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|dc.title||On the Importance of Accounting for Competing Risks in Pediatric Cancer Trials Designed to Delay or Avoid Radiotherapy: I. Basic Concepts and First Analyses|
|dc.identifier.citation||Tai, B.-C., Grundy, R.G., Machin, D. (2010). On the Importance of Accounting for Competing Risks in Pediatric Cancer Trials Designed to Delay or Avoid Radiotherapy: I. Basic Concepts and First Analyses. International Journal of Radiation Oncology Biology Physics 76 (5) : 1493-1499. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ijrobp.2009.03.035|
|dc.description.abstract||Purpose: In trials designed to delay or avoid irradiation among children with malignant brain tumor, although irradiation after disease progression is an important event, patients who have disease progression may decline radiotherapy (RT), or those without disease progression may opt for elective RT. To accurately describe the cumulative need for RT in such instances, it is crucial to account for these distinct events and to evaluate how each contributes to the delay or advancement of irradiation via a competing risks analysis. Methods and Materials: We describe the summary of competing events in such trials using competing risks methods based on cumulative incidence functions and Gray's test. The results obtained are contrasted with standard survival methods based on Kaplan-Meier curves, cause-specific hazard functions and log-rank test. Results: The Kaplan-Meier method overestimates all event-specific rates. The cause-specific hazard analysis showed reduction in hazards for all events (A: RT after progression; B: no RT after progression; C: elective RT) among children with ependymoma. For event A, a higher cumulative incidence was reported for ependymoma. Although Gray's test failed to detect any difference (p = 0.331) between histologic subtypes, the log-rank test suggested marginal evidence (p = 0.057). Similarly, for event C, the log-rank test found stronger evidence of reduction in hazard among those with ependymoma (p = 0.005) as compared with Gray's test (p = 0.086). Conclusions: To evaluate treatment differences, failing to account for competing risks using appropriate methodology may lead to incorrect interpretations. © 2010 Elsevier Inc. All rights reserved.|
|dc.contributor.department||EPIDEMIOLOGY & PUBLIC HEALTH|
|dc.description.sourcetitle||International Journal of Radiation Oncology Biology Physics|
|Appears in Collections:||Staff Publications|
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