The Impact of Ethnicity on Antidepressant Therapy

 

Case # 29- The depressed man who thought he was out of options. 

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            Depression has become a common mental disorder in our elderly population. This has caused a global concern for occur, geriatric patients, as depression often results in a significant burden for families as well as communities. Elderly people who suffer from depression may have an inferior baseline and record for medical assessments than those individuals without depression. Despite consistent evidence of the effectiveness of antidepressants for many with depression,3particularly those with more severe depression, remission rates are disappointingly low. An AHRQ-sponsored report found that only 46% of patients experienced remission from depression during 6 to 12 weeks of treatment with second-generation antidepressants. One major reason for this issue is non-adherence to medications and treatment plans. Studies have shown that patients’ age, race and ethnicity are consistently associated with predictions of outcomes. (Rossom et al., 2016). 

            This case study involves a 69-year old man whose chief complaint is unremitting, chronic depression. After several years of medications and treatments, he feels hopeless for a recovery from his chronic depression. This assignments seeks to explore his family and social support systems, diagnostic testing, differential diagnosis and pharmacologic treatment options for this patient. 

Questions for the client

  1. How have you been sleeping lately? 
  2. How many times in the last week have you had feelings of hopelessness?
  3. Are you having thoughts of harming yourself? Do you have a plan?

These questions are an important yet simple place to start when treating patients. Sleep disturbances plague much of the world’s population and have shown to be a major indicator for mental health issues. Changes in sleep neurophysiology are often observed in depressive patients, and impaired sleep is, in many cases, the chief complaint of depression (Armitage, 2007). Depressed patients with sleep disturbance are likely to present more severe symptoms and difficulties in treatment. In addition, persistent insomnia is the most common residual symptom in depressed patients and is considered a vital predictor of depression relapse and may contribute to unpleasant clinical outcomes (Hinkelmann et al., 20120. Questions involving feelings of hopelessness and suicidal ideations with or without a plan relate to issues of patient safety. Across psychiatric disorders, hopelessness is associated with suicidal ideation and behavior. A meta-analysis of 166 longitudinal studies (sample size not reported) found that hopelessness was associated with an increased risk of ideation (Ribeiro, Huang, Fox, & Franklin, 2018).

Family and social support system

     Family and social support systems are imperative for any patient in recovery. If the patient is agreeable to discussions with family members, then a discussion with his wife would be helpful. Research has shown that strong support systems have a positive effect with those suffering from depression. The perceived availability of support from others can serve as a buffer against the development of a depressive episode. Positive family relationships can improve mental ill-health, while support from family members often facilitates recovery. In contrast, low levels of support have long been associated with the onset of depressive symptoms, delayed recovery, and a tendency towards chronic depression (Lyberg, 2013).

  1. Please tell me about your experiences with your husband on this journey with his depression.
  2. Have there been any significant changes or triggers recently at home? (i.e. deaths in the family, issues with children, living situation).
  3. Have there been any treatments in the past where you have noticed positive changes in your husband?

Physical exams and diagnostic tests

            A complete exam, history and physical will be required for this patient. Given his age and mental health and treatment history, this will give the provider insight into the client’s physical health. Depression may co-occur with medical problems including heart disease, diabetes or cancer. Mental health issues may increase during poor physical health and cause difficulties in managing medical problems in addition to mental health issues. 

            Full blood work analysis including Venlafaxine therapeutic blood levels, CBC, CMP and LFT should be conducted for indicators relating to liver function, thyroid function, anemia, calcium and vitamin D levels. Thyroid function tests should be conducted as there has been a known association between hypothyroid and depressive symptoms. Depression is seen in autoimmune thyroid disorders, both in thyroiditis and normal thyroid function. The presence of thyroid peroxidase antibodies was proposed to be a vulnerability marker for depression (Gibney, 2012). Genotyping may be considered as this approach has shown to be helpful in patients who remain treatment-resistant. 

Differential diagnoses

  1. Treatment resistant depression (TRD): This is the most likely and refers to the treatment of those with major depressive disorder (MDD) and the failure to create acceptable outcomes. There are several reasons why a patient may be treatment-resistant including ethnicity, gender, age, biologic factors and genetic variants.
  2. Adjustment disorder
  3. Medication-Induced Depressive Disorder

