Literature DB >> 33503972

Spatial Variation of Survival for Colorectal Cancer in Malaysia.

Anis Kausar Ghazali1, Thomas Keegan2, Benjamin M Taylor3.   

Abstract

A patient's survival may depend on several known and unknown factors and it may also vary spatially across a region. Socioeconomic status, accessibility to healthcare and other environmental factors are likely to contribute to survival rates. The aim of the study was to model the spatial variation in survival for colorectal cancer patients in Malaysia, accounting for individual and socioeconomic risk factors. We conducted a retrospective study of 4412 colorectal cancer (ICD-10, C18-C20) patients diagnosed from 2008 to 2013 to model survival in CRC patients. We used the data recorded in the database of the Malaysian National Cancer Patient Registry-Colorectal Cancer (NCPR-CRC). Spatial location was assigned based on the patients' central district location, which involves 144 administrative districts of Malaysia. We fitted a parametric proportional hazards model in which the spatially correlated frailties were modelled by a log-Gaussian stochastic process to analyse the spatially referenced survival data, which is also known as a spatial survival model. After controlling for individual and area level characteristics, our findings indicate wide spatial variation in colorectal cancer survival across Malaysia. Better healthcare provision and higher socioeconomic index in the districts where patients live decreased the risk of death from colorectal cancer, but these associations were not statistically significant. Reliable measurement of environmental factors is needed to provide good insight into the effects of potential risk factors for the disease. For example, a better metric is needed to measure socioeconomic status and accessibility to healthcare in the country. The findings provide new information that might be of use to the Ministry of Health in identifying populations with an increased risk of poor survival, and for planning and providing cancer control services.

Entities:  

Keywords:  colorectal cancer; spatial modelling; spatial survival; survival

Mesh:

Year:  2021        PMID: 33503972      PMCID: PMC7908469          DOI: 10.3390/ijerph18031052

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  18 in total

1.  Socio-economic disadvantage and demographics as factors in stage of colorectal cancer presentation and survival.

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2.  Geographic residency status and census tract socioeconomic status as determinants of colorectal cancer outcomes.

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Journal:  Spat Spatiotemporal Epidemiol       Date:  2017-10-05

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5.  Age- and sex-specific spatio-temporal patterns of colorectal cancer mortality in Spain (1975-2008).

Authors:  Jaione Etxeberria; María Dolores Ugarte; Tomás Goicoa; Ana F Militino
Journal:  Popul Health Metr       Date:  2014-07-10

6.  The impact of delayed chemotherapy on its completion and survival outcomes in stage II colon cancer patients.

Authors:  Fang Xu; Alfred A Rimm; Pingfu Fu; Smitha S Krishnamurthi; Gregory S Cooper
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7.  Difference of stage at cancer diagnosis by socioeconomic status for four target cancers of the National Cancer Screening Program in Korea: Results from the Gwangju and Jeonnam cancer registries.

Authors:  Sun-Seog Kweon; Min-Gyeong Kim; Mi-Ran Kang; Min-Ho Shin; Jin-Su Choi
Journal:  J Epidemiol       Date:  2017-03-06       Impact factor: 3.211

8.  Geographic disparities in colorectal cancer survival.

Authors:  Kevin A Henry; Xiaoling Niu; Francis P Boscoe
Journal:  Int J Health Geogr       Date:  2009-07-23       Impact factor: 3.918

9.  The influence of geographical access to health care and material deprivation on colorectal cancer survival: evidence from France and England.

Authors:  O Dejardin; A P Jones; B Rachet; E Morris; V Bouvier; V Jooste; E Coombes; D Forman; A M Bouvier; G Launoy
Journal:  Health Place       Date:  2014-09-06       Impact factor: 4.078

10.  Spatial variation in prostate cancer survival in the Northern and Yorkshire region of England using Bayesian relative survival smoothing.

Authors:  L Fairley; D Forman; R West; S Manda
Journal:  Br J Cancer       Date:  2008-11-04       Impact factor: 7.640

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