CORR Insights®: Kaplan-Meier Survival Analysis Overestimates the Risk of Revision Arthroplasty: A Meta-analysis

Periprosthetic Joint Infection Is the Main Cause of Failure for Modern Knee Arthroplasty: An Analysis of 11,134 Knees

“…In the current study, we combined local hospital data with national joint registry data to provide more-complete followup of patients who have undergone TKA during a long period and to allow accurate clinical and radiographic analyses of these indications. In contrast to registry findings and previous reports from tertiary revision centers, we found PJI to be the dominant mechanism of revision or reoperation during the first 15 years after primary TKA [15,19,21].…”

“…We found the highest incidence of PJI occurred during the first 2 years after primary TKA (1.0%), and after 5 years, the annual incidence was less than 0.2% per year. Some studies report infection as the primary cause for early failure, contributing to 18% to 27% of early revisions [6,19,21,24]. After 8 years, we found aseptic loosening and polyethylene wear became the primary modes of failure and their incidence continued to increase.…”

A 44-gene set constructed for predicting the�prognosis of clear cell renal cell carcinoma

“…Cox regression analysis in the survival package ( 20 ) was applied for selecting prognosis-associated genes, and the log-rank test ( 21 ) was then utilized to calculate significant p-values. The top six genes were selected according to −logRank (P-value), following which Kaplan-Meier (KM) survival curves ( 22 ) were produced for the six genes.…”

“…To examine the predictive effect of the constructed prediction system, KM survival analysis ( 22 ) was performed for the TCGA dataset to assess the association between the classification results of the prognostic prediction system and the real survival time and survival status. In addition, GSE29609 in the GEO data-base was obtained as the validation dataset, which included 39 ccRCC samples (32 samples with survival information).…”

“…Subsequently, the 32 samples were divided into good prognosis and bad prognosis groups according to the aforementioned criteria. In addition, the correlations between the classification results of the prognostic prediction system and the actual survival time and survival status were detected by KM survival analysis ( 22 ).…”