Detection of spatial aggregation of cases of cancer from data on patients and health centres contained in the Minimum Basic Data Set

Submitted: 14 August 2017
Accepted: 6 January 2018
Published: 7 May 2018
Abstract Views: 1415
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The feasibility of the Minimum Basic Data Set (MBDS) as a tool in cancer research was explored monitoring its incidence through the detection of spatial clusters. Case-control studies based on MBDS and marked point process were carried out with the focus on the residence of patients from the Prince of Asturias University Hospital in Alcalá de Henares (Madrid, Spain). Patients older than 39 years with diagnoses of stomach, colorectal, lung, breast, prostate, bladder and kidney cancer, melanoma and haematological tumours were selected. Geocoding of the residence address of the cases was done by locating them in the continuous population roll provided by the Madrid Statistical Institute and extracting the coordinates. The geocoded control group was a random sample of 10 controls per case matched by frequency of age and sex. To assess case clusters, differences in Ripley K functions between cases and controls were calculated. The spatial location of clusters was explored by investigating spatial intensity and its ratio between cases and controls. Results suggest the existence of an aggregation of cancers with a common risk factor such as tobacco smoking (lung, bladder and kidney cancers). These clusters were located in an urban area with high socioeconomic deprivation. The feasibility of designing and carrying out case-control studies from the MBDS is shown and we conclude that MBDS can be a useful epidemiological tool for cancer surveillance and identification of risk factors through case-control spatial point process studies.



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How to Cite

Fernández-Navarro, P., Sanz-Anquela, J.-M., Sánchez Pinilla, A., Arenas Mayorga, R., Salido-Campos, C., & Lòpez-Abente, G. (2018). Detection of spatial aggregation of cases of cancer from data on patients and health centres contained in the Minimum Basic Data Set. Geospatial Health, 13(1).

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