Long-term survival of dental implants placed in the grafted maxillary sinus: systematic review and meta-analysis of treatment modalities

Abstract

Background: A prevalent modality to increase the amount of available bone prior to implantation is grafting of the maxillary sinus. Multiple factors such as the surgical technique, moment of implant placement as well as grafting materials and membranes are known to affect implant survival. However, the role of different factor combinations and associated reciprocal effects remain unclear. Conventional statistical methods do not consider inconsistency of study designs and do not take covariables into account. Hence, a systematic research and meta-analysis was conducted to investigate the influence of various treatment modalities on implant survival in the grafted maxillary sinus.

Materials and methods: A meta-analysis was conducted according to the PRISMA guidelines. Articles published from 1980 through January 2013 were electronically and manually searched in MEDLINE (Ovid), the Cochrane Register of Controlled Trials, the Database of Abstracts of Effects, and the Cochrane Database of Systematic Reviews. Clinical reports on single intervention sinus augmentation with root-form implants, a minimum of 10 patients and 6 months of loading were eligible for inclusion if implant survival was stated or calculable. Results were calculated by non-parametric univariate Kaplan-Meier analysis and Bayesian multivariate interval-censored Cox regression.

Results: A total of 122 publications on 16268 endosseous implants placed in grafted maxillary sinus were included. The treatment parameters surgical approach, grafting material and implant type showed no selective preference. However, application of membranes showed a significantly reduced hazard-ratio, independent of other co-factors.

Conclusions: The use of membranes is the most significant factor to achieve long-term implant survival in sinus augmentation procedures. More data exceeding 3 years follow-up are needed to address prospective confounding and improve clinical evidence.

Figure 1. PRISMA – Flow Diagram.

Figure 2. Univariate Kaplan-Meier analysis plots for interval-censored data and subset of publications used in this meta-analysis.

The gray bars show regions of indetermination from the maximum likelihood estimation of interval-censored data (Turnbull, 1976).

Figure 3. Forest plot of log hazard ratio with 95% confidence intervals for publications in meta-analysis.

n: number of implants, max Years: maximal follow-up time.

Figure 4. Forest plot of logarithmic hazard ratios (HR) and their 95%-confidence intervals for all method combinations.

n: number of implants. Low values at the top represent longer implant survival.

Figure 5. Log hazard ratios (HR) and their 95%-confidence intervals, with simplified model omitting parameter GraftMat.

Absolute values of HR should not be compared with those in Figure 4 because reference values or HR are not comparable. n: number of implants.

Figure 6. Three samples of implant survival curves, estimated from a Cox regression model for interval-censored data.

The curves are similar, and less extreme than the mono-variable survival plot; this is a feature of the Cox regression, where only the hazard ratio determines the degree of stretching. Note that this is not an average curve, but a hypothetical prediction for one study with long observation time.