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. Author manuscript; available in PMC: 2023 Jul 7.
Published in final edited form as: J Affect Disord. 2022 Dec 15;324:102–113. doi: 10.1016/j.jad.2022.12.044

Comorbidity and healthcare utilization in patients with treatment resistant depression: A large-scale retrospective cohort analysis using electronic health records

Prakash Adekkanattu a,*, Mark Olfson b, Leah C Susser a, Braja Patra a, Veer Vekaria a, Brandon J Coombes c, Lauren Lepow d, Brian Fennessy d, Alexander Charney d, Euijung Ryu c, Kurt D Miller c, Lifang Pan b, Tenzin Yangchen b, Ardesheer Talati b, Priya Wickramaratne b, Myrna Weissman b, John Mann b, Joanna M Biernacka c, Jyotishman Pathak a
PMCID: PMC10327872  NIHMSID: NIHMS1890136  PMID: 36529406

Abstract

Background:

Medical comorbidity and healthcare utilization in patients with treatment resistant depression (TRD) is usually reported in convenience samples, making estimates unreliable. There is only limited large-scale clinical research on comorbidities and healthcare utilization in TRD patients.

Methods:

Electronic Health Record data from over 3.3 million patients from the INSIGHT Clinical Research Network in New York City was used to define TRD as initiation of a third antidepressant regimen in a 12-month period among patients diagnosed with major depressive disorder (MDD). Age and sex matched TRD and non-TRD MDD patients were compared for anxiety disorder, 27 comorbid medical conditions, and healthcare utilization.

Results:

Out of 30,218 individuals diagnosed with MDD, 15.2 % of patients met the criteria for TRD (n = 4605). Compared to MDD patients without TRD, the TRD patients had higher rates of anxiety disorder and physical comorbidities. They also had higher odds of ischemic heart disease (OR = 1.38), stroke/transient ischemic attack (OR = 1.57), chronic kidney diseases (OR = 1.53), arthritis (OR = 1.52), hip/pelvic fractures (OR = 2.14), and cancers (OR = 1.41). As compared to non-TRD MDD, TRD patients had higher rates of emergency room visits, and inpatient stays. In relation to patients without MDD, both TRD and non-TRD MDD patients had significantly higher levels of anxiety disorder and physical comorbidities.

Limitations:

The INSIGHT-CRN data lack information on depression severity and medication adherence.

Conclusions:

TRD patients compared to non-TRD MDD patients have a substantially higher prevalence of various psychiatric and medical comorbidities and higher health care utilization. These findings highlight the challenges of developing interventions and care coordination strategies to meet the complex clinical needs of TRD patients.

Keywords: Treatment resistant depression, Major depressive disorder, Medical comorbidities, Healthcare utilization, Electronic health records

1. Introduction

Depression is common worldwide. The World Health Organization (WHO) estimates that about 5 % of adults globally suffer from depression (WHO, 2021, n.d.). The COVID-19 pandemic has significantly increased the prevalence of depression (WHO, 2022, n.d.). Without treatment, depression is likely to become persistent, recurrent, and associated with increased disability (Andrews, 2001). There are often bidirectional associations between depression and physical health: persons with depression are at an increased risk for other chronic medical conditions (Momen et al., 2020), and similarly, individuals diagnosed with chronic medical conditions are at an increased risk for developing depression (Polsky et al., 2005). Medical conditions that are accompanied by a high symptom burden, such as migraine headaches or back pain, can lead to depression (McWilliams et al., 2004). Additionally, depression is associated with risk factors for poor physical health, including cigarette use (Weinberger et al., 2017), poor dental care (Park et al., 2014), and obesity (Luppino et al., 2010). Lastly, depression and chronic medical conditions share common pathways. Inflammation is implicated in the development of both depression and several medical conditions, including diabetes and cardiovascular disease (An et al., 2019; Osimo et al., 2019).

Comorbidity of depression and chronic medical diseases contributes to decreased quality of life, increased healthcare utilization, and premature death (Lichtman et al., 2014; Papaioannou et al., 2013; Park et al., 2013; Zhu et al., 2017). Medical comorbidity accounts for the largest portion of the economic burden of depression (Greenberg et al., 2015). While these factors highlight the importance of considering comorbidities in the treatment of depression, investigations on the relationship between depression and medical conditions have often been limited to small patient populations or a few specific medical conditions (Katon et al., 2007). A comprehensive assessment in a large population could allow comparisons between depression and a spectrum of medical conditions. Data regarding risks of various medical conditions after a diagnosis of depression could help clinicians and healthcare planners optimize treatment and long-term care including prevention or mitigation of medical illnesses in patients with depression.

Treatment resistant depression (TRD) refers to major depressive disorder (MDD) that incompletely responds to an adequate antidepressant trial (Fava, 2003). A consensus is emerging that unipolar MDD is considered resistant when at ≥2 trials with antidepressants from different pharmacologic classes (adequate in dose, duration, and adherence) fail to produce significant clinical improvement (Berlim and Turecki, 2007). Previous studies from our group and others have shown that TRD patients incur higher medical costs compared to patients with MDD but without TRD (Olfson et al., 2018; Gibson et al., 2010). Individuals with TRD are twice as likely to be hospitalized; the cost of these hospitalizations are more than six times the mean total cost for depressed patients who are not treatment-resistant (Crown et al., 2002). TRD can nearly double direct and indirect medical expenditures relative to expenditures for patients whose MDD responds to treatment (Ivanova et al., 2010). Job loss and financial stress are also more prevalent among TRD patients (Amital et al., 2008).

Previous studies of TRD have been mostly based on self-reported surveys, insurance claims data, or clinical data from a single health system/medical center, and therefore might not fully represent the community-level experiences. Large scale studies on the association between TRD and chronic disease using Electronic Health Record (EHR) data on diverse patient populations have been sparse mainly due to their limited availability. Unlike data acquired in clinical trials or self-reported surveys, which are robustly collected but often limited in scope and specific to certain research objectives, EHR data are collected for the clinical encounter and represent a patient’s health status, including demographics, vital signs, diagnosis, labs, procedures, psychosocial interventions within the medical system, and medications and their response. The PCORI-funded INSIGHT Clinical Research Network (INSIGHT-CRN) comprising EHR data on >12 million patients in the greater New York City area provides new opportunities to undertake such investigations using routinely collected clinical data (Kaushal et al., 2014). Using the INSIGHT dataset, we have investigated the association between depression and co-occurring substance use disorder in terms of healthcare utilization (Vekaria et al., 2021). In the present study, we analyzed a subset of INSIGHT data from over 3.3 million patients to investigate patients with TRD for various psychiatric and physical comorbidities and healthcare utilization.

2. Materials and methods

2.1. Study dataset

INSIGHT-CRN brought together seven large healthcare systems across the New York City (NYC) metropolitan region (Kaushal et al., 2014). Each participating site maintains their EHR data following the PCORnet Common Data Model (PCORnet CDM, n.d.). INSIGHT-CRN includes EHR data on patients who received care at one or more of the participating network partners, and the data are linked at an individual-level across different sources while protecting patients’ identities. This federated data structure supports population-based research. The present study is based on a subset of the INSIGHT-CRN data from 2010 to 2020. Patients in this dataset were included based on Current Procedural Terminology (CPT) codes for outpatient services (Supplementary Table S1). We used the inclusion criteria of at least one or more encounters for one of these services. For patients satisfying this initial inclusion criteria, we assembled all their interactions with the healthcare system during outpatient visits, televisits, emergency department visits and inpatient hospital stays. There were 3,328,842 patients in this study population. The study was approved by the Weill Cornell Medicine (New York, NY) institutional review board.

