Time-to-event survival statistics in ophthalmology: Methodological research.

Area of Science:

• Ophthalmology
• Biostatistics
• Medical Research Methodology

Background:

• Accurate analysis of patient outcomes over time is crucial for surgical specialties.
• Time-to-event data analysis is complex, especially with missing (censored) data.
• Transparent reporting of survival analysis is essential for reliable clinical decision-making.

Purpose of the Study:

• To explore transparent data analysis methods for time-to-event data in ophthalmology research.
• To assess the quality of reporting for survival curves and life tables in ophthalmology literature.
• To identify omissions in reporting that could affect patient decision-making.

Main Methods:

• Manual search of articles from top 20 ophthalmology journals published in 2014.
• Identified 4565 articles, with 218 reporting time-to-event outcomes in humans.
• Assessed reporting quality of survival curves and life tables using established criteria.

Main Results:

• Only 31.2% of articles presented survival curves and 53.2% presented life tables; 46.8% presented neither.
• High-quality reporting was low: 2% for survival curves and 13% for life tables.
• 90.36% of articles had poor reporting of time-to-event data due to flawed analysis or omitted graphics.

Conclusions:

• Ophthalmology research frequently omits essential contextual information in time-to-event analyses.
• Poor reporting of survival data can significantly impact patient decision-making.
• Enhancing transparency in reporting survival analysis is critical for advancing ophthalmology research and patient care.