescription after the 180-day washout period. We used published QT Drug Lists from the CredibleMeds website Data Source (https://crediblemeds.org/; CredibleMeds, Oro Valley, AZ) The data source for this study was the US Renal Data System to identify the QT-prolonging potential of SSRIs marketed (USRDS) database. The USRDS is a national ESRD surveil- in the United States during the study period.26 Funded by lance system that collects, analyzes, and distributes infor- the US Food and Drug Administration (FDA), research mation on individuals with ESRD in the United States. The grants, and charitable donations, CredibleMeds is a reliable USRDS database includes the Medical Evidence and ESRD and up-to-date clinical resource that contains information Death NotificationFormsaswellasMedicarestandard about medications that can cause QT prolongation and/or analytic files, including the Medicare enrollment database torsades de pointes.26 On the basis of published medical and final action administrative claims (Medicare Parts A, literature, medication package inserts, and the FDA’s Adverse B, and D). Event Reporting System, CredibleMeds classifies medications

612 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 611–623, 2019 www.jasn.org CLINICAL EPIDEMIOLOGY

Initiation of an SSRI with higher or lower QT prolonging potential Index date Study end End of 1-year follow-up or December 31, 2014

SSRI washout Follow-up period No record of any SSRI Rx Outcome, censoring & competing event assessment

180-day baseline period Obtain covariates

Figure 1. Study design. Initiators of higher and lower QT-prolonging–potential SSRIs were defined as hemodialysis patients who had no record of an SSRI prescription in the previous 180 days (i.e., the SSRI washout period). Higher QT-prolonging–potential SSRIs in- cluded citalopram and escitalopram. Lower QT-prolonging–potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertra- line. The index date was defined as the date of SSRI initiation. Baseline covariates were identified in the 180-day period before the index date. Study follow-up began immediately after the index date. Rx, prescription. as having a known, conditional, or possible risk of torsades de We identified covariates in the 180 days before the index date pointes (corresponding definitions are provided in Table 1).26 using Medicare Part A, B, and D claims. Covariates of interest Citalopram and escitalopram are classified as having a known included patient demographics, comorbid conditions, pre- risk of torsades de pointes. Fluoxetine, fluvoxamine, paroxetine, scription medication use, and metrics of health care utiliza- and sertraline are classified as having a conditional risk of tion. Comorbid conditions were considered present if an torsades de pointes. Thus, we considered (1)citalopramand applicable International Classification of Diseases, Ninth Re- escitalopram new-users as initiators of a higher QT-prolonging– vision discharge code (located in any position) was associated potential SSRI, and (2) fluoxetine, fluvoxamine, paroxetine, and with $1 institutional or physician/supplier claim during the sertraline new-users as initiators of a lower QT-prolonging– 180-day baseline period (Supplemental Table 2). Medica- potential SSRI. tion utilization on the last dayofthebaselineperiodwas The primary outcome of interest was 1-year sudden cardiac determined using Medicare Part D claims and Healthcare death. We defined sudden cardiac death using the established Common Procedure Coding System codes (for medications USRDS definition, death due to cardiac arrhythmia or cardiac not covered by Medicare Part D, such as intravenous drugs). arrest listed as the primary cause (Supplemental Table 1).27 We Non-SSRI QT-prolonging medications of interest included obtained dates and causes of death from the ESRD Death No- drugs classified as having a known, conditional, and possible tification Form. We used a 1-year follow-up period to mirror risk of torsades de pointes according to CredibleMeds (Sup- clinical practice guidelines which recommend that patients plemental Tables 3 and 4).26 Cytochrome P450 inhibitors of starting an initial course of antidepressant pharmacotherapy interest included medications that can reduce the hepatic me- are treated for a minimum of 6–12 weeks to achieve initial tabolism of SSRIs (Supplemental Table 5).29 Use of a 180-day depressive symptom remission, followed by an additional 4–9 baseline period enabled us to: (1) maximize cohort general- months of continued antidepressant treatment to prevent re- izability and (2) capture patient characteristics occurring lapse (i.e., approximately 1 year of total pharmacotherapy).4 close to study medication initiation that may have influenced Baseline covariates included potential confounders and var- SSRI-prescribing decisions30,31 and were highly predictive of iables known to be strong risk factors for the study outcome.28 the study outcome.32

Table 1. CredibleMeds definitions for medications with a known, conditional and possible risk of torsades de pointes CredibleMeds Classification26 Definition Known risk of torsades de pointes Drugs that prolong the QT interval and are clearly associated with a known risk of torsades de pointes, even when taken as recommended. Conditional risk of torsades de pointes Drugs that are associated with torsades de pointes only under certain conditions (e.g., excessive dose, in patients with conditions such as hypokalemia, or when taken with interacting drugs) or drugs that create conditions that facilitate or induce torsades de pointes (e.g., cause an electrolyte disturbance that induces torsades de pointes). Probable risk of torsades de pointes Drugs that can cause QT prolongation but currently lack evidence for a risk of torsades de pointes when taken as recommended.

J Am Soc Nephrol 30: 611–623, 2019 SSRI Cardiac Safety in Hemodialysis Patients 613 CLINICAL EPIDEMIOLOGY www.jasn.org

All statistical analyses were performed using SAS version Table 1). In analyses evaluating cardiovascular mortality, 9.4 (SAS Institute Inc., Cary, NC). We described baseline noncardiovascular death was treated as a competing risk. characteristics across individuals who initiated higher and Second, we compared citalopram and escitalopram initia- lower QT-prolonging–potential SSRIs as count (percent- tors (separately) to initiators of an SSRI with lower QT- age) for categoric variables and as mean6SD for continu- prolonging potential using methods analogous to the ous variables. We compared baseline covariate distributions primary analyses. Third, because exact dates of medication using absolute standardized differences. A standardized dif- discontinuation are not available in administrative claims ference .10% represents an imbalance between exposure data, we repeated primary analyses using longer grace pe- groups.33 riods of 14 and 30 days to define index SSRI discontinua- We used an on-treatment (i.e., per-protocol) analytic ap- tion. Fourth, because long-term antidepressant therapy proach to evaluate the association between the initiation of a may be required in some patients (i.e., those with histories higher versus lower QT-prolonging–potential SSRI and the of multiple major depressive episodes or residual depressive 1-year risk of sudden cardiac death. Individuals were followed symptoms), we repeated primary analyses using all available forward in historical time from the index date to the first follow-up time.4 Fifth, we used an intention-to-treat ana- occurrence of the study outcome, censoring event, or compet- lytic approach (i.e., first-exposure-carried-forward analy- ing event. Censoring events included: (1) change of dialysis sis) to evaluate the SSRI QT-prolonging potential–sudden modality to home hemodialysis or peritoneal dialysis; (2)kid- cardiac death association. In these analyses, we did not con- ney transplantation; (3) recovery of kidney function; (4)loss sider SSRI discontinuation and switching as censoring of Medicare Part A, B, or D coverage; (5) discontinuation of events. Sixth, to test the specificity of our findings we eval- index SSRI therapy; (6) switch to a nonindex SSRI; (7) com- uated the association between the initiation of a higher ver- pletion of 1-year of follow-up; and (8) study end (December sus lower QT-prolonging–potential SSRI and nonsudden 31, 2014). We defined the SSRI discontinuation date as the cardiac death, a negative control outcome that we did not date when the index SSRI was exhausted for .7 days (i.e., grace expect to be influenced by SSRI type.39 In these analyses, period) without a subsequent dispensing of the same SSRI sudden cardiac death was treated as a competing risk. (Supplemental Figure 1). We defined the index SSRI switching date as the date of the first prescription fill for a nonindex SSRI during follow-up. Patients were at risk for a switching RESULTS event only during times of continuous index medication use (Supplemental Figure 1). Study Cohort Characteristics In primary analyses, we assessed the SSRI QT-prolonging Figure 2 displays a flow diagram of study cohort selection. potential–sudden cardiac death association in the full study A total of 65,654 individuals receiving maintenance hemo- cohort using Fine and Gray proportional subdistribution haz- dialysis were included in the study: 30,932 (47.1%) initiators ards models, treating nonsudden cardiac death as a competing of higher QT-prolonging–potential SSRIs and 34,722 risk.34 In prespecified, exploratory secondary analyses, we (52.9%) initiators of lower QT-prolonging–potential SSRIs. evaluated the SSRI QT-prolonging potential–sudden cardiac There were 16,288 (32.3%) citalopram, 14,644 (22.3%) death association within clinically relevant subgroups using escitalopram, 6468 (9.9%) fluoxetine, 44 (0.1%) fluvoxamine, the same analytic approach. Subgroups of interest included 7011 (10.7%) paroxetine, and 21,199 (32.3%) sertraline initiators individuals with and without known risk factors for drug- in the study cohort. Overall, study patients had an average induced QT prolongation: advanced age, female sex, cardiac age of 67.0617.2 years, 52.8% were women, 35.5% were conduction disorder, heart failure, liver disease, and use of black, 19.2% were Hispanic, and the most common cause other non-SSRI QT-prolonging medications.35,36 Across all of ESRD was diabetes (50.2%). Depression (33.2%) and analyses, we used inverse probability of treatment (IPT) anxiety (17.7%) were the most prevalent mental health weighting to control for confounding. Briefly, we calculated conditions. the predicted probability (i.e., propensity score) of receiving The propensity score distribution of initiators of higher and an SSRI with higher versus lower QT-prolonging poten- lower QT-prolonging–potential SSRIs exhibited substantial tial as a function of baseline covariates using multivariable overlap (Supplemental Figure 2), indicating that study groups logistic regression. We generated IPT weights from propen- were highly comparable. Table 2 and Supplemental Table 6 sity scores using standard methods and estimated adjusted show patient baseline characteristics stratified by SSRI QT- hazard ratios (HRs) by applying IPT weights in regression prolonging potential (higher versus lower). Before IPT models.37,38 weighting, baseline covariates were generally well balanced We conducted several sensitivity analyses to evaluate the between treatment groups (standardized differences #10%), robustness of our primary study findings. First, we evaluated with some exceptions (e.g., race other than black or white, year two alternative study outcomes including: (1) a composite of index SSRI fill, depression, and history of stroke). After IPT outcome of sudden cardiac death or hospitalized ventricular weighting, all baseline covariates were well balanced between arrythmia and (2) cardiovascular mortality (Supplemental treatment groups.

