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Contemporary dental education requires a student-centred, competence-based curriculum that facilitates training for our next generation of practitioners, emphasising in particular their roles as clinician scientists, critical thinkers, oral health team leaders and lifelong learners. In this article, Peter Thomson presents a view of dental education from “Down Under” and reviews the Australian Dental Council’s 2023 approach to defining the professional competences required of newly qualified dental practitioners, reflecting on how dental curricula must continually change and adapt to deliver the precise knowledge and skills required of modern dental practitioners.

Patient and population health are influenced by a myriad of factors outside the traditional biomedical model of disease. Health partnerships, based on a collaborative approach and involving both individuals and institutions, provide an important mechanism to improve health service delivery and enhance health outcomes. In order to be successful in delivering health promotion (and therefore improve health itself), the supporting pillars of patients, populations, and relevant and effective partnerships are of fundamental importance in contemporary practice to deliver better health outcomes for our communities.

Cell-free DNA (cfDNA) and cell-free mitochondrial DNA (cf-mtDNA) have been postulated as potential diagnostic and prognostic biomarkers for different human malignancies. Early detection of head and neck malignancies is fundamental for optimal patient management. This study, therefore, aimed to assess the utility of saliva-based liquid biopsy as a noninvasive source of cfDNA and cf-mtDNA for detecting head and neck cancer (HNSCC).One hundred thirty-three patients diagnosed with either oral leukoplakia (OLK) or HNSCC were compared with 137 healthy volunteers. An unstimulated whole saliva sample was collected from each participant. The absolute copy numbers of salivary cf-mtDNA and cfDNA were quantified using Multiplex Quantitative PCR. Two diagnostic indices based on the investigated molecules were assessed for their ability to differentiate between different diagnostic categories.The median scores of cfDNA and cf-mtDNA were statistically significantly higher among HNSCC patients (p 0.05), revealing area under the curve values of 0.758 and 0.826, respectively. The associated accuracy for this test in discriminating HNSCC from other diagnostic categories was 77.37% for the cfDNA-based index and 80.5% for the cf-mtDNA-based index. The median score of cfDNA was statistically significantly higher for patients with severe epithelial dysplasia (OED) compared to those with epithelial keratosis with no OED and mild OED. However, there was no significant difference between controls and OLK individuals.cfDNA and cf-mtDNA showed potential for use as precision medicine tools to detect HNSCC. Further multi-centre prospective studies are warranted to assess the prognostic utility of these molecules.

Machine learning (ML) models are often modelled to predict cancer prognosis but rarely consider spatial factors in a region. Hence this study explored machine learning algorithms utilising Local Government Areas (LGAs) in Queensland, Australia to spatially predict 3- and 5-year prognosis of oral cancer patients and provide clinical interpretability of the predicted outcome made by the ML model.Data from a total of 3,841 oral cancer patients were retrieved from the Queensland Cancer Registry (QCR). Synthesizing minority oversampling technique together with edited nearest neighbours (SMOTE-ENN) was used to pre-process unbalanced datasets. Five ML models: logistic regression, random forest classifier, XGBoost, Gaussian Naïve Bayes and Voting Classifier were trained. Predictive features were age, sex, LGAs, tumour site and differentiation. Outcomes were 3- and 5-year overall survival of patients. Model performances on test set were evaluated using area under the curve and F1 scores. SHapley Additive exPlanations (SHAP) method was applied to the best performing model for model interpretation of the predicted outcome.The Voting Classifier was the best performing model with F1 score of 0.58 and 0.64 for 3- and 5-year overall survival, respectively. Age was the most important feature in the Voting Classifier in 3- and 5-year prognosis prediction. LGAs at diagnosis was the top 3 predictive feature for both 3- and 5-year models.The Voting Classifier demonstrated the best overall performance in classifying both 3- and 5-year overall survival of oral cancer patients in Queensland. SHAP method provided clinical understanding of the predictive features of the Voting Classifier.

Oral squamous cell carcinoma is a lethal and deforming disease of rising global significance. While advances in diagnosis and management have improved many aspects of quality of life, approximately 50% of patients die from progressive, recurrent or metastatic disease. The authors of this paper look towards the future of cancer therapy, combining innovative and imaginative approaches, to hypothesise new, effective tumour targetting therapies that reduce deleterious side effects from contemporary invasive and ablative treatment. Ultimately, they pose the question: can we envisage a time when terminal diseases are regarded as chronic, manageable conditions?

Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms.Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations.Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period.Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

As he approaches his 40th year of clinical practice, Peter Thomson reflects on a professional lifetime as a clinician, surgeon, teacher and researcher. His clinical expertise as an oral oncologist, and his research work in carcinogenesis and interventional management of potentially malignant disease has taken him on an international journey spanning the UK, Singapore, Hong Kong and Australia. Taking time to reflect on his career to date, he poses the fundamental question: if life truly begins at 40, what about dentistry?

Simulation is increasingly recognised as an integral component of modern healthcare education, especially for learning irreversible interventional procedures. Dentistry has utilised various types of simulation activities during preclinical education for many years. This article reviews the application of the simulation clinic in contemporary dental education at James Cook University’s dental school in Australia and offers insight into how ‘making it real’ can stimulate the successful acquisition of clinical skills.

