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 »  Home  »  Endodontic Articles 3  »  Relationship between number of proximal contacts and survival of root canal treated teeth
Relationship between number of proximal contacts and survival of root canal treated teeth
Results.



The disposition of RCT teeth amongst the 180 patients is presented in Table 2. Subjects had up to four RCT teeth, with 148 (82%) of the subjects contributing only one tooth. Of these 148 subjects, 31 (21%) lost that one tooth during the follow-up period. Amongst the 32 subjects who had two or more RCT teeth, 18 (56%) lost at least one tooth. Overall, 55 (25%) of the 221 RCT teeth were extracted during the follow-up period.
To preserve the stability of the regression models, and because only 55 teeth were extracted during follow-up, models were allowed to contain a maximum of 10 variables (Hosmer & Lemeshow 1989). For each of the 10 factors selected for multivariate analyses, Table 3 presents bivariate results in the form of Kaplan–Meier 5- and 10-year survival estimates. Not controlling for confounding variables, RCT teeth with more PCs at access had significantly better survival than teeth with fewer PCs.

Number of patients, by number of RCT teeth included and extracted during follow-up
Table 2. Number of patients, by number of RCT teeth included and extracted during follow-up.

Bivariate relationships between explanatory variables and RCT tooth survival
Table 3. Bivariate relationships between explanatory variables and RCT tooth survival.

Estimates generated during model-building process
Table 4. Estimates generated during model-building process.

Final multivariate Cox proportional hazards regression model for RCT tooth survival
Table 5. Final multivariate Cox proportional hazards regression model for RCT tooth survival.

Table 4 presents s, HRs, and 95% confidence intervals (CIs) for the main exposure variable during each stage of model-building, with the main exposure variable dichotomized as ‘two’ versus ‘zero or one’ PCs. Model 1 contains only the main exposure variable and provides an unadjusted HR of 3.9, implying that RCT teeth with zero or one PC at access were lost at a rate almost four times that of teeth with two PCs. In model 2, the covariate ‘crown status’ was added because its inclusion changed the of the main exposure variable by at least 10% and to a greater degree than any other covariate; this addition results in an adjusted HR of 4.8. In model 3, addition of the covariate ‘tooth type’ decreases the adjusted HR to 3.7, and in model 4, addition of the covariate ‘caries’ reduces the adjusted HR to 3.1. At this point, the addition of no single covariate elicits a change of at least 10% in the of interest, and the removal of no single covariate elicits a change less than 10%, so model 4 is deemed the final model. For comparison, model 5 shows the main exposure with all eligible covariates included. The main exposure is similar for models 4 and 5, indicating minimal confounding of the relationship of interest by the other eligible covariates.
The final model is shown in Table 5. RCT teeth with zero or one PC at access were lost at a rate 3.1 times that of RCT teeth with two PCs (95% CI: 1.9–5.1), controlling for crown status, tooth type, and caries. The model also shows that: (i) teeth that were not crowned were lost at a greater rate than teeth crowned at access, which in turn were lost at a greater rate than teeth crowned after obturation; (ii) second molars were lost at a greater rate; and (iii) teeth that were carious at access were lost at a greater rate.