2.2. Defining treatment resistant depression

Study patients were classified as TRD or non-TRD MDD based on a previously reported EHR algorithm (Lage et al., 2022). An initial cohort of patients with MDD was identified using diagnosis and a prescription of an antidepressant medication. Diagnosis of MDD was defined as one or more International Classification of Diseases, Ninth Revision (ICD9) codes for 311, 296.2x, 296.3x, 300.4x, or Tenth Revision (ICD10) codes F32.x and F33.x and F34.1. TRD patients were further required to have ≥1 MDD diagnosis within 12 weeks after antidepressant prescription, which marks the beginning of the depression treatment episode, as the index antidepressant prescription. This requirement ensures evidence of persistent depression despite antidepressant treatment. Only antidepressants were included when determining prescription regimens (Supplementary Table S2). Patients with a diagnosis of schizophrenia (ICD-9-CM code 295.xx; ICD-10-CM: F20.x, F21.x, F22.x, F25.x), psychosis (ICD-9 code 298.xx; ICD-10: F23.x, F24.x, F28.x, F29.x), bipolar disorder (ICD-9 code 296.0x-296.1x, 296.4x-296.8x; ICD-10-CM: F30.x, F31.x) were excluded. As shown in Fig. 1, TRD was defined as initiating a third medication for depression after two different regimens of antidepressants at adequate dose and duration in the 12-months following the index antidepressant prescription. From the base MDD patient population, we identified two mutually exclusive TRD and non-TRD MDD cohorts. We also identified a third cohort with no known diagnosis of depression, anxiety, bipolar disorder, psychosis, or schizophrenia for comparison purposes. This group is referred to as the non-mental health (non-MH) cohort. To account for potential confounding due to age, sex, and length of EHR, we matched patients 1:1 from the non-TRD MDD cohort and non-MH cohort to the TRD cohort based on age, sex, and initial encounter year (for the non-MH patients) or index diagnosis year (for the non-TRD MDD patients).

Fig. 1.

Fig. 1.

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Clinical definition used to identify TRD patients.

2.3. Defining comorbidities and healthcare services utilization

Comorbidities of TRD patients were determined using the Chronic Conditions Data Warehouse (CCW) 27 flagged comorbid conditions (CDW, 2021, n.d.). We further added anxiety disorder and a category of all cancer combined to the list of 27 CCW categories. We examined comorbidities in two periods: baseline and follow-up. If the date of diagnosis of a chronic condition was within 30 days before or after the index MDD diagnosis date, the patient was defined as within the “baseline” category. If the date of diagnosis of a chronic condition was anytime after 30 days of the index MDD diagnosis date, the patient was defined as within the “follow-up” category. Healthcare utilization was assessed by the number of individual patients accessing a given type of service, number of encounters for a given visit type, and average stay for emergency department visit and hospital stay. Visit types included ambulatory visit (AV), emergency department (ED), emergency department admit to inpatient hospital stay (EI) and inpatient hospital stay (IP). For each visit type, we considered all-cause, depression and anxiety disorder, depression alone, and suicide related outcomes separately on patient and encounter levels. Differences in demographics, comorbidities, and healthcare utilization between the TRD, non-TRD MDD and non-MH cohorts were assessed using a chi-square test. All statistical analyses were performed using R version 3.6.1 (R Core Team, 2019) and associations were considered statistically significant if p < 0.005.

3. Results

As shown in Fig. 2, 301,841 patients with a diagnosis of MDD were identified from a base population of 3,328,842 patients. Applying the prescription and diagnosis within 12 weeks requirement, and removing patients who had a diagnosis of bipolar disorder, psychosis and schizophrenia, 30,218 patients met our initial MDD criteria. A total of 4605 patients were identified with TRD (the “TRD cohort”) and 25,487 patients were identified with non-TRD MDD. We then 1:1 matched patients from the non-TRD group with the TRD cohort based on sex, age at index diagnosis and first MDD diagnosis years to obtain the “non-TRD MDD cohort”. Finally, from the base population after excluding individuals who had a diagnosis of depression, anxiety, bipolar disorder, psychosis or schizophrenia, we randomly selected 4605 1:1 matched patients for the “non-MH cohort” matching on sex, age, and the initial encounter year to the TRD group. Since patients in the non-MH group never had an MDD diagnosis, we matched the initial encounter year with the index MDD diagnosis year in the TRD cohort.

Fig. 2.

Fig. 2.

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TRD, non-TRD MDD and non-MH patient cohorts identified in this study using the INSIGHT-CRN data.

Table 1 provides demographic characteristics for the TRD and non-TRD MDD patients along with the INSIGHT-CRN base patient population. Between TRD and non-TRD MDD patients, no significant variations in age or sex were observed. The average age for these cohorts was ~54 years (SD ~20) with a majority of female patients (66.2 %). Similarly, no significant variations in race or ethnicity were observed between TRD and non-TRD MDD patients. The population included patients of White (~47 %), African American (~7 %), Asian (~2 %), and other/unknown (~43 %) racial ancestry. Hispanic ethnicity was found in around 9 % of the TRD and non-TRD MDD patients. Both MDD and TRD patients were older than the base patient population. The TRD cohort had a slightly lower percentage of patients between the age 40 and 59 than the MDD cohort not meeting the criteria for TRD. The non-TRD MDD and TRD cohorts had a higher percentage (66.2 % and 65.3 %, respectively) of female patients compared to the base patient population (57.7 %).

Table 1.

Study population demographics of the base patient population, MDD patients, MDD after excluding TRD patients, non-TRD MDD patients adjusted for sex/age, and TRD cohorts.