Circulating tumour cells (CTCs) are cancer cells released by cancer into the peripheral circulation. Haematogenous tumour spread is a hallmark of metastatic malignancy and a key factor in cancer recurrence and prognosis. CTCs have diagnostic and prognostic significance for a number of adenocarcinomas and melanoma. A review of the published peer-reviewed literature was performed to determine the clinical relevance of CTCs as a biomarker in the management of oral squamous cell carcinoma (OSCC). Fourteen studies met the eligibility criteria. With regard to patients with OSCC, this review found the following: (1) CTCs have been detected using multiple techniques; (2) the presence of CTCs does not appear to be related to tumour differentiation or size; (3) CTCs may be detected without lymph node involvement; (4) the detection of CTCs may be prognostic for both disease-free survival and overall survival; (5) quantification of CTCs may reflect the efficacy of therapy; (6) CTCs may be of value for ongoing patient monitoring. Preliminary evidence suggests that CTCs have diagnostic and prognostic potential as a biomarker for oral cancer management and warrant further investigation to determine their appropriate place in the management of OSCC patients.

Background: The increasing incidence of oropharyngeal cancer in many developed countries has been attributed to human papillomavirus type 16 (HPV16) infections. Recently, HPV16 E6 serology has been identified as a promising early marker for oropharyngeal cancer. Therefore, characterization of HPV16 E6 seropositivity among individuals without cancer is warranted.Methods: A total of 4,666 controls were pooled from several studies of cancer and HPV seropositivity, all tested within the same laboratory. HPV16 E6 seropositive controls were classified as having (i) moderate [mean fluorescent intensity (MFI) ≥ 484 and Results: Thirty-two (0.7%) HPV16 E6 seropositive controls were identified; 17 (0.4%) with moderate and 15 (0.3%) with high seroreactivity. High HPV16 E6 seroreactivity was associated with former smoking [odds ratio (OR), 5.5; 95% confidence interval (CI), 1.2–51.8], and seropositivity against HPV16 L1 (OR, 4.8; 95% CI, 1.3–15.4); E2 (OR, 7.7; 95% CI, 1.4–29.1); multiple HPV16 proteins (OR, 25.3; 95% CI, 2.6–119.6 for three HPV16 proteins beside E6) and HPV33 E6 (OR, 17.7; 95% CI, 1.9–81.8). No associations were observed with moderate HPV16 E6 seroreactivity.Conclusions: High HPV16 E6 seroreactivity is rare among individuals without diagnosed cancer and was not explained by demographic factors.Impact: Some HPV16 E6 seropositive individuals without diagnosed HPV-driven cancer, especially those with seropositivity against other HPV16 proteins, may harbor a biologically relevant HPV16 infection. Cancer Epidemiol Biomarkers Prev; 24(4); 683–9. ©2015 AACR.

Background: Oral squamous cell carcinoma (OSCC) is a global healthcare problem associated with poor clinical outcomes. Early detection is key to improving patient survival. OSCC may be preceded by clinically recognizable lesions, termed oral potentially malignant disorders (OPMD). As histologic assessment of OPMD does not accurately predict their clinical behavior, biomarkers are required to detect cases at risk of malignant transformation. Epidermal growth factor receptor gene copy number (EGFR GCN) is a validated biomarker in lung non–small cell carcinoma. We examined EGFR GCN in OPMD and OSCC to determine its potential as a biomarker in oral carcinogenesis.Methods: EGFR GCN was examined by in situ hybridization (ISH) in biopsies from 78 patients with OPMD and 92 patients with early-stage (stages I and II) OSCC. EGFR ISH signals were scored by two pathologists and a category assigned by consensus. The data were correlated with patient demographics and clinical outcomes.Results: OPMD with abnormal EGFR GCN were more likely to undergo malignant transformation than diploid cases. EGFR genomic gain was detected in a quarter of early-stage OSCC, but did not correlate with clinical outcomes.Conclusion: These data suggest that abnormal EGFR GCN has clinical utility as a biomarker for the detection of OPMD destined to undergo malignant transformation. Prospective studies are required to verify this finding. It remains to be determined if EGFR GCN could be used to select patients for EGFR-targeted therapies.Impact: Abnormal EGFR GCN is a potential biomarker for identifying OPMD that are at risk of malignant transformation. Cancer Epidemiol Biomarkers Prev; 25(6); 927–35. ©2016 AACR.

Supplementary Table 1 - Characteristics of the two groups of patients, including their clinical outcomes.

Supplemental Table 1. Study-specific definitions for categorization of tobacco and alcohol use.