614 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 611–623, 2019 www.jasn.org CLINICAL EPIDEMIOLOGY

170,109 center-based hemodialysis patients with Medicare coverage who filled ≥1 SSRI Rx during 2007 to 2014

71,899 SSRI initiators who met study inclusion criteriaa

Age <18 years • 34 patients excluded

Dialysis vintage ≤90 days • 3423 patients excluded

Had an implantable cardiac defibrillator • 2021 patients excluded

Hospice care during the baseline period • 555 patients excluded

Missing demographic data • 212 patients excluded

65,654 hemodialysis patients included

30,932 initiators of an SSRI with 34,722 initiators of an SSRI with higher QT-prolonging potentialb lower QT-prolonging potentialb

Figure 2. Flow diagram depicting study cohort assembly. (a) To be included in the study, SSRI new-users had to receive in-center hemodialysis during the 180 days before SSRI initiation (i.e., baseline period) and also have continuous Medicare Part A, B, and D coverage during this period. (b) Higher QT-prolonging–potential SSRIs included citalopram and escitalopram. Lower QT-prolonging– potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Rx, prescription.

Primary Analyses During the 1-year follow-up period, 1303 sudden cardiac Under the on-treatment analytic paradigm, the study cohort deaths occurred at an incidence rate of 78.3 events per 1000 was followed for a total of 16,633 person-years (7858 person- person-years (702 sudden death events occurred at an inci- years for initiators of a higher QT-prolonging–potential dence rate of 89.3 events per 1000 person-years among ini- SSRI and 8775 person-years for initiators of a lower QT- tiators of higher QT-prolonging–potential SSRIs, and 601 prolonging–potential SSRI). A total of 51,005 individuals dis- sudden death events occurred at a rate of 68.5 events per continued index SSRI therapy, and 2017 individuals switched to 1000 person-years among initiators of lower QT-prolonging– nonindex SSRI during follow-up. The median (interquartile potential SSRIs). Figure 3 and Supplemental Table 7 display range) duration of follow-up was 37 (65) days among patients the SSRI QT-prolonging potential–sudden cardiac death as- initiating an SSRI of higher QT-prolonging potential, and sociation. Compared with individuals initiating lower 37 (63) days among patients initiating an SSRI with lower QT- QT-prolonging–potential SSRIs, individuals initiating higher prolonging potential. Exposure to non-SSRI QT-prolonging QT-prolonging–potential SSRIs had a higher 1-year risk of medications during follow-up was similar among initiators sudden cardiac death (adjusted HR, 1.18; 95% confidence of higher and lower QT-prolonging–potential SSRIs. interval, 1.05 to 1.31).

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Table 2. Select baseline characteristics of study patients initiating a higher and lower QT-prolonging–potential SSRI EPIDEMIOLOGY CLINICAL Unweighted Weighted

Characteristic SSRI with Higher QT- SSRI with Lower QT- a SSRI with Higher QT- SSRI with Lower QT- a ora fteAeia oit fNephrology of Society American the of Journal Std Diff Std Diff Prolonging Potential, Prolonging Potential, Prolonging Potential, Prolonging Potential, (%) (%) n=30,932 n=34,722 n=30,927 n=34,730 Age, yr 67.6617.2 66.5617.2 6.2 67.0617.2 67.0617.21 0.0 Female 16,512 (53.4%) 18,121 (52.2%) 2.3 16,316 (52.8%) 18,324 (52.8%) 0.0 Race Black 11,339 (36.7%) 11,959 (34.4%) 6.3 10,967 (35.5%) 12,320 (35.5%) 0.0

White 18,434 (59.6%) 21,005 (60.5%) 1.5 18,589 (60.1%) 20,870 (60.1%) 0.0 www.jasn.org Other 1159 (3.7%) 1758 (5.1%) 33.5 1371 (4.4%) 1540 (4.4%) 0.0 Hispanic 5233 (16.9%) 7346 (21.2%) 22.7 5933 (19.2%) 6654 (19.2%) 0.1 Year index SSRI was filled 2007 3961 (12.8%) 4751 (13.7%) 6.9 4086 (13.2%) 4594 (13.2%) 0.1 2008 4095 (13.2%) 4388 (12.6%) 4.8 3977 (12.9%) 4468 (12.9%) 0.0 2009 4061 (13.1%) 4343 (12.5%) 5.0 3948 (12.8%) 4435 (12.8%) 0.1 2010 4139 (13.4%) 4161 (12.0%) 11.5 3907 (12.6%) 4386 (12.6%) 0.0 2011 4034 (13.0%) 4061 (11.7%) 11.3 3814 (12.3%) 4287 (12.3%) 0.1 2012 3611 (11.7%) 4152 (12.0%) 2.5 3670 (11.9%) 4118 (11.9%) 0.1 2013 3507 (11.3%) 4398 (12.7%) 11.5 3738 (12.1%) 4194 (12.1%) 0.1 2014 3524 (11.4%) 4468 (12.9%) 12.7 3787 (12.2%) 4246 (12.2%) 0.2 Low-dose index SSRIb 27,935 (90.3%) 31,560 (90.9%) 0.6 28,011 (90.6%) 31,456 (90.6%) 0.0 Cause of ESRD Diabetes 15,563 (50.3%) 17,416 (50.2%) 0.3 15,542 (50.3%) 17,458 (50.3%) 0.0 Hypertension 7941 (25.7%) 8760 (25.2%) 1.8 7848 (25.4%) 8813 (25.4%) 0.0 Glomerular disease 3359 (10.9%) 3934 (11.3%) 4.4 3442 (11.1%) 3864 (11.1%) 0.1 Other 4069 (13.2%) 4612 (13.3%) 1.0 4095 (13.2%) 4596 (13.2%) 0.1 Dialysis vintage, yr 0.7–0.9 5467 (17.7%) 5903 (17.0%) 4.0 5364 (17.3%) 6023 (17.3%) 0.0 1.0–1.9 5965 (19.3%) 6622 (19.1%) 1.1 5933 (19.2%) 6661 (19.2%) 0.0 2.0–2.9 4631 (15.0%) 5136 (14.8%) 1.3 4594 (14.9%) 5162 (14.9%) 0.1 $3 14,869 (48.1%) 17,061 (49.1%) 2.2 15,035 (48.6%) 16,883 (48.6%) 0.0 Depression 10,960 (35.4%) 10,851 (31.3%) 12.7 10,298 (33.3%) 11,567 (33.3%) 0.0 Anxiety 5590 (18.1%) 6046 (17.4%) 3.8 5492 (17.8%) 6169 (17.8%) 0.0

mScNephrol Soc Am J Arrythmia 9616 (31.1%) 10,135 (29.2%) 6.4 9327 (30.2%) 10,471 (30.1%) 0.0 Conduction disorder 2434 (7.9%) 2659 (7.7%) 2.9 2403 (7.8%) 2699 (7.8%) 0.0 Dyslipidemia 15,756 (50.9%) 17,566 (50.6%) 0.7 15,723 (50.8%) 17,652 (50.8%) 0.0 Heart failure 14,937 (48.3%) 15,884 (45.7%) 5.5 14,536 (47.0%) 16,321 (47.0%) 0.0 Hypertension 28,289 (91.5%) 31,297 (90.1%) 1.5 28,073 (90.8%) 31,522 (90.8%) 0.0 Ischemic heart disease 15,171 (49.0%) 16,216 (46.7%) 4.9 14,810 (47.9%) 16,624 (47.9%) 0.0 30: Peripheral arterial disease 11,332 (36.6%) 11,737 (33.8%) 8.2 10,878 (35.2%) 12,216 (35.2%) 0.0 611 Stroke 8225 (26.6%) 8033 (23.1%) 14.2 7668 (24.8%) 8615 (24.8%) 0.0 – 2,2019 623, Valvular disease 2112 (6.8%) 2165 (6.2%) 9.8 2023 (6.5%) 2273 (6.5%) 0.1 Chronic liver disease 1385 (4.5%) 1577 (4.5%) 1.6 1400 (4.5%) 1570 (4.5%) 0.1 mScNephrol Soc Am J 30:

611 Table 2. Continued – 2,21 SICricSft nHmdayi Patients Hemodialysis in Safety Cardiac SSRI 2019 623, Unweighted Weighted SSRI with Higher QT- SSRI with Lower QT- SSRI with Higher QT- SSRI with Lower QT- Characteristic Std Diffa Std Diffa Prolonging Potential, Prolonging Potential, Prolonging Potential, Prolonging Potential, (%) (%) n=30,932 n=34,722 n=30,927 n=34,730 Diabetes 21,520 (69.6%) 23,690 (68.2%) 2.0 21,305 (68.9%) 23,927 (68.9%) 0.0 History of noncompliance 3501 (11.3%) 4072 (11.7%) 3.7 3575 (11.6%) 4013 (11.6%) 0.0 Had a cardiac pacemaker 1431 (4.6%) 1463 (4.2%) 10.6 1361 (4.4%) 1529 (4.4%) 0.0 Had cardiac surgery during the last 30 d of baseline 588 (1.9%) 614 (1.8%) 10.7 565 (1.8%) 635 (1.8%) 0.1 Had an ECG during the last 30 d of baseline 9908 (32.0%) 10,796 (31.1%) 3.0 9777 (31.6%) 10,974 (31.6%) 0.1 ACE inhibitor 5749 (18.6%) 6542 (18.8%) 1.4 5801 (18.8%) 6509 (18.7%) 0.1 ARB 3018 (9.8%) 3530 (10.2%) 4.3 3082 (10.0%) 3462 (10.0%) 0.0 b blocker 11,442 (37.0%) 13,114 (37.8%) 2.1 11,562 (37.4%) 12,981 (37.4%) 0.0 Calcium channel blocker 8768 (28.3%) 10,385 (29.9%) 5.5 9031 (29.2%) 10,141 (29.2%) 0.0 Central a agonist 3906 (12.6%) 4413 (12.7%) 0.7 3913 (12.7%) 4394 (12.7%) 0.0 Diuretic 2903 (9.4%) 3565 (10.3%) 9.5 3048 (9.9%) 3420 (9.8%) 0.1 Use of $1 medication with a known risk of TdPc 2919 (9.4%) 3210 (9.2%) 2.2 2891 (9.3%) 3244 (9.3%) 0.1 Use of $1 medication with a conditional risk of TdPc 12,634 (40.8%) 14,238 (41.0%) 0.4 12,675 (41.0%) 14,231 (41.0%) 0.0 Use of $1 medication with a possible risk of TdPc 3228 (10.4%) 3123 (9.0%) 15.6 3001 (9.7%) 3375 (9.7%) 0.1 Use of $1 CYP 1A2 inhibitord 1154 (3.7%) 1290 (3.7%) 0.5 1155 (3.7%) 1296 (3.7%) 0.1 Use of $1 CYP 3A4 inhibitord 2419 (7.8%) 2770 (8.0%) 2.1 2450 (7.9%) 2746 (7.9%) 0.2 Use of $1 CYP 2C9 inhibitord 2074 (6.7%) 2385 (6.9%) 2.6 2104 (6.8%) 2360 (6.8%) 0.1 Use of $1 CYP 2C19 inhibitord 8119 (26.2%) 9022 (26.0%) 1.0 8095 (26.2%) 9087 (26.2%) 0.0 $ d

