Clinical trial quality is often viewed as a final verification step, an endpoint where data are reviewed and approved. In practice, quality is a continuous, multidimensional process that supports every phase of study execution.
This principle guided our team’s research presented at the ISCTM 2025 Autumn Conference in Amsterdam, where three studies examined complementary aspects of quality: data oversight, patient assessment, and measurement efficiency.
Collectively, the findings underscore that quality at every level is fundamental to achieving reliable, interpretable, and clinically meaningful trial outcomes.
Maintaining Reviewer Consistency Through Calibration
Central Quality Reviewers (CQRs) are essential to preserving data integrity, ensuring accurate scoring, confirming subject eligibility, and identifying inconsistencies. However, even experienced reviewers can experience drift as interpretive standards evolve over time.
Our analysis evaluated whether structured calibration exercises could sustain reviewer performance across two therapeutic areas: Major Depressive Disorder (MDD) and Post-Traumatic Stress Disorder (PTSD). Reviewer reliability was measured over multiple calibration rounds.
Results:
- In the MDD study, CQRs achieved moderate to excellent inter-rater reliability (ICC of 0.94 at Calibration 1, ICC of 0.67 at Calibration 2 and ICC of 0.94 at Calibration 3. Their Intra-rater ICCs average was 0.89 (good) following structured calibrations, maintaining high performance
- In the PTSD analysis, CQRs achieved ICCs of 0.71 (moderate) and 0.92 (excellent) across two calibrations
Defined benchmarks and recurring calibration sessions provide a sustainable framework for maintaining CQR reliability.
Understanding the Broader Clinical Profile in Schizophrenia
Our analysis is built on evidence that mood and anxiety symptoms are common among individuals with schizophrenia and can influence both symptom presentation and treatment outcomes.
The study examined the prevalence of clinically meaningful anxiety and depressive symptoms as measured by the PANSS, and how these symptoms relate to overall illness severity and contribute to variability across PANSS total and subscale scores.
A pooled baseline analysis of more than 3,900 participants from 12 acute schizophrenia studies revealed:
- Clinically meaningful anxiety was present in 64% of subjects, depression in 39%
- Clinically meaningful anxiety often appeared independently of clinically meaningful depression (31%), whereas clinically meaningful depression rarely occurred alone (6%), most commonly co-occurring with clinically meaningful anxiety (33%)
- Anxiety was associated with statistically significantly increases in positive symptoms (+0.4 points for each one-point increase in anxiety), decreases in the severity of negative symptoms (-0.4 per one-point increase), and increases in general psychopathology (+0.8 points) and total PANSS scores (+0.8 points)
- Depression was significantly associated only with the increase in general psychopathology subscore (+0.2 points for each one-point increase in depression)
Our findings highlight the wide-ranging impact of anxiety on symptomatology in schizophrenia trials.
Streamlining Measurement Without Compromising Fidelity
The 30 item PANSS is the standard for assessing schizophrenia symptom severity. However, addressing the 30 items can impose operational and patient burden.
To assess whether efficiency could be achieved without loss of validity, a 10-item abbreviated PANSS (PANSS-10) derived post-hoc from the 30 item PANSS was evaluated using data from 3,067 participants across 12 acute schizophrenia studies.
Results:
- Mean difference in percent change from baseline between the 30and 10 item versions was 1%
- Agreement between the 30 and 10 item versions was high (polychoric correlation = 0.94 and a Spearman’s rho of 0.92, both p < 0.001)
Ten items of the PANSS may offer a reliable, time-efficient alternative to the full scale, reducing rater and participant burden while preserving measurement precision. Future research should aim to determine if these findings extend to stand alone administration of 10 items of the PANSS, real-world clinical settings and more diverse patient populations.
Integrating Findings: A Framework for Systematic Quality
Although each study focused on a distinct component of trial conduct, the findings are interdependent:
- Regular calibration supports consistent and accurate assessments
- Enhanced understanding of comorbidities informs better study design and analysis
- Efficient tools sustain data quality while improving operational feasibility
Together, they represent a continuous quality framework, from reviewer performance to patient characterization to measurement optimization, that strengthens both scientific validity and practical execution.
Key Takeaways for Future CNS Trials
- Invest in calibration: Incorporate structured reviewer calibration into study planning and budgeting to sustain data consistency
- Understand your population: Characterize comorbid symptoms early and allow these insights to guide trial design and stratification
- Optimize thoughtfully: Select assessment tools that balance scientific rigor with operational efficiency
These evidence-based strategies reinforce that quality is not a single event but an integrated process, designed from the outset, applied consistently, and measured throughout.
Embedding these principles into CNS trial operations will support data that withstand regulatory scrutiny and advance clinical understanding.
Meet the authors
Marcela Roy, MA, is Executive Director, Clinical Science & Medicine at Signant Health. She has been with Signant for over 15 years and has over 20 years of clinical and research experience. Her focus is Mood Disorders and Endpoint Reliability quality monitoring. She provides strategic direction in the organization, as well as team leadership and business development support.
Dr. Busner has over 35 years of experience as an academic psychiatric researcher, serving as Principal Investigator for 49 clinical trials and Sub-Investigator for 35 more. She has authored or co-authored over 140 peer-reviewed articles and presentations. Before joining Signant Health, she directed psychiatric clinical trials at two major medical schools and served on University IRBs for 20 years. Currently an Affiliate Associate Professor of Psychiatry at Virginia Commonwealth University, Dr. Busner leads studies at Signant on pediatric, rare, and psychiatric disorders, and has trained thousands of clinical trial investigators worldwide.
Dr. Alan Kott is the Practice Leader for Data Analytics at Signant Health, with both academic and industry experience in clinical trials. He has led the development of Signant’s Data Analytics Program, overseeing data analytics in over 200 clinical trials across multiple indications. Prior to joining Signant, Dr. Kott was an Assistant Professor at Charles University and a house officer in psychiatry at General Teaching Hospital in Prague. He holds a Medicinae Universae Doctor (MUDr.) from Charles University.
Dr. David Daniel leads scientific, clinical, and strategic direction for CNS solutions at Signant Health. With over 30 years of experience in psychiatric clinical trials, he has published extensively and holds patents for treatments in epilepsy, anxiety, and psychotic disorders. Dr. Daniel earned his MD from Vanderbilt University, where he also completed psychiatry training as chief resident, and he is a Phi Beta Kappa graduate of Emory University. He previously founded Global Learning, LLC, and held leadership roles at the NIMH and Stanley Foundation.