Health economic evaluation of endodontic therapies.

Healthcare is an expensive endeavour, and it is likely that costs for endodontic treatment will grow over the next decade. The assessment of costs and, in most cases, health outcomes, and the comparison of the cost-health ratio of interventions, is at the heart of health economics. The present review aims to introduce the main concepts of health economic analysis, to systematically review the existing economic endodontic literature, and to deduce further action for the community. Overall, the identified body of evidence on the health economics of endodontic therapies is heterogenous and has several limitations: Not all studies identified robust data to inform their analyses and many relied on a wide range of assumptions, which were only explored for their impact in a limited way. However, a number of themes were identified from the review: (1) Maintaining pulpal vitality is preferable over root canal treatment if possible when it comes to cost-effectiveness. (2) Retaining teeth is usually more cost-effective than removing and replacing them. (3) Endodontic retreatment may be clinically indicated, but not always cost-effective, and should hence be considered carefully. In conclusion, the general sparsity of economic analyses is a concern, as decision makers such as commissioners or those funding dental care increasingly rely on them. The endodontic community is called to action to improve the competency of both researchers to conduct such analyses and consider them when planning research, but also clinicians who should factor in health economics when assigning interventions. Health economics should become an accepted pillar of endodontic research.

Cost-effectiveness analysis of full versus selective root canal retreatment.

AIM: Selective root-canal retreatment has been proposed as an alternative to full retreatment in multirooted, root-canal-filled teeth with evidence of apical pathology, where only the affected root(s) is retreated. Whilst this option may save costs initially, failures and retreatments may compensate for these initial savings. We assessed the cost-effectiveness of full versus selective root-canal retreatment using data from a recent clinical pilot study, employing a modelling approach. METHODOLOGY: A Markov model was constructed to follow up a previously root-canal treated maxillary molar with apical pathology on a single root (mesio-buccal), receiving either selective or full root-canal retreatment. A private-payer perspective in Dutch health care was adopted. Permanent molar teeth with apical lesions on the mesial root were simulated over the lifetime of initially 50-year-old patients. Teeth could have endodontic complications and require interventions such as retreatment or tooth extraction and replacement. Costs were calculated based on the Dutch dental fee catalogues. Monte-Carlo microsimulations were performed to assess lifetime costs and effectiveness (measured as tooth retention time), and the resulting cost-effectiveness. Probabilistic joint uncertainty and sensitivity analyses were performed, and cost-effectiveness at different willingness-to-pay-thresholds was evaluated. RESULTS: In the base-case scenario, selective retreatment was less costly (2137; 2.5%-97.5% percentiles: 1944-2340 Euro) and more effective (19.6; 18.3-20.8 Years) than full retreatment (2495; 2305-2671 Euro; 16.5; 15.2-17.9 Years) in 100% of the simulations and regardless of the willingness-to-pay threshold. Only in a worst case scenario was selective retreatment more costly, but remained more effective. CONCLUSIONS: Selective retreatment, when clinically applicable, is likely to be more cost-effective than full retreatment in endodontically treated molars with persistent apical periodontitis. Our results should be interpreted with caution because the quality of the underlying data is limited.

Machine Learning to Predict Apical Lesions: A Cross-Sectional and Model Development Study.

(1) Background: We aimed to identify factors associated with the presence of apical lesions (AL) in panoramic radiographs and to evaluate the predictive value of the identified factors. (2) Methodology: Panoramic radiographs from 1071 patients (age: 11-93 a, mean: 50.6 a ± 19.7 a) with 27,532 teeth were included. Each radiograph was independently assessed by five experienced dentists for AL. A range of shallow machine learning algorithms (logistic regression, k-nearest neighbor, decision tree, random forest, support vector machine, adaptive and gradient boosting) were employed to identify factors at both the patient and tooth level associated with AL and to predict AL. (3) Results: AL were detected in 522 patients (48.7%) and 1133 teeth (4.1%), whereas males showed a significantly higher prevalence than females (52.5%/44.8%; p < 0.05). Logistic regression found that an existing root canal treatment was the most important risk factor (adjusted Odds Ratio 16.89; 95% CI: 13.98-20.41), followed by the tooth type 'molar' (2.54; 2.1-3.08) and the restoration with a crown (2.1; 1.67-2.63). Associations between factors and AL were stronger and accuracy higher when using fewer complex models like decision tree (F1 score: 0.9 (0.89-0.9)). (4) Conclusions: The presence of AL was higher in root-canal treated teeth, those with crowns and molars. More complex machine learning models did not outperform less-complex ones.

Comparator Choice in Studies Testing Endodontic Instrument Fatigue Resistance: A Network Analysis.

AIMS: Endodontic instruments are frequently compared against each other for their cyclic fatigue resistance (CFR). It is unclear what drives the comparator choice in CFR studies, and how comparators and comparisons have evolved over time. We aimed at evaluating CFR study networks, hypothesizing that indications and instrument properties (alloy, manufacturer) drive comparisons. METHODS: A systematic review was performed via Medline and Embase (1986-2017). In vitro studies analyzing the CFR of ≥2 engine-driven instruments in an artificial curved root canal system were included. We classified instruments according to name, alloy, and manufacturer. Study networks were analyzed using social network analysis techniques. RESULTS: Eighty-five studies on 56 different instruments (9 alloys, 17 manufacturers) were included. For instruments, a low-density (0.19), highly clustered (0.71) network with 3 separate subnetworks (for glide path, shaping, and retreatment instruments) emerged. Certain instruments (ProTaper Universal [Dentsply Maillefer, Ballaigues, Switzerland], Mtwo [VDW Dental, Munich, Germany]) served as hub nodes and possible gold standards. Conventional Nickel-Titanium was the most frequently used alloy. Few manufacturers dominated the network. The diversity of tested instruments, alloys, and manufacturers increased in recent years. CONCLUSIONS: Comparisons of CFR were usually made along indications. Some instruments and alloys (conventional Nickel-Titanium) dominated the networks. Overall risk of bias by comparator choice seems moderate; however, the evidence on certain, less often tested instruments may not be robust. Factors underlying the network geometry (eg, sponsorship) should be explored.