Enhancing Patient Retention in ADHD studies

CenExel is proud to highlight the poster presented at the Annual Meeting of the American Society of Clinical Psychopharmacology (ASCP), May 2022, Scottsdale, AZ.

ABSTRACT

Introduction: Reducing study participant attrition is paramount to a clinical trial’s success, as poor retention leads to biased study results, reduced power, lower internal validity, less generalizability, and higher study costs (Liu et al., 2018). However, a thorough search of attention-deficit/hyperactivity disorder (ADHD) and anxiety disorder publications yielded no overarching research of these indications’ participant clinical trial dropout rates, with the exception of Lurie & Levine’s (2010) meta-analysis of posttraumatic stress disorder (PTSD) trials which found a high average withdrawal rate of 30%. Single studies on adult ADHD and other anxiety disorders, namely generalized anxiety disorder (GAD) and obsessive-compulsive disorder (OCD), found postbaseline attrition concerns, ranging from 33% (Sutherland et al., 2012) for ADHD to 42% for OCD (Foa et al., 2005). As such, the goals of the current investigation were to obtain a more comprehensive understanding of reasons ADHD and anxiety disorder participants withdrawal and recommend strategies to improve retention within these trails. This was accomplished by analyzing several Independent Variables theorized to be linked with participant attrition and some of which have not been previously empirically explored (e.g., number of study scales and participant compensation).

Methods: Across 5 US research sites in the midwest and east and west coasts, 24 outpatient placebo-control (PC; n=21; 148 participants) and open-label (OL; n=3; 13 participants) ADHD, GAD, PTSD, and OCD clinical trials were aggregately evaluated. Examining these disorders compositely is consistent with the ample research regarding their interrelatedness (e.g., Reimherr et al., 2017). Participant attrition postbaseline were collected from Closeout Report Forms submitted to Institutional Review Boards and sponsors at the completion of the analyzed trials. These data served as the Dependent Variable in this investigation, depicting participant’s decisions or circumstances leading to their discontinuation (e.g., withdrew consent and lost to follow-up) rather than matters out of their control (e.g., investigator discretion due to labs or adverse events).

Results: Pearson correlation analyses revealed that regardless of site location, retention was significantly correlated with less study visits (r=-.52; p=.01), higher visit frequencies (r=.46; p=.03), and shorter study duration (r=-.62; p=.002), while dropout was significant associated with more assessment scales in the trial (r=.44; p=.04). When PC were separately analyzed, the above variables remained statistically significant. There were few OL trials to adequately independently analyze.

Conclusions: The results of the current investigation can be applied to developing protocols and implementing strategies with an eye toward managing attrition. For example, the finding regarding assessment scales suggests that sponsors should consider outcome data via tempering the over-use of psychometric measures. Additionally, visit frequencies can be enhanced by having remote (phone call) visits between onsite visits where suicidality and adverse events are evaluated while reminding participants of the trial’s contraception and alcohol / illicit drug restrictions. Other applications from the current investigation’s findings to protocol and study management aimed at reducing attrition as well as study limitations will be discussed in the poster.

BACKGROUND

• The need to expeditiously discover efficacious treatment is crucial for the treatment of attentiondeficit/hyperactivity disorder (ADHD) and anxiety disorders (specifically for the purposes of this poster, these comprise of posttraumatic stress disorder [PTSD], generalized anxiety disorder [GAD], and obsessive-compulsive disorder [OCD]):
  • Adult ADHD is growing four times faster than are ADHD diagnoses among children in the US (Chung et al., 2019) and adults with ADHD are significantly more likely to experience difficulty obtaining and maintaining employment (Halmoy et al., 2009) and develop hardships in various types of relationships compared to adults without ADHD (Ginsburg et al., 2014)
  • An estimated 31% of US adults experience at least one of the above anxiety disorders at some point in their lives (Harvard Medical School, 2007) and these anxiety disorders are significantly associated with long-term disability (Hendriks et al., 2016)
• Curtailing attrition in ADHD and anxiety disorder clinical drug trials is crucial as dropouts lead to missing data, costly delays in study completion (Costello, 2016; Ross et al., 1999), potential premature entire trial termination (Gul & Ali, 2010), negative research site moral (Sullivan, 2004), and questionable validity of the findings (Gul & Ali, 2010; Kadam et al., 2016; Levine et al., 2015; Torous et al., 2020)
• High participant withdrawals have been noted in ADHD and anxiety disorder trials:
  • Lurie & Levine’s (2010) meta-analysis of PTSD trials found an average withdrawal rate of 30%
  • Although not purposed to examine attrition, separate ADHD and anxiety disorder placebocontrolled clinical trials have noted poor participant completion rates: 33% for ADHD (Sutherland et al., 2012), 24% for GAD (Gommoll et al., 2015), and 42% for OCD (Foa et al., 2005) •
• A thorough search of ADHD and anxiety disorder publications yielded no meta-analyses (except the Lurie & Levine study cited above) or overall reviews of these indications’ participant clinical trial dropout rates
• Therefore, the goals of the current investigation were to (a) obtain a more comprehensive understanding of ADHD and anxiety disorder trials’ attrition figures, and (b) identify study characteristics that may be contributing to participant completers by analyzing such studies of various designs possessing Independent Variables (IVs) theorized to be associated with retention (e.g., number of study scales and participant compensation).

