Introduction
Bipolar disorder is a serious mental disorder that is typified by drastic mood fluctuations between mania and depression. The lifetime prevalence of this disorder is about 2.4%.1 Bipolar disorder is a longstanding disease with affective incidents that may elicit substantial personal suffering, social dysfunction and negative outcomes on the sufferers’ mental, social, and professional wellbeing. The treatment of bipolar disorder in developed countries ranges from 3308 to 13,402 US dollars yearly per patient.2 Even though several efficient for the disorder exist, misdiagnoses often lead to complications such as drug-resistance, reduction in cognitive functioning, and rapid-cycling.3
Additionally, the side effects associated with some of the medications lead to high rates of non-adherence in patients. Pharmacogenetic testing entails examining how an individual’s genes predict their response to medications.2 Nevertheless, despite this knowledge, high numbers of treatment non-adherence continue to be reported in patients with bipolar disorder.
The key research question that this study seeks to answer is “Will developing a treatment model, to include pharmacogenetic testing as routine clinical decision support, increase treatment adherence in patients with bipolar disorder?” This study aims to review evidence regarding the impact of including pharmacogenetic testing as routine clinical decision support on treatment adherence in bipolar disorder.
The key terms that will be used in this study are pharmacogenetic testing, adherence, and bipolar disorder. Pharmacogenetic testing refers to the application of knowledge about genetic makeup to determine the best treatment regime. Adherence denotes a commitment to treatment advice and schedule. Bipolar disorder is a mental health condition that results in sudden shifts in temperament between mania and depression.
Literature Review
Scientific evidence shows that interpersonal variations in response to medications are brought about by numerous factors, for example, diagnostic precision, hepatic and renal function, drug-drug interactions, as well as medical and mental comorbidity.4 Furthermore, genetically influenced discrepancies in drug pharmacodynamics and pharmacokinetics can also affect how individuals respond to drugs given that genetics plays a key role in the metabolism of drugs.5 Therefore, pharmacogenetic tests have been suggested as the way forward in determining the most effective treatment regimen with minimal side effects. This level of evidence is mostly from primary articles (randomized controlled trials and systematic reviews and meta-analyses) and can be considered level I.
The theoretical framework that guides this study is the ACCE model of public health genomics.6 It was put forth by the Centers for Disease Control and Prevention (CDC). This model explores the various facets that influence the use of genetic data in disease management.
Methods
The author obtained clearance to conduct research from their institution’s Institutional Review Board (IRB). The process of obtaining IRB clearance entailed evaluating the potential risks and benefits of subjects as well as obtaining informed consent. However, since the study involved a review of the literature, these steps were not necessary.
The research design employed in the study is a systematic review, which is an evaluation of an articulated question. It uses meticulous and unambiguous methods to find, choose, analytically appraise pertinent research and collect information from previously published studies related to the research question. The key feature of a systematic review is that it applies a precise set of benchmarks to evaluate the reliability and validity of previously published research.
Articles were searched from databases such as PubMed, CINAHL, Medline, and Google Scholar. The key terms used were pharmacogenetic testing, bipolar disorder, and treatment adherence. The search was limited to articles published within the last five years. The results were filtered based on their relevance to the subject.
The inclusion criteria entailed quantitative studies, qualitative studies, secondary sources, and clinical practice guidelines or consensus statements addressing the use of pharmacogenomics in general or its application in bipolar disorder. Since bipolar disorder and depression are commonly co-occurring mood ailments, most studies that explore the treatment of mood disorders apply to bipolar disorder and depression.3 Therefore, studies that explored pharmacogenetic testing in major depressive disorder were also included in the review. Articles with explicitly defined treatment and intervention groups were included.
The exclusion criteria encompassed studies that addressed pharmacogenomic in diseases other than major depressive disorder and bipolar disorder. Experimental studies without clearly defined sample attributes were excluded. Articles involving pregnant women as subjects were also excluded from the review.
