A screening model for oral cancer using risk scores: development and validation

Creating area level indices of behaviours impacting cancer in Australia with a Bayesian generalised shared component model

This study develops a model-based index approach called the Generalised Shared Component Model (GSCM) by drawing on the large field of factor models. The proposed fully Bayesian approach accommodates heteroscedastic model error, multiple shared factors and flexible spatial priors. Moreover, unlike previous index approaches, our model provides indices with uncertainty. Focusing on unhealthy behaviors that increase the risk of cancer, the proposed GSCM is used to develop the Area Indices of Behaviors Impacting Cancer product - representing the first area level cancer risk factor index in Australia. This advancement aids in identifying communities with elevated cancer risk, facilitating targeted health interventions.

Risk Prediction Models for Oral Cancer: A Systematic Review

In the last 30 years, there has been an increasing incidence of oral cancer worldwide. Earlier detection of oral cancer has been shown to improve survival rates. However, given the relatively low prevalence of this disease, population-wide screening is likely to be inefficient. Risk prediction models could be used to target screening to those at highest risk or to select individuals for preventative interventions. This review (a) systematically identified published models that predict the development of oral cancer and are suitable for use in the general population and (b) described and compared the identified models, focusing on their development, including risk factors, performance and applicability to risk-stratified screening. A search was carried out in November 2022 in the Medline, Embase and Cochrane Library databases to identify primary research papers that report the development or validation of models predicting the risk of developing oral cancer (cancers of the oral cavity or oropharynx). The PROBAST tool was used to evaluate the risk of bias in the identified studies and the applicability of the models they describe. The search identified 11,222 articles, of which 14 studies (describing 23 models), satisfied the eligibility criteria of this review. The most commonly included risk factors were age (n = 20), alcohol consumption (n = 18) and smoking (n = 17). Six of the included models incorporated genetic information and three used biomarkers as predictors. Including information on human papillomavirus status was shown to improve model performance; however, this was only included in a small number of models. Most of the identified models (n = 13) showed good or excellent discrimination (AUROC > 0.7). Only fourteen models had been validated and only two of these validations were carried out in populations distinct from the model development population (external validation). Conclusions: Several risk prediction models have been identified that could be used to identify individuals at the highest risk of oral cancer within the context of screening programmes. However, external validation of these models in the target population is required, and, subsequently, an assessment of the feasibility of implementation with a risk-stratified screening programme for oral cancer.

Risk prediction models for head and neck cancer: A rapid review

Background

Cancer risk assessment models are used to support prevention and early detection. However, few models have been developed for head and neck cancer (HNC).

Methods

A rapid review of Embase and MEDLINE identified n = 3045 articles. Following dual screening, n = 14 studies were included. Quality appraisal using the PROBAST (risk of bias) instrument was conducted, and a narrative synthesis was performed to identify the best performing models in terms of risk factors and designs.

Results

Six of the 14 models were assessed as "high" quality. Of these, three had high predictive performance achieving area under curve values over 0.8 (0.87-0.89). The common features of these models were their inclusion of predictors carefully tailored to the target population/anatomical subsite and development with external validation.

Conclusions

Some existing models do possess the potential to identify and stratify those at risk of HNC but there is scope for improvement.

Performance of a simplified scoring system for risk stratification in oral cancer and oral potentially malignant disorders screening

BACKGROUND

Impact and efficiency of oral cancer and oral potentially malignant disorders screening are most realized in "at-risk" individuals. However, tools that can provide essential knowledge on individuals' risks are not applied in risk-based screening. This study aims to optimize a simplified risk scoring system for risk stratification in organized oral cancer and oral potentially malignant disorders screening.

METHODS

Participants were invited to attend a community-based oral cancer and oral potentially malignant disorders screening program in Hong Kong. Visual oral examination was performed for all attendees and information on sociodemographic characteristics as well as habitual, lifestyle, familial, and comorbidity risk factors were obtained. Individuals' status of those found to have suspicious lesions following biopsy and histopathology were classified as positive/negative and this outcome was used in a multiple logistic regression analysis with variables collected during screening. Odds ratio weightings were then used to develop a simplified risk scoring system which was validated in an external cohort.

RESULTS

Of 979 participants, 4.5% had positive status following confirmatory diagnosis. A 12-variable simplified risk scoring system with weightings was generated with an AUC, sensitivity, and specificity of 0.82, 0.71, and 0.78 for delineating high-risk cases. Further optimization on the validation cohort of 491 participants yielded a sensitivity and specificity of 0.75 and 0.87 respectively.

