Spatiotemporal pattern of thyroid cancer incidence in South Kerala: A population-based study.

Background: Thyroid cancer (TC) is the most common endocrine cancer and has been increasing over the past decades worldwide. A notable finding is that Kerala's capital Thiruvananthapuram ranks the first among men and the second highest among women in the incidence of TC in India. Reasons for this increase have not been established. Objectives: Here, we investigated the spatiotemporal pattern of TC incidence in Thiruvananthapuram. Materials and Methods: TC incidence data (n = 1937) of Population Based Cancer Registry Thiruvananthapuram, Kerala, India, between 2012 and 2016, were analyzed for identifying geographical patterns by spatial methods, temporal methods for studying spatial variation in TC incidence, distribution of age, gender, and histology in lowland (coastal), midland, and highland. Results: Spatial clustering of TC incidence was identified consistently near the coastal region based on all geospatial analyses. 56.9%, 23.9%, and 19.2% of TC cases were observed in the coastal, midland, and highland areas, respectively. A significant clustered pattern of TC incidence was revealed by Moran's index I (0.49), high-high clusters by local Moran's, hotspot by Getis-Ord-Gi* (P < 0.05), point pattern analysis by nearest neighbor ratio and kernel density estimation. The relative risk of the significant cluster was obtained as 1.60 (95% confidence interval: 1.03-1.84) by SaTScan analysis. Conclusion: This study identified spatial variations in the pattern of TC cases with significant clusters near the coastal region of Thiruvananthapuram. This would help to pinpoint the high-risk geographical areas of TC and for more effective cancer control programs.

Spatio-Temporal Risk-Analysis of Cancer Endemicity in Sulthan Bathery Taluk of Wayanad District of Kerala-A Geo-Informatics Approach.

CONTEXT: Asian countries have to confront with the global burden of cancer and various environmental factors predisposing the incidence. Geoinformatics can assist in spatial autocorrelation and statistical analysis in determining environmental and demographic correspondence to endemicity. What is of prime importance is the availability of the spatial datasets of cancer cases. AIMS: The aim of this study was to reveal the distribution pattern of cancer and its magnitude in the eight panchayats of Sulthan Bathery Taluk of Wayanad district. The present study also attempted to develop and implement a data frame facilitating better data collection. SETTINGS AND DESIGN: This was a taluk-level cross-sectional retrospective analysis and interventional study. SUBJECTS AND METHODS: A retrospective survey created a geodatabase with 547 cancer cases registered along the timeline of 2015-2016. Input datasets were geocoded using Google Earth Pro software. STATISTICAL ANALYSIS USED: The analysis was performed using ArcMap-10.2 version. RESULTS: Registration revealed the high breast cancer incidences and temporal increment mainly in town areas. The incidence depicted male predominance and prevalence along the age group of 30-69 years. The pattern showed cancer incidence at a proximity to state borders and forest regions (Noolpuzha) which are high population density regions, instantiated relation of geographic variables, and cancer incidences. The implementation of data frame ensured structured data collection. CONCLUSIONS: This study concluded the spatial association of cancer incidence demonstrating the high-risk regions with male predominance and role spatial risk analysis in cancer database management.