INSIGHT Base MDD MDD (minus TRD) non-TRD MDD TRD
n 3,328,842 30,218 25,487 4,605 4,605
Age (SD) 42.93 (22.46) 54.32 (19.91) 54.43 (19.71) 54.07 (20.33) 54.06 (20.34)
 < 18 552,233 (16.6 %) 713 (2.4 %) 527 (2.1 %) 136 (3.0 %) 136 (3.0 %)
 18–39 862,716 (25.9 %) 7,317 (24.2 %) 6,160 (24.2 %) 1,133 (24.6 %) 1,133 (24.6 %)
 40–59 858,074 (25.8 %) 9,273 (30.7 %) 7,930 (31.1 %) 1,332 (28.9 %) 1,332 (28.9 %)
 60–79 660,617 (19.8 %) 9,520 (31.5 %) 8,020 (31.5 %) 1,483 (32.2 %) 1,483 (32.2 %)
 ≥80 128,965 (3.9 %) 3,395 (11.2 %) 2,850 (11.2 %) 521 (11.3 %) 521 (11.3 %)
 Unknown 266,237 (8.0 %)
Gender
 Female 1,920,178 (57.7 %) 19,946 (66.0 %) 16,874 (66.2 %) 3,008 (65.3 %) 3,008 (65.3 %)
 Male 1,407,984 (42.3 %) 10,267 (34.0 %) 8,609 (33.8 %) 1,597 (34.7 %) 1,597 (34.7 %)
 Other 680 (0.0 %) 5 (0.0 %) 4 (0.0 %) 0 (0.0 %) 0 (0.0 %)
Race
 Native/Alaskan 5503 (0.2 %) 20 (0.1 %) 18 (0.1 %) 1 (0.0 %) 2 (0.0 %)
 Asian 118,140 (3.5 %) 576 (1.9 %) 473 (1.9 %) 89 (1.9 %) 103 (2.2 %)
 AA 425,562 (12.8 %) 2280 (7.5 %) 1926 (7.6 %) 329 (7.1 %) 345 (7.5 %)
 Hawaiian/PI 15,742 (0.5 %) 39 (0.1 %) 32 (0.1 %) 5 (0.1 %) 7 (0.2 %)
 White 1,240,793 (37.3 %) 14,239 (47.1 %) 12,037 (47.2 %) 2,153 (46.8 %) 2,153 (46.8 %)
 Unknown 1,523,102 (45.8 %) 13,064 (43.2 %) 11,001 (43.2 %) 2,028 (44.0 %) 1,995 (43.3 %)
Ethnicity
 Hispanic 441,921 (13.3 %) 2,690 (8.9 %) 2,280 (8.9 %) 415 (9.0 %) 399 (8.7 %)
 Non-Hispanic 1,809,115 (54.3 %) 18,803 (62.2 %) 15,820 (62.1 %) 2,813 (61.1 %) 2,906 (63.1 %)
 Unknown 1,077,806 (32.4 %) 8,725 (28.9 %) 7,387 (29.0 %) 1,377 (29.9 %) 1,300 (28.2 %)
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Table 2 presents data on comorbidity patterns among the TRD, non-TRD MDD, and non-MH cohorts. Baseline and follow-up comorbidities for both TRD and non-TRD MDD patients were significantly higher than patients without observed mental health diagnoses. Because of the inclusion criteria for the non-MH patients, anxiety disorder was observed among only TRD and non-TRD MDD patients. We observed a gradual increase in prevalence of diagnosis across the range of diseases in ascending order from non-MH to non-TRD MDD to TRD patients. Most variations were observed for anxiety, hypothyroidism, Alzheimer’s disease, dementia, anemia, asthma, cataract, chronic kidney disease, chronic obstructive pulmonary disease (COPD), glaucoma, heart failure, hip/pelvic fracture, osteoporosis, stroke/transient ischemic attack, and various cancers. Among diseases with at least 100 cases in the non-MH cohort and upon comparing the percentage differences, relative onset of new cases of arthritis, anemia, chronic kidney diseases, ischemic heart disease, thyroid, hyperlipidemia, atrial fibrillation, and cancer where higher in TRD cohort compared to non-TRD MDD patients. Both TRD and non-TRD MDD patients were having a low prevalence for new onset of hypertension and diabetes compared to the non-MH patients. Additionally, the non-TRD MDD patients were found to have low prevalence for onset of new cases of hyperlipidemia, thyroid, ischemic heart disease, and cancer.

Table 2.

Baseline and follow-up comorbidities of the matched TRD, non-TRD MDD and non-MH cohorts.

non-MH non-TRD MDD TRD
n
 4,605
 4,605
 4,605
Baseline Follow-up Baseline Follow-up Baseline Follow-up
Charlson Comorbidity Score
 Low (0–2) 4,557(98.9 %) 4,299(93.4 %) 4,327(94.0 %) 3,766(81.8 %) 4,178(90.7 %) 3,326(72.2 %)
 Medium (3–4) 26 (0.6 %) 193 (4.2 %) 139 (3.0 %) 398 (8.6 %) 225 (4.9 %) 597(13.0 %)
 High (≥5) 22 (0.5 %) 113 (2.4 %) 139 (3.0 %) 441 (9.6 %) 202 (4.4 %) 682(14.8 %)
Anxiety 0 (0.0 %) 0 (0.0 %) 1375(29.9 %) 1576(34.2 %) 1748(38.0 %) 2481(53.9 %)
Acquired hypothyroidism 120 (2.6 %) 357 (7.8 %) 373 (8.1 %) 551 (12.0 %) 360 (7.8 %) 696 (15.1 %)
Acute myocardial infarction 28 (0.6 %) 57 (1.2 %) 23 (0.5 %) 67 (1.5 %) 36 (0.8 %) 91 (2.0 %)
Alzheimer’s disease 0 (0.0 %) 4 (0.1 %) 47 (1.0 %) 100 (2.2 %) 58 (1.3 %) 146 (3.2 %)
Dementiaa 1 (0.0 %) 12 (0.3 %) 153 (3.3 %) 297 (6.4 %) 182 (4.0 %) 459 (10.0 %)
Anemia 145 (3.1 %) 538 (11.7 %) 416 (9.0 %) 816 (17.7 %) 554 (12.0 %) 1,207 (26.2 %)
Asthma 92 (2.0 %) 273 (5.9 %) 281 (6.1 %) 489 (10.6 %) 238 (5.2 %) 557 (12.1 %)
Atrial fibrillation 120 (2.6 %) 266 (5.8 %) 237 (5.1 %) 373 (8.1 %) 237 (5.1 %) 416 (9.0 %)
BPH 75 (1.6 %) 211 (4.6 %) 142 (3.1 %) 296 (6.4 %) 154 (3.3 %) 378 (8.2 %)
Cataract 25 (0.5 %) 188 (4.1 %) 48 (1.0 %) 411 (8.9 %) 77 (1.7 %) 521 (11.3 %)
Chronic kidney disease 126 (2.7 %) 424 (9.2 %) 342 (7.4 %) 652 (14.2 %) 407 (8.8 %) 927 (20.1 %)
COPDb 77 (1.7 %) 266 (5.8 %) 177 (3.8 %) 388 (8.4 %) 181 (3.9 %) 515 (11.2 %)
Diabetes 265 (5.8 %) 607 (13.2 %) 545 (11.8 %) 721 (15.7 %) 521 (11.3 %) 849 (18.4 %)
Glaucoma 20 (0.4 %) 104 (2.3 %) 55 (1.2 %) 203 (4.4 %) 77 (1.7 %) 297 (6.4 %)
Heart failure 84 (1.8 %) 238 (5.2 %) 216 (4.7 %) 360 (7.8 %) 210 (4.6 %) 472 (10.2 %)
Hip/pelvic fracture 5 (0.1 %) 23 (0.5 %) 18 (0.4 %) 52 (1.1 %) 26 (0.6 %) 110 (2.4 %)
Hyperlipidemia 535 (11.6 %) 1,285 (27.9 %) 990 (21.5 %) 1,558 (33.8 %) 933 (20.3 %) 1768(38.4 %)
Hypertension 757 (16.4 %) 1,545 (33.6 %) 1,305 (28.3 %) 1,666 (36.2 %) 1,232 (26.8 %) 1,917 (41.6 %)
Ischemic heart disease 235 (5.1 %) 551 (12.0 %) 383 (8.3 %) 648 (14.1 %) 410 (8.9 %) 848 (18.4 %)
Osteoporosis 48 (1.0 %) 227 (4.9 %) 141 (3.1 %) 358 (7.8 %) 146 (3.2 %) 477 (10.4 %)
Arthritisc 272 (5.9 %) 844 (18.3 %) 346 (7.5 %) 1,023 (22.2 %) 399 (8.7 %) 1,394 (30.3 %)
Stroke/TIAd 48 (1.0 %) 150 (3.3 %) 139 (3.0 %) 304 (6.6 %) 194 (4.2 %) 459 (10.0 %)
Female/male breast cancer 60 (1.3 %) 130 (2.8 %) 119 (2.6 %) 183 (4.0 %) 100 (2.2 %) 197 (4.3 %)
Colorectal cancer 13 (0.3 %) 46 (1.0 %) 29 (0.6 %) 51 (1.1 %) 41 (0.9 %) 71 (1.5 %)
Prostate cancer 28 (0.6 %) 96 (2.1 %) 43 (0.9 %) 67 (1.5 %) 45 (1.0 %) 92 (2.0 %)
Lung cancer 20 (0.4 %) 53 (1.2 %) 55 (1.2 %0 77 (1.7 %) 67 (1.5 %) 98 (2.1 %)
Endometrial cancer 4 (0.1 %) 22 (0.5 %) 13 (0.3 %) 23 (0.5 %) 6 (0.1 %) 22 (0.5 %)
All cancers (malignant) 218 (4.7 %) 520 (11.3 %) 490 (10.6 %) 747 (16.2 %) 627 (13.6 %) 987 (21.4 %)
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a

