Reliability assessment and correlation analysis of evaluating orthodontic treatment outcome in Chinese patients

Efficacy of a modified twin block appliance compared with the traditional twin block appliance in children with hyperdivergent mandibular retrognathia: protocol for a single-centre, single-blind, randomised controlled trial

INTRODUCTION

Compensatory mouth breathing, caused by nasopharyngeal obstructive diseases, is the main cause of hyperdivergent mandibular retrognathia in children. Such deformities require effective growth guidance before pubertal growth peaks. The traditional mandibular advancement device, twin block (TB), can guide the forward development of the mandible. However, the side effect of increasing the vertical dimension of the lower facial third, worsens the facial profile of children with divergent growth trends. To solve this problem, a modified TB (LLTB) appliance was designed to control the vertical dimension by intruding incisors and inhibiting the elongation of posterior teeth during the advancement of the mandible, which could avoid the side effects of traditional appliances and effectively guide the growth of the mandible in a normal direction.

METHODS AND ANALYSIS

The study was designed as a single-centre, single-blind, randomised, parallel controlled trial. We aim to enrol 60 children aged 9-14 years with hyperdivergent skeletal class II malocclusion, using a 1:1 allocation ratio. The participants were will be randomly assigned to receive either the TB or LLTB treatment. The primary outcome will be a change in the angle of the mandibular plane relative to the anterior cranial base. The secondary outcomes will include changes in the sagittal maxillomandibular relation, occlusal plane, facial height, morphology of the mandible and upper airway width. Safety endpoints will also be evaluated.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the ethics committee of Shanghai Stomatological Hospital. Both participants and their guardians will be fully informed of the study and sign an informed consent form before participating in the trial. The results will be publicly available in peer-reviewed scientific journals.

TRIAL REGISTRATION NUMBER

ChiCTR2000035882.

Subjective and objective analysis of orthodontic expert consensus on the assessment of orthodontic treatment outcomes

OBJECTIVE

The objective of the study was to explore and validate the consensus of orthodontic experts on the assessment of orthodontic treatment outcomes based on subjective and objective analysis.

MATERIALS AND METHODS

The research consisted of two parts: the exploration and verification of expert consensus. First, a sample of 108 cases randomly selected from six dental schools in China were evaluated by 69 orthodontic experts and measured by researchers based on post-treatment study casts and lateral cephalograms, respectively. Then, through statistical analysis, the objective indicators significantly correlated with experts' subjective evaluations were selected, their weights were determined, and the critical values of satisfactory, acceptable and unacceptable grades were screened. Subsequently, another sample of 72 cases were evaluated by another 36 orthodontic experts, and the subjective evaluation results were compared with the objective measurement results.

RESULTS

There were six model indicators and seven cephalometric indicators being significantly correlated with the experts' subjective evaluations, including occlusal contact, overjet, midline, interproximal contact, alignment, occlusal relationship, L1/NB, ANB, SN/OP, U1/SN, LL-EP, Cm-Sn-UL and Ns-Prn-Pos, with a cumulative R² of 0.704. In the verification part, the correlation coefficient between the 36 experts' subjective scores and objective regression scores was 0.716 (P < .001); the correlation coefficient between the 36 experts' subjective grades and objective grades was 0.757 (P < .001).

CONCLUSIONS

Orthodontic experts had good consistency in the subjective evaluation of the combined records of post-treatment study casts and lateral cephalograms. The objective indicators selected from subjective and objective analysis had good reliability and validity and could further improve the existing occlusal indices.

Machine Learning-Based Evaluation on Craniodentofacial Morphological Harmony of Patients After Orthodontic Treatment

Objectives: Machine learning is increasingly being used in the medical field. Based on machine learning models, the present study aims to improve the prediction performance of craniodentofacial morphological harmony judgment after orthodontic treatment and to determine the most significant factors.

Methods: A dataset of 180 subjects was randomly selected from a large sample of 3,706 finished orthodontic cases from six top orthodontic treatment centers around China. Thirteen algorithms were used to predict the value of the cephalometric morphological harmony score of each subject and to search for the optimal model. Based on the feature importance ranking and by removing features, the regression models of machine learning (including the Adaboost, ExtraTree, XGBoost, and linear regression models) were used to predict and compare the score of harmony for each subject from the dataset with cross validations. By analyzing the prediction values, the most optimal model and the most significant cephalometric characteristics were determined.

