Difficult-to-Treat Generalized Anxiety Disorder: Conceptual Issues and Barriers to Diagnosis

Generalized anxiety disorder (GAD) affects 7.8% of adults in the US during their lifetime.¹ GAD often has a chronic course of illness, as reflected in the presence of symptoms for at least 6 months per the Diagnostic and Statistical Manual of Mental Disorders criteria and is associated with marked impairments across various domains of life.^1,2 There is growing consensus around the need to screen for anxiety to promptly identify patients with GAD and initiate evidence-based care.³ The initial management of GAD can be instituted in primary care setting using approaches that were developed for treating patients with major depression.^4,5 While both pharmacotherapy and psychotherapy options are considered first-line treatments for GAD,⁶ there is considerable uncertainty regarding the work-up and management of patients who do not respond to 1 or more evidence-based treatments. Here, we talk about some of the issues regarding conceptualization of difficult-to-treat GAD and barriers to providing evidence-based care.

Conceptual Issues

Prior reports have preferred the use of treatment-refractory⁷ or treatment-resistant⁸ GAD for patients who did not improve adequately with a first-line treatment. However, consistent with the conceptualization of difficult-to-treat depression, the term difficult-to-treat GAD may be preferred. As outlined by Rush et al,⁹ the difficult-to-treat conceptualization has the advantage of being positioned as a collaborative effort of the patient, their family members and caregivers, and mental health providers. Furthermore, the difficult-to-treat conceptualization also emphasizes the chronic nature of illness and encourages approaches to longer-term management of symptoms and functional impairments in contrast to focusing on acute-phase symptom remission.9 Finally, it also factors in the dimensional nature of improvement (which may fluctuate) instead of a categorical approach (such as response or nonresponse).

Lack of Data Regarding Course of GAD After Nonresponse to First-Line Treatment

A major limitation in the conceptualization of difficult-to-treat GAD is the lack of high-quality data regarding longer-term course of illness after initial nonresponse. For example, the landmark  Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial showed the rates of symptomatic remission among adults with major depressive disorder (using the 16-item Quick Inventory of Depressive Symptomatology Self-Report) were 36.8%, 30.6%, 13.7%, and 13.0% for the first, second, third, and fourth acute treatment steps, respectively.^₁₀ The low remission rates with conventional antidepressants after 2 failed trials underscored the need to develop novel and more specialized approaches (such as esketamine) for these patients. Furthermore, using STAR*D data, Rush et al10 found that those who required more treatment steps to attain remission had higher relapse rates during the naturalistic follow-up phase. Similar studies with sequenced treatments and long-term follow-up to characterize the natural history of GAD are lacking. Therefore, after inadequate improvement with a first-line agent (such as a serotonin reuptake inhibitor) for GAD, it remains uncertain whether the use of an alternate first-line agent (such as buspirone) is appropriate or whether more specialized and off-label treatments should be considered right away.

Challenges of Ascertaining Past Treatment History

Another issue with diagnosing difficult-to-treat GAD is the phenomenon of pseudo-resistance, which refers to apparent nonresponse to treatment that can be attributed to use of a treatment that is not evidence-based (such as supportive psychotherapy) or to the use of an evidence-based treatment in an inappropriate fashion (such as a subtherapeutic dose or too short a period of treatment). A measurement-based care approach¹¹ that systematically evaluates symptom severity, side-effects, and adherence and relies on treatment optimization with regular, frequent follow-up visits should reduce the likelihood of pseudo-resistance. However, clinicians often must rely on patient recall and review of medical/pharmacy records to ascertain past treatment history. Lessons from depression literature may be informative here too. For example, there is a need to develop rating scales for GAD that are similar to the Massachusetts General Hospital Antidepressant Treatment Response Questionnaire¹² or the Antidepressant Treatment History Form¹³ for depression.

In summary, there is a pressing need to develop evidence-based conceptualizations of difficult-to-treat GAD given its wide prevalence and the limited efficacy of currently available treatments. While ongoing and future studies will inform this evidence base, clinicians may use approaches developed initially for other psychiatric disorders (such as measurement-based care) for the management of difficult-to-treat GAD.

-Manish Jha, MBBS

References

1. Ruscio AM, Hallion LS, Lim CCW, et al. Cross-sectional comparison of the epidemiology of DSM-5 generalized anxiety disorder across the globe. JAMA Psychiatry. 2017;74(5):465-475.

2. American psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). 5th Edition. Washington, DC: American Psychiatric Pub; 2013.

3. Gregory KD, Chelmow D, Nelson HD, et al. Screening for anxiety in adolescent and adult women: a recommendation from the Women’s Preventive Services Initiative. Ann Intern Med. 2020;173(1):48-56.

4. Jha MK, Grannemann BD, Trombello JM, et al. A structured approach to detecting and treating depression in primary care: VitalSign6 Project. Ann Fam Med. 2019;17(4):326-335.

5. Locke AB, Kirst N, Shultz CG. Diagnosis and management of generalized anxiety disorder and panic disorder in adults. Am Fam Physician. 2015;91(9):617-624.

6. Stein MB, Sareen J. Clinical practice. Generalized anxiety disorder. N Engl J Med. 2015;373(21):2059-2068.

7. Roy-Byrne P. Treatment-refractory anxiety; definition, risk factors, and treatment challenges. Dialogues Clin Neurosci. 2015;17(2):191-206.

8. Ansara ED. Management of treatment-resistant generalized anxiety disorder. Ment Health Clin. 2020;10(6):326-334.

9. Rush AJ, Aaronson ST, Demyttenaere K. Difficult-to-treat depression: a clinical and research roadmap for when remission is elusive. Aust N Z J Psychiatry. 2019;53(2):109-118.

10. Rush AJ, Trivedi MH, Wisniewski SR, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905-1917.

11. Trivedi MH, Rush AJ, Wisniewski SR, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163(1):28-40.

12. Desseilles M, Witte J, Chang TE, et al. Assessing the adequacy of past antidepressant trials: a clinician's guide to the antidepressant treatment response questionnaire. J Clin Psychiatry. 2011;72(8):1152-1154.

13. Sackeim HA, Aaronson ST, Bunker MT, et al. The assessment of resistance to antidepressant treatment: rationale for the Antidepressant Treatment History Form: Short Form (ATHF-SF). J Psychiatr Res. 2019;113:125-136.

Manish K. Jha, MBBS, is an Assistant Professor of Psychiatry and Neuroscience at the Icahn School of Medicine at Mount Sinai (ISMMS), New York, New York, with substantial expertise in conducting clinical trials and extensive clinical experience in providing care to patients with treatment-refractory psychiatric illnesses. He also serves as the Assistant Director of the Depression and Anxiety Center for Discovery and Treatment (DAC) at ISMMS, a comprehensive research facility and clinical program that aims to develop cutting-edge treatments by identifying factors that contribute to the onset, progression, and course of mood, anxiety and related disorders. His work has focused on often-ignored features of depression such as irritability and he has evaluated clinical and biological markers that can prognosticate clinical outcomes for individuals with mood, anxiety, and related disorders. His  program of research uses functional neuroimaging and affective neuroscience experiments to elucidate the neurocircuit mechanisms in order to develop the next generation of circuit-specific treatments for psychiatric disorders.

The views expressed on this blog are solely those of the blog post author and do not necessarily reflect the views of the Psychiatry & Behavioral Health Learning Network or other Network authors. Blog entries are not medical advice.