Coming at you with another outstanding Clinical Problems in Consultation Psychiatry (CPCP) presentation, this one on the issue of potential antidepressant overtreatment given by Family Medicine resident, Dr. Diana Flint, MD, who really went all out.
The bottom line is that it’s probably not unusual that antidepressant overtreatment is occurring and one controversial scenario that could contribute to it in the era of collaborative care approaches is relying too much on depression screening instruments. A screen should be used to screen, not diagnose. A positive screen should be an indication for referral to a psychiatrist for a thorough diagnostic assessment. As I’ve said before, a screen is more like a point of departure, not the whole journey.
I’m not saying that collaborative care models aren’t effective. There’s plenty of evidence they are, and the IMPACT MODEL is one of them. Another is the DIAMOND MODEL. These models work best if your clinics are staffed with people who are trained to provide psychoeducation and simplified forms of supportive and cognitive behavioral therapy (CBT) as alternatives to or in combination with psychopharmacology. And many believe that this particular form of collaborative care marginalizes psychiatrists even more than we already are.
By the way, you should read Dr. George Dawson’s view on collaborative care for an important perspective.
Primary care physicians work hard and sometimes have less than 10 minutes in which to evaluate a patient’s medical and psychosocial issues. The idea is not to criticize them but to help them help patients.
On the other hand, antidepressants have some nontrivial side effects including but not limited to the controversial tendency to prolong QTc interval leading to torsades de pointes (see reference list below, one of my colleagues is a co-author on the Kumar et al paper, Shinozaki).
One way to help might be to think of other integrated care models, similar to CoMeBeh here at Iowa for example.
Another way would be to come up with a technology which would trigger daggy music (but we need to give Barry Manilow a break; he was not happy about this) in the ears of doctors and care managers, signalling that they should think twice before simply accepting the raw results of a depression screening tool.
Hey, I happen to know this might work because it stopped a martian invasion in 1996 in America as anyone knows who has viewed the excellent documentary film “Mars Attacks!”
My suggestion would be to read Dave Barry’s “Book of Bad Songs,” for effective selections or just pick anything unusual.
In order to see the picture galleries of photos or powerpoint slides, click on one of the slides, which will open up the presentation to fill the screen. Use the arrow buttons to scroll left and right through the slides or up and down to view any annotations.
Jerant, A., et al. (2014). “Potential Antidepressant Overtreatment Associated with Office Use of Brief Depression Symptom Measures.” The Journal of the American Board of Family Medicine 27(5): 611-620.
Background: Use of brief depression symptom measures for identifying or screening cases may help to address depression undertreatment, but whether it also leads to diagnosis and treatment of patients with few or no symptoms—a group unlikely to have major depression or benefit from antidepressants—is unknown. We examined the associations of use of a brief depression symptom measure with depression diagnosis and antidepressant recommendation and prescription among patients with few or no depression symptoms.Methods: We conducted exploratory observational analyses of data from a randomized trial of depression engagement interventions conducted in primary care offices in California. Analyses focused on participants scoring <10 on a study-administered 9-item Patient Health Questionnaire (PHQ-9) (completed immediately before an office visit and not disclosed to the provider) with complete chart review data (n = 595). We reviewed visit notes for evidence of practice administration of a brief symptom measure (independent of the trial) and whether the provider (1) diagnosed depression or (2) recommended and/or prescribed an antidepressant.Results: Among the 545 patients without a practice-administered measure, 57 (10.5%) had a visit diagnosis of depression; 9 (1.6%) were recommended and another 21 (3.8%) prescribed an antidepressant. Among the 50 patients (8.4% of total sample) with a practice-administered measure, 10 (20%) had a visit diagnosis of depression; 6 (12%) were recommended and another 6 (12%) prescribed an antidepressant. Adjusting for nesting within providers, trial intervention, stratification variables, and sample weighting, use of a brief symptom measure was associated with depression diagnosis (adjusted odds ratio, 3.2; 95% confidence interval, 1.1–9.2) and antidepressant recommendation and/or prescription (adjusted odds ratio, 3.80; 95% confidence interval, 1.0–13.9). Analyses using progressively lower PHQ-9 thresholds (<9 to <5) and examining antidepressant prescription alone yielded consistent findings. Analyses by practice-administered measure (PHQ-9 vs PHQ-2) indicated the study findings were largely associated with PHQ-9 use.Conclusions: These exploratory findings suggest administration of brief depression symptom measures, particularly the PHQ-9, may be associated with depression diagnosis and antidepressant recommendation and prescription among patients unlikely to have major depression. If these findings are confirmed, researchers should investigate the balance of benefits and risks (eg, overdiagnosis of depression and overtreatment with antidepressants) associated with use of a brief symptom measure.
