Competing Risks and Their Impact on Treatment Efficacy Assessment in Fractionated Stereotactic Radiotherapy for Brain...

Area of Science:

• Oncology
• Biostatistics
• Radiotherapy

Background:

• Kaplan-Meier (KM) method and competing risk analysis are statistical tools for time-to-event data.
• These methods differ in handling competing events, impacting treatment efficacy interpretation in cancer research.

Purpose of the Study:

• To compare the Kaplan-Meier (KM) method with competing risk analysis (cumulative incidence function - CIF) in analyzing outcomes after radiotherapy for brain metastases.
• To evaluate the impact of competing events, such as premature death, on the interpretation of local failure and new brain metastases.

Main Methods:

• Retrospective analysis of 73 patients treated with fractionated stereotactic radiotherapy for brain metastases.
• Comparison of the complement of the KM method (1-KM) with the cumulative incidence function (CIF) for local failure and new brain metastases.
• Premature deaths were treated as competing events.

Main Results:

• The CIF method estimated cumulative incidences of local failure at 27% and new brain metastases at 55% at 24 months.
• The 1-KM method overestimated local failure by 9-14% and new brain metastases by 13% at 24-36 months.
• 1-KM survival curves were consistently higher than CIF curves, indicating overestimation of event probability.

Conclusions:

• Failure to account for competing risks, as done by the KM method, introduces bias in interpreting treatment outcomes.
• Accurate statistical methodology, like competing risk analysis, is crucial for reliable assessment of treatment efficacy in oncology.
• This study emphasizes the importance of selecting appropriate statistical methods for clinical data analysis.