JMIR Publications

ABSTRACT

Background:

Accurate and rapid clinical decisions based on real-world evidence are essential for patients with cancer. However, the complexity of chemotherapy regimens for cancer impedes retrospective research on observational health databases.

Objective:

To compare the anticancer treatment trajectories and patterns of clinical events according to regimen type using the chemotherapy episodes determined by the algorithm.

Methods:

We developed an algorithm to extract the regimen-level abstracted chemotherapy episodes from medication records in a conventional Observational Medical Outcomes Partnership (OMOP) common data model (CDM) database. The algorithm was validated on the Ajou University School Of Medicine (AUSOM) database by manual review of clinical notes. Using the algorithm, we extracted episodes of chemotherapy from patients in the EHR database and the claims database. We also developed an application software that visualizing the chemotherapy treatment patterns based on the treatment episodes in the OMOP-CDM database. Using this software, we generated the trends in type of the regimen used in the institutions, the patterns of the iterative chemotherapy use, and the trajectories of cancer treatment in two of EHR based OMOP-CDM database. The time of onset of chemotherapy-induced neutropenia according to regimen was measured as a pilot study using the AUSOM database. The anti-cancer treatment trajectories for patients with COVID-19 were also visualized based on the nationwide claims database.

Results:

We generated 178,360 treatment episodes for patients with colorectal, breast, and lung cancer for 85 different regimens. The algorithm precisely identified the type of chemotherapy regimen in 300 patients (positive predictive value: 100%). The trends in the use of routine clinical chemotherapy regimen from 2008 to 2018 were identified for 8,236 patients. In a total of 12 regimens, the number of repeated treatments, which held the largest proportion of patients, was concordant with the protocols for certain cases in wiki for standard chemotherapy regimen. Moreover, the anticancer treatment trajectories for 8,315 patients were shown, including 62 patients with COVID-19. A comparative analysis of neutropenia showed that its onset in colorectal cancer regimens tended to cluster in days 9 to 15, whereas it tended to be clustered in days 2 to 8 for certain regimens for breast cancer or lung cancer.

Conclusions:

We propose a method for generating chemotherapy episodes for introduction into the oncology extension module of the OMOP-CDM databases. The proof-of-concept studies demonstrated the usability, scalability, and interoperability of the proposed framework through a distributed research network.