Bidirectional associations between treatment-resistant depression and general medical conditions

Projecting the 10-year costs of care and mortality burden of depression until 2032: a Markov modelling study developed from real-world data

Background

Based on real-world data, we developed a 10-year prediction model to estimate the burden among patients with depression from the public healthcare system payer's perspective to inform early resource planning in Hong Kong.

Methods

We developed a Markov cohort model with yearly cycles specifically capturing the pathway of treatment-resistant depression (TRD) and comorbidity development along the disease course. Projected from 2023 to 2032, primary outcomes included costs of all-cause and psychiatric care, and secondary outcomes were all-cause deaths, years of life lived, and quality-adjusted life-years. Using the territory-wide electronic medical records, we identified 25,190 patients aged ≥10 years with newly diagnosed depression from 2014 to 2016 with follow-up until 2020 to observe the real-world time-to-event pattern, based on which costs and time-varying transition inputs were derived using negative binomial modelling and parametric survival analysis. We applied the model as both closed cohort, which studied a fixed cohort of incident patients in 2023, and open cohort, which introduced incident patients by year from 2014 to 2032. Utilities and annual new patients were from published sources.

Findings

With 9217 new patients in 2023, our closed cohort model projected the 10-year cumulative costs of all-cause and psychiatric care to reach US$309.0 million and US$58.3 million, respectively, with 899 deaths (case fatality rate: 9.8%) by 2032. In our open cohort model, 55,849-57,896 active prevalent cases would cost more than US$322.3 million and US$60.7 million, respectively, with more than 943 deaths annually from 2023 to 2032. Fewer than 20% of cases would live with TRD or comorbidities but contribute 31-54% of the costs. The greatest collective burden would occur in women aged above 40, but men aged above 65 and below 25 with medical history would have the highest costs per patient-year. The key cost drivers were relevant to the early disease stages.

Interpretation

A limited proportion of patients would develop TRD and comorbidities but contribute to a high proportion of costs, which necessitates appropriate attention and resource allocation. Our projection also demonstrates the application of real-world data to model long-term costs and mortality, which aid policymakers anticipate foreseeable burden and undertake budget planning to prepare for the care need in alternative scenarios.

Funding

Research Impact Fund from the University Grants Committee, Research Grants Council with matching fund from the Hong Kong Association of Pharmaceutical Industry (R7007-22).

Explainable multimodal prediction of treatment-resistance in patients with depression leveraging brain morphometry and natural language processing

Although 20 % of patients with depression receiving treatment do not achieve remission, predicting treatment-resistant depression (TRD) remains challenging. In this study, we aimed to develop an explainable multimodal prediction model for TRD using structured electronic medical record data, brain morphometry, and natural language processing. In total, 247 patients with a new depressive episode were included. TRD-predictive models were developed based on the combination of following parameters: selected tabular dataset features, independent components-map weightings from brain T1-weighted magnetic resonance imaging (MRI), and topic probabilities from clinical notes. All models applied the extreme gradient boosting (XGBoost) algorithm via five-fold cross-validation. The model using all data sources showed the highest area under the receiver operating characteristic of 0.794, followed by models that used combined brain MRI and structured data, brain MRI and clinical notes, clinical notes and structured data, brain MRI only, structured data only, and clinical notes only (0.770, 0.762, 0.728, 0.703, 0.684, and 0.569, respectively). Classifications of TRD were driven by several predictors, such as previous exposure to antidepressants and antihypertensive medications, sensorimotor network, default mode network, and somatic symptoms. Our findings suggest that a combination of clinical data with neuroimaging and natural language processing variables improves the prediction of TRD.

Preclinical models of treatment-resistant depression: challenges and perspectives

Treatment-resistant depression (TRD) is a subgroup of major depressive disorder in which the use of classical antidepressant treatments fails to achieve satisfactory treatment results. Although there are various definitions and grading models for TRD, common criteria for assessing TRD have still not been established. However, a common feature of any TRD model is the lack of response to at least two attempts at antidepressant pharmacotherapy. The causes of TRD are not known; nevertheless, it is estimated that even 60% of TRD patients are so-called pseudo-TRD patients, in which multiple biological factors, e.g., gender, age, and hormonal disturbances are concomitant with depression and involved in antidepressant drug resistance. Whereas the phenomenon of TRD is a complex disorder difficult to diagnose and successfully treat, the search for new treatment strategies is a significant challenge of modern pharmacology. It seems that despite the complexity of the TRD phenomenon, some useful animal models of TRD meet the construct, the face, and the predictive validity criteria. Based on the literature and our own experiences, we will discuss the utility of animals exposed to the stress paradigm (chronic mild stress, CMS), and the Wistar Kyoto rat strain representing an endogenous model of TRD. In this review, we will focus on reviewing research on existing and novel therapies for TRD, including ketamine, deep brain stimulation (DBS), and psychedelic drugs in the context of preclinical studies in representative animal models of TRD.

