OBJECTIVE: Secular change in marginal bone loss (MBL), which is the index adopted for implant success criteria, has often been used to evaluate risk factors. However, the need to revise these criteria has recently been indicated due to rapid developments in implant treatment. The purpose of this study was to evaluate risk factors by analyzing MBL with an alternative statistical method. MATERIAL AND METHODS: The analyses were performed on the outcomes of 366 patients with 1,902 implants during an average follow-up period of 84.8 months (with a maximum follow-up of 258 months). Instead of evaluating annual MBL, time was calculated as one of the explanatory variables because the correlation between MBL and time was small (correlation coefficient of 0.09010). Analysis of covariance (ANCOVA) was used for exploratory assessment of each factor, and multiple regression analysis was then utilized to identify risk factors. The multiple regression analysis was performed twice, once among all implants and another in which one implant per patient was randomly selected. RESULTS: As a result of multiple regression analysis, smoking habits showed a significant effect on MBL. Age, sex, diabetes mellitus, implant positions, guided bone regeneration, and sinus floor elevation did not affect MBL. IMZ® implants were associated with significantly higher MBL than were ANKYLOS® and SPI® implants. There was no significant difference between Straumann® and other implants. CONCLUSION: Our results showed that another statistical process, which eliminated the effect of time rather than comparing annual MBL, could be applied to evaluate MBL because the correlation between MBL and time was small.
OBJECTIVE: Secular change in marginal bone loss (MBL), which is the index adopted for implant success criteria, has often been used to evaluate risk factors. However, the need to revise these criteria has recently been indicated due to rapid developments in implant treatment. The purpose of this study was to evaluate risk factors by analyzing MBL with an alternative statistical method. MATERIAL AND METHODS: The analyses were performed on the outcomes of 366 patients with 1,902 implants during an average follow-up period of 84.8 months (with a maximum follow-up of 258 months). Instead of evaluating annual MBL, time was calculated as one of the explanatory variables because the correlation between MBL and time was small (correlation coefficient of 0.09010). Analysis of covariance (ANCOVA) was used for exploratory assessment of each factor, and multiple regression analysis was then utilized to identify risk factors. The multiple regression analysis was performed twice, once among all implants and another in which one implant per patient was randomly selected. RESULTS: As a result of multiple regression analysis, smoking habits showed a significant effect on MBL. Age, sex, diabetes mellitus, implant positions, guided bone regeneration, and sinus floor elevation did not affect MBL. IMZ® implants were associated with significantly higher MBL than were ANKYLOS® and SPI® implants. There was no significant difference between Straumann® and other implants. CONCLUSION: Our results showed that another statistical process, which eliminated the effect of time rather than comparing annual MBL, could be applied to evaluate MBL because the correlation between MBL and time was small.