Use of 1 CYP 2D6 inhibitor 8777 (28.4%) 9999 (28.8%) 1.5 8845 (28.6%) 9931 (28.6%) 0.0 www.jasn.org Hospitalized during the last 30 d of the baseline period 8701 (28.1%) 8749 (25.2%) 11.2 8248 (26.7%) 9264 (26.7%) 0.0 Had $1 psychotherapy visit during the baseline period 3314 (10.7%) 2738 (7.9%) 31.8 2859 (9.2%) 3211 (9.2%) 0.0 Values are given as number (percentage) for categoric variables and as mean6SD for continuous variables. Higher QT-prolonging–potential SSRIs included citalopram and escitalopram. Lower QT-prolonging– potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. All covariates were measured during the 180-d baseline period before SSRI initiation. The weighted cohort is the pseudo-population generated by the IPT weighting. Std diff, standardized differences; ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; TdP, torsades de pointes; CYP, cytochrome P450. a . 33 Astddiff 10.0% represents meaningful imbalance between groups. EPIDEMIOLOGY CLINICAL bThe definition of low-dose was on the basis of the dosing recommendations found in each SSRI’s package insert.62 –67 Low doses: citalopram#20 mg/d; escitalopram#10 mg/d; fluoxetine#20 mg/d; immediate release fluvoxamine #50 mg/d; controlled release fluvoxamine #100 mg/d; immediate release paroxetine #20 mg/d; controlled release paroxetine #25 mg/d; and sertraline 50 mg/d. cLists of medications with known, conditional, and possible risks of TdP are presented in Supplemental Table 3. dLists of medications that are relevant CYP 1A2, 3A4, 2C9, 2C19, and 2D6 inhibitors are provided in Supplemental Table 4. 617 CLINICAL EPIDEMIOLOGY www.jasn.org

initiation of a higher versus lower QT-prolonging–potential 1.50 SSRI was not associated with the 1-year risk of nonsudden cardiac death (adjusted HR, 1.01; 95% confidence interval, 0.95 to 1.09; Supplemental Table 13). 1.25 1.18 (1.05, 1.31) 1.11 (1.02, 1.22) DISCUSSION 1.00 1.00 (ref.) 1.00 (ref.) This observational study evaluated the comparative cardiac Adjusted HR (95% CI) safety of SSRIs in the hemodialysis population. We found

0.75 that individuals initiating higher (citalopram, escitalopram) versus lower (fluoxetine, fluvoxamine, paroxetine, sertraline) Sudden cardiac Cardiovascular – death mortality QT-prolonging potential SSRIs had a higher 1-year risk of sudden cardiac death. This association was robust across mul- SSRIs with a lower QT prolonging potential tiple sensitivity analyses. Furthermore, our exploratory sub- SSRIs with a higher QT prolonging potential group analyses suggest that the observed SSRI QT-prolonging Figure 3. Initiation of a higher versus lower QT-prolonging–potential potential–sudden cardiac death association may be more pro- SSRI associates with a higher 1-year risk of fatal cardiac outcomes. An nounced among elderly individuals, females, patients with on-treatment analytic approach was used in all analyses. Fine and conduction disorders, and those treated with other non- Gray proportional subdistribution hazards models were used to esti- SSRI QT-prolonging medications. mate the association between the initiation of higher versus lower An undesirable property of SSRIs is their ability to delay QT-prolonging–potential SSRI and the 1-year risk of fatal cardiac ventricular repolarization, an effect that manifests as QT in- outcomes. Higher QT-prolonging–potential SSRIs included citalopram 16218 and escitalopram. Lower QT-prolonging–potential SSRIs included terval prolongation on an electrocardiogram (ECG). All fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted anal- six SSRIs can prolong the QT interval via their antagonistic yses controlled for baseline covariates listed in Supplemental effects on myocardial human ether-a-go-go (hERG) potas- 2 Table 6 using IPT weighting. 95% CI, 95% confidence interval; sium channels.40 45 However, despite their common off- ref., referent. target effects on myocardial potassium channels, individual agents within the SSRI class have differential QT-prolonging abilities.16218 Citalopram and escitalopram (the S-enantiomer Secondary Analyses of the citalopram racemate) prolong the QT interval more Secondary analyses assessing the SSRI QT-prolonging poten- than other SSRIs.16218 In fact, randomized, placebo-controlled tial–sudden cardiac death association within clinically relevant trials conducted in healthy volunteers have demonstrated subgroups produced results analogous to primary study find- that citalopram and escitalopram can prolong the QT in- ings. Across all subgroups, initiation of a higher versus lower terval beyond the threshold of regulatory concern, an in- QT-prolonging–potential SSRI was associated with a higher crease of 5 milliseconds from baseline, 46,47 at therapeutic 1-year risk of sudden cardiac death. However, the ob- doses.19221 served associations were more potent in patients aged To date, data characterizing the QT-prolonging effects and $65 years (versus ,65 years), females (versus males), indi- cardiac safety profiles of SSRIs in the hemodialysis population viduals with (versus without) a cardiac conduction disorder, are limited. QT prolongation and ventricular arrhythmias, and those using (versus not using) $1 other non-SSRI QT- such as torsades de pointes, were not reported in clinical trials prolonging medication (Figure 4, Supplemental Table 8). evaluating the antidepressant efficacy of SSRI therapy in di- alysis patients.6215,48 However, it is likely that cardiac safety Sensitivity Analyses signals could not be detected in these trials due to their small Sensitivity analyses (1) evaluating alternative outcomes sample sizes (7–62 participants) and limited follow-up (a composite outcome of sudden cardiac death or hospital- (4 weeks to 6 months).6215,48 To our knowledge, published ized ventricular arrhythmia; and cardiovascular mortal- evidence linking SSRIs to adverse cardiac outcomes in ESRD is ity, separately), (2) comparing initiators of citalopram and limited to a few case reports of citalopram- and escitalopram- escitalopram (separately) to initiators of lower QT-prolonging– induced QT prolongation and torsades de pointes.49251 Given potential SSRIs, (3) using longer grace periods of 14 and 30 days to the paucity of population-specific data, international experts identify index SSRI discontinuation, (4) considering all possible have called for high-quality safety studies to inform antide- follow-up time, and (5) employing an intent-to-treat analytic ap- pressant prescribing in patients receiving dialysis.52 proach produced results that were consistent with our primary To begin to address this evidence gap, we conducted a phar- analysis (Figure 3, Supplemental Tables 7 and 9–12). In addition, macoepidemiologic study to assess the association between the sensitivity analyses evaluating the SSRI QT-prolonging potential– initiation of higher versus lower QT-prolonging–potential negative control outcome association demonstrated that the SSRIs and sudden cardiac death in the hemodialysis population.

618 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 611–623, 2019 www.jasn.org CLINICAL EPIDEMIOLOGY

Adjusted HR (95% CI) Overall 1.18 (1.05, 1.31)

Age 65 years 1.19 (1.05, 1.35) <65 years 1.13 (1.90, 1.41)

Sex Female 1.23 (1.06, 1.44) Male 1.12 (0.96, 1.31)

Conduction disorder Yes 1.47 (1.05, 2.06) No 1.14 (1.02, 1.28)

Heart failure Yes 1.16 (1.02, 1.32) No 1.21 (1.00, 1.48)

Liver disease Yes 1.20 (0.74, 1.95) No 1.17 (1.05, 1.31)

Use of 1 QT prolonging med Yes 1.29 (1.10, 1.50) No 1.08 (0.93, 1.26)

0.75 1.00 1.25 1.75 2.25 Adjusted HR (95% CI)

Figure 4. Initiation of a higher versus lower QT-prolonging–potential SSRI associates with a higher 1-year risk of sudden cardiac death within clinically relevant subgroups. An on-treatment analytic approach was used in all analyses. Fine and Gray proportional sub- distribution hazards models were used to estimate the association between the initiation of higher versus lower QT-prolonging– potential SSRIs and the 1-year risk of sudden cardiac death within clinically relevant subgroups. Higher QT-prolonging–potential SSRIs included citalopram and escitalopram. Lower QT-prolonging–potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using IPT weighting. The square sizes of HR point estimates are proportional to the size of the subgroup. The larger the square size the larger the subgroup. Within each respective subgroup, the interaction P value was $0.05. 95% CI, 95% confidence interval; med, medication.