Clinical insights into the cross-link between mood disorders and type 2 diabetes: A review of longitudinal studies and Mendelian randomisation analyses

Mood disorders and type 2 diabetes mellitus (T2DM) are prevalent conditions that often co-occur. We reviewed the available evidence from longitudinal and Mendelian randomisation (MR) studies on the relationship between major depressive disorder (MDD), bipolar disorder and T2DM. The clinical implications of this comorbidity on the course of either condition and the impact of antidepressants, mood stabilisers, and antidiabetic drugs were examined. Consistent evidence indicates a bidirectional association between mood disorders and T2DM. T2DM leads to more severe depression, whereas depression is associated with more complications and higher mortality in T2DM. MR studies demonstrated a causal effect of MDD on T2DM in Europeans, while a suggestive causal association in the opposite direction was found in East Asians. Antidepressants, but not lithium, were associated with a higher T2DM risk in the long-term, but confounders cannot be excluded. Some oral antidiabetics, such as pioglitazone and liraglutide, may be effective on depressive and cognitive symptoms. Studies in multi-ethnic populations, with a more careful assessment of confounders and appropriate power, would be important.

Treatment-resistant depression and risk of autoimmune diseases: evidence from a population-based cohort and nested case-control study

Recent literature indicates that patients with depression had increased immune activation. We hypothesised that treatment-resistant depression (TRD), an indicator of non-responsive depression with long-term dysregulated inflammation, could be an independent risk factor for subsequent autoimmune diseases. We performed a cohort study and a nested case-control study to examine the association between TRD and risk of autoimmune diseases, and to explore potential sex-specific difference. Using electronic medical records in Hong Kong, we identified 24,576 patients with incident depression between 2014 and 2016 without autoimmune history and followed up from diagnosis to death or December 2020 to identify TRD status and autoimmune incidence. TRD was defined as having at least two antidepressant regimens and the third regimen to confirm previous treatment failures. Based on age, sex and year of depression, we matched TRD patients 1:4 to the non-TRD in the cohort analysis using nearest-neighbour matching, and matched cases and controls 1:10 using incidence density sampling in the nested case-control analysis. We conducted survival analyses and conditional logistic regression respectively for risk estimation, adjusting for medical history. Across the study period, 4349 patients without autoimmune history (17.7%) developed TRD. With 71,163 person-years of follow-up, the cumulative incidence of 22 types of autoimmune diseases among the TRD patients was generally higher than the non-TRD (21.5 vs. 14.4 per 10,000 person-years). Cox model suggested a non-significant association (HR:1.48, 95% CI: 0.99-2.24, p = 0.059), whereas conditional logistic model showed a significant association (OR: 1.67, 95% CI: 1.10-2.53, p = 0.017) between TRD status and autoimmune diseases. Subgroup analysis showed that the association was significant in organ-specific diseases but not in systemic diseases. Risk magnitudes were generally higher among men compared to women. In conclusion, our findings provide evidence for an increased risk of autoimmune diseases in patients with TRD. Controlling chronic inflammation in hard-to-treat depression might play a role in preventing subsequent autoimmunity.

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

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.

Healthcare resource utilization in patients with treatment-resistant depression—A Danish national registry study

Objectives

To investigate healthcare resource utilization (HRU) and associated costs by depression severity and year of diagnosis among patients with treatment-resistant depression (TRD) in Denmark.

Methods

Including all adult patients with a first-time hospital contact for major depressive disorder (MDD) in 1996–2015, TRD patients were defined at the second shift in depression treatment (antidepressant medicine or electroconvulsive therapy) and matched 1:2 with non-TRD patients. The risk of utilization and amount of HRU and associated costs including medicine expenses 12 months after the TRD-defining date were reported, comparing TRD patients with non-TRD MDD patients.

Results

Identifying 25,321 TRD-patients matched with 50,638 non-TRD patients, the risk of psychiatric hospitalization following TRD diagnosis was 138.4% (95%-confidence interval: 128.3–149.0) higher for TRD patients than for non-TRD MDD patients. The number of hospital bed days and emergency department (ED) visits were also higher among TRD patients, with no significant difference for somatic HRU. Among patients who incurred healthcare costs, the associated HRU costs for TRD patients were 101.9% (97.5–106.4) higher overall, and 55.2% (50.9–59.6) higher for psychiatric services than those of non-TRD patients. The relative differences in costs for TRD-patients vs non-TRD patients were greater for patients with mild depression and tended to increase over the study period (1996–2015), particularly for acute hospitalizations and ED visits.

