Stopping Rules for Efficacy and Futility in Clinical Trials
Stopping rules are pre-specified decision criteria used during interim analyses to determine whether a trial should be discontinued early for:
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Biostatistics in Clinical Research
Interim Analysis in Adaptive Trial Settings: A Practical Guide
Adaptive trials are designed to allow modifications to key trial parameters based on interim data. These modifications must be pre-specified and are subject to stringent control to maintain Type I error rates.
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Interim Results Communication and Regulatory Implications in Clinical Trials
Only specific, pre-defined personnel are permitted access to interim results. These typically include:
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Statistical Analysis Plan (SAP) Considerations for Interim Analysis Planning
Interim analysis involves reviewing accumulating data while the trial is ongoing. Without a predefined plan, such reviews can introduce bias, inflate Type I error, or violate ethical and regulatory standards.
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Examples of Trials Terminated Based on Interim Results
Clinical trials may be halted early due to:
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Ethical Concerns During Interim Analyses in Clinical Trials
Clinical trials are governed by principles of beneficence, non-maleficence, and respect for persons. Interim analyses, when improperly conducted or communicated, can violate these principles by:
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Introduction to Survival Analysis in Clinical Trials
Survival analysis is a statistical technique used to analyze the expected duration of time until one or more events occur. These events can include:
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Kaplan-Meier Curves and Median Survival Estimation in Clinical Trials
A Kaplan-Meier curve is a step-function graph that estimates the survival function from time-to-event data. It shows the probability of surviving beyond certain time points in the presence of censored data.
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Log-Rank Test and Cox Proportional Hazards Models in Clinical Trials
While Kaplan-Meier curves visualize survival distributions, they do not formally test differences or account for covariates. The log-rank test and Cox model fill this gap:
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Censoring and Truncation in Survival Data for Clinical Trials
Censoring occurs when the exact time of the event of interest is unknown for some subjects. This can happen if the event has not occurred by the end of the study, the subject drops out, or the observation is incomplete for other reasons.
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