CONCLUSIONS

The simplified risk scoring system was able to stratify oral cancer and oral potentially malignant disorders risk with satisfactory sensitivity and specificity and can be applied in risk-based disease screening.

Clinical assessment for the detection of oral cavity cancer and potentially malignant disorders in apparently healthy adults

BACKGROUND

The early detection of oral cavity squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMD), followed by appropriate treatment, may improve survival and reduce the risk for malignant transformation respectively. This is an update of a Cochrane Review first published in 2013.

OBJECTIVES

To estimate the diagnostic test accuracy of conventional oral examination, vital rinsing, light-based detection, mouth self-examination, remote screening, and biomarkers, used singly or in combination, for the early detection of OPMD or OSCC in apparently healthy adults.

SEARCH METHODS

Cochrane Oral Health's Information Specialist searched the following databases: Cochrane Oral Health's Trials Register (to 20 October 2020), MEDLINE Ovid (1946 to 20 October 2020), and Embase Ovid (1980 to 20 October 2020). The US National Institutes of Health Trials Registry (ClinicalTrials.gov) and the World Health Organization International Clinical Trials Registry Platform were searched for ongoing trials. No restrictions were placed on the language or date of publication when searching the electronic databases. We conducted citation searches, and screened reference lists of included studies for additional references.

SELECTION CRITERIA

We selected studies that reported the test accuracy of any of the aforementioned tests in detecting OPMD or OSCC during a screening procedure. Diagnosis of OPMD or OSCC was provided by specialist clinicians or pathologists, or alternatively through follow-up.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts for relevance. Eligibility, data extraction, and quality assessment were carried out by at least two authors independently and in duplicate. Studies were assessed for methodological quality using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). We reported the sensitivity and specificity of the included studies. We provided judgement of the certainty of the evidence using a GRADE assessment.

MAIN RESULTS

We included 18 studies, recruiting 72,202 participants, published between 1986 and 2019. These studies evaluated the diagnostic test accuracy of conventional oral examination (10 studies, none new to this update), mouth self-examination (four studies, two new to this update), and remote screening (three studies, all new to this update). One randomised controlled trial of test accuracy directly evaluated conventional oral examination plus vital rinsing versus conventional oral examination alone. There were no eligible studies evaluating light-based detection or blood or salivary sample analysis (which tests for the presence of biomarkers for OPMD and OSCC). Only one study of conventional oral examination was judged as at overall low risk of bias and overall low concern regarding applicability. Given the clinical heterogeneity of the included studies in terms of the participants recruited, setting, prevalence of the target condition, the application of the index test and reference standard, and the flow and timing of the process, the data could not be pooled within the broader categories of index test. For conventional oral examination (10 studies, 25,568 participants), prevalence in the test accuracy sample ranged from 1% to 51%. For the seven studies with prevalence of 10% or lower, a prevalence more comparable to the general population, the sensitivity estimates were variable, and ranged from 0.50 (95% confidence interval (CI) 0.07 to 0.93) to 0.99 (95% CI 0.97 to 1.00); the specificity estimates were more consistent and ranged from 0.94 (95% CI 0.88 to 0.97) to 0.99 (95% CI 0.98 to 1.00). We judged the overall certainty of the evidence to be low, and downgraded for inconsistency and indirectness. Evidence for mouth self-examination and remote screening was more limited. We judged the overall certainty of the evidence for these index tests to be very low, and downgraded for imprecision, inconsistency, and indirectness. We judged the evidence for vital rinsing (toluidine blue) as an adjunct to conventional oral examination compared to conventional oral examination to be moderate, and downgraded for indirectness as the trial was undertaken in a high-risk population.

AUTHORS' CONCLUSIONS

There is a lack of high-certainty evidence to support the use of screening programmes for oral cavity cancer and OPMD in the general population. Frontline screeners such as general dentists, dental hygienists, other allied professionals, and community healthcare workers should remain vigilant for signs of OPMD and OSCC.

