postbaseline

Postbaseline refers to data or assessments collected after the baseline measurement in a study. Baseline assessment occurs before intervention to establish starting values. Postbaseline data track changes over time and are essential in longitudinal studies, randomized trials, and observational cohorts.

In clinical trials, primary efficacy endpoints are often defined using post-baseline measurements at predefined timepoints or as derived changes from baseline. Analysts commonly use repeated-measures models or mixed-effects models with time as a factor, or analysis of covariance that adjusts for baseline values.

Data collection schedules typically include baseline measurements followed by scheduled post-baseline visits (for example at weeks 4, 8, and 12). Post-baseline data can also include safety monitoring, recording adverse events that occur after baseline.

Handling and interpretation: post-baseline data may be missing due to dropout; analysts use methods such as maximum likelihood or multiple imputation. Reporting often presents post-baseline values or changes from baseline, and sensitivity analyses are used to assess the impact of missing data.

The term is used across disciplines beyond medicine, including psychology, education, and environmental science, to distinguish measurements taken after an initial baseline assessment.