Oral cancer may arise from oral leukoplakia and oral lichenoid mucositis (oral lichen planus and oral lichenoid lesions) subtypes of oral potentially malignant disorders. As not all patients will develop oral cancer in their lifetime, the availability of malignant transformation predictive platforms would assist in the individualized treatment planning and formulation of optimal follow-up regimens for these patients. Therefore, this study aims to compare and select optimal machine learning (ML)-based models for stratifying the malignant transformation status of patients with oral leukoplakia and oral lichenoid mucositis. One thousand one hundred and eighty-seven patients with oral leukoplakia and oral lichenoid mucositis treated at three tertiary health institutions in Hong Kong, Newcastle UK, and Lagos Nigeria were included in the study. Demographic, clinical, pathological, and treatment-based factors obtained at diagnosis and during follow-up were used to populate and compare forty-six machine learning-based models. These were implemented as a set of twenty-six predictors for centers with substantial data quantity and fifteen predictors for centers with insufficient data. Two best models were selected according to the number of variables. We found that the optimal ML-based risk models with twenty-six and fifteen predictors achieved an accuracy of 97% and 94% respectively following model testing. Upon external validation, both models achieved a sensitivity, specificity, and F1-score of 1, 0.88, and 0.67 on consecutive patients treated after the construction of the models. Furthermore, the 15-predictor ML model for centers with reduced data achieved a higher sensitivity for identifying oral leukoplakia and oral lichenoid mucositis patients that developed malignancies in other treatment settings compared to the binary oral epithelial dysplasia system for risk stratification (0.96 vs 0.82). These findings suggest that machine learning-based models could be useful potentially to stratify patients with oral leukoplakia and oral lichenoid mucositis according to their risk of malignant transformation in different settings.

The east of Cali is composed of loose sand deposits with high water table levels. This condition and the high seismic hazard of the city make cyclic liquefaction one of the main hazards in the city, which may affect more than 600,000 citizens and important infrastructures such as the city’s main drinking water treatment plants. Therefore, it was decided to design and implement a seismic monitoring center to study the behavior of liquefiable soils under local seismogenic conditions, in which subduction earthquakes predominate. First, more than 130 earthquakes from two seismic monitoring centers with liquefiable layers in the USA were studied to determine the requirements for the adequate design of the monitoring center. Then, a robust geotechnical and seismic characterization of the study area including SPT, CPTu, and seismic and ambient noise tests were carried out. From this information, the specifications and location of the instruments and, in general, the characteristics of the monitoring center were defined. The monitoring center has been planned to be established in two stages, and the first one has already been built and commissioned. The implementation of the first stage allowed to adequately record 35 earthquakes from different seismogenic sources, most of them from subduction earthquakes, and to verify that the potentially liquefiable layer remains saturated throughout the year. Subsequent ground motion sensors will allow to deeply study and understand large shear strains and excess pore pressures generation in the soil deposit, as well as their relationships with different intensity measures. The experience shared herein can benefit the design, construction, and operation of other seismic monitoring centers across the world.

Within a New Zealand business cycle context, we assess whether Hamilton’s (H84) OLS regression methodology produces stylised business cycle facts which are materially different from the Hodrick–Prescott (HP) and Baxter–King (BK) measures, and whether using the H84 predictor for forecast-extension improves the HP filter’s properties at the ends of series. Stylised business cycle facts were computed for a set of key New Zealand macroeconomic variables. In general, H84 produces greater volatilities and less credible trend movements during key economic periods than either HP or BK, and so for this purpose there is no material advantage in using H84 over HP or BK. At the ends of series, we evaluate the performance of the forecast-extended HP filter for three representative business cycle environments. The forecast-extension methods compared include the H84 predictor, the informed forecasts of three leading New Zealand economic agencies, two methods based on models of past data, and the HP filter with no extension. As expected, the better the forecast-extension the more accurate the HP filter at the ends of series and, as reported elsewhere in the literature, the HP filter with no extension performed poorly. However, in all cases considered the H84 predictor performed worst.

Patagonian toothfish (Dissostichus eleginoides) is an economically and ecologically important fish species in the family Nototheniidae, found at depths between 70 and 2,500 meters on the southern shelves and slopes around the sub-Antarctic islands of the Southern Ocean. Genomic sequence data for this species is limited. Here, we report a high-quality assembly and annotation of theD. eleginoidesgenome, generated using a combination of Illumina, PacBio and Omni-C sequencing technologies. To aid the genome annotation, the transcriptome derived from a variety of toothfish tissues was also generated using both short and long read sequencing methods. The final genome assembly was 797.8 Mb with a N50 scaffold length of 3.5 Mb. Approximately 31.7% of the genome consisted of repetitive elements. A total of 35,543 putative protein-coding regions were identified, of which 50% have been functionally annotated. Transcriptomics analysis showed that approximately 64% of the predicted genes (22,617 genes) were found to be expressed in the tissues sampled. Comparative genomics analysis revealed that the anti-freeze glycoprotein (AFGP) locus ofD. eleginoidesdoes not contain any AFGP proteins compared to the same locus in the Antarctic toothfish (Dissostichus mawsoni). This is in agreement with previously published results looking at hybridization signals and confirms that Patagonian toothfish do not possess AFGP coding sequences in their genome. The high-quality genome assembly of the Patagonian toothfish will provide a valuable genetic resource for ecological and evolutionary studies on this and other closely related species.

