Ghazali, Anis Kausar and Taylor, Benjamin and Keegan, Thomas (2018) Modelling of survival and incidence for colorectal cancer in Malaysia. PhD thesis, Lancaster University.
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Abstract
Colorectal cancer is the third most common cancer worldwide, with an estimated 1.36 million new cases and 694,000 deaths recorded in 2012. This number is expected to increase by 80% reaching approximately 2.4 million cases in 2035, and contributing to 1.3 million deaths globally per year. In Malaysia, colorectal cancer is the second most common cancer, in both men and women, behind lung cancer in men and breast cancer in women respectively. The most recent estimate gives the incidence of colorectal cancer in Malaysia as 21.3 cases per 100,000 population and 9.8 deaths per 100,000 population for the six years period reported between 2008 and 2013. The incidence of colorectal cancer is known to vary by place and by time period. However, most research on the spatial and variation in cancer incidence has taken place outside South East Asia, and such research on this is still scarce in Malaysia. The research presented in this thesis investigates individual factors affecting survival, and the spatial variation in incidence and survival of colorectal cancer in Malaysia. This has not been done before in Malaysia. There are three objectives addressed in this thesis: (1) to investigate the individual characteristics that affect survival of colorectal cancer in Malaysia, (2) to investigate and model the spatial variation of survival in colorectal cancer in Malaysia, (3) to investigate and model the spatial variation in the incidence of colorectal cancer in Malaysia. The research was involved 4412 of colorectal cancer patients in Malaysia with histologically verified primary colorectal cancer who were diagnosed between 2008 and 2013 (ICD-10, C18-C20), recorded in the database of National Cancer Patient Registry- Colorectal Cancer (NCPR-CC) Malaysia. We investigated the effect of individual characteristics such as age, gender, education as well as clinical characteristics such as cancer staging, cancer site and treatment modalities on survival prognosis after a diagnosis of colorectal cancer using a Cox regression model. The analysis was then been extended to model the spatial variation in survival for colorectal cancer patients in Malaysia, accounting for individual and socioeconomic characteristics using a spatial survival model. We then applied a Generalized Linear Mixed Effects model, which is derived from the log-Gaussian Cox Process, in order to model the incidence of colorectal cancer in Peninsular Malaysia. Our findings show that the severity of disease at diagnosis as measured by cancer staging, tumour grading and the presence of distant metastases, plays an important role in the prognosis of patients with colorectal cancer in Malaysia, and that this remains even after controlling for spatial correlation on space. Our research allows us to shows the geographical variation in survival of colorectal cancer in Malaysia, and what variation persists once individual and socioeconomic characteristics are taken into account. Our model that developed to predict the colorectal cancer incidence found that that some places had greater risk of an incidence exceeding the national average. The map for probability of exceedance relative risk of colorectal cancer incidence in the North West of Peninsular Malaysia shows variation in the risk for colorectal cancer cases across the region. We noted that town areas are highly likely to exceed the threshold of relative risk of increased number of colorectal cancer cases, and this effect is present even though we account for the additional population there. Spatial variation in survival and incidence of colorectal cancer in Malaysia needs to be investigated further. To the best of our knowledge, this is the first research that uses spatial modelling to identify potential factors affecting the incidence and survival for colorectal cancer in Malaysia, as well as to map the risks in survival and incidence. Our findings can help public health authorities to plan better management of the resources used to prevent and treat this disease.