ObjectivesThis study was performed to analyze the cumulative survival rate of Osstem implants (Osstem Implant Co., Ltd.) over a seven-year period.Materials and MethodsA total of 105 patients who had 467 Osstem implants that were placed at the Section of Dentistry, Seoul National University Bundang Hospital (Seongnam, Korea) from June 2003 through December 2005 were analyzed. The life table method and a cross-tubulation analysis, log rank test were used to evaluate the survival curve and the influence that the prognostic factors. The prognostic factors, i.e., age and gender of patients, diameter and length, type of implants, bone graft history and loading time were determined with a Cox proportional hazard model based on logistic regression analysis.ResultsThe seven-year cumulative survival rate of Osstem implants was 95.37%. The Cox proportional hazard model revealed that the following factors had a significant influence on survival rate; increased diameter, reduced prosthetic loading period and performance of bone grafting.ConclusionThe osstem implants showed satisfactory results over the seven-year study period.

were analyzed. The life table method and a cross-tubulation analysis, log rank test were used to evaluate the survival curve and the influence that the prognostic factors. The prognostic factors, i.e., age and gender of patients, diameter and length, type of implants, bone graft history and loading time were determined with a Cox proportional hazard model based on logistic regression analysis. After correctionMaterials and Methods: A total of 105 patients who had 467 Osstem implants that were placed at the Section of Dentistry, Seoul National University Bundang Hospital (Seongnam, Korea) from June 2003 through December 2005 were analyzed. The life table method and a cross-tabulation analysis were performed to evaluate the cumulative survival rate. The log rank test was used to evaluate the survival curve. The influence that the prognostic factors had on the survival rate was determined with a Cox proportional hazard model based on logistic regression analysis. This is an open-access article distributed under the terms of the Creative Commons Attribution