BackgroundThe impact and utility of machine learning (ML)-based prediction tools for cancer outcomes including assistive diagnosis, risk stratification, and adjunctive decision-making have been largely described and realized in the high income and upper-middle-income countries. However, statistical projections have estimated higher cancer incidence and mortality risks in low and lower-middle-income countries (LLMICs). Therefore, this review aimed to evaluate the utilization, model construction methods, and degree of implementation of ML-based models for cancer outcomes in LLMICs.MethodsPubMed/Medline, Scopus, and Web of Science databases were searched and articles describing the use of ML-based models for cancer among local populations in LLMICs between 2002 and 2022 were included. A total of 140 articles from 22,516 citations that met the eligibility criteria were included in this study.ResultsML-based models from LLMICs were often based on traditional ML algorithms than deep or deep hybrid learning. We found that the construction of ML-based models was skewed to particular LLMICs such as India, Iran, Pakistan, and Egypt with a paucity of applications in sub-Saharan Africa. Moreover, models for breast, head and neck, and brain cancer outcomes were frequently explored. Many models were deemed suboptimal according to the Prediction model Risk of Bias Assessment tool (PROBAST) due to sample size constraints and technical flaws in ML modeling even though their performance accuracy ranged from 0.65 to 1.00. While the development and internal validation were described for all models included (n=137), only 4.4% (6/137) have been validated in independent cohorts and 0.7% (1/137) have been assessed for clinical impact and efficacy.ConclusionOverall, the application of ML for modeling cancer outcomes in LLMICs is increasing. However, model development is largely unsatisfactory. We recommend model retraining using larger sample sizes, intensified external validation practices, and increased impact assessment studies using randomized controlled trial designsSystematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=308345, identifier CRD42022308345.

As Peter Thomson returns to Australia to take up the position of head of dentistry at James Cook University in northern Queensland, he reflects on the unique rural and regional clinical educational base as well as the significant contributions that the College of Medicine and Dentistry is making to ensure relevance and effectiveness in the delivery of education and contemporary clinical practice in the tropics.

This study aims to examine the feasibility of ML-assisted salivary-liquid-biopsy platforms using genome-wide methylation analysis at the base-pair and regional resolution for delineating oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). A nested cohort of patients with OSCC and OPMDs was randomly selected from among patients with oral mucosal diseases. Saliva samples were collected, and DNA extracted from cell pellets was processed for reduced-representation bisulfite sequencing. Reads with a minimum of 10× coverage were used to identify differentially methylated CpG sites (DMCs) and 100 bp regions (DMRs). The performance of eight ML models and three feature-selection methods (ANOVA, MRMR, and LASSO) were then compared to determine the optimal biomarker models based on DMCs and DMRs. A total of 1745 DMCs and 105 DMRs were identified for detecting OSCC. The proportion of hypomethylated and hypermethylated DMCs was similar (51% vs. 49%), while most DMRs were hypermethylated (62.9%). Furthermore, more DMRs than DMCs were annotated to promoter regions (36% vs. 16%) and more DMCs than DMRs were annotated to intergenic regions (50% vs. 36%). Of all the ML models compared, the linear SVM model based on 11 optimal DMRs selected by LASSO had a perfect AUC, recall, specificity, and calibration (1.00) for OSCC detection. Overall, genome-wide DNA methylation techniques can be applied directly to saliva samples for biomarker discovery and ML-based platforms may be useful in stratifying OSCC during disease screening and monitoring.

Introduction: Treatment of anemia in dialysis patients has been associated with increased risk of vascular access thrombosis (VAT). Proactive IV irOn Therapy in hemodiALysis Patients (PIVOTAL) was a clinical trial of proactive compared with reactive i.v. iron therapy in patients requiring hemodialysis. We analyzed the trial data to determine whether randomized treatment arm, alongside other clinical and laboratory variables, independently associated with VAT.Methods: In PIVOTAL, 2141 adult patients were randomized. The type of vascular access (arteriovenous fistula [AVF], arteriovenous graft [AVG], or central venous catheter [CVC]) was recorded at baseline and every month after randomization. The associations between clinical and laboratory data and first VAT were evaluated in a multivariate analysis.Results: A total of 480 (22.4%) participants experienced VAT in a median of 2.1 years of follow-up. In multivariable analyses, treatment arm (proactive vs. reactive) was not an independent predictor of VAT (hazard ratio [HR] 1.13, P = 0.18). Diabetic kidney disease (HR 1.45, P < 0.001), AVG use (HR 2.29, P < 0.001), digoxin use (HR 2.48, P < 0.001), diuretic use (HR 1.25, P = 0.02), female sex (HR 1.33, P = 0.002), and previous/current smoker (HR 1.47, P = 0.004) were independently associated with a higher risk of VAT. Angiotensin receptor blocker (ARB) use (HR 0.66, P = 0.01) was independently associated with a lower risk of VAT.Conclusion: In PIVOTAL, VAT occurred in nearly 1 quarter of participants in a median of just >2 years. In this post hoc analysis, randomization to proactive i.v. iron treatment arms did not increase the risk of VAT.

Oral squamous cell carcinoma (OSCC) is a lethal and deforming disease of rising global significance. Although traditionally presenting in older patients, evidence suggests that OSCC is increasingly seen in the young (≤45 years at diagnosis), who are believed to exhibit aggressive disease and poor prognosis. By reviewing a cohort of 467 consecutive OSCC patients treated over a 19-year period, this study investigates the demographic profile, clinicopathological features and clinical outcomes characteristic of young OSCC patients in Hong Kong.