The evidence was rated into different levels using the Polit and Beck hierarchy of evidence tool, whereas the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool was used to determine the quality of evidence. Recommendations of the study findings were made based on the Appraisal of Guidelines for Research and Evaluation II (AGREE II) Collaboration framework.
Results
A total of 12 articles were selected based on the inclusion and exclusion criteria listed above. They included 4 quantitative studies, 2 qualitative studies, 5 secondary sources, and 2 clinical practice guidelines and consensus statements. The overall observation was that pharmacogenetic testing improved the treatment outcomes in bipolar disorder. The key findings are summarized in Table 1.
Table 1: Summary of key findings.
Discussion
The current clinical guidelines recommend that the treatment of bipolar disorder uses lithium or lamotrigine monotherapy as first-line treatments. In resistance cases, mood stabilizers such as Divalproex can be used together with lithium.20 Applying pharmacogenetics in the initial stages would help to determine the most appropriate treatment in the initial stages.
The study has several strengths including the use of recent research findings to address the research question. The study combines evidence from different angles of research to answer the research question. It considers findings from qualitative, quantitative research, secondary sources, and clinical practice recommendations. The weaknesses of the study encompass the shortcomings of the individual studies that were used to generate the evidence. For example, in one article, no tangible findings were reported and only the impact of pharmacogenetic testing on the action of lithium was explored.9 Other studies did not explore the specific use of pharmacogenetic testing in bipolar disorder.7,11,12, 13,14,15,16,17
The limitations of the study include the review of a few articles with high strength of evidence. Only 3 out of the 13 studies reviewed were level I or II. Therefore, the overall strength of evidence was low.
Conclusion
The synthesis of evidence shows that pharmacogenetic testing improves treatment outcomes in mood disorders. However, it is highly underutilized in clinical settings. Nurse practitioners and other health care providers should consider integrating pharmacogenetic testing in the development of treatment regimens for patients with bipolar disorder. Implications for research are that additional testing of specific medications in large samples should be done to provide critical data on tolerability and efficiency. Personalized medicine is a great step towards personalized care that can transform treatment outcomes in bipolar disorder if used appropriately.
References
- Ielmini, M., Poloni, N., Caselli, I., Espadaler, J., Tuson, M., Grecchi, A., & Callegari, C. (2018). The utility of pharmacogenetic testing to support the treatment of bipolar disorder. Pharmgenomics Pers. Med., 11, 35-42. Web.
- Callegari, C., Isella, C., Caselli, I., Poloni, N., & Ielmini, M. (2019). Pharmacogenetic tests in reducing accesses to emergency services and days of hospitalization in bipolar disorder: A 2-year mirror analysis. J. Pers. Med., 9(2), 1-8. Web.
- Steardo Jr, L., Fabrazzo, M., Sampogna, G., Monteleone, A. M., D’Agostino, G., Monteleone, P., & Maj, M. (2019). Impaired glucose metabolism in bipolar patients and response to mood stabilizer treatments. J. Affect. Disord., 245, 174-179. Web.
- Altar, A. C. (2017). Pharmacogenomics for selecting psychiatric medications: From research to patient response. Eur. Neuropsychopharm., 27(suppl. 3), S365-S366. Web.
- Bangwal, R., Bisht, S., Saklani, S., Garg, S., & Dhayani, M. (2020). Psychotic disorders, definition, sign and symptoms, antipsychotic drugs, mechanism of action, pharmacokinetics & pharmacodynamics with side effects & adverse drug reactions: Updated systematic review article. J. Drug Deliv. Ther., 10(1), 163-172. Web.
- National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Board on the Health of Select Populations, Committee on the Evidence Base for Genetic Testing. (2017). An evidence framework for genetic testing. National Academies Press.
- Heale, B. S. E., Khalifa, A., Stone, B. L., Nelson, S., & Del Fiol, G. (2017). Physicians’ pharmacogenomics information needs and seeking behavior: A study with case vignettes. BMC Med. Inform. Decis. Mak., 17(1), 113. Web.