Our findings provide initial evidence that the heterogenous torsades de pointes reported to pharmaceutic regulatory agen- QT-prolonging potential of SSRIs may differentially cies primarily involved individuals with risk factors for drug- affect cardiac outcomes in hemodialysis-dependent ESRD. In induced QT prolongation (e.g., female sex, preexisting QT addition, results from our exploratory subgroup analyses suggest prolongation, or known cardiac disease).20,21 that patients with risk factors for drug-induced QT prolongation Relative to the general population, individuals receiving (e.g., advanced age, female sex, cardiac conduction disorders, maintenance hemodialysis may have an increased suscepti- and use of non-SSRI QT-prolonging medications) may have bility to the QT-prolonging effects of citalopram and escita- heightened susceptibly to the proarrhythmic effects of higher lopram for several reasons. First, cardiovascular comorbid QT-prolonging–potential SSRIs. Although our subgroup analy- conditions that result in structural heart damage are common ses should be considered preliminary in nature, our findings do in ESRD. Cardiovascular remodeling due to coronary artery align with published postmarketing surveillance data. Cases of disease,leftventricularhypertrophy,andheartfailurecanlead citalopram- and escitalopram-induced QT prolongation and to a progressive downregulation of myocardial ion channels,

J Am Soc Nephrol 30: 611–623, 2019 SSRI Cardiac Safety in Hemodialysis Patients 619 CLINICAL EPIDEMIOLOGY www.jasn.org diminishing cardiac repolarization reserve,53255 ultimately SSRIs with a higher versus lower QT-prolonging potential leaving the heart vulnerable to proarrhythmic triggers such reflects a clinically meaningful treatment decision encoun- as QT-prolonging drugs. Second, patients on hemodialysis tered by prescribers in real-world practice.30,31 Finally, we are exposed to electrolyte shifts during dialysis treatments. It performed multiple sensitivity analyses to test the robustness is plausible that rapid dialytic removal of electrolytes, such as of our primary results. potassium, and the use of proarrhythmic medications have Our findings should be considered within the context of additive QT-prolonging effects. Exposure to wider versus study limitations. First, because our study was observational, narrower blood-to-dialysate electrolyte gradients results in residual confounding may remain. However, we adjusted for a more extensive dialysis-induced QT prolongation.56 Fur- wide-range of clinical and health care utilization metrics in our thermore, in vitro models have demonstrated that reductions analyses to minimize confounding from difficult-to-measure in extracellular potassium enhance the degree of drug- factors such as ambient health status. In particular, the lack of induced inhibition of the cardiac repolarizing ionic current an observed association between SSRI QT-prolonging poten- 57 IKr. Finally, patients receiving hemodialysis have high med- tial and nonsudden cardiac death (the negative control out- ication burdens, increasing the likelihood that they are ex- come) suggests that the influence of unmeasured confounding posed to interacting medications. Concurrent use of two or in our study was minimal.39 Second, although we were able to more QT-prolonging medications and the use of a QT-prolonging determine whether an ECG was conducted in the month medication in combination with a metabolic inhibitor may result before SSRI initiation, we lacked accompanying clinical infor- in QT interval lengthening.35,36 mation to know whether ECG findings were used to inform Future studies are needed to fully elucidate the cardiac safety SSRI-prescribing decisions. Third, although we defined our profiles of SSRIs in the hemodialysis population, including the primary study outcome using the established USRDS sudden frequency and magnitude of SSRI-induced QT prolongation cardiac death definition, contemporary information on the measured via serial ECG monitoring or implantable loop re- validity of this outcome definition (e.g., sensitivity, specificity, corders. However, in the interim, our results suggest that SSRI positive predictive value, and negative predictive value) is lim- therapy selection should be individualized and clinicians ited.59,60 Because cause of death information was taken from should consider the differential QT-prolonging properties of the ESRD Death Notification Form, outcome misclassifica- SSRIs, among other factors, in their prescribing choices. tion may have occurred. However, such misclassification In particular, prescribers should be mindful of the demo- would likely be nondifferential (i.e.,notdependentonexpo- graphic, comorbid, and medication-related risk factors for sure classification), biasing results toward the null.61 Reassur- drug-induced QT prolongation, taking into account patient ingly, sensitivity analyses considering broader cardiac medical history, laboratory results, ECG findings, and con- outcomes produced consistent results. Fourth, information comitant medication use when selecting an SSRI. A lower on missed or shortened hemodialysis treatments is not avail- QT-prolonging–potential SSRI may be a better option for able in USRDS data. However, to minimize associated patients at high risk for drug-induced QT prolongation, confounding, we adjusted our analyses for a history of such as women, the elderly, individuals with cardiac conduc- noncompliance (International Classification of Diseases, tion abnormalities, and those treated with other non-SSRI Ninth Revision diagnosis codes V15.81 and V45.12). Fifth, QT-prolonging medications.35,36 However, if citalopram or information on laboratory parameters, including serum elec- escitalopram therapy is unavoidable in a high-risk patient, trolytes, and patient-reported medication ineffectiveness or clinicians should look to the drug safety warnings issued by side effects were not available. We were unable to determine pharmaceutic regulatory agencies for guidance on therapeutic the clinical factor(s) that may have led to SSRI discontinuation monitoring.19224 Regulatory agencies, including the FDA, or therapy switches during follow-up. Sixth, our subgroup recommend serial ECG monitoring throughout the course analyses had limited power. Despite strong biologic plausibil- of therapy in high-risk patients.19,22224 If the length of a pa- ity, additional research is needed to confirm our findings. tient’s corrected QT interval surpasses 500 milliseconds, treat- Finally, our study population was comprised of prevalent ment should be withdrawn gradually.19,22,23 ESRD patients receiving in-center hemodialysis. Our Our study has several strengths. First, the use of Medicare results may not generalize to excluded populations such claims data enabled us to conduct a large-scale safety study in a as incident hemodialysis, home hemodialysis, or perito- cohort of .65,000 hemodialysis patients initiating SSRI ther- neal dialysis patients. Understanding the relative risk-benefit apy. Second, we utilized a new-user study design to mitigate profiles of SSRIs in excluded patient populations is an area for biases common to observational studies of prescription drugs future inquiry. such as selection and immortal time biases.25 Third, by In conclusion, we observed that the initiation of a higher performing a head-to-head comparison of SSRIs with higher versus lower QT-prolonging–potential SSRI was associated versus lower QT-prolonging potential, we minimized the in- with a higher 1-year risk of sudden cardiac death in a cohort of fluence of bias due to confounding by indication because med- prevalent patients on hemodialysis. Data from our subgroup ications within the SSRI class have similar clinical indications analyses suggest that the SSRI QT-prolonging potential–sudden and therapeutic roles.30,58 Furthermore, the comparison of cardiac death association may be more potent among individuals

620 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 611–623, 2019 www.jasn.org CLINICAL EPIDEMIOLOGY with established risk factors for drug-induced QT prolongation. Supplemental Table 8. Association between the initiation of a When prescribing SSRIs to hemodialysis patients, providers higher versus lower QT-prolonging–potential SSRI and the 1-year should consider the QT-prolonging potential of these agents. risk of sudden cardiac death within clinically relevant subgroups. Supplemental Table 9. Association between the initiation of individual higher QT-prolonging–potential SSRIs versus lower QT-prolonging– ACKNOWLEDGMENTS potential SSRIs and the 1-year risk of sudden cardiac death. Supplemental Table 10. Association between the initiation of a – J.E.F. is supported by grant K23 DK109401 awarded by the National higher versus lower QT-prolonging potential SSRI and the 1-year InstituteofDiabetesand DigestiveandKidney Diseasesofthe National risk of sudden cardiac death when longer grace periods were used to fi Institutes of Health. de ne SSRI discontinuation. Aspects of this study were presented in an oral abstract at the 2018 Supplemental Table 11. Association between the initiation of a – AmericanSocietyofNephrologyKidneyWeekmeetinginSanDiego,CA. higher versus lower QT-prolonging potential SSRI and the risk of The data reported here have been provided by the US Renal Data sudden cardiac death considering all possible follow-up time. System. The interpretation and reporting of these data are the re- Supplemental Table 12. Association between the initiation of a higher – sponsibility of the authors and in no way should be seen as official versus lower QT-prolonging potential SSRI and the 1-year risk of policy or interpretation of the United States government. sudden cardiac death using an intent-to-treat analytic approach. Research ideaand studydesign:M.M.A. and J.E.F.;data acquisition: Supplemental Table 13. Association between the initiation of an M.M.A., M.A.B., and J.E.F.; statistical analysis: M.M.A.; data in- SSRIwith higher versus lower QT-prolonging potential and the 1-year terpretation: M.M.A., M.A.B., and J.E.F.; and supervision: J.E.F. All risk of the negative control outcome. authors approved the final version of the manuscript.

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622 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 611–623, 2019 www.jasn.org CLINICAL EPIDEMIOLOGY

49. Kanjanauthai S, Kanluen T, Chareonthaitawee P: Citalopram induced 58. Lund JL, Richardson DB, Stürmer T: The active comparator, new user torsade de pointes, a rare life threatening side effect. Int J Cardiol 131: study design in pharmacoepidemiology: Historical foundations and e33–e34, 2008 contemporary application. Curr Epidemiol Rep 2: 221–228, 2015 50. Van Asbroeck PJ, Huybrechts W, De Soir R: Case report, aetiology, 59. Bleyer AJ, Hartman J, Brannon PC, Reeves-Daniel A, Satko SG, Russell and treatment of an acquired long-QT syndrome. Acta Clin Belg 69: G: Characteristics of sudden death in hemodialysis patients. Kidney Int 132–134, 2014 69: 2268–2273, 2006 51. Medsafe the New Zealand Medicines and Medical Devices Safety 60. Pun PH, Herzog CA, Middleton JP: Improving ascertainment of sudden Authority: Reminder: Citalopram and QT prolongation. 2015. Available cardiac death in patients with end stage renal disease. Clin J Am Soc at: https://medsafe.govt.nz/profs/PUArticles/Sep2015/Citalopram& Nephrol 7: 116–122, 2012 QTReminder.htm. Accessed September 27, 2018 61. Rothman KJ, Greenland S, Lash TL: Modern Epidemiology, 3rd Ed., 52. Nagler EV, Webster AC, Vanholder R, Zoccali C: Antidepressants for edited by Rothman KJ, Greenland S, Lash TL, Philadelphia, Wolters depression in stage 3-5 chronic kidney disease: A systematic review Kluwer Health/Lippincott Williams & Wilkins, 2008, pp 142–143 of pharmacokinetics, efficacy and safety with recommendations by 62. CelexaÒ (citalopram hydrobromide) [package insert], Irvine, CA, Allergan European Renal Best Practice (ERBP). Nephrol Dial Transplant 27: USA Inc., 2017 3736–3745, 2012 63. LexaproÒ (escitalopram oxalate) [package insert], Irvine, CA, Allergan 53. Nattel S, Maguy A, Le Bouter S, Yeh YH: Arrhythmogenic ion-channel USA Inc., 2017 remodeling in the heart: Heart failure, myocardial infarction, and atrial 64. ProzacÒ (fluoxetine hydrochloride) [package insert], Indianapolis, IN, fibrillation. Physiol Rev 87: 425–456, 2007 Lilly USA LLC, 2017 54. Varró A, Baczkó I: Cardiac ventricular repolarization reserve: A principle 65. Fluvoxamine maleate [package insert], Baudette, MN, ANI Pharma- for understanding drug-related proarrhythmic risk. Br J Pharmacol 164: ceuticals Inc., 2017 14–36, 2011 66. PaxilÒ (paroxetine hydrochloride) [package insert], Research Triangle 55. Gussak I, Gussak HM: Sudden cardiac death in nephrology: Focus on Park, NC, GlaxoSmithKline, 2017 acquired long QT syndrome. Nephrol Dial Transplant 22: 12–14, 2007 67. ZoloftÒ (sertraline hydrochloride) [package insert], New York, NY, 56. Genovesi S, Dossi C, Viganò MR, Galbiati E, Prolo F, Stella A, et al.: Pfizer, 2017 Electrolyte concentration during haemodialysis and QT interval pro- longation in uraemic patients. Europace 10: 771–777, 2008 57. Yang T, Roden DM: Extracellular potassium modulation of drug block of IKr. Implications for torsade de pointes and reverse use-dependence. See related editorial, “Piecing Together the Risk of Sudden Cardiac Death on Circulation 93: 407–411, 1996 Dialysis,” on pages 521–523.