This work presents a novel technique for estimating the prestressing forces in simply supported beams with axial prestress force. The technique is based on the use of generic finite elements for modeling the beam and experimental time-domain response to simultaneously identify axial forces and generic parameters. Parameter updating is accomplished using a Simulated Annealing algorithm implemented for the solution of the prestress force identification problem. The effectiveness of the method was assessed in numerical simulations and was further verified on an experimental prestressed concrete beam. The results show that the inclusion of generic elements allows the identification of the force to be achieved even in the presence of errors in model parameters, thus eliminating the restraints of previous approaches.

To compare the treatment response and prognosis of oral cavity cancer between non-smoking and non-alcohol-drinking (NSND) patients and smoking and alcohol-drinking (SD) patients. A total of 313 consecutively treated patients from 2000 to 2019 were included. Demographic, clinicopathologic, treatment, and prognosis information were obtained. Relapse-free survival (RFS), disease-specific survival (DSS), and overall survival (OS) were compared between NSND and SD groups using Kaplan-Meier plots, log-rank test, and multivariate Cox regression analysis. Sample prevalence of NSND patients was 54.6%. These patients were predominantly females in their eighth decade with lower prevalence of floor of the mouth cancers compared to SD patients (1.8% vs 14.8%). No difference in the RFS and DSS between both groups was found following multivariable analysis; however, NSND patients had better OS (HR (95% CI) − 0.47 (0.29–0.75); p = 0.002). Extracapsular extension was associated with significantly poorer OS, DSS, and RFS in this oral cavity cancer cohort. Treatment response and disease-specific prognosis are comparable between NSND and SD patients with oral cavity cancer. However, NSND patients have better OS. This study shows that oral cavity cancer in NSND is not less or more aggressive compared to SD patients. Although better survival is expected for NSND than SD patients, this is likely due to the reduced incidence of other chronic diseases in the NSND group.

Traditional Chinese medicine (TCM) is an ancient practice that dates back more than 2,000 years and has evolved into a unique system of diagnosis and disease management that, in particular, employs herbal medicines and dietary therapies but in addition utilises acupuncture, massage and qigong (meditation, breathing and movement) exercises.1,2 It is especially popular in Hong Kong and, following legislation to establish the Chinese Medicine Ordinance in 1999 and subsequent registration of TCM practitioners via the Chinese Medicine Council of Hong Kong, has seen widened patient participation.

Objectives: This study aims to determine the diagnostic test accuracy (DTA) of hypermethylated DNA biomarkers in saliva and oral swabs for oral squamous cell carcinoma (OSCC) detection from the prevalidation studies available. Materials and Methods: Electronic database searching of PubMed, EMBASE, Cochrane Library, Scopus, Web of Science, and LILACS was conducted to identify relevant articles that were published between January 1, 2000, and August 1, 2020. Results: Meta-analysis was conducted based on 11 of 20 studies selected for review. Included studies had high bias concerns on the QUADAS-2 study assessment tool. We found that salivary and oral swab hypermethylation markers had better specificity than sensitivity for oral cancer detection. Summary sensitivity and specificity (95% CI) of hypermethylation panels were 86.2% (60–96.2) and 90.6% (85.9–93.9) while for individual markers, summary sensitivity and specificity (95% CI) were 70% (56.9–80.5) and 91.9% (80.3–96.9), respectively. Respective positive and negative likelihood ratios for combined markers were 9.2 (5.89–14.36) and 0.15 (0.05–0.5), and 8.61 (3.39–21.87) and 0.33 (0.22–0.49) for single-application biomarkers. Conclusion: DNA hypermethylation biomarkers especially in combination have acceptable DTA that warrants further optimization with rigorous biomarker evaluation methods for conclusive determination of their efficacy.

Advanced chronic kidney disease is a serious and common medical condition with significant treatment choices incurring varying high treatment burdens. Better understanding on how to best collect quality of life (QoL) in this unique situation may help guide critical decisions. This study investigates the acceptability of digital QoL questionnaires completed during routine haemodialysis sessions. Qualitative data was collected from patient (n=23) and clinical researcher (n=2) interviews alongside analysis of data from questionnaires completed by patients (n=101) during a 6-week validation study. Interviews refined the content and format of digital QoL questionnaires and provided novel insights regarding how patients assessed and completed QoL questions. This study suggests collecting QoL data using digital tablet technology during routine haemodialysis clinics is both feasible and acceptable to patients and has provided novel insights that are not routinely available with traditional methods.

Advanced chronic kidney disease is a serious and common medical condition with significant treatment choices incurring varying high treatment burdens. Better understanding on how to best collect quality of life (QoL) in this unique situation may help guide critical decisions. This study investigates the acceptability of digital QoL questionnaires completed during routine haemodialysis sessions. Qualitative data was collected from patient (n=23) and clinical researcher (n=2) interviews alongside analysis of data from questionnaires completed by patients (n=101) during a 6-week validation study. Interviews refined the content and format of digital QoL questionnaires and provided novel insights regarding how patients assessed and completed QoL questions. This study suggests collecting QoL data using digital tablet technology during routine haemodialysis clinics is both feasible and acceptable to patients and has provided novel insights that are not routinely available with traditional methods.