Results: When nine features were included, the performance of the XGBoost regression model was MAE = 0.267, RMSE = 0.341, and Pearson correlation coefficient = 0.683, which indicated that the XGBoost regression model exhibited the best fitting and predicting performance for craniodentofacial morphological harmony judgment. Nine cephalometric features including L1/NB (inclination of the lower central incisors), ANB (sagittal position between the maxilla and mandible), LL-EP (distance from the point of the prominence of the lower lip to the aesthetic plane), SN/OP (inclination of the occlusal plane), SNB (sagittal position of the mandible in relation to the cranial base), U1/SN (inclination of the upper incisors to the cranial base), L1-NB (protrusion of the lower central incisors), Ns-Prn-Pos (nasal protrusion), and U1/L1 (relationship between the protrusions of the upper and lower central incisors) were revealed to significantly influence the judgment.

Conclusion: The application of the XGBoost regression model enhanced the predictive ability regarding the craniodentofacial morphological harmony evaluation by experts after orthodontic treatment. Teeth position, teeth alignment, jaw position, and soft tissue morphology would be the most significant factors influencing the judgment. The methodology also provided guidance for the application of machine learning models to resolve medical problems characterized by limited sample size.

Orthodontic radiology: development of a clinical practice guideline

OBJECTIVES

Radiographs are considered essential in orthodontics. However, their diagnostic value and indications for use are still uncertain, while exposure to radiation carries health risks. This study aimed to report on the development of a clinical practice guideline on orthodontic radiology.

METHODS

A Guideline Development Taskforce was set up. The GRADE methodology was used for development and the RIGHT Statement for reporting of the guideline. We systematically reviewed articles to address the main clinical question: how different types of radiographs contribute to orthodontic diagnosis, treatment planning and post-treatment outcome evaluation. After a literature search and data extraction, we formulated conclusions and assessed the strength of the evidence according to the GRADE method. Both literature conclusions and the most important considerations, such as patient preferences, organizational matters and expert opinions were taken into account to finally issue recommendations.

RESULTS

7 clinical questions focused on orthopantomograms, lateral cephalograms, hand-wrist radiographs, peri-apical radiographs, bitewings, antero-occlusal radiographs, and cone-beam computer tomographic imaging. The literature search lead to 484 unique studies, of which 17 were included in the analysis. The strength of evidence of the conclusions was graded low or very low. We formulated considerations and took them into account when issuing the 13 clinical recommendations to address the clinical questions.

CONCLUSIONS

There was a considerable lack of scientific evidence on this topic. Nonetheless, this guideline provides clinicians with a tool for decision-making regarding radiographic records while enhancing patient radiation protection. More research of higher quality is recommended for a future update.

[Efficiency of cephalometry in orthodontic treatment planning: cephalometric parameters and their age-related changes]

The aim of the study was to evaluate the efficiency of cephalometry in orthodontic treatment planning in patients with teeth crowding and Angle Class I molars relation. Cephalometric parameters were analyzed in 70 patients that completed orthodontic treatment in 'Orthodont' dental clinic (Samara). Cephalometric X-rays were taken at baseline examination and after treatment. In patients with crowding and Class I molars relationship treated with extraction of all four first premolars correlation between N-Se and mandibular and maxillary length was disturbed. These patients showed higher N-Se and reduced jaws length than patients with no extraction or extraction of 2 premolars. The observed increase of G angle with reduced mandibular length assumes compensatory changes of mandible position. These disproportions were aggravated by facial growth. In certain cases cephalometric assessment is inefficient for treatment strategy choice.

Measuring the Value of New Drugs: Validity and Reliability of 4 Value Assessment Frameworks in the Oncology Setting

BACKGROUND

Several organizations have developed frameworks to systematically assess the value of new drugs.

OBJECTIVE

To evaluate the convergent validity and interrater reliability of 4 value frameworks to understand the extent to which these tools can facilitate value-based treatment decisions in oncology.