Examining Bias and Reporting in Oral Health Prediction Modeling Studies

Recent efforts to improve the reliability and efficiency of scientific research have caught the attention of researchers conducting prediction modeling studies (PMSs). Use of prediction models in oral health has become more common over the past decades for predicting the risk of diseases and treatment outcomes. Risk of bias and insufficient reporting present challenges to the reproducibility and implementation of these models. A recent tool for bias assessment and a reporting guideline—PROBAST (Prediction Model Risk of Bias Assessment Tool) and TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis)—have been proposed to guide researchers in the development and reporting of PMSs, but their application has been limited. Following the standards proposed in these tools and a systematic review approach, a literature search was carried out in PubMed to identify oral health PMSs published in dental, epidemiologic, and biostatistical journals. Risk of bias and transparency of reporting were assessed with PROBAST and TRIPOD. Among 2,881 papers identified, 34 studies containing 58 models were included. The most investigated outcomes were periodontal diseases (42%) and oral cancers (30%). Seventy-five percent of the studies were susceptible to at least 4 of 20 sources of bias, including measurement error in predictors ( n = 12) and/or outcome ( n = 7), omitting samples with missing data ( n = 10), selecting variables based on univariate analyses ( n = 9), overfitting ( n = 13), and lack of model performance assessment ( n = 24). Based on TRIPOD, at least 5 of 31 items were inadequately reported in 95% of the studies. These items included sampling approaches ( n = 15), participant eligibility criteria ( n = 6), and model-building procedures ( n = 16). There was a general lack of transparent reporting and identification of bias across the studies. Application of the recommendations proposed in PROBAST and TRIPOD can benefit future research and improve the reproducibility and applicability of prediction models in oral health.

Assessment of the cancerization risk for oral potentially malignant disorders by clinical risk model combined with autofluorescence and brush biopsy with DNA-image cytometry

PURPOSE

To explore the feasibility of assessing the cancerization risk of oral potentially malignant disorders (OPMD) through a clinical risk model combined with autofluorescence and brush biopsy with DNA-image cytometry.

METHODS

We collected the baseline clinical data of 269 patients; then, performed autofluorescence, brush biopsy with DNA-image cytometry and histopathological examination. Then, we obtained the significant factors by univariate logistic analysis, constructed the clinical risk model by multiple logistic regression and selected the optimal cutoff value according to the maximum Youden index. Finally, we calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the clinical risk score ≥ cutoff value, autofluorescence and brush biopsy with DNA-image cytometry, and plotted the receiver-operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

The clinical risk model is represented by the formula: 1 × gender + 1.6 × age group + 1 × lesion site + 1.4 × local stimulus + 1.5 × drink. The area under the curve (AUC) was 0.83, and the optimal cutoff score was 3. The AUC indicated that the clinical risk score ≥ 3 (0.74) and autofluorescence (0.77) had a certain diagnostic values, while brush biopsy with DNA-image cytometry (0.92) displayed a good value. Besides, the DCA showed that all three tests had clinical significance.

CONCLUSIONS

The cancerization risk of patients can be assessed by the clinical risk model combined with sequence application of autofluorescence and brush biopsy with DNA-image cytometry, to decide whether histopathological examination or other intervention measures should be selected.

Variants in FAT1 and COL9A1 genes in male population with or without substance use to assess the risk factors for oral malignancy

A number of genetic variants were suggested to be associated with oral malignancy, few variants can be replicated. The aim of this study was to identify significant variants that enhanced personal risk prediction for oral malignancy. A total of 360 patients diagnosed with oral squamous cell carcinoma, 486 controls and 17 newly diagnosed patients with OPMD including leukoplakia or oral submucous fibrosis were recruited. Fifteen tagSNPs which were derived from somatic mutations were genotyped and examined in associations with the occurrence of oral malignancy. Environmental variables along with the SNPs data were used to developed risk predictive models for oral malignancy occurrence. The stepwise model analysis was conducted to fit the best model in an economically efficient way. Two tagSNPs, rs28647489 in FAT1 gene and rs550675 in COL9A1 gene, were significantly associated with the risk of oral malignancy. The sensitivity and specificity were 85.7% and 85.5%, respectively (area under the receiver operating characteristic curve (AUC) was 0.91) for predicting oral squamous cell carcinoma occurrence with the combined genetic variants, betel-quid, alcohol and age. The AUC for OPMD was only 0.69. The predictive probability of squamous cell carcinoma occurrence for genetic risk score without substance use increased from 10% up to 43%; with substance use increased from 73% up to 92%. Genetic variants with or without substance use may enhance risk prediction for oral malignancy occurrence in male population. The prediction model may be useful as a clinical index for oral malignancy occurrence and its risk assessments.

