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Objectives: Over the past several decades, oral cancer has been the most common malignancy among Sri Lankan males and the top 10 cancer among females, disproportionately affecting low socio‐economic groups. Sri Lanka is a lower‐middle‐income developing country (LMIC), currently striking through an economic crisis, and social and political unrest. Occurring at an accessible body site and predominantly attributed to potentially modifiable health‐related behaviours, oral cancer should be preventable and controllable. Unfortunately, broader contextual factors that are socio‐cultural, environmental, economic, and political and mediated through social determinants of people's lives consistently hinder progress. Many LMICs with a high burden of oral cancer are now gripped by economic crises, consequent social and political unrest, all compounded by reduced public health investments. The aim of this review is to provide a critical commentary on key aspects of oral cancer epidemiology including inequalities, using Sri Lanka as a case study. Methods: The review synthesizes evidence from multiple data sources, such as published studies, web‐based national cancer incidence data, national surveys on smokeless tobacco (ST) and areca nut use, smoking and alcohol consumption, poverty headcount ratios, economic growth, and Gross Domestic Product (GDP) health expenditure. National trends in the oral cancer, ST use, smoking and alcohol consumption in Sri Lanka are identified alongside inequalities. Results: Using these evidence sources, we discuss 'where are we now?', together with the availability, accessibility and affordability of oral cancer treatment services, oral cancer prevention and control programmes, tobacco and alcohol control policies, and finally, outline macroeconomic perspectives of Sri Lanka. Conclusions: Finally, we speculate, 'where to next?' Our overarching goal of this review is to initiate a critical discourse on bridging the gaps and crossing the divides to tackle oral cancer inequalities in LMIC such as Sri Lanka. [ABSTRACT FROM AUTHOR]

Background: It has been suggested that the EQ-5D-3 L preference-based measure of health outcome lacks sensitivity to discriminate between health states in cancer patients. An alternative approach is to use a disease (cancer) specific preference-based measure, such as the EORTC-8D. A limited number of comparisons have been made between generic and disease specific preference-based measures. The aim of this study was to compare the utility scores from the EQ-5D-3 L and the EORTC-8D in a group of patients with oral cancer or with oral potentially malignant disorders (OPMD).Methods: Patients (n = 151) with OPMD or oral cancer were recruited consecutively from six hospitals in Sri Lanka. All participants completed both the EQ-5D-3 L and the EORTC's QLQC-30 instrument. The Sri Lankan EQ-5D-3 L and EORTC-8D scoring algorithms were employed to estimate utility scores. The utility scores from the two instruments were compared for discrimination, responsiveness and correlation.Results: There were significant differences across the two utility scores. The EQ-5D-3 L showed better discrimination than EORTC-8D with higher effect sizes. There were higher ceiling effects observed in the EQ-5D-3 L. There was poor correlation between the dimensions of the two instruments except for the mobility and physical functions.Conclusion: The two instruments captured different aspects of quality of life. The EQ-5D-3 L demonstrated better discrimination than the EORTC-8D. In mild conditions EORTC-8D was more responsive and we recommend further validation of this instrument in diverse cancer conditions. [ABSTRACT FROM AUTHOR]

Background: Health Related Quality of Life (HRQoL) is an important outcome measure in health economic evaluation that guides health resource allocations. Population norms for HRQoL are an essential ingredient in health economics and in the evaluation of population health. The aim of this study was to produce EQ-5D-3L-derived population norms for Sri Lanka. Method: A population sample (n =  780) was selected from four districts of Sri Lanka. A stratified cluster sampling approach with probability proportionate to size was employed. Twenty six clusters of 30 participants each were selected; each participant completed the EQ-5D-3L in a face-to-face interview. Utility weights for their EQ-5D-3L health states were assigned using the Sri Lankan EQ-5D-3L algorithm. The population norms are reported by age and socio-economic variables. Results: The EQ-5D-3L was completed by 736 people, representing a 94% response rate. Sixty per cent of the sample reported being in full health. The percentage of people responding to any problems in the five EQ-5D-3L dimensions increased with age. The mean EQ-5D-3L weight was 0.85 (SD 0.008; 95%CI 0.84-0.87). The mean EQ-5D-3L weight was significantly associated with age, housing type, disease experience and religiosity. People above 70 years of age were 7.5 times more likely to report mobility problems and 3.7 times more likely to report pain/discomfort than those aged 18-29 years. Those with a tertiary education were five times less likely to report any HRQoL problems than those without a tertiary education. A person living in a shanty was 4.3 more likely to have problems in usual activities than a person living in a single house. Conclusion: The population norms in Sri Lanka vary with socio-demographic characteristics. The socioeconomically disadvantaged have a lower HRQoL. The trends of population norms observed in this lower middle income country were generally similar to those previously reported in high income countries. [ABSTRACT FROM AUTHOR]