Alzheimer’s disease and related disorders or senile dementia.

b

Chronic obstructive pulmonary disease and bronchiectasis.

c

Rheumatoid arthritis/ osteoarthritis (RA/OA).

d

Stroke/transient ischemic attack,

While the prevalence rates of most comorbidities at baseline were similar for both TRD and non-TRD MDD patient cohorts, we observed significant increases in comorbidities for TRD patients over time. Tables 3 and 4 show the odds ratio (OR) and statistical significance calculated for various disease categories between TRD and non-TRD MDD patients for the baseline and follow-up timeframes, respectively. At baseline, only anxiety disorder (OR = 1.44; 95%CI = 1.32–1.57; p < 005), anemia (OR = 1.38; 95%CI = 1.20–1.58; p < 005), Stroke/Transient Ischemic Attack (OR = 1.41; 95%CI = 1.13–1.77; p < 005) and all cancers combined (OR = 1.32; 95%CI = 1.17–1.50; p < 005) were significantly higher in TRD patients compared to non-TRD MDD patients. However, overtime TRD patients were had a higher prevalence for anxiety disorder and various other diagnoses. Anxiety disorder diagnoses were significantly more common among TRD patients (OR = 2.24; 95%CI = 2.06–2.44; p < 005). Other diseases such as hypothyroidism (OR = 1.31; 95%CI = 1.16–1.48; p < 005), Alzheimer’s disease (OR = 1.47; 95%CI = 1.14–1.91; p < 005), dementia (OR = 1.61; 95%CI = 1.38–1.87; p < 005), anemia (OR = 1.65; 95%CI = 1.49–1.82; p < 005), chronic kidney disease (OR = 1.53; 95%CI = 1.37–1.71; p < 005), COPD (OR = 1.37; 95%CI = 1.19–1.57; p < 005), glaucoma (OR = 1.49; 95%CI = 1.25–1.80; p < 005), heart failure (OR = 1.35; 95%CI = 1.17–1.56; p < 005), hip/pelvic fracture (OR = 2.14; 95%CI = 1.54–3.01; p < 005), ischemic heart disease (OR = 1.38; 95%CI = 1.23–1.54; p < 005), osteoporosis (OR = 1.37; 95%CI = 1.19–1.58; p < 005), stroke/transient ischemic attack (OR = 1.57; 95%CI = 1.35–1.82; p < 005), and all cancers combined (OR = 1.41; 95%CI = 1.27–1.57; p < 005) had significantly higher odds among TRD patients over time.

Table 3.

Odds ratio and p values estimated for various disease diagnoses between the matched TRD and non-TRD MDD cohorts at baseline.

Non-TRD MDD TRD OR (95 % CI) p
n 4,605 4,605
Anxiety 1,375 1,748 1.44 (1.32–1.57) <0.005
Acquired hypothyroidism 373 360 0.96 (0.83–1.12) 0.62
Acute myocardial infarction 23 36 1.57 (0.93–2.69) 0.09
Alzheimer’s disease 47 58 1.24 (0.84–1.83) 0.28
Dementiaa 153 182 1.20 (0.96–1.49) 0.11
Anemia 416 554 1.38 (1.20–1.58) <0.005
Asthma 281 238 0.84 (0.70–1.00) 0.05
Atrial fibrillation 237 237 1.00 (0.83–1.20) 1
Benign prostatic hyperplasia 142 154 1.09 (0.86–1.37) 0.48
Cataract 48 77 1.61 (1.13–2.33) 0.01
Chronic kidney disease 342 407 1.21 (1.04–1.40) 0.01
COPDb 177 181 1.02 (0.83–1.26) 0.83
Diabetes 545 521 0.95 (0.84–1.08) 0.43
Glaucoma 55 77 1.41 (0.99–2.00) 0.05
Heart failure 216 210 0.97 (0.80–1.18) 0.77
Hip/pelvic fracture 18 26 1.44 (0.79–2.69) 0.23
Hyperlipidemia 990 933 0.93 (0.84–1.03) 0.14
Hypertension 1,305 1,232 0.92 (0.84–1.01) 0.09
Ischemic heart disease 383 410 1.08 (0.93–1.25) 0.32
Osteoporosis 141 146 1.04 (0.82–1.31) 0.76
Arthritisc 346 399 1.17 (1.00–1.36) 0.04
Stroke/TIAd 139 194 1.41 (1.13–1.77) <0.005
Female/male breast cancer 119 100 0.84 (0.64–1.10) 0.19
Colorectal cancer 29 41 1.42 (0.88–2.30) 0.15
Prostate cancer 43 45 1.05 (0.69–1.60) 0.83
Lung cancer 55 67 1.22 (0.85–1.75) 0.27
Endometrial cancer 13 6 0.47 (0.16–1.20) 0.11
Cancer (all) 490 627 1.32 (1.17–1.50) <0.005
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a

Alzheimer’s disease and related disorders or senile dementia.

b

Chronic obstructive pulmonary disease and bronchiectasis.

c

Rheumatoid arthritis/ osteoarthritis (RA/OA).

d

Stroke/transient ischemic attack,

Table 4.

Odds ratios and p values estimated for various disease diagnoses between the matched TRD and non-TRD MDD cohorts at follow-up.

NON-TRD MDD TRD OR (95%CI) p
n 4,605 4,605
Anxiety 1,576 2,481 2.24 (2.06–2.44) <0.005
Acquired hypothyroidism 551 696 1.31 (1.16–1.48) <0.005
Acute myocardial infarction 67 91 1.36 (0.99–1.88) 0.05
Alzheimer’s disease 100 146 1.47 (1.14–1.91) <0.005
Dementiaa 297 459 1.61 (1.38–1.87) <0.005
Anemia 816 1,207 1.65 (1.49–1.82) <0.005
Asthma 489 557 1.16 (1.02–1.32) 0.03
Atrial fibrillation 373 416 1.13 (0.97–1.3) 0.11
Benign prostatic hyperplasia 296 378 1.3 (1.11–1.53) <0.005
Cataract 411 521 1.3 (1.14–1.49) <0.005
Chronic kidney disease 652 927 1.53 (1.37–1.71) <0.005
COPDb 388 515 1.37 (1.19–1.57) <0.005
Diabetes 721 849 1.22 (1.09–1.36) <0.005
Glaucoma 203 297 1.49 (1.25–1.8) <0.005
Heart failure 360 472 1.35 (1.17–1.56) <0.005
Hip/pelvic fracture 52 110 2.14 (1.54–3.01) <0.005
Hyperlipidemia 1,558 1,768 1.22 (1.12–1.33) <0.005
Hypertension 1,666 1,917 1.26 (1.16–1.37) <0.005
Ischemic heart disease 648 848 1.38 (1.23–1.54) <0.005
Osteoporosis 358 477 1.37 (1.19–1.58) <0.005
Arthritisc 1,023 1,394 1.52 (1.38–1.67) <0.005
Stroke/TIAd 304 459 1.57 (1.35–1.82) <0.005
Female/male breast cancer 183 197 1.08 (0.88–1.33) 0.46
Colorectal cancer 51 71 1.4 (0.97–2.02) 0.07
Prostate cancer 67 92 1.38 (1.01–1.9) 0.05
Lung cancer 77 98 1.28 (0.95–1.73) 0.11
Endometrial cancer 23 22 0.96 (0.53–1.73) 0.88
Cancer (all) 747 987 1.41 (1.27–1.57) <0.005
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a

