Casauria Sarah, Collins Felicity, White Susan M, Konings Paul, Wallis Mathew, Pachter Nicholas, McGaughran Julie, Barnett Christopher, Best Stephanie
Australian Genomics, Murdoch Children's Research Institute, Melbourne, VIC, Australia.
Clinical Genetics Service, Institute of Precision Medicine and Bioinformatics, RPAH, Sydney, NSW, Australia.
Eur J Hum Genet. 2025 Apr;33(4):496-503. doi: 10.1038/s41431-024-01746-0. Epub 2024 Nov 27.
The role of genomic testing in rare disease clinical management is growing. However, geographical and socioeconomic factors contribute to inequitable uptake of testing. Geographical investigations of genomic testing across Australia have not been undertaken. Therefore, we aimed to investigate the geospatial distribution of genomic testing nationally between remoteness areas, and areas of varying socioeconomic advantage and disadvantage. We requested patient postcodes, age, and test type from genomic testing records from seven Australian laboratories for a 6-month period between August 2019 and June 2022. Postcode data were aggregated to Local Government Areas (LGAs) and visualised geospatially. Data were further aggregated to Remoteness Areas and Socio-Economic Index for Areas (SEIFA) quintiles for exploratory analysis. 11,706 records were eligible for analysis. Most tests recorded were paediatric (n = 8358, 71.4%). Microarray was the most common test captured (n = 8186, 69.9%). The median number of tests per LGA was 5.4 (IQR 1.0-21.0). Fifty-seven (10.4%) LGAs had zero tests recorded. Remoteness level was negatively correlated with number of tests across LGAs (rho = -0.781, p < 0.001). However, remote areas recorded the highest rate of testing per 100,000 populations. SEIFA score positively correlated with number of tests across LGAs (rho = 0.386, p < 0.001). The third SEIFA quintile showed the highest rate of testing per 100,000 populations. Our study establishes a foundation for ongoing assessment of genomic testing accessibility and equity and highlights the need to improve access to genomic testing for patients who are disadvantaged geographically or socioeconomically. Future research should include additional laboratories to achieve a larger representation of genomic testing rates nationally.
基因检测在罕见病临床管理中的作用日益增强。然而,地理和社会经济因素导致检测的不公平应用。澳大利亚尚未开展关于基因检测的地理调查。因此,我们旨在调查全国范围内偏远地区以及社会经济优势和劣势不同地区之间基因检测的地理空间分布。我们从澳大利亚七个实验室2019年8月至2022年6月的6个月基因检测记录中获取患者邮政编码、年龄和检测类型。邮政编码数据汇总到地方政府区域(LGA)并进行地理空间可视化。数据进一步汇总到偏远地区和地区社会经济指数(SEIFA)五分位数进行探索性分析。11706条记录符合分析条件。记录的大多数检测是儿科检测(n = 8358,71.4%)。微阵列是最常见的检测类型(n = 8186,69.9%)。每个LGA的检测中位数为5.4(四分位距1.0 - 21.0)。57个(10.4%)LGA记录的检测数为零。偏远程度与各LGA的检测数呈负相关(rho = -0.781,p < 0.001)。然而,偏远地区每10万人口的检测率最高。SEIFA分数与各LGA的检测数呈正相关(rho = 0.386,p < 0.001)。第三个SEIFA五分位数显示每10万人口的检测率最高。我们的研究为持续评估基因检测的可及性和公平性奠定了基础,并强调需要改善地理或社会经济条件不利患者的基因检测获取情况。未来的研究应纳入更多实验室,以在全国范围内更广泛地代表基因检测率。