METHODS

• Table 1 lists the research site locations who participated in the investigation and the number and type of outpatient CNS clinical trials analyzed from those sites
• The trials analyzed for the present study were conducted any time starting 2018 and must have been completed (Last Patient Out) by May 2020
• Table 2 lists the IV and Dependent Variables (DV) analyzed in this study.
• Dropouts were operationalized as participants withdrawing post-baseline (a) as obtained from the Closeout Report Forms submitted to Institutional Review Boards and sponsors and (b) directly due to participant decisions or factors (e.g., lost to follow-up and withdrew consent) rather than matters out of their control (e.g., investigator discretion due to labs and adverse events)
• ADHD and anxiety disorders were combined in the analyses given the clinical overlap (interaction as well as comorbidity) of these two indications that cannot be accounted for simply by referral bias or related symptom assessment (Bloch et al., 2017; Pliszka, 2009, 2019; Reimherr et al., 2017). This also enhanced the current study’s power to detect a true effect.
• All data were entered into an Excel spreadsheet and transferred / analyzed via a statistical program (SPSS v25.)

RESULTS

• 21 PC and 3 OL ADHD and anxiety disorder clinical trials (see Table 1) conducted at 5 research sites across the US were analyzed
• Bivariate associations between the IV and DV were assessed via Pearson correlation analysis for continuous variables and point-biserial correlation analysis for a mixture of binary and continuous variables
  • Note we use IV and DP terminology ‘loosely’ as the statistical analyses in this study were not regressions, but rather correlational
  • Percent Dropout (and Total n Randomized / n Completed) across all participating research sites for PC trials were 29% (148/105) and for OL trials 31% (13/9)
• Results indicated a significant correlation for PC ADHD and anxiety studies’ retention post-baseline and less study visits (r=-.52; p=.01), higher visit frequency (r=.46; p=.03), and shorter study duration (r=-.62; p=.002), while attrition was significantly associated with the study requiring more assessment scales (r=.44; p=.04); see Figures 1, 2, 3, and 4, respectively. IVs not reported here were non-significantly associated with the dropout DVs.
  • When OL trials were taken out of the analysis and only PC studies were evaluated, the above findings were still statistically significant
• The findings are consistent in correlational direction across the study’s US sites, although definitively concluding these results are consistent regardless of site location is difficult because the East coast and Midwest sites had low sample sizes (of trials) compared to the West coast sites, thus impacting statistical power in regard comparative data between sites.

DISCUSSION

• The below describes the current investigation results applicable to developing protocols and managing study procedures aimed at participant retention:
  • Sponsors can more accurately predict attrition rates for ADHD and anxiety disorder trials (estimated at 30%) given that the current investigation findings mirror other trials of these indications cited in this poster and per our literate review. Based on our results, the below study methodology recommendations may help reduce participant withdrawals.
  • Our data seem to connect higher retention with shorter study duration and less study visits. This finding may be tethered to the individual’s ADHD / anxiety symptoms: impatience and/or nervousness can understandably be persuasively powerful motivations for discontinuing study participation. Protocol developers are thus encouraged to be purposeful when designing a study’s length and visit structure so that they balance the need for data collection and retention.
  • Research sites are often consulted about the likelihood of participants completing a trial based on the schedule of events and the current results provide empirical validation for having enhanced study visit frequencies. As such, a recommendation can include having phone calls occurring between onsite visits where suicidality and adverse events are remotely evaluated along with reminding participants of the trial’s contraception and alcohol and illicit drug restrictions.
  • Trials administering more psychometric scales tended to have higher dropouts. Our research team have long anecdotally noticed this too, as participants seemed to be frustrated with several study measures, often perceived by the participants as asking redundant questions. Protocol developers should consider what instruments are necessary to collect the trial’s endpoint data as opposed to over exploring.
• Current study LIMITATIONS: (a) The low number of studies ad well as data from US sites (n=5) whose studies were analyzed may reduce the generalizability of the current findings; (b) new findings reported in this poster (e.g., visit frequency and number of scales) should be further investigated for confirmation; and (c) a reminder that correlational data is not causational and other factors may have contributed to the current results.

Elan A. Cohen,¹ Howard A. Hassman,¹ David P. Walling,² Vera M. Grindell,² John G. Sonnenberg,^3,4 Katarzyna Wyka,⁵ Brett A. English,^1,2 Jaclyn M. Lobb,¹ Djouher Hough,¹ Cassie L. Blanchard,¹ and Larry Ereshefsky ^1,2,6

Hassman Research Institute, A Division of Apex Innovative Sciences¹; Collaborative Neuroscience Network, A Division of Apex Innovative Sciences²; Uptown Research Institute³; Northwestern University Feinberg School of Medicine⁴; The City University of New York, Graduate School of Public Health and Health Policy⁵; Retired Professor, The University of Texas⁶

References provided upon request to ecohen@hritrials.com