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Matchar DB, Thakur ME, Grossman I, et al. Testing for Cytochrome P450 Polymorphisms in Adults With Non-Psychotic Depression Treated With Selective Serotonin Reuptake Inhibitors (SSRIs). Rockville (MD): Agency for Healthcare Research and Quality (US); 2007 Jan. (Evidence Reports/Technology Assessments, No. 146.)

  • This publication is provided for historical reference only and the information may be out of date.

This publication is provided for historical reference only and the information may be out of date.

Cover of Testing for Cytochrome P450 Polymorphisms in Adults With Non-Psychotic Depression Treated With Selective Serotonin Reuptake Inhibitors (SSRIs)

Testing for Cytochrome P450 Polymorphisms in Adults With Non-Psychotic Depression Treated With Selective Serotonin Reuptake Inhibitors (SSRIs).

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5Future Research

We propose the following conceptual model to guide future research in cytochrome P450 (CYP450) polymorphism testing for depression management. Broadly speaking, the rationale behind CYP450 testing in patients with non-psychotic depression is as follows:

(a)

Major depressive disorder is a significant public health problem.

(b)

While selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for depression, they are associated with a high rate of non-response to treatment, harboring a potential opportunity to improve public health by improving response rates to SSRI treatment.

(c)

SSRI treatment efficacy involves modulation of brain levels of neurotransmitters and consequent adjustments of related pathways, processes that require several weeks to achieve a new steady state. One factor that possibly makes identification of the optimal SSRI treatment (i.e., specific SSRI and/or optimal dose) difficult in a specific clinical situation is the CYP polymorphism-associated differences between patients in the rate of metabolism of SSRIs.

(d)

CYP450 testing can potentially be used to predict the rate of SSRI metabolism (i.e., to classify patients as poor, intermediate, extensive, or ultra-rapid metabolizers) and, thus, potentially can reduce the amount of trial and error required to select the optimal SSRI in a specific clinical situation.

(e)

The better the operating characteristics of CYP450 testing in predicting metabolizer status, the greater the potential of CYP450 testing to improve the process of identifying the optimal SSRI treatment.

(f)

However, the more that factors other than CYP450 enzymes affect the metabolism of SSRIs (e.g., environmental effects, concomitant medications) or SSRI-associated outcomes (e.g., genetic factors associated with the pharmacodynamics of SSRIs, including genetic variability in serotonin receptor proteins, or transporter proteins), the less useful CYP450 testing will be.

(g)

Because depression is not often acutely life-threatening (except in severe cases with suicidal ideation) and SSRIs are rarely associated with life-threatening adverse effects, the main impact of CYP450 testing is likely to be in reducing the time to find the optimal SSRI, and in reducing the likelihood of adverse effects that would have been expected to occur with a suboptimal SSRI that might have been prescribed in the absence of CYP450 testing, thereby potentially reducing disease-management costs.

(h)

Finally, the impact of reducing the time to find the optimal SSRI and reducing the likelihood of SSRI-related adverse effects during the initial dosing period is strong enough to be important to patients (e.g., by improving their quality of life or decreasing absenteeism from work).

The eight elements described above can be specifically matched to our key questions as follows:

  • Question 1: Points (a) through (h).
  • Question 2: Point (e).
  • Question 3a, 3b, 3c: Points (c), (d), (e), and (f).
  • Question 4a, 4b, 4c: Points (g) and (h).
  • Question 5: Points (c) through (h).

This report reviewed the literature pertaining to the above rationale and found that, although some information exists, as a whole it is not sufficient to draw firm conclusions about whether this rationale, while intuitively reasonable, is in fact true. Nevertheless, this rationale can be used to help classify the future research that we recommend would be helpful. In particular, two types of studies can be envisioned.

The first type of study would better elucidate individual steps in the above rationale. For example, although we do not recommend that any additional studies are needed for points (a) and (b), the other points need additional studies that could be designed as follows:

  • Regarding point (c), studies that better describe the CYP polymorphism-associated differences in the rate of metabolism of individual SSRIs between patients could be designed. These should overcome the limitations of current literature addressing this issue, such that they are adequately powered, address individual SSRIs, account for diet, and co-medications, particularly CYP inhibiting or inducing drugs.
  • Regarding point (d), there is a need to perform studies of CYP genotyping in a large variety of populations to ascertain sensitivity and specificity of genotyping as applicable in real-world settings. It is essential that such studies explore a large range of the known possible polymorphisms functionally affecting each enzyme, refraining from focusing solely on the detection of the major alleles relevant to Caucasians and African-Americans. In order to reliably assess the performance of these tests the sample sizes employed must bear power to report results within narrow margins of confidence interval, repeatedly and consistently concluding identical genotype calls.
  • Regarding points (e) and (f), multivariable pathway analysis studies underway may provide guidance regarding extent of variation in depression treatment response attributable to CYP enzymes, albeit this may reflect only a subset of patients treated with citalopram.109
  • Regarding points (e), (f), and (g), studies that could better ascertain the predictive value of CYP genotyping in depression treatment outcomes, and its impact on medical or personal decisionmaking, could be designed. The suggested study design would be a properly sized (likely to be large) randomized trial of CYP genotyping-guided treatment versus treatment as usual. Such a trial should be in keeping with design standards aimed at minimizing bias (e.g., using intent-to-treat analysis, blinding of physicians and patients), maximizing generalizability (e.g., representative of individuals with severe non-psychotic depression), and including meaningful outcomes (e.g., short-term treatment success, satisfaction, resource utilization). Such a study would provide answers about rates of dropouts/non-response in individuals who were genotyped versus those who were not. It would also provide data about treatment decisions by providers and patients, based on genotyping, and the outcome of such genotyping-guided treatment (e.g., higher starting doses in ultra-rapid metabolizers or lower doses in poor metabolizers) in comparison to the current practice of “trial and error.” It may also provide valuable information about harms.
  • Regarding point (h), studies that could better examine the importance to patients of potential outcomes, such as time to response or quality of life during the early treatment of depression, could be designed. A suggested study would be a utility or a “willingness-to-pay” model to determine value of these outcomes to patients.

The second type of study would encompass multiple steps in the above rationale. In particular, recognizing that having evidence in favor of all of the steps in the rationale only supports, but does not prove, the thesis that adopting CYP450 testing will improve patient outcomes, various randomized trials could be considered that would test this linkage directly. The simplest study would involve linking a specific genotype to SSRI type and dose. This would provide a direct test of the rationale provided by the foundational studies described above (i.e., when clinicians a treat in a way indicated by evidence, does it make a difference?). However, such a study would not be a direct test of the utility of genotyping in clinical practice if the utility of testing is highly patient-specific and not suitable to being described by an algorithm. In an alternative design, patients would be randomized to being genotyped, without mandating that treatment be based on the results. The most pragmatic, but also the most difficult type of study would be a “practical clinical trial.”111 Rather than randomizing by patient, such a study would involve randomizing clusters (e.g., clinicians, practices, or regions) to have genotyping available (or perhaps reimbursed) or not. This would provide a test of the overarching question, “What difference does having genotyping available make in clinical practice?”

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