Alzheimer’s disease and related disorders or senile dementia.

b

Chronic obstructive pulmonary disease and bronchiectasis.

c

Rheumatoid arthritis/ osteoarthritis (RA/OA).

d

Stroke/transient ischemic attack,

We also compared the prevalence of diagnosis of various comorbidities between non-TRD MDD and non-MH patient cohorts, and between TRD and non-MH patient cohorts. Since the baseline for the non-MH patients was for non-mental health related encounters, we only calculated prevalence for these two cohorts during the follow-up period. Table 5 shows the odds ratio and statistical significance calculated for various disease categories between non-TRD MDD and non-MH patients, and between TRD and non-MH at follow-up. Since the non-MH cohort by definition had no diagnosis of anxiety, the corresponding odds were not computed. When compared to patients with no mental illnesses, non-TRD MDD patients have a high prevalence of diagnosis of various diseases. TRD patients exhibited a significantly higher disease burden than non-TRD MDD patients. TRD patients were increasingly diagnosed with various medical conditions for the entire range of CCW disease categories. Diseases such as hypothyroidism (OR = 2.12; 95%CI = 1.85–2.43; p < 0.005), Alzheimer’s disease (OR = 36.24; 95%CI = 15.31–119.99; p < 0.005), dementia (OR = 41.81; 95%CI = 24.66–78.84; p < 0.005), anemia (OR = 2.68; 95%CI = 2.40–3.00; p < 0.005), asthma (OR = 2.18; 95%CI = 1.88–2.54; p < 0.005), cataract (OR = 3.00; 95%CI = 2.53–3.57; p < 0.005), chronic kidney disease (OR = 2.48; 95%CI = 2.20–2.81; p < 0.005), COPD (OR = 2.05; 95%CI = 1.76–2.40; p < 0.005), glaucoma (OR = 2.98; 95%CI = 2.38–3.76; p < 0.005), heart failure (OR = 2.09; 95%CI = 1.78–2.47; p < 0.005), hip/pelvic fracture (OR = 4.85; 95%CI = 3.15–7.81; p < 0.005), osteoporosis (OR = 2.23; 95%CI = 1.89–2.63; p < 0.005), stroke/transient ischemic attack (OR = 3.29; 95%CI = 2.73–3.98; p < 0.005), and all cancers combined (OR = 2.14; 95%CI = 1.91–2.41; p < 0.005) had more than double the odds of diagnosis among TRD patients over time.

Table 5.

Odds ratios and p values estimated for various disease diagnoses between the matched non-MH and non-TRD MDD cohorts, and between the matched non-MH and TRD cohorts at follow-up.

Non-MH vs. non-TRD MDD patients
 Non-MH vs. TRD patients
OR (95%CI) p OR (95%CI) p
Anxiety NA NA NA NA
Acquired hypothyroidism 1.62 (1.41–1.86) <0.005 2.12 (1.85–2.43) <0.005
Acute myocardial infarction 1.18 (0.83–1.69) 0.37 1.61 (1.15–2.26) <0.005
Alzheimer’s disease 24.58 (10.29–81.88) <0.005 36.24 (15.31–119.99) <0.005
Dementiaa 26.04 (15.28–49.23) <0.005 41.81 (24.66–78.84) <0.005
Anemia 1.63 (1.45–1.83) <0.005 2.68 (2.4–3) <0.005
Asthma 1.88 (1.62–2.2) <0.005 2.18 (1.88–2.54) <0.005
Atrial fibrillation 1.44 (1.22–1.69) <0.005 1.62 (1.38–1.9) <0.005
Benign prostatic hyperplasia 1.43 (1.19–1.72) <0.005 1.86 (1.57–2.22) <0.005
Cataract 2.3 (1.93–2.75) <0.005 3 (2.53–3.57) <0.005
Chronic kidney disease 1.63 (1.43–1.85) <0.005 2.48 (2.2–2.81) <0.005
COPDb 1.5 (1.28–1.77) <0.005 2.05 (1.76–2.4) <0.005
Diabetes 1.22 (1.09–1.37) <0.005 1.49 (1.33–1.67) <0.005
Glaucoma 1.99 (1.57–2.54) <0.005 2.98 (2.38–3.76) <0.005
Heart failure 1.56 (1.31–1.84) <0.005 2.09 (1.78–2.47) <0.005
Hip/pelvic fracture 2.27 (1.4–3.78) <0.005 4.85 (3.15–7.81) <0.005
Hyperlipidemia 1.32 (1.21–1.44) <0.005 1.61 (1.48–1.76) <0.005
Hypertension 1.12 (1.03–1.22) 0.01 1.41 (1.3–1.54) <0.005
Ischemic heart disease 1.2 (1.07–1.36) <0.005 1.66 (1.48–1.87) <0.005
Osteoporosis 1.63 (1.37–1.93) <0.005 2.23 (1.89–2.63) <0.005
Arthritisc 1.17 (1–1.36) 0.04 1.17 (1–1.36) 0.04
Stroke/TIAd 2.1 (1.72–2.57) <0.005 3.29 (2.73–3.98) <0.005
Female/male breast cancer 1.42 (1.13–1.79) <0.005 1.54 (1.23–1.93) <0.005
Colorectal cancer 1.11 (0.74–1.66) 0.61 1.55 (1.07–2.27) 0.02
Prostate cancer 0.69 (0.5–0.95) 0.02 0.96 (0.72–1.28) 0.77
Lung cancer 1.46 (1.03–2.09) 0.03 1.86 (1.34–2.63) <0.005
Endometrial cancer 1.05 (0.58–1.89) 0.88 1 (0.55–1.82) 1
Cancer (all) 1.52 (1.35–1.72) <0.005 2.14 (1.91–2.41) <0.005
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a

Alzheimer’s disease and related disorders or senile dementia.

b

Chronic obstructive pulmonary disease and bronchiectasis.

c

Rheumatoid arthritis/ osteoarthritis (RA/OA).

d

Stroke/transient ischemic attack,

Table 6 shows healthcare utilization for TRD and non-TRD MDD patients for the entire observation period. While all cause visits were similar for TRD and non-TRD MDD patients, TRD patients were more likely than non-TRD MDD patients to receive anxiety disorder and depression related services in outpatient settings. TRD patients were significantly more likely than non-TRD MDD patients to receive ED care or ED admissions for hospital stays, or inpatient stays for any reason, as well as for anxiety disorder and depression. TRD patients generally stayed longer in the hospital than non-TRD MDD patients. Although patients with encounters related to suicidal symptoms were low (<1 %) for both TRD and non-TRD MDD patients, TRD patients had a higher prevalence for all visit types. Given that both TRD and non-TRD MDD cohorts had the same number of patients, the higher healthcare utilization of TRD patients was further evident from the total encounters of these patients for various visit types (Table 7). For all visit types, TRD patients had more encounters for all-cause, anxiety disorder, depression related, and suicide related encounters than non-TRD MDD patients.

Table 6.

Patient level healthcare utilization for matched TRD and non-TRD MDD cohorts for various encounter types.