J Am Soc Nephrol 30: 611–623, 2019 SSRI Cardiac Safety in Hemodialysis Patients 623 SUPPLEMENTAL MATERIAL TABLE OF CONTENTS SUPPLEMENTAL FIGURES ...... 2

Supplemental Figure 1. Illustration of SSRI discontinuation and switching events ...... 2 Supplemental Figure 2. Propensity score distribution of patients treated with higher and lower QT- prolonging-potential SSRIs...... 3 SUPPLEMENTAL TABLES ...... 4

Supplemental Table 1. Outcome definitions ...... 4 Supplemental Table 2. ICD-9 diagnosis, ICD-9 procedure and CPT procedure codes used to identify relevant baseline covariates ...... 5 Supplemental Table 3. List of non-SSRI QT prolonging medications ...... 6 Supplemental Table 4. HCPCS codes used to identify QT prolonging medications not billable to Medicare Part D ...... 7 Supplemental Table 5. List of cytochrome P450 inhibitors ...... 8 Supplemental Table 6. Full list of baseline characteristics among study patients initiating a higher and lower QT-prolonging-potential SSRI ...... 9 Supplemental Table 7. Association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of fatal cardiac outcomes ...... 13 Supplemental Table 8. Association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of sudden cardiac death within clinically relevant subgroups ...... 14 Supplemental Table 9. Association between the initiation of individual higher QT-prolonging-potential SSRIs versus lower QT-prolonging-potential SSRIs and the 1-year risk of sudden cardiac death ...... 16 Supplemental Table 10. Association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of the sudden cardiac death when longer grace periods were used to define SSRI discontinuation ...... 17 Supplemental Table 11. Association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the risk of sudden cardiac death considering all possible follow-up time ...... 18 Supplemental Table 12. Association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of the sudden cardiac death using an intent-to-treat analytic approach ...... 19 Supplemental Table 13. Association between the initiation of an SSRI with higher versus lower QT- prolonging potential and the 1-year risk of the negative control outcome ...... 20

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SUPPLEMENTAL FIGURES

Supplemental Figure 1. Illustration of SSRI discontinuation and switching events

Panel A. SSRI discontinuation

Panel B. SSRI switching

Patients were censored during study follow-up if they discontinued index SSRI therapy or if they switched from their index SSRI to a different generic product (i.e. from citalopram to sertraline). We defined the SSRI discontinuation date as the date when the index SSRI was exhausted for greater than 7-days (i.e. grace period) without a subsequent dispensing of the same SSRI (Panel A). We defined the SSRI switch date as the date of the first prescription fill for a non-index SSRI during follow-up (Panel B). Patients were only “at risk” for a switching event during times of continuous index medication use (i.e. prior to the end of the 7 day grace period).

Abbreviations: Rx, prescription; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Figure 2. Propensity score distribution of patients treated with higher and lower QT- prolonging-potential SSRIs

The black dashed line is the propensity score distribution for initiators of SSRIs with higher QT-prolonging potential SSRIs. The gray solid line represents the propensity score distribution for initiators of lower QT-prolonging-potential SSRIs. Higher QT- prolonging-potential SSRIs include citalopram and escitalopram. Lower QT-prolonging-potential SSRIs include fluoxetine, fluvoxamine, paroxetine, and sertraline.

Abbreviations: SSRI, selective serotonin reuptake inhibitor.

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SUPPLEMENTAL TABLES

Supplemental Table 1. Outcome definitions

Primary study outcome Outcome Specification

Sudden cardiac death27 Death with a cardiac arrhythmia or cardiac arrest cause of death code (28, 29) listed as the primary cause on the ESRD Death Notification Form.

Alternative study outcomes considered in sensitivity analyses Outcome Specification

Composite outcome of sudden Death with a cardiac arrhythmia or cardiac arrest cause of death code cardiac death or hospitalized (28, 29) listed as the primary cause on the ESRD Death Notification ventricular arrythmia Form.

or

An inpatient hospitalizationa for ventricular arrythmia (ICD-9 codes 427.1 or 427.4 in the primary position).

Cardiovascular mortality27 Death with any cardiovascular cause death codeb (23, 25, 26, 27, 28, 29, 30, 31, 32, 35 or 36) listed as the primary cause on the ESRD Death Notification Form.

Alternative study outcomes considered in sensitivity analyses

Outcome Specification

Non-sudden cardiac death Death with a non-sudden cardiac death code (all codes except 28 and 29) listed as the primary cause on the ESRD Death Notification Form.

a Inpatient hospitalizations were identified using Medicare Part A claims (i.e. institutional claims). Specified four-digit ICD-9 diagnosis codes included all existing 5th digit diagnosis codes.

b The cardiovascular cause of death codes include the following clinical conditions: acute myocardial infarction, pericarditis (including cardiac tamponade), atherosclerotic heart disease, cardiomyopathy, cardiac arrhythmia, cardiac arrest (cause unknown), valvular heart disease, pulmonary edema due to exogenous fluid, congestive heart failure, pulmonary embolus, and cerebrovascular accident (including intracranial hemorrhage).

Abbreviations: ESRD, end-stage renal disease; ICD-9, International Classification of Diseases, Ninth Revision.

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Supplemental Table 2. ICD-9 diagnosis, ICD-9 procedure and CPT procedure codes used to identify relevant baseline covariates

Baseline comorbidities Comorbid condition ICD-9 diagnosis code(s)a Depression 296.2, 296.3, 296.5, 300.4, 309.0, 309.1, 309.28, 311 Anxiety 300.0 Bipolar disorder 296.0, 296.4–296.8 Schizophrenia 295 Delusional disorders 297 Personality disorders 301 Dementia 331.0-331.2, 331.7, 290.0-290.4, 294.0-294.2, 294.8, 797 Arrythmia 427 Conduction disorder 426 Dyslipidemia 272.0–272.2, 272.4 Heart failure 398.91, 402.x1, 404.x1, 404.x3, 428 Hypertension 401–405 Ischemic heart disease 410–414

Peripheral arterial disease 249.9, 250.7, 440.2, 440.3, 440.4, 440.8, 440.9, 443.1, 443.22, 443.81, 443.89, 443.9, 444.22, 444.81, 445.02

Stroke 430–438 Valvular disease 394–397 Cancer 140–209 COPD or asthma 491–494, 496 Chronic liver disease 571 Diabetes 250 Diabetic neuropathy 250.6

GI bleed 531.0, 531.2, 531.4, 531.6, 532.0, 532.2, 532.4, 532.6, 533.0, 533.2, 533.4, 533.6, 534.0, 534.2, 534.4, 534.6, 562.02, 562.03, 562.12, 562.13, 569.3, 569.85, 578.0, 578.1, 578.9

Hypothyroidism 243, 244 History of alcohol abuse 303, 305.0 History of cocaine abuse 304.2, 305.6 Tobacco use 305.1 History of non-compliance V15.81, V45.12 Cardiac pacemaker V45.01 Baseline procedures Procedure ICD-9 procedure code(s)b or CPT procedure code(s) Cardiac surgery ICD-9 procedure codes: 35, 36, 37 Electrocardiogram CPT procedure codes: 93000, 93005, 93010, 93040, 93041, 93042

CPT procedure codes: 90785, 90804–90819, 90821–90824, 90826–90829, 90832– Psychotherapy 90834, 90836–90844, 90846–90847, 90849, 90853, 90855, 90857, 90863

a Specified three-digit ICD-9 diagnosis code categories included all existing 4th and 5th digit diagnosis codes and specified four- digit ICD-9 diagnosis code categories included all existing 5th digit diagnosis codes. b Specified two-digit ICD-9 procedure code categories included all existing 3rd and 4th digit procedure codes.

Abbreviations: COPD, chronic obstructive pulmonary disease; CPT, Current Procedural Terminology; GI, gastrointestinal; ICD-9, International Classification of Diseases, Ninth Revision. 5

Supplemental Table 3. List of non-SSRI QT prolonging medications

Known risk of torsades de pointesa

Amiodarone, anagrelide, arsenic trioxide, astemizole, azithromycin, bepridil, chloroquine chlorpromazine, cilostazol, ciprofloxacin, clarithromycin, cocaine, disopyramide, dofetilide, donepezil, dronedarone, droperidol, erythromycin, flecainide, fluconazole, gatifloxacin, grepafloxacin, haloperidol, ibutilide, levofloxacin, levomethadyl, mesoridazine, methadone, moxifloxacin, ondansetron, oxaliplatin, papaverine, pentamidine, pimozide, probucol, procainamide, propofol, quinidine, sevoflurane, sotalol, sparfloxacin, terfenadine, thioridazine and vandetanib

Conditional risk of torsades de pointesb

Amantadine, amitriptyline, amphotericin B, atazanavir, chloral hydrate, cimetidine, diphenhydramine, doxepin, esomeprazole, famotidine, furosemide, galantamine, hydrochlorothiazide, hydroxychloroquine, hydroxyzine, indapamide, itraconazole, ivabradine, ketoconazole, lansoprazole, loperamide, metoclopramide, metolazone, metronidazole, nelfinavir, olanzapine, omeprazole, pantoprazole, piperacillin/tazobactam, posaconazole, propafenone, quetiapine, quinine sulfate, ranolazine, solifenacin, telaprevir, torsemide, trazodone, voriconazole and ziprasidone

