Factors affecting oral cancer prognosis in Assam: A binary logistic regression study

Introduction

Cancer is a disease caused by an uncontrolled division of abnormal cells in the parts of the body. Cancer has become more than just a global health problem and is also a cause of deep suffering to the individual patients, their families and to the community at large. GLOBOCAN (Global Cancer Observatory), a project of the International Agency for Research on Cancer (IARC) provides data on Cancer incidence, mortality and geographic variability. The data is used to predict the future magnitude of cancer incidence and to evaluate national cancer control efforts. The GLOBOCAN 2020 estimates that there were 19.3 million new cases of cancer and almost 10 million deaths from cancer in 2020. According to World Health Organisation (WHO), cancer is found to be second leading cause of death throughout the global [1]. National Centre for Disease Informatics and Research (NCDIR) situated in Begaluru was established in 2011 by the Indian Council of Medical Research (ICMR). However, the ICMR-NCDIR coordinates the National Cancer Registry Programme (NCRP), which was established in 1981. The ICMR-NCDIR provides training, technical support, data evaluation and analysis to the Population Base Cancer Registries (PBCR). According to ICMR-NCDIR latest report [2], oral cancer is among the top three cancers in India and it is among the top five cancers in Assam. The study is trying to analyse the prognosis of oral cancer in different categories of patients in the region. In this study, a logistic regression model will be applied to understand the factors influencing the prognosis of the oral cancer in the region. In this study the probable factors influencing the prognosis of oral cancer have been classified into two categories, viz., personal factors and clinical factors. The study is based on the patients database (2015 -2020) is provided by North East Cancer Hospital & Research Institute (NECHRI), which established in 2008 has emerged as the most comprehensive and leading cancer hospital in North East India located in Jorabat, G.S. Road, Guwahati-781023. Its therapeutic and diagnostic facilities, according to several eminent experts are comparable with national level hospitals. The reason of choosing NECHRI for the study area is that it is one of the best premier cancer research institutes in India, the cancer patients of all the districts of Assam come to the institute to avail their treatments.

Personal Factors

Personal factors include Demographic factors, Behavioural factors, socioeconomic factors and Food habits. Demographic factors are classified into age and gender. Behavioural factors are the factors that the patients are habituated to abuse substances like areca nut, tobacco, smoking and alcohol. In Socioeconomic factors, it is considered as Education and Family income (pa). Education is classified as under metric, under graduate and graduate or others. Food habits include whether the patients taking foods veg or non-veg. Treatment given prior to registration (TGPR) TGPR has three options -Yes, No and Unknown.

Clinical Factors

Metabolic Risk Factors (MRF)

Metabolic syndrome is not a disease in itself. Instead, it's a group of risks factors-high blood pressure, high blood sugar, unhealthy cholesterol levels and abdominal fats. Occurrence of these factors in a person are influenced by his / her lifestyle. The metabolic factors generally support the growth of any disease. According to NCDIR [2] report, it is found that 80% of cancer patients have the following metabolic factors- Overweight / Obese BMI > 25  Raised blood pressure  Raised blood glucose (random)

The study is trying to analyse the two probable factors -Personal factors and Clinical factors influencing the prognosis of Oral cancer in context of Assam. In this analysis, a logistic regression model, have been applied to study the influence of these two factors on the status of the patients in term of Death or Alive.

Review of Literature

Different literatures on related topics have been reviewed and some of them are present as follows.  Babu B. Madana Mahana (2008) [4] discussed the various treatments and compare the effects of the treatments by observing the responses of the cancer patients by using various statistical tools basically probability distributions and logistic regression models. By the study, it was observed that male patients have more risk than female patients, the risk in discontinue treatments of the patients is higher than those patients who are continuing the treatments, the patients who are in stage 4 are having higher risk when compared to the patients who are in stage 2 and the male patients who are above 80 years are having more risk when compared to other age groups.  Hamidi A.Al-Hakimi et al. (2016) [5] [12] concluded that the logistic regression models that can identify the factors which affect the status of last contact of the cancer patients, are also used predict the status of cancer patients. The results showed that death occurred more to male cancer patients than female patients. The death percentage of the male patients was higher than the female patients although females were the ones who were mostly diagnosed with cancers. For the cancer site, most of the male patients suffered from digestive organ cancer. For female, the genital organs cancer had the highest number of occurrences. There are few numbers of male patients who were diagnosed with genital organs cancer.  Suresh Neena, Thomas Binu, Joseph Jeena (2024) [15] aims to investigate the research productivity of heart disease classification using logistic regression model to analyse the current patterns and potential future trends through bibliometric analysis.

Analysis and Interpretations

The effective sample size taken for this study is 1000 patients all over the Assam. The questionnaire is designed from the proforma given by Indian Council of Medical Research (ICMR) (Annexure1). Personal data of the patients are collected by taking interview of the patients or relatives over phone and personal interviews were also conducted who are accessible and the clinical data of the patients are collected from the hospital records.

Analysis of the model

The data are analysed by applying logistic regression model in SPSS. The outcomes are given below. By the Table 6, it is observed that all the cases are included in the analysis and so there is no missing case. Patient status is the dependent binary variable taking 0 as the patient is death and 1 as the patient is alive as shown in the Table 7. given prior to registration.  the mortality rate increases in higher metabolic risk factors (over weight, raised blood pressure, raised blood glucose)  The mortality rate is higher in urban areas.  There are eight outliers by using the model. Among them there seven are false predictions and one is true prediction.

References

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