Non- TRD MDD TRD OR (95%CI) p
n 4605 4605
AV = ambulatory visit
 All cause 4605 4605 n/a n/a
 Depression and anxiety disorder 3993 4098 1.24 (1.09–1.4) <0.005
 Depression alone 3896 3913 1.03 (0.92–1.15) 0.62
 Suicidal symptoms 44 68 1.55 (1.06–2.29) 0.02
ED = emergency department
 All cause 1935 2372 1.47 (1.35–1.59) <0.005
 Depression and anxiety disorder 243 468 2.03 (1.73–2.39) <0.005
 Depression alone 155 291 1.94 (1.59–2.37) <0.005
 Suicidal symptoms 28 56 2.01 (1.28–3.21) <0.005
EI = emergency department admit to inpatient hospital stay
 All cause 799 1324 1.92 (1.74–2.12) <0.005
 Depression and anxiety disorder 457 861 2.09 (1.85–2.36) <0.005
 Depression alone 393 726 2.01 (1.76–2.29) <0.005
 Suicidal symptoms 8 21 2.60 (1.19–6.32) 0.02
 Number of days - median
  All cause 4 5
  Depression and anxiety disorder 5 6
  Depression alone 5 6
  Suicidal symptoms 7 8
IP=inpatient hospital stay
 All cause 1689 2149 1.51 (1.39–1.64) <0.005
 Depression and anxiety disorder 831 1124 1.47 (1.33–1.62) <0.005
 Depression alone 739 968 1.39 (1.25–1.55) <0.005
 Suicidal symptoms 19 32 1.68 (0.96–3.04) 0.07
 Number of days - median
  All cause 4 4
  Depression and anxiety disorder 5 6
  Depression alone 5 6
  Suicidal symptoms 7 8
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Table 7.

Encounter level healthcare utilization for TRD and non-TRD MDD patients for various encounter types.

Non-TRD MDD TRD OR (95%CI) p
n 4,605 4,605
Total encounters 608,390 1,034,884
AV = ambulatory visit 594,003 (97.6 %) 1,012,615 (97.8 %) 1.1 (1.08–1.12) <0.005
ED = emergency department 7,876 (1.3 %) 11,573 (1.1 %) 0.86 (0.84–0.89) <0.005
EI = emergency department admit to inpatient hospital stay 1,968 (0.3 %) 3,682 (0.4 %) 1.1 (1.04–1.16) <0.005
IP=inpatient hospital stay 4,352 (0.7 %) 6,808 (0.7 %) 0.92 (0.88–0.95) <0.005
AV = ambulatory visit
 All cause 594,003 1,012,615
 Depression and anxiety disorder 24,656 55,623 1.34 (1.32–1.36) <0.005
 Depression alone 16,588 34,818 1.24 (1.22–1.26) <0.005
 Suicidal symptoms 59 99 0.98 (0.71–1.36) 0.92
ED = emergency department
 All cause 7,876 11,573
 Depression and anxiety disorder 335 830 1.74 (1.53–1.98) <0.005
 Depression alone 196 429 1.51 (1.27–1.79) <0.005
 Suicidal symptoms 29 65 1.52 (0.99–2.4) 0.06
EI = emergency department admit to inpatient hospital stay
 All cause 1,968 3,682
 Depression and anxiety disorder 766 1,698 1.34 (1.2–1.5) <0.005
 Depression alone 590 1,287 1.25 (1.12–1.41) <0.005
 Suicidal symptoms 8 23 1.52 (0.7–3.67) 0.29
IP=inpatient hospital stay
 All cause 4,352 6,808
 Depression and anxiety disorder 1,249 2,068 1.08 (1–1.18) 0.06
 Depression alone 1,030 1,565 1.39 (1.25–1.55) <0.005
 Suicidal symptoms 21 37 1.12 (0.66–1.96) 0.66
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Table 8 shows acute care healthcare use for various medical conditions in TRD, non-TRD MDD, and non-MH patients for the entire observation period. We combined all encounters for ED, EI, and IP for defining the acute care. While both TRD and non-TRD MDD patients had high healthcare utilization over the entire spectrum of diseases when compared to non-MH cohort, the utilization was significantly higher among TRD patients as indicated by the high odds ratio observed. Similarly, the median number of stays for acute care is also higher among TRD and non-TRD MDD patients. TRD patients generally stayed longer compared to non-TRD MDD patients.

Table 8.

Acute healthcare utilization on patient level for non-MH, non-TRD MDD and TRD patients for various medical conditions.

Non-MH Non-TRD MDD TRD Non-MH vs non-TRD MDD Non-MH vs TRD
n 4,605 4,605 4,605
Acute care (ED + EI+ IP) OR (95%CI) p OR (95%CI) p
All cause 1,255 2,494 3,017 3.15 (2.89–3.44) <0.005 5.07 (4.64–5.54) <0.005
Hypothyroidism 98 325 447 3.49 (2.78–4.41) <0.005 4.94 (3.97–6.2) <0.005
Myocardial infarction 50 91 121 1.83 (1.3–2.61) <0.005 2.45 (1.77–3.45) <0.005
Alzheimer’s disease 0 39 70 34.45 (7.59–805.58) <0.005 62.15(14.02–1440.2) <0.005
Dementiaa 6 177 273 29.85 (14.46–76.59) <0.005 47.05 (22.93–119.8) <0.005
Anemia 232 662 974 3.16 (2.71–3.7) <0.005 5.05 (4.36–5.88) <0.005
Asthma 100 349 388 3.69 (2.95–4.65) <0.005 4.14 (3.32–5.2) <0.005
Atrial fibrillation 94 333 373 3.74 (2.97–4.74) <0.005 4.22 (3.37–5.34) <0.005
BPH 64 205 267 3.3 (2.5–4.41) <0.005 4.36 (3.33–5.79) <0.005
Cataract 9 39 56 4.3 (2.17–9.54) <0.005 6.19 (3.21–13.5) <0.005
Chronic kidney disease 184 587 808 3.51 (2.96–4.17) <0.005 5.11 (4.34–6.05) <0.005
COPDb 78 239 342 3.17 (2.46–4.13) <0.005 4.65 (3.64–6.01) <0.005
Diabetes 219 519 675 2.54 (2.16–3) <0.005 3.44 (2.94–4.04) <0.005
Glaucoma 20 84 125 4.23 (2.65–7.11) <0.005 6.35 (4.05–10.52) <0.005
Heart failure 109 345 431 3.34 (2.69–4.17) <0.005 4.25 (3.45–5.29) <0.005
Hip/pelvic fracture 14 60 119 4.29 (2.46–8.02) <0.005 8.61 (5.12–15.72) <0.005
Hyperlipidemia 318 863 1,111 3.11 (2.72–3.56) <0.005 4.28 (3.76–4.9) <0.005
Hypertension 527 1,191 1,456 2.7 (2.41–3.02) <0.005 3.58 (3.21–4) <0.005
Ischemic heart disease 199 524 708 2.84 (2.4–3.37) <0.005 4.02 (3.42–4.74) <0.005
Osteoporosis 37 169 219 4.69 (3.32–6.81) <0.005 6.14 (4.38–8.86) <0.005
Arthritisc 145 434 640 3.2 (2.64–3.89) <0.005 4.96 (4.13–5.99) <0.005
Stroke/TIAd 50 198 316 4.08 (3.01–5.64) <0.005 6.69 (5–9.15) <0.005
Breast cancer 34 102 119 3.04 (2.08–4.55) <0.005 3.55 (2.45–5.29) <0.005
Colorectal cancer 17 38 58 2.23 (1.28–4.08) <0.005 3.42 (2.03–6.08) <0.005
Prostate cancer 26 47 63 1.81 (1.13–2.97) 0.01 2.43 (1.56–3.92) <0.005
Lung cancer 27 64 85 2.38 (1.53–3.81) <0.005 3.18 (2.08–5) <0.005
Endometrial cancer 5 23 20 4.5 (1.84–13.66) <0.005 3.92 (1.57–12) <0.005
Cancer (all) 133 459 698 3.72 (3.06–4.55) <0.005 6 (4.98–7.29) <0.005
Number of days
All cause 3 4 6
Hypothyroidism 3 4 4
Myocardial infarction 4 6 5
Alzheimer’s disease – 3 6
Dementiaa 4 5 6
Anemia 5 8 9
Asthma 1 3 2
Atrial fibrillation 4 5 6
BPH 3 4 4
Cataract 6 4 5
Chronic kidney disease 5 6 7
COPDb 3 5 5
Diabetes 2 4 5
Glaucoma 5 3 4
Heart failure 6 7 7
Hip/pelvic fracture 5 6 6
Hyperlipidemia 2 3 3
Hypertension 1 3 3
Ischemic heart disease 2 4 4
Osteoporosis 3 3 4
Arthritisc 2 3 3
Stroke/TIAd 5 6 9
Breast cancer 2 6 5
Colorectal cancer 5 8 9
Prostate cancer 2 2 6
Lung cancer 5 5 7
Endometrial cancer 1 2 6
Cancer (all) 6 8 8
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a

