背景:在全球范围内,前列腺癌是男性癌症死亡的第二大原因。它是澳大利亚最常见的癌症。由于疾病本身及其相关并发症,与普通人群相比,前列腺癌患者的生活质量较差。然而,关于维多利亚州生活质量的地理格局及其危险因素的研究有限。因此,对生活质量差的时空模式和危险因素的检查,以及空间权重矩阵对估计和模型性能的影响,进行了。
方法:根据维多利亚前列腺癌结果登记数据进行回顾性研究。患者数据(n=5238)从前列腺癌结果注册表中提取,2015年至2021年基于人群的临床质量结果评估。采用贝叶斯时空多水平模型来识别生活质量差的危险因素。本研究还评估了基于距离和邻接的空间权重矩阵的影响。使用Gelman-Rubin统计图评估模型收敛性,模型比较基于渡边-Akaike信息标准。
结果:在我们的研究中,共有1906例(36.38%)接受手术的前列腺癌患者经历了较差的生活质量。属于76至85岁之间的年龄组(调整后的优势比(AOR)=2.90,95%可信区间(CrI):1.39,2.08),前列腺特异性抗原水平在10.1和20.0之间(AOR=1.33,95%CrI:1.12,1.58),在公立医院接受治疗(AOR=1.35,95%CrI:1.17,1.53)与较高的生活质量差几率显著相关.相反,居住在高度可接近区域(AOR=0.60,95%CrI:0.38,0.94)与前列腺特异性抗原水平低的几率显著相关.根据空间权重矩阵的选择,可以观察到估计值和模型性能的变化。
结论:属于年龄较大的人群,具有较高的前列腺特异性抗原水平,在公立医院接受治疗,和偏远是与生活质量差相关的统计学显著因素。在维多利亚州各地方政府地区观察到生活质量差的时空变化。基于距离的权重矩阵比基于邻接的矩阵表现得更好。这项研究发现强调了减少生活质量地理差异的必要性。本研究中开发的统计方法也可能适用于其他基于人群的临床注册设置。
BACKGROUND: Globally, prostate cancer is the second leading cause of cancer deaths among males. It is the most commonly diagnosed cancer in Australia. The quality of life of prostate cancer patients is poorer when compared to the general population due to the disease itself and its related complications. However, there is limited research on the geographic pattern of quality of life and its risk factors in
Victoria. Therefore, an examination of the spatio-temporal pattern and risk factors of poor quality of life, along with the impact of spatial weight matrices on estimates and model performance, was conducted.
METHODS: A retrospective study was undertaken based on the Prostate Cancer Outcome Registry-
Victoria data. Patient data (n = 5238) were extracted from the Prostate Cancer Outcome Registry, a population-based clinical quality outcome assessment from 2015 to 2021. A Bayesian spatio-temporal multilevel model was fitted to identify risk factors for poor quality of life. This study also evaluated the impact of distance- and adjacency-based spatial weight matrices. Model convergence was assessed using Gelman-Rubin statistical plots, and model comparison was based on the Watanabe-Akaike Information Criterion.
RESULTS: A total of 1906 (36.38%) prostate cancer patients who had undergone surgery experienced poor quality of life in our study. Belonging to the age group between 76 and 85 years (adjusted odds ratio (AOR) = 2.90, 95% credible interval (CrI): 1.39, 2.08), having a prostate-specific antigen level between 10.1 and 20.0 (AOR = 1.33, 95% CrI: 1.12, 1.58), and being treated in a public hospital (AOR = 1.35, 95% CrI: 1.17, 1.53) were significantly associated with higher odds of poor quality of life. Conversely, residing in highly accessible areas (AOR = 0.60, 95% CrI: 0.38, 0.94) was significantly associated with lower odds of poor prostate-specific antigen levels. Variations in estimates and model performance were observed depending on the choice of spatial weight matrices.
CONCLUSIONS: Belonging to an older age group, having a high prostate-specific antigen level, receiving treatment in public hospitals, and remoteness were statistically significant factors linked to poor quality of life. Substantial spatio-temporal variations in poor quality of life were observed in
Victoria across local government areas. The distance-based weight matrix performed better than the adjacency-based matrix. This research finding highlights the need to reduce geographical disparities in quality of life. The statistical methods developed in this study may also be useful to apply to other population-based clinical registry settings.