Guarding the Gate: Remote Structured Assessments to Enhance Enrollment Precision in Depression Trials.

BACKGROUND: Failed treatment trials are common in major depressive disorder and treatment-resistant depression, and remotely performed multifaceted, centralized structured interviews can potentially enhance signal detection by ensuring that enrolled patients meet eligibility criteria.

METHODS: We assessed the use of a specific remote structured interview that validated the diagnosis, level of treatment resistance, and depression severity. The objectives were to (1) assess the rate at which patients who were deemed eligible for participation in trials by site investigators were ineligible, (2) assess the reasons for ineligibility, (3) compare rates of ineligibility between academic and nonacademic sites, (4) compare eligibility between US and non-US sites, and (5) report the placebo response rates in trials utilizing this quality assurance approach, comparing its placebo response rates with those reported in the literature. Methods included a pooled analysis of 9 studies that utilized this methodology (SAFER interviews).

RESULTS: Overall, 15.33% of patients who had been deemed eligible at research sites were not eligible after the structured interviews. The most common reason was that patients did not meet the study requirements for level of treatment resistance. Pass rates were significantly higher at non-US compared with US sites (94.6% vs 83.3%, respectively; P < 0.001). There was not a significant difference between academic and nonacademic sites (87.8% vs 82.4%; P = 0.08). Placebo response rates were 13.0% to 27.3%, below the 30% to 40% average in antidepressant clinical trials, suggesting a benefit of the quality assurance provided by these interviews.

CONCLUSIONS: The use of a remotely structured interview by experienced clinical researchers was feasible and possibly contributed to lower-than-average placebo response rates. The difference between US and non-US sites should be the subject of further research.