Alzheimer’s disease and related disorders or senile dementia.

b

Chronic obstructive pulmonary disease and bronchiectasis.

c

Rheumatoid arthritis/osteoarthritis (RA/OA).

d

Stroke/transient ischemic attack,

4. Discussion

Given variability in the criteria used to define TRD, estimates of prevalence and burden of treatment-resistant depression (TRD) vary widely in the literature. Older age and female sex appear to be at a higher risk for antidepressant treatment non-response (Souery et al., 1999). We found a minor decrease in percentage of patients between 40 and 59 in the TRD cohort compared to MDD patients who did not meet the TRD criteria. However, we did not observe any significant difference in gender distribution between these cohorts. Previous studies have reported about 30 % to 50 % of patients diagnosed with MDD do not respond to an initial antidepressant trial of adequate dose and duration (Fava and Davidson, 1996). Although most patients respond to an additional antidepressant, some patients fail to achieve a significant decrease in depressive symptoms. Approximately 20 % of depressed patients continue to suffer from depression for up to 2 years after initial onset of a major depressive episode (Malhi et al., 2005). Despite the completion of multiple antidepressant medication treatments and more aggressive treatment regimens, 15 % of patients diagnosed with MDD continue to suffer from depression (Keller et al., 1982). These findings are consistent with our observations.

Close association between depression and anxiety has been extensively studied in the literature (Trevino et al., 2014). Psychiatric co-morbidity, personality, anxiety, and substance-related disorders have all been associated with TRD or reduced responsiveness to antidepressant treatments. Symptoms and syndromes of anxiety frequently overlap with MDD and represent an important target for antidepressant treatment. High levels of anxiety also have a negative impact on the treatment of depression as anxiety increases not only the risk of non-response during acute treatment but also the risk of recurrence after response (Kennedy, 2008). TRD patients had a higher prevalence of anxiety disorders at baseline compared to non-TRD MDD patients (38.0 % vs 29.9 %). The prevalence of anxiety diagnoses was even higher (53.9 % vs 34.3 %) during the subsequent period after the index diagnosis of MDD. This finding suggests that TRD patients without previous diagnosis of anxiety disorder were increasingly diagnosed with anxiety disorders. In a multicenter study involving 702 patients, a high prevalence of anxiety disorders and other mental health disorders were associated with TRD (Souery et al., 1999). The observed odds ratio of 2.24 in the present study is slightly lower than the 2.6 odds ratio reported in this study.

Depression in patients with dementia and Alzheimer’s disease (AD) has also been studied extensively. Dementia is associated with increased risk of developing depression, and conversely depression may increase the risk of subsequently developing dementia (Kessing, 2012). Regarding the latter association, meta analyses concluded that depression increases the risk of developing subsequent dementia (da Silva et al., 2013). At baseline, we found that TRD patients had increased risk of developing AD (OR = 1.24) and dementia (OR = 1.20) compared to non-TRD MDD patients. During follow-up, the risks increased to 1.47 for AD and 1.61 for dementia. This is consistent with results from a longitudinal study of adults >65 years in which TRD was associated with a significantly increased risk of dementia and AD, with hazard ratios of 5.19 and 4.44, respectively (Chan et al., 2020).

Although multiple cross-sectional studies have reported associations between MDD and chronic medical conditions, previous studies investigating the prevalence and extent of these associations in patients with TRD are limited and often conflicting. In a multicenter epidemiological survey of patients with MDD, no significant difference was reported between TRD and non-TRD MDD patients for comorbid disease in various disease categories (Amital et al., 2013). On the other hand, using commercial claims data, a >30 % increase in prevalence of comorbid conditions such as muscle and joint pain, anxiety and panic disorder, fatigue, headache/migraine was found in TRD patients compared to non-TRD MDD patients (Kubitz et al., 2013). In a recent study using Danish prescription registry data of 154,513 patients, 8294 patients were identified for TRD as defined by having at least two shifts in treatment regimens (Madsen et al., 2021). Patients with TRD had higher prevalence of prior medical conditions related to the immune or neurological systems, musculoskeletal disorders, and migraine. For subsequent medical conditions, TRD patients were found to have high prevalence for a broader spectrum of disease categories including cardiovascular, endocrine, and neurological disorders (Madsen et al., 2021). These observations are consistent with findings from the present study.

Depression in patients with cardiovascular disease is independently associated with progression of heart disease, major adverse cardiac events, and mortality (Carney and Freedland, 2009). Among patients with coronary artery disease (CAD), depression is common. Approximately 30 % of patients with CAD have elevated depressive symptoms, and 15 % to 20 % meet criteria for MDD, a rate that is 2 to 3 times higher than in the general population (Serrano et al., 2011). Ho et al. investigated factors associated with the risk of developing CAD in patients with MDD, and reported that severity of depression interacted with triglyceride level to increase the Framingham risk score (Ho et al., 2018) Depression prevalence is comparably elevated in patients with heart failure (Zambrano et al., 2020). Among patients with myocardial infarction (MI) and MDD, TRD was strongly associated with long-term mortality (Glassman et al., 2009). In a meta-analysis, the overall relative risk for the development of coronary heart disease (CHD) in depressed subjects was 1.64 (Rugulies, 2002). These observations are consistent with the findings from the current study. While TRD and non-TRD MDD patients have essentially the same odds of being diagnosed with CVD at baseline, a higher percentage of TRD patients developed CHD as shown by the corresponding odds ratio for heart failure (OR = 1.35) and ischemic heart disease (OR = 1.38) at follow-up.

While the association between depression and COPD has been well documented (Putman-Casdorph and McCrone, 2009), the prevalence of COPD in TRD patients has not been explicitly investigated. In a systematic review and meta-analysis, Zhang et al. investigated prevalence of depressive symptoms in patients with COPD and concluded that compared to a control group without COPD, individuals with COPD were significantly more likely to have depressive symptoms (Zhang et al., 2011) Findings from the current study suggest that TRD patients have an increased risk of developing COPD diagnosis over time, although both TRD and non-TRD MDD patients have about the same risk of being diagnosed with COPD at baseline.

Previous studies have confirmed a high prevalence of depression and anxiety among patients with chronic kidney disease (CKD) (Bautovich et al., 2014). One study reported that 23.7 % of patients with CKD have depression (Amira, 2011). Depression among those with CKD has been estimated to be even greater than that reported for patients with other chronic diseases (Palmer et al., 2013). Furthermore, depression in CKD has been associated with multiple poor outcomes (Hedayati et al., 2010). However, the reverse association of prevalence of CKD in TRD patients has been less studied. In one analysis, the estimated odds ratio was 0.77 (women) and 0.95 (men) at baseline and hazard ratio of 1.12 (women) and 1.18 (men) at follow-up (Madsen et al., 2021). We found an odds ratio of 1.21 at baseline and 1.53 at follow-up for diagnosis of CKD among TRD patients, which is higher than the values reported in the above study and needs to be investigated further.

