Subjects With Major Depression and PCRS

CenExel is proud to highlight the poster presented at the​ Annual Meeting of the International Society for CNS Clinical Trials and Methodology Conference, February 2018, Washington, DC.

ABSTRACT​

Introduction: The challenge to reliably achieve signal detection in major depressive disorder (MDD) clinical trials cannot be overstated. MDD presents with the heaviest burden of disability among mental/behavioral disorders (NIH, 2017), yet less than 50% of double-blind, randomized, placebo-controlled trials (RCTs) demonstrate statistical superiority for active comparator drug over placebo (Khan et al., 2017). While researchers (Weber et al., 2005) have identified key factors which induce the placebo response (site-subject interactions, subject expectations of benefit, lack of subject understanding of placebo, and subject uncertainty of their role in the trial), the literature reveals few targeted methodological interventions which address the crucial Placebo Response Factors (PRFs). There are strategies addressing rater influence on placebo response (e.g., centralized raters), but they are not subject focused. MDD RCTs employing techniques aimed at educating subjects on PRFs can be additive to other strategies. 

Methods: MDD patients (N=64) participated in this pretest-posttest randomized-control group investigation. Subjects completed a Placebo Awareness Questionnaire (PAQ) containing 5 multiple choice questions to assess their awareness of the key PRFs. Upon completion of the PAQ, subjects were randomly assigned to the Control Group (CG) or Intervention Group (IG). The intervention was a seven-minute video educating subjects about the PRFs. Immediately after the IG subjects watched the video, they completed the same PAQ without access to their first responses. To match the temporality of the IG, the CG subjects completed the PAQ seven minutes after completing the first PAQ. 

Results: A repeated measures ANOVA showed a significant difference between the IG and the CG, demonstrating IG subjects were better able to identify the PRFs after watching the video (p < .001). Secondary analysis indicated this finding was true across age and gender (all p < .05 except for the 20-29 age group). Within-group analyses suggested a differential effect of the intervention on subgroups (e.g., IG females scored higher than IG males post video by 7 points) but not at a significant level. 

Conclusions: Despite MDE subjects prescreening for an RCT, these subjects could not identify PRFs. Subjects who watched a brief video had significantly greater awareness of these issues and their role in reducing placebo response as compared to subjects who did not watch the video. While a limitation of the study is that there were no outcome measures demonstrating improved signal detection, the current study results indicate that sponsors, research sites and rater training vendors should seriously consider implementing PRF training strategies for MDD subjects (e.g., the video used in this investigation or similarly purposed video) in order to potentially enhance signal detection and reduce placebo response. Learning style and attention theories may provide an explanation for why the 20‐29‐year‐old IG subgroup did not score significantly better than the CG of that same age group. It is recommended this study be replicated using other indications, evaluate the duration of improved understanding across study visits, and impact on placebo response.

INTRODUCTION

• There is a disconcerting high (approximately 50%) placebo effect within major depressive disorder (MDD) double-blind, randomized, placebo-controlled trials (RCTs) (Khan et al., 2017). Walsh et al. (2002) found that over the past 20 years, subjects in depression RCTs responded to placebo by seven percent. ​
• While various methodological strategies have been implemented or recommended to reduce the placebo effect (e.g., centralized ratings, remote rater monitoring, lessening assessment duration, subject duration of current illness exacerbation, and different lead-in phase procedures), evidence indicates the effect is only increasing as time progresses (Kemp et al., 2010; Loebel et al., 2010) with a profound risk for Big Pharma losing $2.5 Billion per new drug (Mullin, 2014).​
• There is general consensus (e.g., Alphs et al., 2012; Weber et al., 2005) about the subject-producing causes of the high placebo rate or Placebo Response Factors (PRFs), including: ​
  • Lack of subject understanding of the placebo​
  • Subject expectations of benefit​
  • Subject misconception of expected interactions with research site staff​
  • Subject uncertainty of his/her role in the trial ​
• Despite the PRFs, research has been arguably scarce in directly targeting how potential interventions specifically aimed at subjects (one of the clear sources of the placebo effect) may help minimize study participants’ response to placebo. As such, interventions focused on educating subjects about the PRFs is warranted. ​
• The current study explores if a brief video aimed at educating subjects in a major depressive episode (MDE) helps them understand the PRFs, and if so, investigates potential variability among subjects’ gender and age regarding this increased PRF awareness. Examining if subjects can enhance their understanding of the PRFs is merits an empirical answer since arguably these factors are subjective and complex, perhaps particularly for patients who are in a MDE and may not have the cognitive energy and wherewithal to comprehend the PRFs.

METHODS

• This study implemented a pretest-posttest randomized control group design, as described below.​
• Subjects completed the site’s consent to treat paperwork and were diagnosed by qualified site staff as experiencing a current major depressive episode (MDE) per the American Psychiatric Association’s (2013) Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5).​
• Subjects then completed the Placebo Awareness Questionnaire (PAQ) containing 5 multiple choice questions (one correct answer per item) to assess subjects’ awareness of the key factors related to the placebo response. Percent correct answer was computed  for each subject. ​
• The PAQ was developed specifically for this study to ascertain subject knowledge about the key placebo response factors (see left side Figure 1). ​
• Upon completion of the Pre-Test PAQ, subjects were stratified based age and gender and randomly assigned to the Control Group (CG) or Intervention Group (IP) in a 1:1 ratio to ensure each group had an equivalent sample of these features. ​
• Subjects in the IG immediately watched a 7-minute educational video after completing the Pre-Test PAQ. The video consisted of two of the current poster’s co-authors  (one with a DO and the other with a PHD degree) sitting in a chair facing the video camera and teaching (carefully reviewing) the four PRFs. Four chapters were identified in the video respective of the four PRFs. (Video transcripts are provided at the ISCTM poster session or by contacting the poster’s second author at ecohen@hritrials.com).​
• At the conclusion of the video, IG participants completed the Post-Test PAQ without access to their first responses.
• To match the temporality of the experimental group, the CG subjects completed the Post-Test PAQ seven minutes after completing their first PAQ.​
• The order of the Post-Test PAQ questions for all subjects were changed to avoid response bias and ensure subjects read each question carefully (Rubin, 2005). ​
• CG subjects did watch the placebo response video after completing the Post-Test PAQ to ensure the video intervention and its potential lessons were not withheld from any study subjects.​

