A clinical prediction model is a tool for predicting healthcare outcomes, usually within a specific population and context. A common approach is to develop a new clinical prediction model for each population and context; however, this wastes potentially useful historical information. A better approach is to update or incorporate the existing clinical prediction models already developed for use in similar contexts or populations. In addition, clinical prediction models commonly become miscalibrated over time, and need replacing or updating. In this article, we review a range of approaches for re-using and updating clinical prediction models; these fall in into three main categories: simple coefficient updating, combining multiple previous clinical prediction models in a meta-model and dynamic updating of models. We evaluated the performance (discrimination and calibration) of the different strategies using data on mortality following cardiac surgery in the United Kingdom: We found that no single strategy performed sufficiently well to be used to the exclusion of the others. In conclusion, useful tools exist for updating existing clinical prediction models to a new population or context, and these should be implemented rather than developing a new clinical prediction model from scratch, using a breadth of complementary statistical methods.

The World Health Organization (WHO) stated that globally, dental caries is the most important oral condition. To develop effective prevention strategies requires an understanding of how this condition develops and progresses over time, but there are few longitudinal studies of caries onset and progression in children. The aim of the study was to establish the pattern of caries development from childhood into adolescence and to explore the role of potential risk factors (age, sex, ethnicity, and social deprivation). Of particular interest was the disease trajectory of dentinal caries in the permanent teeth in groups defined by the presence or absence of dentinal caries in the primary teeth. Intraoral examinations to assess oral health were performed at 4 time points by trained and calibrated dentist examiners using a standardized, national diagnostic protocol. Clinical data were available from 6,651 children. Mean caries prevalence (% D₃MFT > 0) was 16.7% at the first clinical examination (ages 7–9 y), increasing to 31.0%, 42.2%, and 45.7% at subsequent examinations. A population-averaged model (generalized estimating equations) was used to model the longitudinal data. Estimated mean values indicated a rising D₃MFT count as pupils aged (consistent with new teeth emerging), which was significantly higher (4.49 times; 95% confidence interval, 3.90–5.16) in those pupils with caries in their primary dentition than in those without. This study is one of the few large longitudinal studies to report the development of dental caries from childhood into adolescence. Children who developed caries in their primary dentition had a very different caries trajectory in their permanent dentition compared to their caries-free contemporaries. In light of these results, caries-free and caries-active children should be considered as 2 separate populations, suggesting different prevention strategies are required to address their different risk profiles.

The Herbst appliance is an orthodontic appliance that is used for the correction of class II malocclusion with skeletal discrepancies. Research has shown that this is effective. However, a potential harm is excessive protrusion of the lower front teeth. This is associated with gingival recession, loss of tooth support, and root resorption. This trial evaluates a method of reducing this problem. The study is a single-center, randomised, assessor-blinded, superiority clinical trial with parallel 1:1 allocation. Male and female young people (10–14 years old) with prominent front teeth (class II, division 1) will be treated in one orthodontic clinic. Group 1 will be treated with the conventional Herbst appliance with dental anchorage and group 2 with the Herbst appliance with indirect skeletal anchorage for 12 months. The primary objective will be to compare the proclination of the lower incisors between the Herbst appliance with dental anchorage and skeletal anchorage. Secondary objectives will be to evaluate the changes occurring between the groups in the mandible, maxilla, lower and upper molars, and in gingival recession and root resorption at the end of the treatment. Additionally, the young patient’s experience using the appliances will be assessed. The primary outcome measure will be the amount of lower incisor proclination at the end of treatment. This will be assessed by cone-beam computed tomography (CBCT) superimposition. Secondary outcome measures will be the changes in the mandible, maxilla, lower and upper molars at the end of treatment assessed by tomography superimposition and the young patient’s experience using the appliances assessed by self-reported questionnaires and semi-structured interviews. The randomisation method will be blocked randomisation, using software to generate a randomised list. The allocation concealment will be done in opaque envelopes numbered from 1 to 40 containing the treatment modality. The randomisation will be implemented by the secretary of the Department of Orthodontics of Rio de Janeiro State University before the beginning of the study. The patients and the orthodontists who will treat the patients cannot be blinded, as they will know the type of appliance used. The technician who will take the CBCT image and the data analyst will be blinded to patients’ group allocation. If this new intervention is effective, the findings can change orthodontic practice and may also be relevant to other forms of treatment in which appliances are fixed to the bones of the jaws. However, if the bone anchoring is not effective, the trial will provide much needed information on the use of this comparatively new development. ClinicalTrials.gov, protocol ID: NCT0241812 . Registered on 26 March 2015.