Correlation of wear in vivo and six laboratory wear methods.

OBJECTIVE: We examined the correlation between clinical wear rates of restorative materials and enamel (TRAC Research Foundation, Provo, USA) and the results of six laboratory test methods (ACTA, Alabama (generalized, localized), Ivoclar (vertical, volumetric), Munich, OHSU (abrasion, attrition), Zurich). METHODS: Individual clinical wear data were available from clinical trials that were conducted by TRAC Research Foundation (formerly CRA) together with general practitioners. For each of the n=28 materials (21 composite resins for intra-coronal restorations [20 direct and 1 indirect], 5 resin materials for crowns, 1 amalgam, enamel) a minimum of 30 restorations had been placed in posterior teeth, mainly molars. The recall intervals were up to 5 years with the majority of materials (n=27) being monitored, however, only for up to 2 years. For the laboratory data, the databases MEDLINE and IADR abstracts were searched for wear data on materials which were also clinically tested by TRAC Research Foundation. Only those data for which the same test parameters (e.g. number of cycles, loading force, type of antagonist) had been published were included in the study. A different quantity of data was available for each laboratory method: Ivoclar (n=22), Zurich (n=20), Alabama (n=17), OHSU and ACTA (n=12), Munich (n=7). The clinical results were summed up in an index and a linear mixed model was fitted to the log wear measurements including the following factors: material, time (0.5, 1, 2 and 3 years), tooth (premolar/molar) and gender (male/female) as fixed effects, and patient as random effect. Relative ranks were created for each material and method; the same was performed with the clinical results. RESULTS: The mean age of the subjects was 40 (±12) years. The materials had been mostly applied in molars (81%) and 95% of the intracoronal restorations were Class II restorations. The mean number of individual wear data per material was 25 (range 14-42). The mean coefficient of variation of clinical wear data was 53%. The only significant correlation was reached by OHSU (abrasion) with a Spearman r of 0.86 (p=0.001). Zurich, ACTA, Alabama generalized wear and Ivoclar (volume) had correlation coefficients between 0.3 and 0.4. For Zurich, Alabama generalized wear and Munich, the correlation coefficient improved if only composites for direct use were taken into consideration. The combination of different laboratory methods did not significantly improve the correlation. SIGNIFICANCE: The clinical wear of composite resins is mainly dependent on differences between patients and less on the differences between materials. Laboratory methods to test conventional resins for wear are therefore less important, especially since most of them do not reflect the clinical wear.

Problems of allometric scaling analysis: examples from mammalian reproductive biology.

Biological scaling analyses employing the widely used bivariate allometric model are beset by at least four interacting problems: (1) choice of an appropriate best-fit line with due attention to the influence of outliers; (2) objective recognition of divergent subsets in the data (allometric grades); (3) potential restrictions on statistical independence resulting from phylogenetic inertia; and (4) the need for extreme caution in inferring causation from correlation. A new non-parametric line-fitting technique has been developed that eliminates requirements for normality of distribution, greatly reduces the influence of outliers and permits objective recognition of grade shifts in substantial datasets. This technique is applied in scaling analyses of mammalian gestation periods and of neonatal body mass in primates. These analyses feed into a re-examination, conducted with partial correlation analysis, of the maternal energy hypothesis relating to mammalian brain evolution, which suggests links between body size and brain size in neonates and adults, gestation period and basal metabolic rate. Much has been made of the potential problem of phylogenetic inertia as a confounding factor in scaling analyses. However, this problem may be less severe than suspected earlier because nested analyses of variance conducted on residual variation (rather than on raw values) reveals that there is considerable variance at low taxonomic levels. In fact, limited divergence in body size between closely related species is one of the prime examples of phylogenetic inertia. One common approach to eliminating perceived problems of phylogenetic inertia in allometric analyses has been calculation of 'independent contrast values'. It is demonstrated that the reasoning behind this approach is flawed in several ways. Calculation of contrast values for closely related species of similar body size is, in fact, highly questionable, particularly when there are major deviations from the best-fit line for the scaling relationship under scrutiny.