Multiplicity 1: Subgroup analyses

Rate of upper incisor retraction in Class II division 1 patients managed with palatal versus buccal miniscrew supported segmental orthodontics: Randomized parallel clinical trial

OBJECTIVE

This study was conducted to compare maxillary incisor retraction rates using buccal orthodontics with segmented arch approach supported by a buccal or palatal mini-screw in non-growing Class II Division 1 patients during a 3-month period.

PATIENTS AND METHODS

All patients between September 2018 and December 2021 with following criteria were included: non-growing class II division 1 protrusion, indication for premolar extraction, no or little crowding, normal overbite, no previous orthodontic treatment, no systematic disease, good oral hygiene, no periodontal problems or oral habits. Mini-implant was inserted buccally or palatally between upper second premolar and first molar bilaterally. Incisor retraction was manipulated by a 200-gram force through a nickel-titanium closed-coil spring extended from the mini-implant to the segmental design. Study casts were made before retraction and after every 4 weeks (T0: baseline, T1: 4 weeks, T2, 8 weeks, T3: 12 weeks). A repeated measures ANOVA was performed for total comparison of data (mm of retraction) on 3D casts. A pairwise t test with Bonferroni correction was used for comparison between two experimental periods for the same group. An independent samples t-test was also used for comparison between two groups for the same experimental period.

RESULTS

Of 30 patients meeting the eligibility criteria, only 28 were included with mean age 16±2.5 years. Repeated measures ANOVA revealed significant differences in incisor retraction between the time intervals for both buccal and palatal groups (P=0.001). In addition, the paired-sample t test indicated a significant difference between each time interval for both the buccal and palatal groups (P=0.001), except between T3 and T2 for the palatal group (P=0.09). The independent sample t-test revealed significant differences between the buccal and palatal groups at T1 (Mean: 0.55 [0.355-0.748],=0.001) and T2 (Mean: 1.4 [0.91-1.88], P=0.001); whereas no significant difference was found at T3 (Mean: 1.15 [0.67-1.63], P=0.945).

CONCLUSIONS

Anterior retraction using a segmental palatal model with mini-screws was effective regardless of the buccal or palatal situation of the minivis. Retraction of incisors with palatal miniscrews was significantly faster in the first two months.

Are longitudinal randomised controlled oral health trials properly analysed? A meta-epidemiological study

INTRODUCTION

Longitudinal designs with multiple outcome measurements are commonly encountered in oral health randomised controlled trials (RCTs). The aim of this meta epidemiological study was to assess whether optimal statistical analysis approaches have been used in longitudinal oral health RCTs.

DATA SOURCES

PubMed search was undertaken in September 2021 for longitudinal oral health RCTs with at least 3 repeated outcome measurements which have been published between 2016- 2020 in the highest impact general and specialty dental journals.

STUDY SELECTION

Study selection and data extraction were accomplished independently and in duplicate. The statistical methods undertaken in the selected articles were tabulated, and the association between study characteristics and use of optimal analyses were assessed using X² or Fisher's exact test and logistic regression.

RESULTS

Five hundred and five oral health RCTs were deemed eligible for inclusion. Of these, only 28.3% RCTs used optimal statistical analyses for a longitudinal trial design. For the trials with an optimal statistical approach, the most frequent test used was repeated measures analysis of variance (RM-ANOVA) followed by mixed effect models (MEM). The use of optimal statistical tests was predicated by the involvement of a statistician (OR: 2, 95% CI:1.27 - 3.18, p<0.01), the journal impact factor (OR:1.19, 95% CI;1.1 - 1.29), continent of first author (likelihood ratio test p=0.01), number of the authors (OR:1.22, 95% CI;1.12-1.3, p<0.001), protocol registration (OR: 1.48, 95%CI; 1 to 2.2, p=0.05), funding(OR:2.4, 95%CI; 1.6 - 3.7, p<0.001), and dental specialty (likelihood ratio test p<0.001).

CONCLUSIONS

Most longitudinal oral health RCTs did not use optimal statistical analyses. Greater awareness of optimal analyses used to assess longitudinal data reported in oral health trials is required to circumvent the reporting of suboptimal inferences, selective reporting and research waste.

CLINICAL SIGNIFICANCE

Further progress is required to avoid suboptimal statistical analyses and fully utilise the benefits of the repeated measurements over time in oral health RCTs.

Do longitudinal orthodontic trials use appropriate statistical analyses? A meta-epidemiological study

BACKGROUND

In orthodontic trials, longitudinal designs with multiple outcome measurements over time are common. The aim of this epidemiological study was to examine whether optimal statistical analysis approaches have been used in longitudinal orthodontic trials.

METHODS

Pubmed was searched in August 2021 for longitudinal orthodontic trials with at least three time points of outcome assessment published in the 2017-20 period. Study selection and data extraction were done independently and in duplicate. The analysis approaches undertaken were tabulated and associations between study characteristics and the use of optimal analysis or not were assessed using Fisher's exact test and logistic regression.

RESULTS

One hundred forty-seven out of 563 unique records were deemed eligible for inclusion. Only 26.50% of these trials used an optimal statistical analysis for longitudinal data where the data structure is accounted for. None of the study characteristics except the statistical significance of the results were associated with the appropriateness of the statistical analysis. The odds of significant results in studies with suboptimal analyses were higher than that in studies with optimal longitudinal analyses (odds ratio: 3.48, 95% confidence interval: 1.62, 7.46, P = 0.001). For the studies with optimal analysis, the most frequent test was repeated-measure analysis of variance (RM-ANOVA). The reporting of the statistical analysis section was suboptimal in the majority of the trials.

CONCLUSION

Most longitudinal orthodontic trials are not analysed using optimal statistical approaches. Inferences and interpretation of their results are likely to be compromised.