Introduction: PCa is one of the cancers that exhibits the widest disparity gaps. Geographical place of residence has been shown to be associated with healthcare access/utilization and PCa outcomes. Geographical Information Systems (GIS) are widely being utilized for PCa disparities research, however, inconsistencies in their application exist. This systematic review will summarize GIS application within PCa disparities research, highlight gaps in the literature, and propose alternative approaches.Methods: This paper followed the methods of the Cochrane Collaboration and the criteria set of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles published in peer-reviewed journals were searched through the PubMed, Embase, and Web of Science databases until December 2022. The main inclusion criteria were employing a GIS approach and examining a relationship between geographical components and PCa disparities. The main exclusion criteria were studies conducted outside the US and those that were not published in English.Results: A total of 25 articles were included; 23 focused on PCa measures as outcomes: incidence, survival, and mortality, while only 2 examined PCa management. GIS application in PCa disparities research was grouped into three main categories: mapping, processing, and analysis. GIS mapping allowed for the visualization of quantitative, qualitative, and temporal trends of PCa factors. GIS processing was mainly used for geocoding and smoothing of PCa rates. GIS analysis mainly served to evaluate global spatial autocorrelation and distribution of PCa cases, while local cluster identification techniques were mainly employed to identify locations with poorer PCa outcomes, soliciting public health interventions.Discussion: Varied GIS applications and methodologies have been used in researching PCa disparities. Multiple geographical scales were adopted, leading to variations in associations and outcomes. Geocoding quality varied considerably, leading to less robust findings. Limitations in cluster-detection approaches were identified, especially when variations were captured using the Spatial Scan Statistic. GIS approaches utilized in other diseases might be applied within PCa disparities research for more accurate inferences. A novel approach for GIS research in PCa disparities could be focusing more on geospatial disparities in procedure utilization especially when it comes to PCa screening techniques.Conclusions: This systematic review summarized and described the current state and trend of GIS application in PCa disparities research. Although GIS is of crucial importance when it comes to PCa disparities research, future studies should rely on more robust GIS techniques, carefully select the geographical scale studied, and partner with GIS scientists for more accurate inferences. Such interdisciplinary approaches have the potential to bridge the gaps between GIS and cancer prevention and control to further advance cancer equity.
引言：前列腺癌（PCa）是健康差异最为显著的癌症之一。研究表明，居住地理位置与医疗服务的可及性/利用情况及前列腺癌预后存在关联。地理信息系统（GIS）已广泛应用于前列腺癌差异研究，但其应用方法尚不一致。本系统综述将总结GIS在前列腺癌差异研究中的应用现状，指出文献中的空白领域，并提出替代性研究方法。 方法：本研究遵循Cochrane协作网方法学及系统综述和荟萃分析优先报告条目（PRISMA）标准，通过PubMed、Embase和Web of Science数据库检索截至2022年12月发表于同行评审期刊的相关文献。主要纳入标准为采用GIS方法并探讨地理要素与前列腺癌差异关联的研究；主要排除标准为在美国境外开展或非英文发表的文献。 结果：共纳入25篇文献，其中23篇以前列腺癌相关指标（发病率、生存率、死亡率）为结局变量，仅2篇关注前列腺癌管理。前列腺癌差异研究中的GIS应用可分为三大类：制图、处理与分析。GIS制图实现了前列腺癌相关因素的定量、定性及时间趋势可视化；GIS处理主要用于地理编码与前列腺癌率平滑化；GIS分析主要评估前列腺癌病例的全局空间自相关与分布特征，而局部聚类识别技术则侧重于定位预后较差区域以指导公共卫生干预。 讨论：前列腺癌差异研究采用了多样化的GIS应用与方法。多尺度地理分析导致关联性与研究结果的异质性。地理编码质量参差不齐影响了研究结论的稳健性。研究识别出聚类检测方法的局限性，特别是在使用空间扫描统计量捕捉变异时。其他疾病研究中成熟的GIS技术或可应用于前列腺癌差异研究以提升推断准确性。未来前列腺癌差异的GIS研究可创新性地聚焦于诊疗流程利用的地理空间差异，特别是在筛查技术应用方面。 结论：本系统综述总结并阐述了GIS在前列腺癌差异研究中的应用现状与发展趋势。尽管GIS在前列腺癌差异研究中至关重要，未来研究应采用更稳健的GIS技术，审慎选择地理分析尺度，并与GIS专家协作以提升推断准确性。此类跨学科方法有望弥合GIS技术与癌症防控领域的隔阂，进一步推动癌症健康公平。
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