English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The timeliness of survival monitoring is particularly important in a field such as transplantation medicine, where progress occurs rapidly. Period analysis, a method successfully applied for improving the timeliness of survival monitoring in population-based cancer survival analysis, could potentially be useful in the field of transplantation as well. Using data from the Collaborative Transplant Study, the authors compared the ability of traditional, cohort-based analysis methods and the period analysis method to provide timely 5-year graft and patient survival estimates for kidney, heart, and liver transplants in 6 age groups (0-17, 18-29, 30-39, 40-49, 50-59, &gt;or=60 years) on 378 occasions between 1990-1992 and 2000-2002. Overall, period estimates provided superior predictions for the survival of most recent transplants on 344 of 378 occasions (91%); in the organ-specific analysis, this proportion ranged between 83% for heart and 100% for kidney graft survival. This evaluation provides evidence that the period analysis method can improve the timeliness of survival monitoring in solid organ transplantation. The method appears useful for providing more up-to-date long-term survival estimates than traditional methods, and its use in pertinent studies is encouraged.

From Cancer to Transplantation: An Evaluation of Period Analysis for Calculating Up-to-date Long-term Survival Estimates