Geographical information system (GIS) as a new tool to evaluate epidemiology based on spatial analysis and clinical outcomes in acromegaly

Geographical information systems (GIS) have emerged as a group of innovative software components useful for projects in epidemiology and planning in Health Care System. This is an original study to investigate environmental and geographical influences on epidemiology of acromegaly in Brazil. We aimed to validate a method to link an acromegaly registry with a GIS mapping program, to describe the spatial distribution of patients, to identify disease clusters and to evaluate if the access to Health Care could influence the outcome of the disease. Clinical data from 112 consecutive patients were collected and home addresses were plotted in the GIS software for spatial analysis. The buffer spatial distribution of patients living in Brasilia showed that 38.1 % lived from 0.33 to 8.66 km, 17.7 % from 8.67 to 18.06 km, 22.2 % from 18.07 to 25.67 km and 22 % from 25.68 to 36.70 km distant to the Reference Medical Center (RMC), and no unexpected clusters were identified. Migration of 26 patients from 11 others cities in different regions of the country was observed. Most of patients (64 %) with adenomas bigger than 25 mm lived more than 20 km away from RMC, but no significant correlation between the distance from patient’s home to the RMC and tumor diameter (r = 0.45 p = 0.20) nor for delay in diagnosis (r = 0.43 p = 0.30) was found. The geographical distribution of diagnosed cases did not impact in the latency of diagnosis or tumor size but the recognition of significant migration denotes that improvements in the medical assistance network are needed.

[1]  Laura A. Levit,et al.  Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research. Washington, DC: National Academies Press , 2009 .

[2]  L. Vilar,et al.  Increase of classic and nonclassic cardiovascular risk factors in patients with acromegaly. , 2007, Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists.

[3]  A. Ebrahimi,et al.  Histone Acetylation Patterns of Typical and Atypical Pituitary Adenomas Indicate Epigenetic Shift of these Tumours , 2011, Journal of neuroendocrinology.

[4]  V. Esposito,et al.  Expression of aryl hydrocarbon receptor (AHR) and AHR-interacting protein in pituitary adenomas: pathological and clinical implications. , 2009, Endocrine-related cancer.

[5]  Shereen Ezzat,et al.  The prevalence of pituitary adenomas , 2004, Cancer.

[6]  Geoffrey M. Jacquez,et al.  Design and implementation of a Space-Time Intelligence System for disease surveillance , 2005, J. Geogr. Syst..

[7]  D. Hallam.  Pituitary , 2001 .

[8]  G. Sesmilo.  [Epidemiology of acromegaly in Spain]. , 2013, Endocrinologia y nutricion : organo de la Sociedad Espanola de Endocrinologia y Nutricion.

[9]  Geoffrey M. Jacquez,et al.  Improving exposure assessment in environmental epidemiology: Application of spatio-temporal visualization tools , 2005, J. Geogr. Syst..

[10]  David M. Mark,et al.  Measuring similarity between geospatial lifelines in studies of environmental health , 2005, J. Geogr. Syst..

[11]  Sheng Gao,et al.  Online GIS services for mapping and sharing disease information , 2008, International journal of health geographics.

[12]  M. Ragonese,et al.  Increased prevalence of acromegaly in a highly polluted area. , 2010, European journal of endocrinology.

[13]  M. Sheppard,et al.  Does acromegaly enhance mortality? , 2008, Reviews in Endocrine and Metabolic Disorders.

[14]  S. Melmed.  Medical progress: Acromegaly. , 2006, The New England journal of medicine.

[15]  G. Sesmilo.  Epidemiología de la acromegalia en España , 2013 .

[16]  S. Melmed.  Acromegaly pathogenesis and treatment. , 2009, The Journal of clinical investigation.

[17]  S. Hurel,et al.  Pituitary tumours , 1994, BMJ.

[18]  P. Chanson,et al.  Diabetes in acromegaly, prevalence, risk factors, and evolution: data from the French Acromegaly Registry. , 2011, European journal of endocrinology.

[19]  M. Gadelha,et al.  Prevalence of gsp oncogene in somatotropinomas and clinically non-functioning pituitary adenomas: our experience , 2008, Pituitary.

[20]  Maged N Kamel Boulos,et al.  International Journal of Health Geographics Open Access towards Evidence-based, Gis-driven National Spatial Health Information Infrastructure and Surveillance Services in the United Kingdom , 2022 .

[21]  J. Vandenbroucke,et al.  Mortality in acromegaly: a metaanalysis. , 2008, The Journal of clinical endocrinology and metabolism.

[22]  S. Melmed,et al.  Pathophysiology of pituitary adenomas. , 2005, Journal of endocrinological investigation.

[23]  Martin Kulldorff,et al.  Lumping or splitting: seeking the preferred areal unit for health geography studies , 2005, International journal of health geographics.

[24]  Didier Martin,et al.  The Liege Acromegaly Survey (LAS): a new software tool for the study of acromegaly. , 2012, Annales d'endocrinologie.

[25]  W. Farrell,et al.  Review: Pituitary tumours , 2001 .

[26]  A. Barkan.  Acromegaly , 1890, Trends in Endocrinology & Metabolism.

[27]  P. Wrightson,et al.  Determinants of clinical outcome and survival in acromegaly , 1994, Clinical endocrinology.

[28]  B. Estour,et al.  Cyclin-dependent kinase inhibitor 1B (CDKN1B) gene variants in AIP mutation-negative familial isolated pituitary adenoma kindreds. , 2012, Endocrine-related cancer.

[29]  S. Melmed.  Pathogenesis of pituitary tumors. , 1999, Endocrinology and metabolism clinics of North America.

[30]  A. Beckers,et al.  High prevalence of pituitary adenomas: a cross-sectional study in the province of Liege, Belgium. , 2006, The Journal of clinical endocrinology and metabolism.

[31]  C. Viegas,et al.  Using clinical data to predict sleep hypoxemia in patients with acromegaly. , 2007, Arquivos de neuro-psiquiatria.

[32]  Giles M. Foody,et al.  GIS: health applications , 2006 .

[33]  A. Grossman,et al.  The molecular pathogenesis of pituitary tumors: implications for clinical management. , 2012, Minerva endocrinologica.

[34]  V. Bours,et al.  Variable pathological and clinical features of a large Brazilian family harboring a mutation in the aryl hydrocarbon receptor-interacting protein gene. , 2007, European journal of endocrinology.

[35]  G. Rushton,et al.  Geographically masking health data to preserve confidentiality. , 1999, Statistics in medicine.

[36]  M. Junier,et al.  Hyperplasia-adenoma sequence in pituitary tumorigenesis related to aryl hydrocarbon receptor interacting protein gene mutation. , 2011, Endocrine-related cancer.

[37]  R. Paschke,et al.  Clinical characteristics and therapeutic responses in patients with germ-line AIP mutations and pituitary adenomas: an international collaborative study. , 2010, The Journal of clinical endocrinology and metabolism.

[38]  Tahsin Yomralioglu,et al.  Geo-Relationship between Cancer Cases and the Environment by GIS: A Case Study of Trabzon in Turkey , 2009, International Journal of Environmental Research and Public Health.

[39]  M. Rytkönen.  Not all maps are equal: GIS and spatial analysis in epidemiology , 2004, International journal of circumpolar health.

[40]  H. Galal,et al.  Mapping Cancer Disease Using Geographical Information System (GIS) in Gezira State-Sudan , 2012, Journal of Community Health.

[41]  T. Sano,et al.  Growth hormone-releasing hormone-producing tumors: clinical, biochemical, and morphological manifestations. , 1988, Endocrine reviews.