RESULTS

• There were a total of 64 subjects (see Table 1 for subgroup sample size)
• As expected, there were no statistical differences of the Pre-Test CG and IG as a whole, as well as by gender or age. All study subjects seemed to have a similar poor understanding of the PRFs. For example, the randomized Pre-Test CG subjects scored M = 46.25 (SD = 19.30) on the PAQ and the randomized Pre-Test IG subjects scored M = 46.88 (SD = 22.40) (a difference of only 0.63 points) – see Figure 2 for an illustration.​
• After testing for normality, a repeated measures two-way analysis of variance (ANOVA) was conducted (see Figure 2), indicating there was a significant difference (time by group interaction p < .001) between the Post-Test IG and CG overall, such that the IG was significantly better able to identify the factors (i.e., their role) associated with reducing a placebo response after watching the video as compared to the CG (Post-Test CG vs IG: M =  81.88, SD = 19.91 vs. M = 46.25, SD = 22.40). ​
• The Post-Test CG and IG comparison results were replicated among males (interaction p = .003) and females (interaction p < .001; see Figure 2). Although not significantly different (p = .219), Post-Test IG females scored higher (M = 86.25, SD = 18.93) than their male counterparts (M = 77.50, SD = 20.49) by 9 points (see Conclusions Section). ​
• The findings were also replicated across age groups (all p < .005), except for the 20-29 age sample (p = .224; see Figure 2). While the 30-39, 40-49 and 50+ age IG samples showed significant improvement on PAQ scores at Post-Test (M = 87.50-90.00) compared to their Pre-Test scores, the 20-29 age group did not (M = 57.50, SD = 16.69). ​

CONCLUSIONS

• Our thorough review of the literature revealed that the current study is the only one which empirically examines potential differences of subjects in a major depressive episode by gender and age in relation to subjects’ understanding of the commonly cited PRFs known to cause a placebo effect in clinical trials (including MDD studies).​
• The results of the study indicate that MDE subjects were quite naïve about the placebo response factors and this held true across gender and age. However, the results are encouraging because they indicate that a brief (7-minute) psychoeducational video which carefully addresses the PRFs significantly increased subjects’ understanding of these crucial issues no matter what gender and age (exception within the 20-29 age group). ​
• Learning style and attention theories may provide a critical explanation for why the Post-Test IG 20-29-year-old subgroup (M = 57.50) did not score significantly better than the Post-Test CG (M = 42.50) of that same age group, although it is noteworthy that the IG scored higher by 15 points. The study’s 20-29-year-olds represents an amalgam of Generations Y (the Millennials) and Z which tend to have a shorter attention span and strong preference for multitasking, using digital technology, social stimulation, and visual graphics when learning new materials (G. Patel, 2017; Seemiller & Grace, 2016; Smith, 2012; Swanson, 2016). The medium of the 7-minute placebo response DVD lecture-oriented video may not have met these requirements. For example, subjects were not allowed to look at their cell phone while watching the video, but research has shown that Generation Y and Z respond to advertisements and also gain knowledge when they are able to use three or more devices simultaneously that provide instant answers (D. Patel, 2017; Wotapka, 2017).​
• Given the above generational learning preferences, it is recommended that a quick (one-minute) placebo response script that encourages discussion or other forms of medium be explored as a placebo response educational tool.  ​
• Post-Test IG females scored higher by 9 points than their male counterparts, although this difference was not significant (p=.219). This difference seemed to have been a function of the video since the Pre-Test IG females scored only 1.25 points higher than the Pre-Test IG males. Learning and cognitive style theories may also be applied to explain the Post-Test IG female and male 9 point difference. Males tend to prefer multimodal visual learning content compared to females (Sinha et al., 2013; Wehrwein et al., 2007). The placebo response video was unimodal and auditory: approaches preferred by females. Future tools aimed at enhancing males’ learning of the key placebo response factors should take these learning styles into account.  ​
• Study limitations: (a) the study does not address whether subjects’ increased PRF knowledge translates to greater drug-placebo separation; and (b) it is unknown if subjects remember the PRFs throughout their trial participation (some sites have begun to read a script explaining these factors to each subject per study visit which should extend their understanding throughout the trial). Future studies should address these matters.​

Howard A. Hassman, DO¹, Elan A. Cohen, Ph.D.¹, Roberta R. Ball, DO¹, Ashok V. Joseph, MD¹, Katarzyna Wyka, Ph.D.³, M. Lobb, MS¹, and Larry Ereshefsky, Pharm.D., BCPP^1,2,4

¹CenExel Hassman Research Institute ²CenExel Collaborative Neuroscience Network ³The City University of New York, Graduate School of Public Health and Health Policy ⁴Retired Professor, The University of Texas