Pharmacologic agents

  1. Venlafaxine (VLX). The client is currently on 450 mg XR with good results. Venlafaxine (VLX) is a serotonin–norepinephrine reuptake inhibitor marketed for the treatment of depression disorders. It provides a reasonable second-step choice for patients with depression and is used extensively in psychiatric practice. VLX is primarily metabolised into the active metabolite O-desmethyl-VLX (ODV), with serotonin and noradrenaline reuptake inhibition properties. The mean plasma half-lives (± SD) of VLX and ODV are 5(±2) hours and 11(±2) hours, respectively (Lloret-Linares et al., 2017). Pharmacodynamic and pharmacokinetic considerations include the prolonged half-life and reduced clearance. Due to this concern, it is important to continue to monitor for renal and hepatic impairment.
  2. Desvenlafaxine up to 200 mg dose. This SNRI inhibits the reuptake of serotonin and norepinephrine. Desvenlafaxine, as desvenlafaxine succinate, is a novel salt form of the isolated major active metabolite (O-desmethylvenlafaxine) of the SNRI venlafaxine. Desvenlafaxine appears to be well absorbed after oral administration, and it has a large volume of distribution. Desvenlafaxine can be taken without regard to meals, and the absolute oral bioavailability after oral administration is approximately 80%.The mean terminal half-life (t1/2) is approximately 11 hours, and mean time to peak plasma concentrations (Tmax) after oral administration is approximately 7.5 hours. The pharmacokinetics of desvenlafaxine are minimally affected by food. Plasma protein binding of desvenlafaxine is low (30%) and independent of drug concentration (Liebowitz,& Tourian, 2010). 

Take-home points

 Take home points from this assignment are to never give up on finding the right therapies for our clients. There may be several reasons why a specific medication is not working as expected and by considering Pharmacodynamic and pharmacokinetic factors may assist in gaining insight as therapeutic drug monitoring may offer resolve. Pharmacogenetics is a subcategory of pharmacogenomics that refers to the role of genetic variation in response to a drug. Pharmacogenetics generally is used to refer to a specific DNA polymorphism or coding variant rather than epigenetic or transcriptomic changes across the genome. In practice, pharmacogenetics and pharmacogenomics are often used interchangeably. Pharmacokinetics (PK) refers to how a drug moves through an individual’s body.  A drug’s PK includes its absorption, distribution, metabolism, and elimination, all of which affect the drug’s effect by altering the drug’s concentration at its site of action. (Preskorn & Hatt, 2013). The importance of this lies with how much of the drug is reaching the brain, not necessarily how much of the drug is taken orally. 

References

Armitage R. Sleep and circadian rhythms in mood disorders. Acta Psychiatric Scand Suppl. 2007;115(433):104–115. 

Gibney SM, Drexhage HA. Evidence for a dysregulated immune system in the etiology of psychiatric disorders. J Neuroimmune Pharmacol. 2013;8(4):900–920. doi: 10.1007/s11481-013-9462-8. 

Hinkelmann K, Moritz S, Botzenhardt J, et al. Changes in cortisol secretion during antidepressive treatment and cognitive improvement in patients with major depression: a longitudinal study. Psychoneuroendocrinology. 2012;37(5):685–692. 

Liebowitz, M. R., & Tourian, K. A. (2010). Efficacy, safety, and tolerability of Desvenlafaxine 50 mg/d for the treatment of major depressive disorder:a systematic review of clinical trials. Primary care companion to the Journal of clinical psychiatry, 12(3), PCC.09r00845. https://doi.org/10.4088/PCC.09r00845blu

Lloret-Linares, C., Daali, Y., Chevret, S., Nieto, I., Molière, F., Courtet, P., Galtier, F., Richieri, R. M., Morange, S., Llorca, P. M., El-Hage, W., Desmidt, T., Haesebaert, F., Vignaud, P., Holtzmann, J., Cracowski, J. L., Leboyer, M., Yrondi, A., Calvas, F., Yon, L., … Bellivier, F. (2017). Exploring venlafaxine pharmacokinetic variability with a phenotyping approach, a multicentric french-swiss study (MARVEL study). BMC pharmacology & toxicology, 18(1), 70. https://doi.org/10.1186/s40360-017-0173-2

Lyberg, A., Holm, A. L., Lassenius, E., Berggren, I., & Severinsson, E. (2013). Older persons’ experiences of depressive ill-health and family support. Nursing research and practice, 2013, 837529. https://doi.org/10.1155/2013/837529

Preskorn, S. H., & Hatt, C. R. (2013). How Pharmacogenomics (PG) Are Changing Practice. Journal of Psychiatric Practice, 19(2), 142–149. doi: 10.1097/01.pra.0000428559.01953.73

Rossom, R. C., Shortreed, S., Coleman, K. J., Beck, A., Waitzfelder, B. E., Stewart, C., Ahmedani, B. K., Zeber, J. E., & Simon, G. E. (2016). ANTIDEPRESSANT ADHERENCE ACROSS DIVERSE POPULATIONS AND HEALTHCARE SETTINGS. Depression and anxiety, 33(8), 765–774. https://doi.org/10.1002/da.22532

Ribeiro, J., Huang, X., Fox, K., & Franklin, J. (2018). Depression and hopelessness as risk factors for suicide ideation, attempts and death: Meta-analysis of longitudinal studies. British Journal of Psychiatry, 212(5), 279-286. doi:10.1192/bjp.2018.27

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