Assessing Agreement Between Acuvera Capture and Paper-Based Methods for BCVA Data Recording in Ophthalmic Trials (VALiCAPTURE)

Background and Rationale: Best Corrected Visual Acuity (BCVA) is the most widely accepted and clinically meaningful functional endpoint in ophthalmic clinical trials. It is routinely used to assess treatment efficacy, disease progression, and visual function across a broad spectrum of ocular diseases, including age-related macular degeneration (AMD), diabetic retinopathy, and inherited retinal diseases. Regulatory authorities such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) recognize BCVA as a primary endpoint in pivotal trials, and therapeutic approvals often hinge on statistically and clinically significant changes in BCVA outcomes (1-3).

Despite this critical role, BCVA data collection in clinical trials remains vulnerable when recorded on traditional paper forms. Common challenges include:

Calculation errors: Manual determination of the total number of letters correctly identified during BCVA testing is prone to human error, particularly when partial lines are read or when examiners must manually apply line-by-line scoring rules. Miscounting or incorrect summation of letter scores can result in inaccurate BCVA values and distort subsequent data analyses. These errors are inherent to paper-based recording processes and highlight the need for standardized, automated systems capable of performing real-time calculations to ensure data accuracy and consistency across study sites (1,2,3).

Transcription Errors: Manual transfer of BCVA scores from testing charts to case report forms can result in numerical misentries and calculation mistakes (4).

Omission and Misrecording: Missed data points, illegible handwriting, or recording the wrong line/letter score can compromise data integrity (5).

Protocol Deviations: Variations in testing procedures (e.g., incorrect testing distance, inappropriate prompting, or examiner bias) are not always detected in real time, introducing variability and bias (6).

Delayed Error Detection: Errors are often identified only retrospectively, during central reading or data monitoring, causing delays in data cleaning, increased trial costs, and, in some cases, regulatory queries (7).

Digital capture solutions such as Acuvera Capture address these limitations by embedding real-time quality control at the point of care. The application incorporates automated error detection, warning systems for protocol deviations, and standardized workflow guidance, ensuring higher data fidelity. By minimizing calculation, transcription and protocol errors, Acuvera Capture has the potential to strengthen data reliability, streamline trial conduct, and increase regulatory confidence in BCVA endpoints.

Given that BCVA is the most critical functional endpoint in ophthalmic clinical trials, even small improvements in accuracy and reproducibility can substantially impact study outcomes, regulatory acceptability, and sponsor credibility. This study will directly compare Acuvera Capture against paper-based recording to validate data agreement and assess error rates, efficiency, and usability, thereby generating essential evidence to support digital transformation of BCVA data collection.