Possible risk of torsades de pointesc

Alfuzosin, apomorphine, aripiprazole, asenapine, atomoxetine, bedaquiline, bendamustine, betrixaban, bortezomib, bosutinib, buprenorphine, cabozantinib, capecitabine, ceritinib, clomipramine, clozapine, crizotinib, dabrafenib, dasatinib, degarelix, delamanid, desipramine, deutetrabenazine, dexmedetomidine, dolasetron, efavirenz, eliglustat, epirubicin, eribulin, ezogabine, retigabine, felbamate, fingolimod, fluorouracil, gemifloxacin, granisetron, hydrocodone (extended release formulations), iloperidone, imipramine, melipramine, inotuzumab, isradipine, lapatinib, lenvatinib, leuprolide, lithium, lopinavir/ritonavir, maprotiline, memantine, midostaurin, mifepristone, mirabegron, mirtazapine, moexipril/hctz, necitumumab, nicardipine, nilotinib, norfloxacin, nortriptyline, nusinersen, ofloxacin, osimertinib, oxytocin, paliperidone, palonosetron, panobinostat, pasireotide, pazopanib, perflutren, perphenazine, pimavanserin, primaquine, promethazine, ribociclib, rilpivirine, risperidone, romidepsin, saquinavir, sorafenib, sunitinib, tacrolimus, tamoxifen, telavancin, telithromycin, tetrabenazine, tipiracil/trifluridine, tizanidine, tolterodine, toremifene, tramadol, trimipramine, valbenazine, vardenafil, vemurafenib, venlafaxine, vorinostat

Medication lists were obtained from the CredibleMeds® website (www.Crediblemeds.org) on September 27, 2018.

a According to the CredibleMeds® website, medications with a known risk of torsades de pointes are defined as drugs that prolong the QT interval and are clearly associated with a known risk of torsades de pointes, even when taken as recommended.26

b According to the CredibleMeds® website, medications with a conditional risk of torsades de pointes are defined as drugs are associated with torsades de pointes only under certain conditions (e.g. excessive dose, in patients with conditions such as hypokalemia, or when taken with interacting drugs) or medications that create conditions that facilitate or induce torsades de pointes (e.g. cause an electrolyte disturbance that induces torsades de pointes).26

c According to the CredibleMeds® website, medications with a possible risk of torsades de pointes are defined as drugs that can cause QT prolongation but currently lack evidence for a risk of torsades de pointes when taken as recommended.26

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Supplemental Table 4. HCPCS codes used to identify QT prolonging medications not billable to Medicare Part D

Known risk of Torsades de pointesa Medication HCPCS code(s) Arsenic trioxide J9017 Droperidol J1790, J1810 Ibutilide J1742 Oxaliplatin J9263 Papaverine J2440 Pentamidine J2545, J7676 Procainamide J2690 Propofol J2704 Conditional risk of Torsades de pointesb Medication HCPCS code(s) Amphotericin B J0285, J0287, J0288, J0289 Piperacillin/tazobactam J2543 Possible risk of Torsades de pointesc Medication HCPCS code(s) Bendamustine J9033, J9034 Bortezomib J9041 Degarelix J9155 Epirubicin J9178 Eribulin J9179 Fluorouracil J9190 Inotuzumab FDA approved after the study period Leuprolide J1950, J9217, J9218, J9219 Necitumumab J9295 Nusinersen J2326 Oxytocin J2590 Palonosetron J2469, J8655 Pasireotide J2502 Perflutren Q9957 Romidepsin J9315 Telavancin J3095

HCPCS codes used to identify QT prolonging medications not billable to Medicare Part D were identified in Medicare Part A and B claims (i.e. institutional and physician/supplier claims). a According to the CredibleMeds® website, medications with a known risk of torsades de pointes are defined as drugs that prolong the QT interval and are clearly associated with a known risk of torsades de pointes, even when taken as recommended.26 b According to the CredibleMeds® website, medications with a conditional risk of torsades de pointes are defined as drugs are associated with torsades de pointes only under certain conditions (e.g. excessive dose, in patients with conditions such as hypokalemia, or when taken with interacting drugs) or medications that create conditions that facilitate or induce torsades de pointes (e.g. cause an electrolyte disturbance that induces torsades de pointes).26 c According to the CredibleMeds® website, medications with a possible risk of torsades de pointes are defined as drugs that can cause QT prolongation but currently lack evidence for a risk of torsades de pointes when taken as recommended.26

Abbreviations: FDA, Food and Drug Administration; HCPCS, Healthcare Common Procedure Coding System.

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Supplemental Table 5. List of cytochrome P450 inhibitors

Inhibitors of cytochrome P450 1A2

Amiodarone, cimetidine, ciprofloxacin, efavirenz, interferon alpha, methoxsalen, ticlopidine

Inhibitors of cytochrome P450 3A4

Amiodarone, aprepitant, buprenorphine, chloramphenicol, cimetidine, ciprofloxacin, clarithromycin, delavirdine, diethyldithiocarbamate, diltiazem, erythromycin, fluconazole, gestodene, imatinib, indinavir, itraconazole, ketoconazole, mifepristone, nefazodone, nelfinavir, norfloxacin, ritonavir, saquinavir, telaprevir, telithromycin, verapamil, voriconazole

Inhibitors of cytochrome P450 2C9

Amiodarone, efavirenz, fenofibrate, fluconazole, fluvastatin, isoniazid, lovastatin, metronidazole,

phenylbutazone, probenecid, sulfamethoxazole, sulfaphenazole, teniposide, voriconazole, zafirlukast

Inhibitors of cytochrome P450 2C19

Chloramphenicol, cimetidine, esomeprazole, felbamate, indomethacin, isoniazid, ketoconazole, lansoprazole, modafinil, omeprazole, oral contraceptives, oxcarbazepine, pantoprazole, probenecid, ticlopidine, topiramate, voriconazole Inhibitors of cytochrome P450 2D6

Amiodarone, bupropion, celecoxib, chlorpheniramine, chlorpromazine, cimetidine, cinacalcet, clemastine, clomipramine, diphenhydramine, doxepin, doxorubicin, duloxetine, haloperidol, hydroxyzine, methadone, metoclopramide, midodrine, moclobemide, perphenazine, promethazine, quinidine, ranitidine, ritonavir, terbinafine, ticlopidine, tripelennamine

List of medications that can inhibit the metabolism of SSRIs via cytochrome P450 isoenzyme interactions were obtained from the Flockhart Table™ website (https://drug-interactions.medicine.iu.edu/Main-Table.aspx) on September 27, 2018.29 Citalopram and escitalopram are major substrates of cytochrome P450 3A4 and 2C19. Fluoxetine is a major substrate of cytochrome P450 2C9 and 2D6. Fluvoxamine is a major substrate of cytochrome P450 1A2 and 2D6. Paroxetine is a major substrate of cytochrome P450 2D6.

Abbreviations: SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 6. Full list of baseline characteristics among study patients initiating a higher and lower QT-prolonging-potential SSRI

Unweighted Weighted

SSRI with higher QT- SSRI with lower QT- SSRI with higher QT- SSRI with lower QT- Std diffa Std diffa Characteristic prolonging potential prolonging potential prolonging potential prolonging potential (%) (%) n = 30,932 n = 34,722 n = 30,927 n = 34,730

Age (years) 67.6 ± 17.2 66.5 ± 17.2 6.2 67.0 ± 17.2 67.0 ± 17.21 0.0 Female 16,512 (53.4%) 18,121 (52.2%) 2.3 16,316 (52.8%) 18,324 (52.8%) 0.0 Race Black 11,339 (36.7%) 11,959 (34.4%) 6.3 10,967 (35.5%) 12,320 (35.5%) 0.0 White 18,434 (59.6%) 21,005 (60.5%) 1.5 18,589 (60.1%) 20,870 (60.1%) 0.0 Other 1,159 (3.7%) 1,758 (5.1%) 33.5 1,371 (4.4%) 1,540 (4.4%) 0.0 Hispanic 5,233 (16.9%) 7,346 (21.2%) 22.7 5,933 (19.2%) 6,654 (19.2%) 0.1 Year index SSRI was filled 2007 3,961 (12.8%) 4,751 (13.7%) 6.9 4,086 (13.2%) 4,594 (13.2%) 0.1 2008 4,095 (13.2%) 4,388 (12.6%) 4.8 3,977 (12.9%) 4,468 (12.9%) 0.0 2009 4,061 (13.1%) 4,343 (12.5%) 5.0 3,948 (12.8%) 4,435 (12.8%) 0.1 2010 4,139 (13.4%) 4,161 (12.0%) 11.5 3,907 (12.6%) 4,386 (12.6%) 0.0 2011 4,034 (13.0%) 4,061 (11.7%) 11.3 3,814 (12.3%) 4,287 (12.3%) 0.1 2012 3,611 (11.7%) 4,152 (12.0%) 2.5 3,670 (11.9%) 4,118 (11.9%) 0.1 2013 3,507 (11.3%) 4,398 (12.7%) 11.5 3,738 (12.1%) 4,194 (12.1%) 0.1 2014 3,524 (11.4%) 4,468 (12.9%) 12.7 3,787 (12.2%) 4,246 (12.2%) 0.2 Low-dose index SSRIb 27,935 (90.3%) 31,560 (90.9%) 0.6 28,011 (90.6%) 31,456 (90.6%) 0.0 Cause of ESRD Diabetes 15,563 (50.3%) 17,416 (50.2%) 0.3 15,542 (50.3%) 17,458 (50.3%) 0.0 Hypertension 7,941 (25.7%) 8,760 (25.2%) 1.8 7,848 (25.4%) 8,813 (25.4%) 0.0 Glomerular disease 3,359 (10.9%) 3,934 (11.3%) 4.4 3,442 (11.1%) 3,864 (11.1%) 0.1 Other 4,069 (13.2%) 4,612 (13.3%) 1.0 4,095 (13.2%) 4,596 (13.2%) 0.1 Dialysis vintage 0.7 – 0.9 years 5,467 (17.7%) 5,903 (17.0%) 4.0 5,364 (17.3%) 6,023 (17.3%) 0.0 1.0 – 1.9 years 5,965 (19.3%) 6,622 (19.1%) 1.1 5,933 (19.2%) 6,661 (19.2%) 0.0 2.0 – 2.9 years 4,631 (15.0%) 5,136 (14.8%) 1.3 4,594 (14.9%) 5,162 (14.9%) 0.1 ≥ 3 years 14,869 (48.1%) 17,061 (49.1%) 2.2 15,035 (48.6%) 16,883 (48.6%) 0.0 History of a failed kidney 2,029 (6.6%) 2,377 (6.8%) 4.6 2,083 (6.7%) 2,336 (6.7%) 0.1 transplant 9