There has been a paucity of research on the prevalence of stroke and transient ischemic diseases in patients with TRD. In a meta-analysis of polymorphisms of the serotonin transporter genes, Mak et al. reported that post-stroke depression was positively associated with the homozygous short variation (S) allele genotype of the 5-HTTLPR (SS) and negatively associated with the homozygous long variation (L) allele genotype of the 5-HTTLPR (LL) and PSD (Mak et al., 2013). Madsen et al. estimated an odds ratio of 1.10 for women and 0.70 for men for prior diagnosis of stroke in TRD patients. This is lower than the observed odds ratio 1.41 at the baseline and 1.57 during the follow-up period we observed for the TRD patients compared to non-TRD MDD patients.

Whereas comorbid depression is common with rheumatoid arthritis and leads to worse health outcomes (Margaretten et al., 2011), prevalence of RA and osteoarthritis in TRD patients has not been previously studied. In a systematic review on the bidirectional association between rheumatoid arthritis (RA) and depression, Ng et al. concluded that RA patients had a 47 % greater risk of incident depression compared to controls (Ng et al., 2022). Lue et al. studied the role of interleukin (IL)-17 in anxiety and depression in RA patients and found that IL-17 levels were significantly higher in RA patients with depression than in patients without depression (Liu et al., 2012). Ho et al. investigated clinical and psychosocial factors associated with depression and anxiety in RA patients and found that low income, high levels of rheumatoid factor and poor mental health were associated with depression in RA (Ho et al., 2011). The odds ratio of 1.17 at baseline and 1.52 during follow-up in the current study suggest an increased risk of developing RA and osteoarthritis in TRD patients compared to non-TRD MDD patients. Similarly, the increased odds ratio from 1.38 to 1.65 suggest increased risk of developing anemia in TRD patients compared to non-TRD MDD patients. There have been multiple studies examining the association between depression and hip fracture. A recent meta-analysis concluded that patients with depression had a higher risk of hip fracture than non-depressed patients (Shi et al., 2019). However, the prevalence of pelvic and hip fracture in TRD patients has not been previously characterized. The observed odds ratio of 1.44 at baseline and 2.14 during follow-up is significant and suggests that TRD patients are at significantly increased risk of pelvic/hip fractures over time than non-TRD MDD patients.

The association between depression and cancer has been extensively studied. The prevalence of depression in cancer patients exceeds that observed in the general population, and the increased prevalence is not solely explained by the psychosocial stress associated with the diagnosis. Biomarkers such as cytokines are believed to contribute to symptoms overlapping those of clinical depression and increased inflammation in patients with cancer (Sotelo et al., 2014). Madsen et al. reported an odds ratio of 0.79 (women) and 0.85 (men) for prior diagnosis of cancer in TRD patients, and risk ratio of 1.07 (women) and 1.01 (men) for subsequent diagnosis of cancers in TRD patients compared to non-TRD MDD cohorts. Findings from the present study, however, demonstrated increased prevalence of various cancers at the baseline and follow-up period.

Unlike medical comorbidity, multiple studies have reported on the economic burden and healthcare utilization of TRD patients compared to non-TRD MDD patients (Brenner et al., 2021; Greenberg et al., 2015; Jaffe et al., 2019; Li et al., 2020; Mahlich et al., 2018; Olfson et al., 2018). These studies have consistently shown significantly higher healthcare utilization and economic burden for TRD than non-TRD MDD patients. Ho et al. reported that patients with severe depressive disorder incurred significantly higher annual direct and indirect costs compared to those with mild or moderate depressive disorders (Ho et al., 2013). The findings from the current study further support those results. During the study period from 2010 through 2020, both at a patient level and individual encounter level, TRD patients had significantly high ED visits, ED visits admitted to inpatient hospital, and inpatient visits. TRD patients were admitted at double the rate of non-TRD MDD for ED visits and ED visits admitted to inpatient hospital stay when the encounters are for depression and anxiety. Similarly, TRD patients were admitted for inpatient hospital stays at a significantly higher rate than non-TRD MDD patients for all-cause, depression and anxiety, and depression alone visits. For inpatient hospital stay, TRD patients generally stayed longer (~1 day) compared to non-TRD MDD patients, consistent with previous observations (Olfson et al., 2018). Comprehensive data on healthcare utilization of TRD patients on individual medical condition is limited. As shown in Table 8, TRD patients seeking significantly higher level of acute care for various medical conditions compared to non-TRD MDD patients is also consistent with the high prevalence of these conditions among TRD patients.

The present study faces some challenges of EHR based cohort analysis as compared to clinical trials or survey research (Pathak et al., 2013). Clinical trials or population survey studies obtain data designed to address a specific research question, whereas EHR data were collected for clinical care. Despite the size and multiple collaborating health systems within the INSIGHT-CRN, it is an open system with data limited to few aspects of patient care. The absence of information on depression symptom severity is a case in point. PHQ-9, Hamilton Rating Scale for Depression (HAM—D), or other depression severity screening instruments that clinicians routinely administer and document either as structured or unstructured data in the EHR can be used to measure depression symptom severity. However, the INSIGHT-CRN data currently does not include measurements of depression severity screening instruments. In addition, the lack of information on antidepressant adherence is a major challenge in EHR based cohort analyses. It is estimated that nearly half of the patients discontinue antidepressants by 6 months (Sansone and Sansone, 2012). EHR systems generally do not collect this information routinely, and although INSIGHT-CRN collects data on medication orders, it does not include data on patient medication refills and adherence. It is also possible that some patients in the TRD group changed medications frequently due to side effects or tolerability concerns rather than lack of response, a distinction that depression scales could help clarify. Yet another limitation is the problem with the direction of causality between TRD and the medical comorbidities. Often with these medical conditions, clinicians have to change antidepressants because of medication interactions or to minimize side-effects that might worsen the impact of the medical condition. Findings from the present study should therefore be interpreted in the context of these challenges of EHR-based cohort studies.

5. Conclusion

In a large-scale data analysis, we investigated the association between treatment resistant depression and medical comorbidity and healthcare utilization using the EHR data of over 3.3 million patients from INSIGHT-CRN in New York City. The large patient population from multiple health systems in the current study is more representative of a community level patient population as against, for example, randomized control trials involving a small cohort or claims data from a single payer. EHRs provide a more comprehensive and reliable diagnosis made directly by physicians. Consistent with previous reports, TRD patients compared to non-TRD MDD patients were found to have higher levels of anxiety disorder and medical comorbidities. We further identified some differences in medical conditions such as cardiovascular disease, chronic kidney diseases, arthritis, hip/pelvic fractures, and cancer that are significantly higher than previously reported, which warrant additional investigations. Furthermore, TRD patients incur a higher healthcare utilization than non-TRD MDD patients. When compared to patients without other mental illness diagnoses, both TRD and non-TRD MDD patients had significantly high levels of anxiety disorder and physical comorbidities. In conclusion, the higher disease burden and increasing healthcare utilization of TRD patients when compared to non-TRD MDD patients highlight challenges of developing interventions and care coordination strategies to meet their complex clinical needs. TRD patients may require closer medical follow up due to risk of developing medical diseases and with potentially greater adverse consequences of missing routine follow-up appointments.

Supplementary Material

Supplementary Material

Acknowledgement

This study was supported by the National Institute of Mental Health (NIMH) grants: R01MH121922, R01MH121924, R01MH121923, and R01MH121921.

Abbreviations:

TRD

Treatment resistant depression

MDD

Major depressive disorder

EHR

Electronic health records

Footnotes

Declaration of competing interest

Each of the authors confirms that they have no conflict of interest to disclose.

Disclosure

None.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jad.2022.12.044.

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