Selecting Antidepressants Based on Medical History and Stress Mechanism

Purpose At present, clinicians typically prescribe antidepressants based on the widely accepted “serotonin hypothesis.” This study explores an alternative mechanism, the stress mechanism, for selecting antidepressants based on patients’ medical history. Methods This study investigated clinicians’ prescribing patterns for the 15 most common antidepressants, including amitriptyline, bupropion, citalopram, desvenlafaxine, doxepin, duloxetine, escitalopram, fluoxetine, mirtazapine, nortriptyline, paroxetine, ropinirole, sertraline, trazodone, and Venlafaxine. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to identify factors that affect the remission of depression symptoms after receiving an antidepressant. Results The study found that a wide range of factors influenced the propensity of clinicians to prescribe antidepressants, with the number of predictors ranging from 51 to 206 variables. The prevalence of prescribing an antidepressant ranged from 0.5% for doxepin to 24% for the combination of more than one antidepressant. The area under the receiver operating curves (AROC) ranged from 77.2% for venlafaxine to 90.5% for ropinirole, with an average AROC of 82% for predicting the propensity of medications. A variety of diagnoses and prior medications affected remission, in agreement that the central mechanism for the impact of medications on the brain is through stress reduction. For example, psychotherapy, whether done individually or in a group, whether done for a short or long time, and whether done with evaluation/assessment or not, had an impact on remission. Specifically, teenagers and octogenarians were less likely to benefit from bupropion, citalopram, escitalopram, fluoxetine, and sertraline compared to patients between 40 and 65 years old. The findings of this study suggest that considering a patient’s medical history and individual characteristics is crucial for selecting the most effective antidepressant treatment. Conclusions Many studies have raised doubt about the serotonin hypothesis as the central mechanism for depression treatment. The identification of a wide range of predictors for prescribing antidepressants highlights the complexity of depression treatment and the need for individualized approaches that consider patients’ comorbidities and previous treatments. The significant impact of comorbidities on the response to treatment makes it improbable that the mechanism of action of antidepressants is solely based on the serotonin hypothesis. It is hard to explain how comorbidities lead to the depletion of serotonin. These findings open up a variety of courses of action for the clinical treatment of depression, each addressing a different source of chronic stress in the brain. Overall, this study contributes to a better understanding of depression treatment and provides valuable insights for clinicians in selecting antidepressants based on patients’ medical history.


Introduction
Depression is treatable, but the mechanism of response to treatment is not yet fully understood. There are two types of treatment options available for depression: pharmacological and non-pharmacological. Nonpharmacological treatments include physical activity, cognitive behavior therapy (CBT), and general support [1,2]. Studies showed that exercise-based treatments for depression affected the brain, including the prefrontal cortex, anterior cingulate cortex, hippocampus, and corpus callosum [1]. Antidepressants are a popular pharmacological treatment choice for depression, and one of the most frequently prescribed medications in the USA. The major classes of antidepressants in practice include selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), norepinephrine and There is an alternative mechanism of action for antidepressants. We assumed that chronic stress, introduced by a variety of brain and body illnesses, affects stress, corticotropin-releasing factor (CRF) 1, endocrine, and other autonomic responses [18]. Brain and pituitary corticotropin-releasing factor receptors mediate endocrine, behavioral, and autonomic responses to stress [32]. Eventually, repeated stress affects the performance of the hypothalamic-pituitary-adrenal (HPA) axis [33,34]. Then, the activation of the HPA axis could be the key mechanism for the patient's response to antidepressants [35][36][37][38][39][40]. This mechanism explains the role of chronic pain in depression [41], why chronic sleep deprivation increases depression [42] and exercise reduces mild depression [1,43], all of which affect stress levels. This opens up a wide variety of courses of action for the clinical treatment of depression, each addressing a different source of chronic stress.
A key assumption of the stress reduction mechanism is that patients' comorbidities affect their responses to depression treatment. Several diagnoses are known to affect response to depression treatment, including cognitive disorders [12], substance use disorders [44,45], obesity [46,47], insomnia [48], cardiovascular or cerebrovascular diseases [49][50][51], hormone imbalances [52][53][54], cancer [55,56], and posttraumatic stress disorder [57]. However, a comprehensive list is not available. The purpose of this paper is to identify a more complete list of comorbidities that affect response to treatment and therefore further support the role of stress mechanism in the treatment of depression.

