Advancing Statistical Literacy in Eye Care: A Series for Enhanced Clinical Decision-Making: Part 3: Design and Analysis of Clinical Research in Eye and Vision Studies

Purpose. To provide comprehensive guidance on designing and analysing clinical research studies in ophthalmology and optometry, encompassing observational studies, non-randomised controlled trials, randomised controlled trials, and advanced trial methodologies including platform trials, adaptive designs, and decentralised trials. This article addresses the unique methodological challenges in eye and vision research while integrating contemporary frameworks such as the estimands approach for defining treatment effects and the ethical imperative of systematic reviews before initiating new trials.

Material and Methods. A comprehensive literature review was conducted using PubMed, Scopus, Web of Science, and Cochrane databases, focusing on study designs applicable to eye care research with emphasis on methodological innovations from 2019 to 2025. Simulated datasets representing common ophthalmic research scenarios were generated using Python to illustrate design principles and analytical approaches. International guidelines including ICH E9(R1), CONSORT 2025, and regulatory guidance from FDA and EMA were synthesised to provide current best-practice recommendations.

Results. Different study designs serve distinct purposes in advancing eye care knowledge. Observational studies excel at identifying associations and generating hypotheses but require careful consideration of confounding factors. Non-randomised controlled trials, strengthened by propensity score methods and target trial emulation frameworks, offer pragmatic evaluation when randomisation is not feasible. Randomised controlled trials remain the gold standard for establishing causality but benefit from modern innovations including adaptive designs, platform trials enabling evaluation of multiple treatments, and the estimands framework clarifying precisely what treatment effects trials measure. Sequential Multiple Assignment Randomised Trials address the clinical reality that optimal treatment often requires adaptive sequencing. Decentralised trial elements expand access while maintaining scientific rigour. Key considerations for eye research include accounting for inter-eye correlation, managing paired organ data, and addressing masking challenges in surgical interventions.

Conclusion. Successful clinical research in eye and vision research requires matching study design to research questions, available resources, and ethical considerations. Modern trial methodology offers sophisticated tools for generating robust evidence efficiently, from the estimands framework ensuring trials measure clinically meaningful effects to platform designs enabling adaptive evaluation of multiple interventions. By understanding the strengths and limitations of each design type and applying appropriate analytical methods, researchers can advance evidence-based eye care while reducing research waste.