Nomograms and risk scores for predicting the risk of oral cancer in different sexes: a large-scale case-control study

Background: Although previous studies have explored the associations of modifiable lifestyle factors with oral cancer risk, few studies integrated these factors and established predictive tools for oral cancer risk in different sexes.

Methods: Using a case-control study design, a total of 978 oral cancer cases and 2646 healthy controls were recruited in this study. Nomograms were constructed according to significant factors in multivariable logistic regression. Risk scores were calculated based on the nomograms and quantified the risk of oral cancer using restricted cubic spline.

Results: Multivariate analyses demonstrated that smoking, alcohol drinking, tea, intake of fish, seafood, vegetables, fruits, teeth loss, regular dental visits and repetitive dental ulcer were independent factors for male oral cancer. Passive smoking, age at first intercourse, cooking oil fumes exposure, tea, intake of beans, vegetables, fruits, teeth loss, regular dental visits and repetitive dental ulcer were associated with female oral cancer. Then, two nomograms were developed for predicting the probability of oral cancer in men and women with the C-index of 0.768 (95% CI: 0.723-0.813) and 0.700 (95% CI: 0.635-0.765), respectively. Restricted cubic splines graphically revealed the risk of oral cancer in individuals with different risk scores. Moreover, the risk escalated continuously with the increasing number of the risk scores among both sexes.

Conclusions: Combining nomograms with risk scores developed in this study could precisely predict oral cancer occurrence and provide an accurate risk assessment.

Associations between oral hygiene habits, diet, tobacco and alcohol and risk of oral cancer: A case-control study from India

OBJECTIVE

This study examines the association between the incidence of oral cancer in India and oral hygiene habits, diet, chewing and smoking tobacco, and drinking alcohol. We also assessed the effects of oral hygiene habits with oral cancer risk among chewers versus never chewers.

METHODS

A hospital-based case-control study was conducted in Pune, India, based on face-to-face interviews, anthropometry, and intra-oral examinations conducted for 187 oral cancer cases and 240 controls.

RESULTS

Poor oral hygiene score was associated with a significant risk of oral cancer (adjusted OR=6.98; 95%CI 3.72-13.05). When stratified by tobacco-chewing habit, the poor oral hygiene score was a significant risk factor only among ever tobacco chewers (adjusted OR=14.74; 95%CI 6.49-33.46) compared with never chewers (adjusted OR=0.71; 95%CI 0.14-3.63). Dental check-ups only at the time of pain by ever-chewers with poor oral hygiene was associated with an elevated risk (adjusted OR=4.22; 95%CI 2.44-7.29), while consumption of green, yellow, and cruciferous vegetables and citrus fruits was protective. A linear dose-response association was observed between oral cancer and chewing tobacco in terms of age at initiation, duration, and frequency of chewing per day (P<0.001). Smoking more than 10 bidis/cigarettes per day (adjusted OR=2.74; 95%CI 1.28-5.89) and for a duration >25 years (adjusted OR=2.31; 95%CI 1.14-4.71) elevated the risk of oral cancer.

CONCLUSION

Good oral hygiene habits - as characterized by healthy gums, brushing more than once daily, use of toothpaste, annual dental check-ups, and a minimal number of missing teeth - can reduce the risk of oral cancer significantly. In addition to refraining from chewing/smoking tobacco, a diet adequate in fruits and vegetables may protect against the disease.

Knowledge and Attitudes About Oral Cancer Among Dental Students After Bologna Plan Implementation

Oral cancer is the most common of head and neck tumours. Dentists have an important role in the most effective prevention measures: controlling aetiological factors and early detection. Dental curriculum has suffered changes in their structures and contents during Bologna process. The aim of this study is to explore oral cancer knowledge and attitudes among dental students of Granada after the implementation of the Bologna plan. A cross-sectional study was carried out in the School of Dentistry of the University of Granada. A questionnaire was delivered to dental students in the fourth and fifth years (of study) to assess knowledge and attitudes about oral cancer area. 79.3 % related that they examined the oral mucosa from their patients regularly. Almost the whole sample (95.9 %) said that they would advise their patients about risk factors for oral cancer when they graduated. Tobacco followed by alcohol was the main oral cancer risk factor identified (94.2 and 72.7 %, respectively). 96.7 % of the sample would like to receive more information about this subject. Fourth year students had taught self-examination for early detection of oral cancer more frequently than fifth year students (42.5 versus 22.9 %, respectively). The results of this study revealed that dental students had good attitudes in the area of oral cancer. On the other hand, it highlights the need for an improvement of the teaching program regarding risk factors for oral cancer and performing routine oral examination.