METHODS

Eight panelists used the American Society of Clinical Oncology (ASCO), European Society for Medical Oncology (ESMO), Institute for Clinical and Economic Review (ICER), and National Comprehensive Cancer Network (NCCN) frameworks to conduct value assessments of 15 drugs for advanced lung and breast cancers and castration-refractory prostate cancer. Panelists received instructions and published clinical data required to complete the assessments, assigning each drug a numeric or letter score. Kendall's Coefficient of Concordance for Ranks (Kendall's W) was used to measure convergent validity by cancer type among the 4 frameworks. Intraclass correlation coefficients (ICCs) were used to measure interrater reliability for each framework across cancers. Panelists were surveyed on their experiences.

RESULTS

Kendall's W across all 4 frameworks for breast, lung, and prostate cancer drugs was 0.560 (P= 0.010), 0.562 (P = 0.010), and 0.920 (P < 0.001), respectively. Pairwise, Kendall's W for breast cancer drugs was highest for ESMO-ICER and ICER-NCCN (W = 0.950, P = 0.019 for both pairs) and lowest for ASCO-NCCN (W = 0.300, P = 0.748). For lung cancer drugs, W was highest pairwise for ESMO-ICER (W = 0.974, P = 0.007) and lowest for ASCO-NCCN (W = 0.218, P = 0.839); for prostate cancer drugs, pairwise W was highest for ICER-NCCN (W = 1.000, P < 0.001) and lowest for ESMO-ICER and ESMO-NCCN (W = 0.900, P = 0.052 for both pairs). When ranking drugs on distinct framework subdomains, Kendall's W among breast cancer drugs was highest for certainty (ICER, NCCN: W = 0.908, P = 0.046) and lowest for clinical benefit (ASCO, ESMO, NCCN: W = 0.345, P = 0.436). Among lung cancer drugs, W was highest for toxicity (ASCO, ESMO, NCCN: W = 0. 944, P < 0.001) and lowest for certainty (ICER, NCCN: W = 0.230, P = 0.827); and among prostate cancer drugs, it was highest for quality of life (ASCO, ESMO: W = 0.986, P = 0.003) and lowest for toxicity (ASCO, ESMO, NCCN: W = 0.200, P = 0.711). ICC (95% CI) for ASCO, ESMO, ICER, and NCCN were 0.800 (0.660-0.913), 0.818 (0.686-0.921), 0.652 (0.466-0.834), and 0.153 (0.045-0.371), respectively. When scores were rescaled to 0-100, NCCN provided the narrowest band of scores. When asked about their experiences using the ASCO, ESMO, ICER, and NCCN frameworks, panelists generally agreed that the frameworks were logically organized and reasonably easy to use, with NCCN rated somewhat easier.

CONCLUSIONS

Convergent validity among the ASCO, ESMO, ICER, and NCCN frameworks was fair to excellent, increasing with clinical benefit subdomain concordance and simplicity of drug trial data. Interrater reliability, highest for ASCO and ESMO, improved with clarity of instructions and specificity of score definitions. Continued use, analyses, and refinements of these frameworks will bring us closer to the ultimate goal of using value-based treatment decisions to improve patient care and outcomes.

DISCLOSURES

This work was funded by Eisai Inc. Copher and Knoth are employees of Eisai Inc. Bentley, Lee, Zambrano, and Broder are employees of Partnership for Health Analytic Research, a health services research company paid by Eisai Inc. to conduct this research. For this study, Cohen, Huynh, and Neville report fees from Partnership for Health Analytic Research. Outside of this study, Cohen receives grants and direct consulting fees from various companies that manufacture and market pharmaceuticals. Mei reports a grant from Eisai Inc. during this study. The other authors have no disclosures to report. Study concept and design were contributed by Bentley and Broder, with assistance from Elkin and Cohen. Bentley took the lead in data collection, along with Elkin, Huynh, Mukherjea, Neville, Mei, Popescu, Lee, and Zambrano. Data interpretation was performed by Bentley and Broder, along with Elkin, Cohen, Copher, and Knoth. The manuscript was written primarily by Bentley, along with Elkin and Broder, and revised by Bentley, Broder, Elkin, Cohen, Copher, and Knoth. Select components of this work's methods were presented at ISPOR 19th Annual European Congress held in Vienna, Austria, October 29-November 2, 2016, and Society for Medical Decision Making 38th Annual North American Meeting held in Vancouver, Canada, October 23-26, 2016.