Source and size of data
The cohort was organized using claims data available through OptumLabs. The data included 71,721,417 patients during the timeframe between January 1, 2001, and December 31, 2018. Among these, 11,472,471 took one or more antidepressants and 6,897,748 also had a diagnosis of major depression. We excluded 2,790,721 patients who had a short medical history (defined as being eligible for the health plan for at least one year prior to their first antidepressant). After all inclusions and exclusions, we focused the analysis on 3,678,082 unique patients in 10,221,145 treatment episodes. The average follow-up period was 2.93 years, post their first antidepressant use. This cohort included a total of 15,096,055 person-years of data. Details of the selection of the cohort, including codes used to select the cohort, are available in Alemi et al. [26].

Measurement of remission
Patient-reported remission of depression symptoms was not consistently available in our data. Therefore, a surrogate measure was defined based on patterns of use of antidepressants, including (1) duration of use, (2) reaching therapeutic dose, (3) not switching from one antidepressant to another, (4) not augmenting the antidepressant with another medication, and (5) low use of antidepressants prior to the start of this medication [58].

Measurement of depression comorbidities
The study statistically controlled for patients' history of illness-affected responses to antidepressants. Every diagnosis (i.e., International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9CM)) is treated as a separate binary variable. A total of 16,811 outpatient predictors derived from the patients' diagnoses were included in the analysis. For example, we statistically controlled for cognitive disorders, substance use disorders, obesity, diabetes, insomnia, cerebrovascular diseases, hormone imbalances, cancer, posttraumatic stress disorder, and other diseases [18].

Measurement of treatment of comorbidities
The study also statistically controlled for procedures or medications that affected responses to antidepressants. We defined a separate variable for each mental health procedure identified using either Current Procedural Terminology version 4 (CPT4) or ICD codes. A total of 4,364 binary procedure variables for mental health encounters were included in the analysis. We also included 4,253 medications as generic drug names, measured through the pharmacy claims data [10].

Methods of analysis
The least absolute shrinkage and selection operator (LASSO) logistic regression was used to identify factors that affect remission of depression symptoms after receiving one of the 15 most common antidepressants, including amitriptyline, bupropion, citalopram, desvenlafaxine, doxepin, duloxetine, escitalopram, fluoxetine, mirtazapine, nortriptyline, paroxetine, ropinirole, sertraline, trazodone, and venlafaxine. The area under the receiver operating curves (AROC) was used to measure the performance of regression models.

Results
We observed that clinicians prescribed an antidepressant based on patients' medical conditions including their comorbidities, procedures, and medication history. The number of robust variables for predicting the propensity of prescribing antidepressants ranged from 51 to 206 predictors ( Table 1). The "Other" category included a combination of medications. The prevalence of prescribing an antidepressant ranged from 0.5% for doxepin to 24% for Other (e.g., combination). The AROC ranged from 77.2% for venlafaxine to 90.5% for ropinirole. The average AROC for predicting the propensity of medications was 82%. These data suggest that the regression equations explained a large portion of the variance in response to treatment.             Table 3 provides a partial list of robust predictors of remission for the top 5 most common antidepressants. A complete list is available in the Appendices. An examination of the coefficients of these predictors shows that psychotherapy, whether done individually or in a group, whether done for a short or long time, and whether done with evaluation/assessment or not, had an impact on remission. If the patient had a history of participating in psychotherapy and depression had returned, they were unlikely to benefit from citalopram, escitalopram, fluoxetine, or sertraline, but they could benefit from bupropion. The same was also true if the patient had gone through a session for pharmacological management or psychiatric evaluations: they would benefit from bupropion, but not the other remaining four common antidepressants. Teenagers and octogenarians were less likely to benefit from these five antidepressants than 40-to 65-yearold patients, although considerable variation existed.

