Using Big Data in oncology to prospectively impact clinical patient care: A proof of concept study

Objective: Big Data is widely seen as a major opportunity for progress in the practice of personalized medicine, attracting the attention from medical societies and presidential teams alike as it offers a unique opportunity to enlarge the base of evidence, especially for older patients underrepresented in clinical trials. This study prospectively assessed the real-time availability of clinical cases in the Health & Research Informatics Total Cancer Care™ (TCC) database matching community patients with cancer, and the impact of such a consultation on treatment.

Materials and methods: Patients aged 70 and older seen at the Lynn Cancer Institute (LCI) with a documented malignancy were eligible. Geriatric screening information and the oncologist's pre-consultation treatment plan were sent to Moffitt. A search for similar patients was done in TCC and additional information retrieved from Electronic Medical Records. A report summarizing the data was sent and the utility of such a consultation was assessed per email after the treatment decision.

Results: Thirty one patients were included. The geriatric screening was positive in 87.1% (27) of them. The oncogeriatric consultation took on average 2.2 working days. It influenced treatment in 38.7% (12), and modified it in 19.4% (6). The consultation was perceived as "somewhat" to "very useful" in 83.9% (26).

Conclusion: This study establishes a proof of concept of the feasibility of real time use of Big Data for clinical practice. The geriatric screening and the consultation report influenced treatment in 38.7% of cases and modified it in 19.4%, which compares very well with oncogeriatric literature. Additional steps are needed to render it financially and clinically viable.