Limitations

TRD was defined by prescription patterns besides ECT treatments.

Conclusion

TRD was associated with increased psychiatric-related HRU. Particularly the difference in acute hospitalizations and ED visits between TRD and non-TRD patients increased over the study period.

Healthcare utilization, costs, and productivity losses in treatment-resistant depression in Finland - a matched cohort study

BACKGROUND

Due to its relatively high prevalence and recurrent nature, depression causes a major burden on healthcare systems, societies and individuals. Our objective was to investigate healthcare resource utilization and costs associated with treatment-resistant depression (TRD) compared with non-treatment-resistant depression in Finland.

METHODS

Of all patients aged 16-65 years and diagnosed with depression in Finland during 2004-2016, persons with TRD (N = 15,405) were identified from nationwide registers and matched 1:1 with comparison persons with depression who initiated antidepressant use but did not have TRD at the time of matching. TRD was defined as initiation of a third treatment trial after having failed two pharmacological treatment trials. Follow-up period covered 5 years after TRD or corresponding matching date (until end of 2018). Health care resource utilization was studied with negative binomial regression and costs of TRD (per patient per year) with generalized estimating equations, by adjusting for baseline costs, comorbidity and baseline severity of depression.

RESULTS

Persons with TRD (mean age 38.7, SD 13.1, 60.0% women) had more health care utilization and work disability (sick leaves and disability pensions), adjusted incidence rate ratio for work disability days was 1.72 (95% CI 1.64-1.80). This resulted in 1.9-fold higher total costs for persons with TRD (15,907 versus 8335 EUR), adjusted mean difference 7572 (95% CI 7215-7929) EUR per patient per year, higher productivity losses (due to sick leaves and disability pensions, mean difference 5296, 95% CI 5042-5550), and direct healthcare costs (2003, 95% CI 1853-2151) compared with non-TRD patients. Mean difference was the highest during the first year after TRD (total costs difference 11,760, 95% CI 11,314-12,206) and the difference decreased gradually after that.

CONCLUSION

Treatment-resistant depression is associated with about two-fold cost burden compared with non-treatment-resistant depression.

Economic impact of treatment-resistant depression: A retrospective observational study

BACKGROUND

To determine the incidence of Treatment-Resistant Depression (TRD) in Spain and to estimate its economic burden, using real world data.

METHODS

A retrospective, observational-study was carried out using data from the BIG-PAC database®. Patients aged ≥18 years with a diagnosis of major depressive-disorder (MDD) who initiated a new antidepressant treatment in 2015-2017 were included. The patients were classified as TRD and non-TRD. Patients were classified as TRD if they had, during the first year of antidepressant treatment: a) failure with ≥2 antidepressants including the prescription of ≥3 antidepressants (N06A) or ≥2 antidepressant and ≥1 antipsychotic (N05A; including lithium) b) antidepressants administered for ≥ 4 weeks each, and c) the time between the end of one treatment and the initiation of the next was ≤ 90 days. Inherent limitations of data collection from databases should also be considered in this analysis (e.g., lack of information about adherence to treatment). Follow-up period: 18 months. The incidence rate was calculated as the number of TRD patients per 1,000 persons-year divided by the population attended.

OUTCOMES

direct healthcare and indirect costs. Two sensitivity analyses were performed varying the index date and the period used to define TRD patients (6 vs.12 months).

RESULTS

21,630 patients with MDD aged ≥ 18 years (mean age: 53.2 years; female: 67.2%) were analyzed, of whom 3,559 met TRD criteria, yielding a 3-year cumulative incidence of 16.5% (95%CI: 16%-17%) among MDD patients. The annual population incidence rate of TRD in 2015-2017, was 0.59, 1.02 and 1.18/1,000 person-years, respectively (mean: 0.93/1,000 person-year). Overall, mean total costs per MDD patient were €4,147.9, being higher for TRD than for non-TRD patients (€6,096 vs. €3,846; p<0.001): a) direct costs (€1,341 vs. €624; p<0.001), b) lost productivity (€1,274 vs. €821; p<0.001) and c) permanent disability (€3,481 vs. €2,401; p<0.001, adjusted). Sensitivity analyses showed no differences with the reported results.

CONCLUSIONS

The population based TRD incidence in Spain was similar to recent data from other European countries. TRD is associated with greater resource use and higher costs compared with non-TRD patients.