BACKGROUND AND AIMS Although the risk for congestive heart failure (CHF) decreases after kidney transplantation (KT) compared with dialysis, it remains a significant clinical concern associated with a higher risk of mortality, cardiovascular events and kidney graft loss. Available epidemiological data on CHF after KT are limited, outdated and have mostly focused on traditional risk factors. We aim to describe the risk, predictors and outcomes associated with de novo CHF after KT. METHOD We used electronic patient records from the West of Scotland renal database to retrospectively investigate de novo CHF in adult kidney transplant recipients between 1 January 2010 and 31 March 2020. Heart failure was ascertained using a combination of physician-reported diagnosis, echocardiographic criteria, radiological evidence of heart failure and elevation of NT-proBNP levels. Participants were followed up until 15 April 2021. Multivariable regression analysis was used to identify independent correlates of post-transplantation de novo CHF (odds ratio [OR] and 95% confidence interval [CI]) and examine de novo CHF as a predictor of death and graft loss after transplantation. RESULTS One hundred and four (8.9%) of 1172 transplant recipients had de novo CHF [mean age, 50 ± 13 years; 470 (40%) women]. The cumulative incidences of de novo CHF were 3.8% (95% CI: 2.9–5.1), 5.2% (95% CI: 4.1–6.7) and 7.1% (95% CI: 5.6–8.9) at 1, 3 and 5 years, respectively. Risk factors for de novo CHF included older recipient age (OR: 1.04; 95% CI: 1.02–1.06; P CONCLUSION Congestive heart failure is a common complication after kidney transplantation associated with markedly increased risk for death and graft loss. Identification and optimization of pretransplantation risk factors for CHF and pre-emptive transplantation, suggests targets for improving outcomes.

BACKGROUND AND AIMS Physical activity (PA) is widely recommended for the prevention of chronic conditions including cardiovascular (CV) disease. In chronic kidney disease (CKD), it is unclear whether PA confers a similar benefit. We examined whether the duration and intensity of PA are associated with the risk of CV disease and mortality and whether the relationship differs in CKD. METHOD Participants were from UK Biobank: a prospective cohort study with over 500 000 participants. The estimated glomerular filtration rate was calculated using cystatin C (eGFRcys). CKD was defined according to the KDIGO guidelines and participants were categorized as no CKD (eGFRcys > 90mL/min/1.73m2), CKD G1-2 (eGFRcys 60–89mL/min/1.73m2) or CKD G3-5 (eGFRcys < 60mL/min/1.73m2). Exercise duration and intensity were self-reported using the international physical activity questionnaire (IPAQ) and participants were categorized into four groups: inactive (reference), low, moderate and vigorous PA, according to World Health Organisation (WHO) weekly PA recommendations. Cox proportional hazards models tested associations between PA category and a composite endpoint of CV disease (myocardial infarction or stroke) or all-cause mortality across CKD categories. Models were adjusted for other known risk factors for CV disease and death including age, smoking status, blood pressure, eGFRcys and albuminuria. RESULTS Of 502 460 participants in UK Biobank, 123 167 were excluded because of missing biochemistry or IPAQ data and a further 21 084 were excluded because of pre-existing CV disease: 358 209 participants were included in the analyses. Of these 182 457 (51.0%) were classed as no CKD, 162 621 (45.4%) as CKD G1-2 and 13 131 (3.7%) as CKD G3-5. A total of 48 369 (13.5%) of participants were classed as inactive and 211 591 (16.5%) as undertaking vigorous PA. In participants without CKD, any PA above inactivity was associated with a reduced risk of reaching the combined endpoint by approximately 20% (low: hazard ratio, HR 0.77, 95% confidence interval, CI 0.67–0.89; moderate: HR 0.80, 95%CI 0.70–0.91; vigorous: HR 0.81, 95%CI 0.73–0.90, P < 0.001). This relationship is maintained in CKD G1-2, but in CKD G3-5, moderate (HR 0.75, 95%CI 0.61–0.93) and vigorous (HR 0.77, CI 0.66–0.89, P < 0.001) activity are associated with reduced risk of the combined endpoint (Table 1). Interestingly across all categories of CKD, the majority of participants considered that they undertook more than the WHO minimum recommended PA per week. CONCLUSION Achieving the minimum weekly targets for PA set by WHO is associated with a significantly reduced risk of a combined endpoint of CV disease and death. This relationship is preserved in those with CKD G1-2, even when adjusted for other recognized risk factors. The benefit is seen in CKD G3-5 with increased intensity of PA, above the WHO minimum. PA data is self-reported which limits the accuracy and association does not prove causality. However, patients with CKD have a much higher risk of CVD and death and PA is a simple, low-cost intervention that warrants further study to improve CV morbidity and all-cause mortality amongst people with CKD.

Delivering clinical excellence is fundamental to the success of a 21st century dental school's mission and yet, our ability to define clinical excellence in practice remains surprisingly elusive. In this paper, Peter Thomson explores the complex and multi-faceted nature of clinical excellence, confirming its pivotal role throughout knowledge creation, teaching, training, lifelong education and clinical practice. Ultimately, our ability to deliver optimal patient care, manage new and emergent disease and enhance prevention and health promotion for the future require dental education and clinical service to be better aligned and more fully integrated with general healthcare provision for all.

