Ramamurthy Poornima, Sharma Dileep, Adeoye John, Choi Siu-Wai, Thomson Peter
College of Medicine and Dentistry, James Cook University, Cairns, Queensland 4878, Australia.
School of Health Sciences, College of Health, Medicine and Wellbeing, The University of Newcastle, Ourimbah, NSW 2258, Australia.
Int J Dent. 2023 Nov 2;2023:3243373. doi: 10.1155/2023/3243373. eCollection 2023.
Bayesian mapping is an effective spatiotemporal approach to identify high-risk geographic areas for diseases and has not been used to identify oral cancer hotspots in Australia previously. This retrospective disease mapping study was undertaken to identify the oral cancer trends and patterns within the Queensland state in Australia.
This study included data obtained from Queensland state Cancer Registry from 1982 to 2018. Domains mapped included the oral cancer incidence and mortality in Queensland (QLD). Local government areas (LGAs) and suburbs were utilized as geographical units for the estimation using Bayesian mapping approach.
Of the 78 LGAs, 21 showed high-oral cancer incidence as measured using higher median smoothed incidence risk (SIR), above the state average. Specifically, nine LGAs within predominantly rural areas had SIR above 100% of the state average. Of these, only one LGA (Mount Isa City) had a median smoothed SIR and 95% CI of 2.61 (2.14-3.15) which was constantly above 100% of the state average. Furthermore, mortality risk estimated using smoothed mortality risk (SMR), were significantly higher than the state average in 31 LGAs. Seventeen LGAs had a median SMR above 100% of the state average while three LGAs had the highest overall, 3- and 5-year mortality risks. Considering the 95% credible interval which is indicative of the uncertainty around the estimates, three LGAs had the highest overall mortality risks-Yarrabah Aboriginal Shire (3.80 (2.16-6.39)), Cook Shire (3.37 (2.21-5.06)), and Mount Isa City (3.04 (2.40-3.80)).
Bayesian disease mapping approach identified multiple incidence and mortality hotspots within regional areas of the Queensland. Findings from our study can aid in designing targeted public health screening and interventions for primary prevention of oral cancer in regional and remote communities.
贝叶斯映射是一种有效的时空方法，用于识别疾病的高风险地理区域，此前尚未用于识别澳大利亚的口腔癌热点地区。本回顾性疾病映射研究旨在确定澳大利亚昆士兰州内的口腔癌趋势和模式。
本研究纳入了1982年至2018年从昆士兰州癌症登记处获得的数据。映射的领域包括昆士兰州（QLD）的口腔癌发病率和死亡率。使用贝叶斯映射方法，将地方政府区域（LGAs）和郊区作为地理单位进行估计。
在78个LGAs中，有21个显示出高口腔癌发病率，以较高的中位数平滑发病率风险（SIR）衡量，高于该州平均水平。具体而言，主要为农村地区的9个LGAs的SIR高于该州平均水平的100%。其中，只有一个LGAs（芒特艾萨市）的中位数平滑SIR和95%置信区间为2.61（2.14 - 3.15），持续高于该州平均水平的100%。此外，使用平滑死亡率风险（SMR）估计的死亡风险在31个LGAs中显著高于该州平均水平。17个LGAs的中位数SMR高于该州平均水平的100%，而3个LGAs的总体、3年和5年死亡风险最高。考虑到表示估计值周围不确定性的95%可信区间，3个LGAs的总体死亡风险最高——亚拉巴土著郡（3.80（2.16 - 6.39））、库克郡（3.37（2.21 - 5.06））和芒特艾萨市（3.04（2.40 - 3.80））。
贝叶斯疾病映射方法在昆士兰州的区域内识别出多个发病率和死亡率热点地区。我们研究的结果有助于设计有针对性的公共卫生筛查和干预措施，以在区域和偏远社区中对口腔癌进行一级预防。