Screening and early detection of oral cancer: current controversies

Some evidence suggests that the early detection of oral cancer (OC) during surveillance might improve survival rates. In addition to this, interventions aimed at enhancing public awareness and knowledge of signs, symptoms and risk factors of OC are thought to decrease the burden of disease. Nevertheless, there is much controversy with regard to the cost-effectiveness of population-based strategies for OC screening. Here, we present and briefly discuss timely findings that have put under scrutiny the applicability of approaches targeted at the early identification of patients with OC.

Relationship of Lifetime Exposure to Tobacco, Alcohol and Second Hand Tobacco Smoke with Upper aero-digestive tract cancers in India: a Case-Control Study with a Life-Course Perspective

Background:

Squamous cell carcinomas of the upper aero-digestive tract (UADTSCC) are a multifaceted public health problem. Effects of lifestyle risk factors, including tobacco (chewing and smoking), alcohol drinking and exposure to second hand tobacco smoke (SHS) at home and their association with UADT cancers was assessed in a case-control study with a life-course perspective. The study was conducted at two different hospitals in Pune, India.

Material and methods:

The total sample size (N=480) included 240 histopathologically confirmed cases of UADT cancers and an equal number of controls frequency matched with cases by gender and age distribution (+5 years). All the patients were interviewed face-face using structured questionnaires. Self-reported information on socio-demographic and lifestyle risk factors from childhood to the date of diagnosis of disease/cancer was obtained. Frequency, duration and age of initiation of habits were also recorded to study dose-response relationships. Odds ratios and their 95% confidence intervals were calculated through unconditional logistic regression, adjusting for relevant potential confounders.

Results:

Chewing tobacco emerged as the strongest predictor for UADT cancers (OR=7.61; 95% CI 4.65-12.45) in comparison to smoking and drinking alcohol. Exposure to SHS during childhood (<16 years) rather than ≥16 years increased the risk (OR=4.05; 95% CI 2.06-7.95). Combined effects of tobacco and alcohol consumption habits elevated the risk by twelve fold (OR=12.05; 95% 4.61-31.49) in comparison to never users of these habits. Furthermore, the combination of these lifestyle risk factors accounted for 86.8% of population attributable risk.

Conclusions:

Early exposure to various modifiable lifestyle risk factors has a strong positive association with UADT cancer incidence. Effective future public health interventions with focus on vital time points in life targeting these risk factors could possibly be a major step in primary prevention and control of this cancer at the population level.

A risk factor-based model for upper aerodigestive tract cancers in India: predicting and validating the receiver operating characteristic curve

BACKGROUND

A study was conducted to develop and validate a screening model using risk scores to identify individuals at high risk for developing upper aerodigestive tract (UADT) cancers in an Indian population.

METHODS

A hospital-based case-control study (n = 480) was conducted in Pune, India. We assessed risk factors for UADT cancers by administering a questionnaire through face-to-face interviews. We developed a risk factor model based on the statistically significant risk factors in multiple logistic regression. A total, single risk score was calculated per individual based on the adjusted odds ratio for each of their risk factors. Standard receiver operator characteristic curve was plotted for the total score and the presence of UADT cancers. The stratification ability of the model was determined using the c-statistic. The optimal criterion value was determined at the point on curve at which the Youden's index was maximal. Confidence intervals were calculated by bootstrapping.

RESULTS

Total risk score for each individual ranged from 0 to 26. Area under the receiver operating characteristic curve (95.8; P < 0.001) suggests strong predictive ability. A risk score criterion value of ≤10 produced optimal sensitivity (93.5%), specificity (71.1%), false-positive rate (28.8%), false-negative rate (6.4%), positive predictive value (74.8%), and negative predictive value (96.6%).

CONCLUSION

This risk factor-based model has the potential of satisfactorily screening and detection of UADT cancers at its early stage in a high-risk population like India. The identified at-risk individuals can then be targeted for clinical examination and for focused preventive/treatment measures at the hospital.