Correlation Between Cancer Research Trends and Real World Data: An Analysis on Altmetric Data

The field of cancer research is overall ambiguous to the general population and apart from medical news, not a lot is known of the proceedings. This study aims to provide some clarity towards cancer research, especially towards the correlations between research of different types of cancer. The amount of research papers pertaining to different types of cancers is compared against mortality and diagnosis rates to determine the amount of research attention towards a type of cancer in relation to its overall importance or danger level to the general population.

This is achieved through the use of many computational tools such as Python, R, and Microsoft Excel. Python is used to parse through the JSON files and extract the abstract and Altmetric score onto a single CSV file. R is used to iterate through the rows of the CSV files and count the appearance of each type of cancer in the abstract. As well as this, R creates the histograms describing Altmetric scores and file frequency. Microsoft Excel is used to provide further data analysis and find correlations between Altmetrics data and Canadian Cancer Society data.

The analysis from these tools revealed that breast cancer was the most researched cancer by a large margin with nearly 1,700 papers. Although there were a large number of cancer research papers, the Altmetric scores revealed that most of these papers did not gain significant attention.

By comparing these results to Canadian Cancer Society data, it was uncovered that Breast Cancer was receiving research attention that was not merited. There were four times more breast cancer research papers than the second most researched cancer, prostate cancer. This was despite the fact that breast cancer was fourth in mortality and third in new cases among all cancers. Inversely, lung cancer was underrepresented with only 401 research papers in spite of being the deadliest cancer in Canada.