Kumar, Y., et al. (2014). “CYP2C19 variation, not citalopram dose nor serum level, is associated with QTc prolongation.” Journal of Psychopharmacology 28(12): 1143-1148.
Recently, a FDA Safety Communication warned of a dose-dependent risk for QTc prolongation with citalopram, which is metabolized by CYP2C19 of the cytochrome P450 system. We investigate associations between citalopram and escitalopram dose, serum concentration, CYP2C19 phenotype, and QTc. We undertook a retrospective chart review of citalopram or escitalopram patients with the inclusion criteria of consistent medication dose, CYP2C19 phenotype (extensive metabolizers [EM], intermediate metabolizers [IM], poor metabolizers [PM]), and QTc interval on ECG. We further identified 42 citalopram users with citalopram serum concentration measurements and ECG. Regression and one-way ANOVA were used to examine the relationship between citalopram dose, citalopram serum concentration, CYP2C19 phenotype, and QTc interval. Of 75 citalopram patients, the EM group had significantly shorter QTc intervals than a combined IM+PM group (427.1±23.6 ms vs. 440.1±26.6 ms, one-tailed t-test, p=0.029). In the 80 escitalopram cohort, there was no significant difference in QTc between phenotype groups. There was no statistical correlation between citalopram (p=0.62) or escitalopram (p=0.30) dose and QTc. QTc was not associated with citalopram serum level (p=0.45). In contrast to the FDA warning, this study found no association between citalopram/escitalopram dose and QTc. However, PM of the drug tended to have longer QTc intervals. Our findings suggest cytochrome P450 genotyping in select patients may be helpful to guide medication optimization while limiting harmful effects.
Cooke, M. J. and W. S. Waring (2013). “Citalopram and cardiac toxicity.” Eur J Clin Pharmacol 69(4): 755-760.
PURPOSE: Citalopram is a selective serotonin reuptake inhibitor (SSRI) antidepressant that is widely used in clinical practice. Recent data have indicated that high therapeutic citalopram doses may cause electrocardiographic abnormalities, and the regulatory authorities have amended its licenced dosage. The present manuscript reviews the available data concerning citalopram and cardiac toxicity. METHODS: Published data concerning the cardiac effects of citalopram were ascertained, and clinical data were considered separately between adverse effects arising from therapeutic use versus toxicity in the setting of intentional overdose. RESULTS: The occurrence of electrocardiographic abnormalities has long been recognised as a complication of acute citalopram overdose; a dose-effect relationship for QT prolongation has been described in a number of large case series, including several cases of torsades de pointes. In contrast, few data indicate the occurrence of QT prolongation and arrhythmia after therapeutic doses, and a dose-effect relationship within the therapeutic range has only recently been established. Citalopram is more likely to cause QT prolongation in patients with metabolic disturbance or pre-existing cardiac disease. CONCLUSIONS: A dose-effect relationship for QT prolongation exists across a broad range of citalopram doses, such that caution must be exercised when prescribing high doses or if there are co-existent risk factors for QT effects. The available data illustrate how clinical toxicity data may offer an earlier signal of cardiac effects than ascertained from conventional pharmacovigilance methods.