As routine care was suspended in most countries, one could anticipate progression of undiagnosed and managed oral disease. Patients are usually unaware of the development of oral disease as it is not visible to them and largely asymptomatic, especially in its early stages. The natural progression of conditions such as caries and periodontitis is inevitable without diagnosis and management. The full extent of patient harm because of the suspension of routine dental care can only be estimated when routine oral examinations are fully re-established, and even then, we will probably never know the number of individuals impacted or the extent of disease progression and harm. In first-world countries, there has always been a back-up emergency treatment system for dental problems. For example, in the UK, the safety net for life-threatening swellings and for acute pain relief is the accident and emergency services. This system remained in place during the COVID-19 pandemic. Courts could be expected to understand the coronavirus context and would take this into account should there be a complaint against the clinician about access to care. The suspension of routine dental care to save lives will lead to the closure of many dental practices due to substantial financial impact. The return to routine care will be slow, with prioritisation of non-aerosol generating procedures while we look to further understand methods to mitigate transmission risk via infected aerosol and spatter. Inevitably, the cost of personal protective equipment and the lower volume of patients pose a continued threat to businesses., Key points Natural history of oral disease progression if not managed is described.Concerns about the medico-legal consequences of reduced access to dental care are discussed.The economic repercussions of the COVID-19 need for suspension of routine care and the future increased costs of practice are presented.

This review sought to determine the range and nature of prospective-sampling and blinding methods for validating nonviral biofluid markers diagnostic of head and neck carcinomas. Electronic database searching was conducted to identify studies published in English from January 1, 2009 to August 1, 2020. Sixteen studies from 17 articles published between 2011 and 2020 were included in this review. We found that about 3 out of 100 studies utilized at least one of the mock testing approaches for biomarker validation. Protein, mRNA, and metabolomic markers also represented the only groups whose validation has been attempted using these methods. Furthermore, studies that utilized both methods were found to have lower bias concerns on the quality assessment of diagnostic accuracy studies (QUADAS-2) tool. Overall, there is a need to include these protocols in research endeavours verifying diagnostic biomarkers for head and neck carcinomas following the preliminary establishment of their classification accuracy.

Internationalisation may be defined as a series of processes whereby an institute strives to increase its influence and effectiveness through global networking. In higher education, this offers opportunities to enhance communication and mobilisation between educational systems. To be globally competitive, the international university of the future must embrace digital technology, online courses and ongoing lifetime learning, especially for alumni to facilitate networks of global expertise. Oral disease neither recognises nor respects international boundaries, nor therefore should dental education, research and clinical expertise which are highly valued commodities in society. For dentistry, internationalisation offers real opportunities to influence and promote the highest standards of oral health education and clinical practice throughout the world. The international university of the future must recognise the importance of setting the highest standards for oral health across the world while maintaining regional structures and priorities.

Background: The global burden of oral squamous cell carcinoma (OSCC) remains formidable. Identifying factors predictive of aggressive tumour behaviour, disease progression and reduced survival time may assist in early identification of “high-risk” patients and appropriately target combination cancer therapies. Methods: A retrospective review of 467 OSCC patients treated over a 19-year period facilitated detailed clinico-pathological database analysis and determination of clinical outcome categories based upon time to progressive disease (loco-regional tumour recurrence and/or distant metastasis), overall death and OSCC-related death (death directly attributable to OSCC). Odds ratio (OR) and hazard ratio (HR) statistical measures were used to investigate relationships between patient demographics and clinico-pathological tumour features with clinical outcome. Results: Older age at presentation (P =.002) and a history of previous non–head and neck cancer (P =.010) increased the risk of overall death. OR for progressive disease development (P =.008) and OSCC-related death (P =.019) was most significant for buccal tumours. HR confirmed advanced-stage disease increased the risk of progressive disease (P

Background: A large number of oral squamous cell carcinomas (OSCCs) are believed to be preceded by oral potentially malignant disorders (OPMD) that have an increased likelihood of malignant transformation compared to clinically normal mucosa. This study was performed to identify differentially expressed genes between OPMDs that underwent malignant transformation (MT) and those that did not, termed “non-transforming” (NT) cases. Methods: Total RNA was extracted from formalin-fixed paraffin-embedded tissue biopsies of 20 OPMD cases with known clinical outcomes (10 MT vs. 10 NT). Samples were assessed for quantity, quality and integrity of RNA prior to sequencing. Analysis for differential gene expression between MT and NT was performed using statistical packages in R. Genes were considered to be significantly differentially expressed if the False Discovery Rate corrected P-value was 1.90). Analysis of RNA-Sequencing outputs revealed 41 genes (34 protein-coding; 7 non-coding) that were significantly differentially expressed between MT and NT cases. The log2 fold change for the statistically significant differentially expressed genes ranged from −2.63 to 2.48, with 23 protein-coding genes being downregulated and 11 protein-coding genes being upregulated in MT cases compared to NT cases. Conclusion: Several candidate genes that may play a role in malignant transformation of OPMD have been identified. Experiments to validate these candidates are underway. It is anticipated that this work will contribute to better understanding of the etiopathogenesis of OPMD and development of novel biomarkers.