Significant and robust independent variables in one-
year medical history

Discussion
Depression is heterogeneous. There are 227 possible ways to meet the symptom criteria for major depressive disorder [59]. For many people, this makes it difficult to find an effective treatment since there is no onesize-fits-all approach. Clinicians prescribe antidepressants based on the "serotonin hypothesis," but only about 40% of patients have an improvement in their symptoms following the first treatment [60]. Thus, the majority of patients do not benefit from their first treatment, typically an SSRI. The serotonin hypothesis is a part of the monoamine hypothesis, which also includes the roles of dopamine and norepinephrine.
Additionally, factors such as neuroinflammation, circadian rhythms, genes, environment, and neurotrophic factors are known to play roles in depression. The role of comorbidities in the management of depression has been known, but it has not always been clear by what mechanism comorbidities affect depression. In other diseases, comorbidities worsen the prognosis of patients by increasing stress on vital functions. The significant impact of comorbidities on the response to treatment makes it improbable that the mechanism of action of antidepressants is solely based on the serotonin hypothesis. This study suggests that it is more plausible that the effectiveness of depression treatment is linked to the regulation of stress in the brain. The hypothesis is that sustained stress and pain is the mechanism for the development of depression. Tailoring treatment for each individual based on his or her own conditions may add some benefit.
Many studies have shown that patients' physical health is closely related to their mental health. People with chronic diseases such as cancer, heart disease, obesity, and diabetes are at high risk of depression. Meanwhile, people with depression are also at high risk of these chronic diseases [61]. Emotional impairment is often a reaction to organic illness, while depression can worsen comorbidities and increase mortality [62]. In ordinary psychiatric practice, psychiatrists may overlook the physical health of their patients. To address this issue, the World Psychiatric Association (WPA) has created a working group to encourage collaboration between psychiatrists and primary care physicians [63]. It is noteworthy that patients with comorbidities have been excluded from pharmaceutical clinical trials [64]. Medications may not be effective for a number of patients with a given diagnosis or comorbidities. Our study aimed to address this issue by investigating patients' medical history (i.e., diagnoses and prior medications) that affected remission.
Some data supported guidelines for the two-tiered prescription of antidepressants [6,65,66]. For example, if patients had experienced remission in their past antidepressants, they were likely to experience remission again no matter which of the five common antidepressants they used. Patients who had tried four or more antidepressants in the prior year, i.e., treatment-resistant patients, did not benefit from escitalopram or fluoxetine, which are generally known as tier 1 medications.
The stress mechanism is also supported by the large number of diagnoses that affect response to antidepressants, as listed in Table 2 and Table 3. There were 237 unique diagnoses that affected the selection of an antidepressant, too many to discuss in this paper. The full details of these relationships are provided in the Appendices; here, we mention a few of the findings. Patients with morbid obesity benefitted from escitalopram. Patients with multiple sclerosis benefited from fluoxetine. Patients with a history of myopia benefitted from bupropion. Patients with obstructive sleep apnea benefited most from escitalopram. Depressed patients in postpartum follow-up or with normal pregnancy were likely to experience symptom remission if they were prescribed citalopram.

Conclusions
This study aims to address the mixed findings regarding the serotonin hypothesis and the overreliance on serotonin in treating depression by providing a novel approach. The response to treatment is affected by the comorbidity of patients and their treatment. Since many comorbidities affect the response to treatment, it is unlikely that the mechanism of action of antidepressants is solely through the serotonin hypothesis. It is more likely that the response to depression treatment is through the regulation of stress in the brain. The selection of treatments is based on a patient's medical history, and the underlying mechanisms of their depression can provide insights into novel treatment techniques. Our findings open up a wide variety of courses of action for the clinical treatment of depression, each addressing a different source of chronic stress in the brain.

Appendices
The complete list of robust predictors of remission for the top 5 most common antidepressants is shown in Table 4.

Additional Information Disclosures
Human subjects: Consent was obtained or waived by all participants in this study. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an