Objectives: Cancer of the oral cavity is the leading malignancy amongst males in Sri Lanka, and eighth amongst women. Almost all malignancies are developed from a clinically visible precursor stage called an oral potentially malignant disorder (OPMD). The objective of this study was to estimate costs of managing patients with OPMD in Sri Lanka for a 12‐month period from diagnosis. Methods: A hospital‐based costing study was conducted in Sri Lanka in the years 2016‐2017. Three selected treatment centres participated. For societal perspectives, healthcare, household and indirect costs were used. Costs to the healthcare system included clinic visits, diagnostic biopsy, consumables and drug costs. Capital costs included apportioned value of land, buildings, equipment and furniture. Household costs consisted of out‐of‐pocket expenditure and indirect costs of lost income. Results: Sixty‐two patients were recruited (39 male and 23 female). The majority had awareness of oral potentially malignant disorders (OPMDs). Total average cost of managing a single patient with an OPMD for 1 year was SLR 19 547 (US$ 140) which includes a health system cost of SLR 7320 (US$ 52) and household cost of SLR 12 227 (US$ 87). Travel loss and income loss were a substantial burden to patients and their families. Conclusions: Managing patients with an OPMD, even with annual monitoring, is less costly than managing patients with oral cancer. Out‐of‐pocket costs are very high, and these could be reduced by revising the National Management Guidelines to allow care closer to home. [ABSTRACT FROM AUTHOR]

Background: Economic evaluations to inform decisions about allocation of health resources are scarce in Low and Middle Income Countries, including in Sri Lanka. This is in part due to a lack of country-specific utility weights, which are necessary to derive appropriate Quality Adjusted Life Years. The EQ-5D-3L, a generic multi-attribute instrument (MAUI), is most widely used to measure and value health states in high income countries; nevertheless, the sensitivity of generic MAUIs has been criticised in some conditions such as cancer. This article describes a protocol to produce both a generic EQ-5D-3L and cancer specific EORTC-8D utility index in Sri Lanka. Method: EQ-5D-3L and EORTC-8D health states will be valued using the Time Trade-Off technique, by a representative population sample (n = 780 invited) identified using stratified multi-stage cluster sampling with probability proportionate to size method. Households will be randomly selected within 30 clusters across four districts; one adult (=18 years) within each household will be selected using the Kish grid method. Data will be collected via face-to-face interview, with a Time Trade-Off board employed as a visual aid. Of the 243 EQ-5D-3L and 81,290 EORTC-8D health states, 196 and 84 respectively will be directly valued. In EQ-5D-3L, all health states that combine level 3 on mobility with either level 1 on usual activities or self-care were excluded. Each participant will first complete the EQ-5D-3L, rank and value 14 EQ-5D-3L states (plus the worst health state and "immediate death"), and then rank and value seven EORTC-8D states (plus "immediate death"). Participant demographic and health characteristics will be also collected. Regression models will be fitted to estimate utility indices for EQ-5D-3L and EORTC-8D health states for Sri Lanka. The dependent variable will be the utility value. Different specifications of independent variables will be derived from the ordinal EQ-5D-3L to test for the best-fitting model. Discussion: In Sri Lanka, a LMIC health state valuation will have to be carried out using face to face interview instead of online methods. The proposed study will provide the first country-specific health state valuations for Sri Lanka, and one of the first valuations to be completed in a South Asian Country. [ABSTRACT FROM AUTHOR]

Amarasinghe HK, Usgodaarachchi US, Johnson NW, Lalloo R, Warnakulasuriya S. Public awareness of oral cancer, of oral potentially malignant disorders and of their risk factors in some rural populations in Sri Lanka. Community Dent Oral Epidemiol 2010; 38: 540-548. © 2010 John Wiley & Sons A/S The aim of this study was to investigate the level of public awareness of oral cancer, of oral potentially malignant disorders (OPMD) and of risk factors for developing these diseases in a province of Sri Lanka, a country with one of the highest incidences of these diseases in the world. A cross-sectional community-based survey was carried out in Sabaragamuwa province by interviewing 1029 subjects above 30 years of age, over a 1-year period from November 2006. The level of public awareness of oral cancer was 84%, but only 23% for OPMD. Awareness was especially poor in low socioeconomic groups. The majority of subjects were not aware of the symptoms of oral cancer and of OPMD. Thirty-two percent were unaware that chewing betel quid was a risk factor for these diseases, as were 65% for tobacco smoking and 81% for heavy consumption of alcohol. Overall, 76% were not aware of any of the dangers inherent in the frequent use of areca nut. The majority of smokers, betel quid chewers and alcohol consumers were not aware that their lifestyles were placing their long-term health at serious risk. Knowledge of oral cancer, OPMD and their associated risk factors was poor among this population, indicating an urgent need to implement public health education and promotion strategies. [ABSTRACT FROM AUTHOR]

Summary: We investigated the prevalence of, and risk factors for, oral potentially malignant disorders (OPMDs) in rural Sri Lanka. A cross-sectional community-based study was conducted by interview and oral examination of 1029 subjects aged over 30years. A community-based nested case-control study then took those with OPMDs as ‘cases’, “controls” being those with no oral abnormalities at time of initial screening. The prevalence of OPMD was 11.3% (95% CI: 9.4–13.2), after weighting for place of residence and gender. Risk factors were betel-quid (BQ) chewing daily [OR=10.6 (95% CI: 3.6–31.0)] and alcohol drinking daily or weekly [OR=3.55 (1.6–8.0)]. A significant dose–response relationship existed for BQ chewing. Smoking did not emerge when adjusted for covariates. A synergistic effect of chewing and alcohol consumption existed. The attributable risk (AR) of daily BQ chewing was 90.6%, the population AR 84%. This study demonstrates high prevalence of OPMD, betel-quid chewing with or without tobacco being the major risk factor. [Copyright &y& Elsevier]