Background: The natural history of oral squamous cell carcinoma (OSCC) is complicated by progressive disease including loco-regional tumour recurrence and development of distant metastases. Accurate prediction of tumour behaviour is crucial in delivering individualized treatment plans and developing optimal patient follow-up and surveillance strategies. Machine learning algorithms may be employed in oncology research to improve clinical outcome prediction. Methods: Retrospective review of 467 OSCC patients treated over a 19-year period facilitated construction of a detailed clinicopathological database. 34 prognostic features from the database were used to populate 4 machine learning algorithms, linear regression (LR), decision tree (DT), support vector machine (SVM) and k-nearest neighbours (KNN) models, to attempt progressive disease outcome prediction. Principal component analysis (PCA) and bivariate analysis were used to reduce data dimensionality and highlight correlated variables. Models were validated for accuracy, sensitivity and specificity, with predictive ability assessed by receiver operating characteristic (ROC) and area under the curve (AUC) calculation. Results: Out of 408 fully characterized OSCC patients, 151 (37%) had died and 131 (32%) exhibited progressive disease at the time of data retrieval. The DT model with 34 prognostic features was most successful in identifying “true positive” progressive disease, achieving 70.59% accuracy (AUC 0.67), 41.98% sensitivity and a high specificity of 84.12%. Conclusion: Machine learning models assist clinicians in accessing digitized health information and appear promising in predicting progressive disease outcomes. The future will see increasing emphasis on the use of artificial intelligence to enhance understanding of aggressive tumour behaviour, recurrence and disease progression.

Background: Oral squamous cell carcinoma (OSCC) is a lethal and deforming disease of rising incidence. With poor 5-year survival rates associated with higher stage disease, there is a need in clinical practice for reliable prognostic determinants to consolidate treatment planning and coordinate therapeutic approaches to improve long-term clinical outcomes for patients. Methods: A retrospective clinicopathological review of 467 OSCC patients with documented clinical outcome and treated in Hong Kong over a 19-year period was undertaken to investigate the potential prognostic role of 4 specific histopathological features of invasive tumour behaviour: perineural invasion (PNI), bone invasion (BNI), lymphovascular invasion (LVI) and extra-nodal extension (ENE) in metastatic neck disease. Results: Histopathological data for PNI, BNI, LVI and ENE, and stratified as zero, one, two, three or four positives, were available for 279 patients. A trend for decreased disease-free status was seen with increasing numbers of positive histopathological features, although this was not statistically significant (P =.1076). The time to onset of further disease (loco-regional recurrence and/or distant metastasis) was statistically significant, however, with progressive disease presenting most rapidly with increasing numbers of positive invasive parameters (P =.000152). Conclusion: PNI, BNI, LVI and ENE, especially when found in combination, show promise as prognostic markers of poor clinical outcome following OSCC treatment. Further, multi-centre prospective studies are required to confirm the predictive value of multi-positive histopathological features in clinical practice and to help improve individualised treatment planning.

To realise the benefits of new diagnostic techniques for the prediction of oral cancer, further validation and multicentre analyses are needed to determine their clinical impact in contemporary practice.

Background: Preventive and early diagnostic methods such as health promotion and disease screening are increasingly advocated to improve detection and survival rates for oral cancer. These strategies are most effective when targeted at "high-risk" individuals and populations. Bayesian disease-mapping modelling is a statistical method to quantify and explain spatial and temporal patterns for risk and covariate factor influence, thereby identifying "high-risk" sub-regions or "case clustering" for targeted intervention. Rarely applied to oral cancer epidemiology, this paper highlights the efficacy of disease mapping for the Hong Kong population. Methods: Following ethical approval, anonymized individual-level data for oral cancer diagnoses were obtained retrospectively from the Clinical Data Analysis and Reporting System (CDARS) of the Hong Kong Hospital Authority (HA) database for a 7-year period (January 2013 to December 2019). Data facilitated disease mapping and estimation of relative risks of oral cancer incidence and mortality. Results: A total of 3,341 new oral cancer cases and 1,506 oral cancer-related deaths were recorded during the 7-year study period. Five districts, located in Hong Kong Island and Kowloon, exhibited considerably higher relative incidence risks with 1 significant "case cluster" hotspot. Six districts displayed higher mortality risks than expected from territory-wide values, with highest risk identified for two districts of Hong Kong Island. Conclusion: Bayesian disease mapping is successful in identifying and characterizing "high-risk" areas for oral cancer incidence and mortality within a community. This should facilitate targeted preventive and interventional strategies. Further work is encouraged to enhance global-level data and comprehensive mapping of oral cancer incidence, mortality and survival.

How can underlying disease be identified in patients with apparently routine signs and symptoms?

Oral squamous cell carcinoma is one of the commonest head and neck malignancies with approximately 350 000 cases reported annually and a mortality rate of 50% often attributed to late clinical presentation. Due to the close relationship between saliva bio-fluid and tumour lesions, optimizing salivary biomarkers for disease detection and screening provides a major new research direction in diagnostic oral oncology. As inter-tumour heterogeneity and intra-tumour heterogeneity are common within oral cavity neoplasms, it is unlikely that a single diagnostic or "risk-stratifying" saliva biomarker will suffice for universal translation to clinical practice. Therefore, this article highlights a number of promising saliva biomarker combinations for oral cavity cancer detection that require further research and validation to determine their true diagnostic potential.