Medicare Part D low income 24,601 (79.5%) 27,694 (79.8%) 0.3 24,620 (79.6%) 27,653 (79.6%) 0.0 subsidy Depression 10,960 (35.4%) 10,851 (31.3%) 12.7 10,298 (33.3%) 11,567 (33.3%) 0.0 Anxiety 5,590 (18.1%) 6,046 (17.4%) 3.8 5,492 (17.8%) 6,169 (17.8%) 0.0 Bipolar disorder 810 (2.6%) 741 (2.1%) 26.6 734 (2.4%) 825 (2.4%) 0.2 Other mental health disordersc 872 (2.8%) 794 (2.3%) 26.5 786 (2.5%) 884 (2.5%) 0.2 Dementia 3,978 (12.9%) 3,174 (9.1%) 34.9 3,380 (10.9%) 3,800 (10.9%) 0.1 Arrythmia 9,616 (31.1%) 10,135 (29.2%) 6.4 9,327 (30.2%) 10,471 (30.1%) 0.0 Conduction disorder 2,434 (7.9%) 2,659 (7.7%) 2.9 2,403 (7.8%) 2,699 (7.8%) 0.0 Dyslipidemia 15,756 (50.9%) 17,566 (50.6%) 0.7 15,723 (50.8%) 17,652 (50.8%) 0.0 Heart failure 14,937 (48.3%) 15,884 (45.7%) 5.5 14,536 (47.0%) 16,321 (47.0%) 0.0 Hypertension 28,289 (91.5%) 31,297 (90.1%) 1.5 28,073 (90.8%) 31,522 (90.8%) 0.0 Ischemic heart disease 15,171 (49.0%) 16,216 (46.7%) 4.9 14,810 (47.9%) 16,624 (47.9%) 0.0 Peripheral arterial disease 11,332 (36.6%) 11,737 (33.8%) 8.2 10,878 (35.2%) 12,216 (35.2%) 0.0 Stroke 8,225 (26.6%) 8,033 (23.1%) 14.2 7,668 (24.8%) 8,615 (24.8%) 0.0 Valvular disease 2,112 (6.8%) 2,165 (6.2%) 9.8 2,023 (6.5%) 2,273 (6.5%) 0.1 Cancer 2,671 (8.6%) 2,763 (8.0%) 8.7 2,564 (8.3%) 2,881 (8.3%) 0.1 COPD or asthma 9,384 (30.3%) 9,980 (28.7%) 5.5 9,134 (29.5%) 10,255 (29.5%) 0.0 Chronic liver disease 1,385 (4.5%) 1,577 (4.5%) 1.6 1,400 (4.5%) 1,570 (4.5%) 0.1 Diabetes 21,520 (69.6%) 23,690 (68.2%) 2.0 21,305 (68.9%) 23,927 (68.9%) 0.0 Diabetic neuropathy 7,718 (25.0%) 8,352 (24.1%) 3.7 7,584 (24.5%) 8,523 (24.5%) 0.1 GI bleed 3,586 (11.6%) 3,582 (10.3%) 12.2 3,378 (10.9%) 3,793 (10.9%) 0.0 Hypothyroidism 5,567 (18.0%) 5,960 (17.2%) 4.9 5,440 (17.6%) 6,110 (17.6%) 0.0 History of alcohol abuse 785 (2.5%) 795 (2.3%) 13.4 745 (2.4%) 835 (2.4%) 0.2 History of cocaine abuse 529 (1.7%) 554 (1.6%) 11.0 510 (1.6%) 572 (1.6%) 0.0 Tobacco use 4,327 (14.0%) 4,829 (13.9%) 0.6 4,321 (14.0%) 4,857 (14.0%) 0.1 History of non-compliance 3,501 (11.3%) 4,072 (11.7%) 3.7 3,575 (11.6%) 4,013 (11.6%) 0.0 Had a cardiac pacemaker 1,431 (4.6%) 1,463 (4.2%) 10.6 1,361 (4.4%) 1,529 (4.4%) 0.0 Had cardiac surgery during the 588 (1.9%) 614 (1.8%) 10.7 565 (1.8%) 635 (1.8%) 0.1 last 30 days of baseline Had an ECG during the last 30 9,908 (32.0%) 10,796 (31.1%) 3.0 9,777 (31.6%) 10,974 (31.6%) 0.1 days of baseline Alpha-blocker 240 (0.8%) 285 (0.8%) 11.2 249 (0.8%) 280 (0.8%) 0.0 10

ACE inhibitor 5,749 (18.6%) 6,542 (18.8%) 1.4 5,801 (18.8%) 6,509 (18.7%) 0.1 ARB 3,018 (9.8%) 3,530 (10.2%) 4.3 3,082 (10.0%) 3,462 (10.0%) 0.0 Beta blocker 11,442 (37.0%) 13,114 (37.8%) 2.1 11,562 (37.4%) 12,981 (37.4%) 0.0 Calcium channel blocker 8,768 (28.3%) 10,385 (29.9%) 5.5 9,031 (29.2%) 10,141 (29.2%) 0.0 Central alpha agonist 3,906 (12.6%) 4,413 (12.7%) 0.7 3,913 (12.7%) 4,394 (12.7%) 0.0 Diuretic 2,903 (9.4%) 3,565 (10.3%) 9.5 3,048 (9.9%) 3,420 (9.8%) 0.1 Vasodilator 3,292 (10.6%) 3,837 (11.1%) 3.9 3,364 (10.9%) 3,779 (10.9%) 0.0 Anticoagulant 2,279 (7.4%) 2,450 (7.1%) 4.7 2,233 (7.2%) 2,506 (7.2%) 0.1 Antiplatelet agent 3,520 (11.4%) 3,980 (11.5%) 0.8 3,530 (11.4%) 3,964 (11.4%) 0.0 Digoxin 515 (1.7%) 596 (1.7%) 4.8 529 (1.7%) 592 (1.7%) 0.5 Nitrate 1,987 (6.4%) 2,299 (6.6%) 3.3 2,016 (6.5%) 2,264 (6.5%) 0.0 Statin 7,492 (24.2%) 8,885 (25.6%) 5.6 7,721 (25.0%) 8,671 (25.0%) 0.0 Other cholesterol medicationd 1,244 (4.0%) 1,429 (4.1%) 2.7 1,260 (4.1%) 1,414 (4.1%) 0.0 Midodrine 732 (2.4%) 874 (2.5%) 8.0 754 (2.4%) 848 (2.4%) 0.2 Use of ≥ 1 medication with a 2,919 (9.4%) 3,210 (9.2%) 2.2 2,891 (9.3%) 3,244 (9.3%) 0.1 known risk of TdPe Use of ≥ 1 medication with a 12,634 (40.8%) 14,238 (41.0%) 0.4 12,675 (41.0%) 14,231 (41.0%) 0.0 conditional risk of TdPe Use of ≥ 1 medication with a 3,228 (10.4%) 3,123 (9.0%) 15.6 3,001 (9.7%) 3,375 (9.7%) 0.1 possible risk of TdPe Use of ≥ 1 CYP 1A2 inhibitorf 1,154 (3.7%) 1,290 (3.7%) 0.5 1,155 (3.7%) 1,296 (3.7%) 0.1 Use of ≥ 1 CYP 3A4 inhibitorf 2,419 (7.8%) 2,770 (8.0%) 2.1 2,450 (7.9%) 2,746 (7.9%) 0.2 Use of ≥ 1 CYP 2C9 inhibitorf 2,074 (6.7%) 2,385 (6.9%) 2.6 2,104 (6.8%) 2,360 (6.8%) 0.1 Use of ≥ 1 CYP 2C19 inhibitorf 8,119 (26.2%) 9,022 (26.0%) 1.0 8,095 (26.2%) 9,087 (26.2%) 0.0 Use of ≥ 1 CYP 2D6 inhibitorf 8,777 (28.4%) 9,999 (28.8%) 1.5 8,845 (28.6%) 9,931 (28.6%) 0.0 Hospitalized during the last 30 8,701 (28.1%) 8,749 (25.2%) 11.2 8,248 (26.7%) 9,264 (26.7%) 0.0 days of the baseline period Number of hospital admissions during the baseline period 0 11,219 (36.3%) 14,063 (40.5%) 11.2 11,890 (38.4%) 13,354 (38.5%) 0.0 1 – 2 13,223 (42.7%) 14,199 (40.9%) 4.5 12,916 (41.8%) 14,499 (41.7%) 0.0 3 – 4 4,704 (15.2%) 4,651 (13.4%) 13.1 4,421 (14.3%) 4,965 (14.3%) 0.0 ≥ 5 1,786 (5.8%) 1,809 (5.2%) 11.3 1,700 (5.5%) 1,911 (5.5%) 0.1 11

Number of ED visits during the

baseline period 0 7,621 (24.6%) 9,625 (27.7%) 12.0 8,113 (26.2%) 9,114 (26.2%) 0.0 1 – 2 11,966 (38.7%) 13,336 (38.4%) 0.7 11,918 (38.5%) 13,379 (38.5%) 0.0 3 – 4 6,135 (19.8%) 6,436 (18.5%) 6.9 5,924 (19.2%) 6,651 (19.2%) 0.0 ≥ 5 5,210 (16.8%) 5,325 (15.3%) 9.7 4,973 (16.1%) 5,585 (16.1%) 0.0 Had ≥ 1 psychotherapy visit 3,314 (10.7%) 2,738 (7.9%) 31.8 2,859 (9.2%) 3,211 (9.2%) 0.0 during the baseline period Had ≥ 1 skilled nursing facility admission during the baseline 7,947 (25.7%) 6,566 (18.9%) 30.7 6,853 (22.2%) 7,701 (22.2%) 0.1 period Values are given as number (percent) for categorical variables and as mean ± standard deviation for continuous variables. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower QT-prolonging-potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. All-covariates were measured during the 180-day baseline period prior to SSRI initiation. The weighted cohort is the pseudo-population generated by inverse probability of treatment weighting. a A std diff > 10.0% represents meaningful imbalance between groups.33 b The definition of low-dose was based on the dosing recommendations found in each SSRI’s package insert.62-67 Low doses: citalopram ≤ 20 mg/day; escitalopram ≤ 10 mg/day; fluoxetine ≤ 20 mg per day; immediate release fluvoxamine ≤ 50 mg/day; controlled release fluvoxamine ≤ 100 mg/day; immediate release paroxetine ≤ 20 mg/day; controlled release paroxetine ≤ 25 mg/day; and sertraline 50 mg/day. c Other mental health disorders included schizophrenia, delusional disorders, and personality disorders. d Other cholesterol medications (i.e. non-statin cholesterol medications) included bile acid sequestrants, cholesterol absorption inhibitors, fibrates, and niacin. e Lists medications with known, conditional, and possible risks of TdP are presented in Supplemental Table 3. f Lists of medications that are relevant CYP 1A2, 3A4, 2C9, 2C19, and 2D6 inhibitors provided in Supplemental Table 4.

Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; COPD, chronic obstructive pulmonary disease; CYP, cytochrome P450; ED, emergency department; ECG, electrocardiogram; ESRD, end-stage renal disease; GI, gastrointestinal; SSRI, selective serotonin reuptake inhibitor; std diff, standardized differences; TdP, torsades de pointes.

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Supplemental Table 7. Association between the initiation of a higher versus lower QT-prolonging- potential SSRI and the 1-year risk of fatal cardiac outcomes

Sudden cardiac death – primary outcome No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 601 68.5 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 702 89.3 1.30 (1.16, 1.45) 1.18 (1.05, 1.31) Composite of sudden cardiac death or hospitalized ventricular arrythmia – alternative outcome No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 635 72.4 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 742 94.5 1.30 (1.17, 1.44) 1.18 (1.06, 1.31) Cardiovascular mortality – alternative outcome No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 912 103.9 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 1,002 127.5 1.22 (1.12, 1.34) 1.11 (1.02, 1.22)

An on-treatment analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the initiation of higher versus lower QT-prolonging-potential SSRIs and the 1-year risk of fatal cardiac outcomes. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower QT-prolonging potential-SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 8. Association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of sudden cardiac death within clinically relevant subgroups

Age subgroups

Age ≥ 65 years Age < 65 years

No. of Rate per Unadjusted Adjusted No. of Rate per Unadjusted Adjusted SSRI n n events 1,000 p-y HR (95% CI) HR (95% CI) events 1,000 p-y HR (95% CI) HR (95% CI)

1.00 1.00 1.00 Lower QT-prolonging-potential 19,631 446 85.0 15,091 161 43.9 1.00 (ref.) (ref.) (ref.) (ref.)

1.29 1.19 1.24 1.13 Higher QT-prolonging-potential 18,259 541 110.1 12,673 155 54.7 (1.13, 1.46) (1.05, 1.35) (1.00, 1.56) (0.90, 1.41)

Sex subgroups

Female Male

No. of Rate per Unadjusted Adjusted No. of Rate per Unadjusted Adjusted SSRI n n events 1,000 p-y HR (95% CI) HR (95% CI) events 1,000 p-y HR (95% CI) HR (95% CI)

1.00 1.00 1.00 1.00 Lower QT-prolonging-potential 18,121 280 61.6 16,601 321 75.9 (ref.) (ref.) (ref.) (ref.)

1.38 1.23 1.23 1.12 Higher QT-prolonging-potential 16,512 356 85.7 14,420 346 93.4 (1.18, 1.62) (1.06, 1.44) (1.05, 1.43) (0.96, 1.31)

Conduction disorder subgroups

(+) Conduction disorder (-) Conduction disorder

No. of Rate per Unadjusted Adjusted No. of Rate per Unadjusted Adjusted SSRI n n events 1,000 p-y HR (95% CI) HR (95% CI) events 1,000 p-y HR (95% CI) HR (95% CI)

1.00 1.00 1.00 1.00 Lower QT-prolonging-potential 2,659 54 84.4 32,063 547 67.2 (ref.) (ref.) (ref.) (ref.)

1.64 1.47 1.26 1.14 Higher QT-prolonging-potential 2,434 83 138.5 28,498 619 85.3 (1.16, 2.30) (1.05, 2.06) (1.12, 1.42) (1.02, 1.28)

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Heart failure subgroups

(+) Heart failure (-) Heart failure

No. of Rate per Unadjusted Adjusted No. of Rate per Unadjusted Adjusted SSRI n n events 1,000 p-y HR (95% CI) HR (95% CI) events 1,000 p-y HR (95% CI) HR (95% CI) 1.00 1.00 1.00 1.00 Lower QT-prolonging-potential 15,884 413 105.6 18,838 188 38.7 (ref.) (ref.) (ref.) (ref.)

1.24 1.16 1.34 1.21 Higher QT-prolonging-potential 14,937 484 131.8 15,995 218 52.1 (1.09, 1.42) (1.02, 1.32) (1.20, 1.63) (1.00, 1.48)

Liver disease subgroups

(+) Liver disease (-) Liver disease

No. of Rate per Unadjusted Adjusted No. of Rate per Unadjusted Adjusted SSRI n n events 1,000 p-y HR (95% CI) HR (95% CI) events 1,000 p-y HR (95% CI) HR (95% CI) 1.00 1.00 1.00 1.00 Lower QT-prolonging-potential 1,577 31 87.8 33,145 570 67.7 (ref.) (ref.) (ref.) (ref.)

1.32 1.20 1.30 1.17 Higher QT-prolonging-potential 1,385 35 115.5 29,547 667 88.3 (0.82, 2.13) (0.74, 1.95) (1.16, 1.45) (1.05, 1.31)

Non-SSRI QT-prolonging medication subgroups

Use of ≥ 1 non-SSRI QT-prolonging medication Use of zero non-SSRI QT-prolonging medications

No. of Rate per Unadjusted Adjusted No. of Rate per Unadjusted Adjusted SSRI n n events 1,000 p-y HR (95% CI) HR (95% CI) events 1,000 p-y HR (95% CI) HR (95% CI) 1.00 1.00 1.00 1.00 Lower QT-prolonging-potential 16,478 286 62.7 18,244 315 74.8 (ref.) (ref.) (ref.) (ref.)

1.38 1.29 1.22 1.08 Higher QT-prolonging-potential 14,774 356 86.9 16,158 346 92.0 (1.18, 1.61) (1.10, 1.50) (1.05, 1.43) (0.93, 1.26)

An on-treatment analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of sudden cardiac death within clinically relevant subgroups. Higher QT-prolonging- potential SSRIs included citalopram and escitalopram. Lower QT-prolonging-potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 9. Association between the initiation of individual higher QT-prolonging-potential SSRIs versus lower QT-prolonging-potential SSRIs and the 1-year risk of sudden cardiac death

Citalopram versus SSRIs with lower QT prolonging potential No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 601 68.5 1.00 (ref.) 1.00 (ref.) Citalopram 16,288 366 85.6 1.25 (1.10, 1.42) 1.16 (1.02, 1.32) Escitalopram versus SSRIs with lower QT prolonging potential No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 601 68.5 1.00 (ref.) 1.00 (ref.) Escitalopram 14,644 336 93.8 1.36 (1.19, 1.55) 1.21 (1.05, 1.38)

An on-treatment analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate: 1) the association between the initiation of citalopram versus lower QT-prolonging-potential SSRIs and the 1- year risk of sudden cardiac death, and 2) the association between the initiation of escitalopram versus lower QT-prolonging- potential SSRIs and the 1-year risk of sudden cardiac death. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower QT-prolonging-potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 10. Association between the initiation of a higher versus lower QT-prolonging- potential SSRI and the 1-year risk of the sudden cardiac death when longer grace periods were used to define SSRI discontinuation

14-day grace period used to define discontinuation No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 746 71.8 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 845 90.6 1.26 (1.14, 1.39) 1.14 (1.03, 1.26) 30-day grace period grace period used to define discontinuation No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 966 73.9 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 1,083 92.6 1.25 (1.14, 1.36) 1.14 (1.04, 1.24)

An on-treatment analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of sudden cardiac death. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower QT-prolonging- potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 11. Association between the initiation of a higher versus lower QT-prolonging- potential SSRI and the risk of sudden cardiac death considering all possible follow-up time

Sudden cardiac death – primary outcome No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 688 65.4 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 791 84.3 1.28 (1.15, 1.42) 1.17 (1.05, 1.29)

An on-treatment analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the initiation of higher versus lower QT-prolonging-potential SSRIs and the 1-year risk of sudden cardiac death. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower-QT-prolonging potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 12. Association between the initiation of a higher versus lower QT-prolonging- potential SSRI and the 1-year risk of the sudden cardiac death using an intent-to-treat analytic approach

Intention-to-treat analysis No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 2,015 74.4 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 2,184 92.0 1.22 (1.15, 1.30) 1.13 (1.07, 1.20)

An intention-to-treat analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the initiation of a higher versus lower QT prolonging potential SSRI and the 1-year risk of sudden cardiac death. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower QT-prolonging- potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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Supplemental Table 13. Association between the initiation of an SSRI with higher versus lower QT- prolonging potential and the 1-year risk of the negative control outcome

Non-sudden cardiac death – negative control outcome No. of Rate per Unadjusted Adjusted SSRI n events 1,000 p-y HR (95% CI) HR (95% CI) Lower QT-prolonging-potential 34,722 1,519 173.1 1.00 (ref.) 1.00 (ref.) Higher QT-prolonging-potential 30,932 1,552 197.5 1.14 (1.06, 1.22) 1.01 (0.95, 1.09)

An on-treatment analytic approach was used in all analyses. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the initiation of a higher versus lower QT-prolonging-potential SSRI and the 1-year risk of the negative control outcome, non-sudden cardiac death. Higher QT-prolonging-potential SSRIs included citalopram and escitalopram. Lower QT-prolonging-potential SSRIs included fluoxetine, fluvoxamine, paroxetine, and sertraline. Adjusted analyses controlled for baseline covariates listed in Supplemental Table 6 using inverse probability of treatment weighting.

Abbreviations: CI, confidence interval; HR, hazard ratio; ref., referent; No., number; p-y, person-years; SSRI, selective serotonin reuptake inhibitor.

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