- Rosenblat, J. D., Lee, Y., & McIntyre, R. S. (2018). The effect of pharmacogenomic testing on response and remission rates in the acute treatment of major depressive disorder: A meta-analysis. J. Affect. Disord., 241, 484-491. Web.
- Oedegaard, K. J., Alda, M., Anand, A., Andreassen, O. A., Balaraman, Y., Berrettini, W. H., & Calkin, C. V. (2016). The Pharmacogenomics of Bipolar Disorder study (PGBD): identification of genes for lithium response in a prospective sample. BMC Psych., 16(1), 129. Web.
- Oni-Orisan, A., Haldar, T., Ranatunga, D.K., Medina, M.W., Schaefer, C., Krauss, R.M., Iribarren, C., Risch, N., & Hoffmann, T.J. (2020). The impact of adjusting for baseline in pharmacogenomic genome-wide association studies of quantitative change. NPJ Genom. Med., 5, 1. Web.
- Veilleux, S., Bouffard, M., & Bourque Bouliane, M. (2020). Patient and health care provider needs and preferences in understanding pharmacogenomic and genomic testing: A meta-data analysis. Qual. Health Res., 30(1), 43-59. Web.
- Lemke, A. A., Hutten Selkirk, C. G., Glaser, N. S., Sereika, A. W., Wake, D. T., Hulick, P. J., & Dunnenberger, H. M. (2017). Primary care physician experiences with integrated pharmacogenomic testing in a community health system. Pers. Med., 14(5), 389-400. Web.
- Thiele, I., Clancy, C. M., Heinken, A., & Fleming, R. M. (2017). Quantitative systems pharmacology and the personalized drug–microbiota–diet axis. Cur. Opin. Sys. Biol., 4, 43-52. Web.
- Fulton, C.R., Swart, M., De Luca, T., Liu, S.N., Collins, K.S., Desta, Z., Gufford, B.T., & Eadon, M.T. (2018). Pharmacogenetics and practice: Tailoring prescribing for safety and effectiveness. J. Nurse Pract., 14(10), 697-704. Web.
- Ramey, J., Reddy, P. M., Datla, N. S. V., Prakash, S., & Acharya, Y. (2019). Understanding clinical pharmacogenomics: A descriptive review. EJMO 3(2), 92-100. Web.
- Routhieaux, M., Keels, J., & Tillery, E. E. (2018). The use of pharmacogenetic testing in patients with schizophrenia or bipolar disorder: A systematic review. Ment. Health Clin., 8(6), 294-302. Web.
- Tonozzi, T. R., Braunstein, G. D., Kammesheidt, A., Curran, C., Golshan, S., & Kelsoe, J. (2018). Pharmacogenetic profile and major depressive and/or bipolar disorder treatment: A retrospective, cross-sectional study. Pharmacogenomics, 19(15), 1169-1179. Web.
- Caudle, K.E., Klein, T. E., Hoffman, J.M., Muller, D.J., Whirl-Carrillo, M., Gong, L., McDonagh, E.M., Sangkuhl, K., Thorn, C.F., Schwab, M., Agundez, J.A., Freimuth, R.R., Huser, V., Lee, M.T., Iwuchukwu, O.F., Crews, K.R., Scott, S.A., Wadelius, M., Swen, J.J.,… Johnson, S.G. (2014). Incorporation of pharmacogenomics into routine clinical practice: The Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline development process. Curr. Drug Metab., 15(2), 209-217. Web.
- Brown, J.T., Bishop, J.R., Sangkuhl, K., Nurmi, E.L., Mueller, D.J., Dinh, J.C., Gaedigk, A., Klein, T.E., Caudle, K.E., McCracken, J.T., & de Leon, J. (2019). Clinical Pharmacogenetics Implementation Consortium guideline for cytochrome P450 (CYP) 2D6 genotype and atomoxetine therapy. Clin. Pharmacol. Ther., 106(1), 94-102. Web.
- Malhi, G. S., Gessler, D., & Outhred, T. (2017). The use of lithium for the treatment of bipolar disorder: Recommendations from clinical practice guidelines. J. Affect. Disord., 217, 266-280. Web.