The results indicated that the number of patients with breast cancer has been steadily increasing since 2000, and reached 1.12 million in 2019, accounting for around 1% of the total population of India. Our ARIMA model predicts that the number of patients with BC in India will continue to increase in the future. There are various possible reasons for such an increasing number of patients with BC in India, such as; genetic factors and family history of breast cancer (inheritance of BRCA1 and BRCA2 genes), obesity, poor lifestyle, ultra-processed food consumption, smoking, and drinking alcohol can increase your risk significantly. Over the last 26 years, the age-standardised incidence rate of BC in females increased by 39.1% (95% uncertainty interval, 5.1 to 85.5) from 1990 to 2016, with the increase observed in every state of the country. (25) Current trends point out that a higher proportion of the disease is occurring at a younger age in Indian women, as compared to the West. The survival rate of patients with breast cancer is poor in India as compared to Western countries due to earlier age at onset, late stage of disease at presentation, delayed initiation of definitive management and inadequate/fragmented treatment. [9]
In this study, the economic burden of breast cancer also showed an upward trend from 2019 to 2030. The total economic burden of breast cancer in India was estimated at $34 billion in 2019, and according to our prediction, it will increase to $95 billion by 2030. The total economic burden of breast cancer in 2019 was 0.8% of Gross Domestic Product (GDP) and 17.64% of total health expenditure in India. Breast cancer imposes a heavy economic burden on India for the following possible reasons: Firstly, breast cancer is associated with lower levels of physical activity, socioeconomic status, utilization of health facilities and health insurance. A study conducted in a single-centre public tertiary cancer hospital in Mumbai city showed that 14.2% of patients discontinued treatment, and only 9% of the patients were covered by any health insurance scheme (26). Breast cancer is also associated with high co-morbidity, with hypertension and diabetes being the most common, adding to additional costs for the management of these diseases, and thus contributing to a high economic burden. Breast cancer in India primarily affects women in the prime working and reproductive age group thus contributing to high productivity loss, with the relative share of food, utility and other expenditure related to household consumption declining during cancer treatment.
The existing studies on the prevalence trends and economic burden of breast in India mostly describe and analyze the current situation but lack the prediction of the future situation in India. In 2022, a study predicted the number and prevalence of breast cancer patients in India from 2018 to 2025, and the results showed that the prevalence of breast cancer in India would increase. (28) Consistent with the results of the above study, the results of this study indicated that the number of breast cancer patients in India would also be on the rise. In addition, our study estimated the economic burden of breast cancer in India in the coming years. Therefore, this study might provide a more comprehensive assessment of the future risk of breast cancer in India. Projections from 204 countries and territories highlighted from 2020 to 2050 using a decision analytical model estimated that breast cancer will be among the top 5 cancers with the highest economic costs. (28) Within-country rankings of cancer type by economic cost were observed to be highly correlated with within-country rankings of cancer type by DALYs and shown to be affected by factors such as economic development and regional policies. Projections for 2021 and 2025 using Markov Chain Monte Carlo (MCMC) showed that breast cancer ranked first in incidence irrespective of region and was listed among the top five causes of more than 5% DALYs. (28)
The results of the above studies are consistent with this study, indicating that breast cancer has become one of the important public health problems worldwide. However, compared with these studies, the ARIMA model has better model accuracy (smaller relative error of prediction) and precision (more specific model effect evaluation indicators) in predicting the number of patients with breast cancer and can predict the number of patients with breast cancer per year and its economic burden in the future. Therefore, the ARIMA model can be one of the methods to predict the future prevalence trend and economic burden of breast cancer.
A steady increase in cancer deaths in India over the two decades is worrisome and has made researchers explore vastly in the domain. (29) Cancer remains to be the third or fourth major cause of premature mortality in 45 more nations. (30) The mortality rates of the transitional countries and the low-and middle-income countries (LMICs) remain comparable compared to those in the developed countries. This reveals the complex and varied dynamics of cancer and the risk it poses across various geographies and socioeconomic groups. In countries like India, the increase in deaths could also be associated with the rise in population and ageing demographics. BC also has emerged to be the widely detected cancer in 154 of 185 nations and shares a major proportion of deaths in over 100 countries (29). Several factors like nulliparity, history of BC, early age at menarche, late age at menopause, smoking, alcohol consumption, oral contraceptive use, obesity, and genetic mutation contribute to BC. Presence of a national-level cancer registry and accurate reporting of the deaths would improve the tracking of associated incidence and deaths. (9) The presence of a real-time data repository would reduce the discrepancies that exist in the statistical models and predictions made using the cancer registry data. Public awareness programmes to enhance the lifestyle could play a pivotal role in reducing the incidence and premature mortality.
Limitations
There are several limitations of this study. Firstly, in calculating the economic burden of breast cancer from 2020 to 2030, we used the treatment cost per capita and GNI per capita in 2019, without considering economic factors such as inflation and currency depreciation. Secondly, this study did not use the various stages of breast cancer for analysis. A more detailed analysis of the prevalence trend and economic impact of breast cancer is possible if data about each stage of the disease can be acquired.