Purpose: RENORT is a novel data mining application developed to extract relevant clinical data from oncology information systems (OIS; ARIA and Mosaiq) used in radiation oncology (RO).
Methods/patients: We used RENORT to extract demographic and clinical data from the OIS of all patients treated at the RO Department at the General Hospital of Valencia during the year 2019.
Results: A total of 1158 treatments were performed. The female/male ratio was 39.3%/60.7%, with a mean age of 66 years. The mean waiting time between the treatment decision/proposal to the first visit was 10.1 days. Mean duration of the treatment preparation process was 21 days. Most patients (90.4%) completed treatment within the prescribed time ± 7 days. The most common sites/treatment types were: metastatic/palliative treatments (n = 300; 25.9%), breast (209; 18.0%), genitourinary (195; 16.8%), digestive (116; 10.0%), thoracic (104; 9.0%), head and neck (62; 5.4%), and skin cancer (51; 4.4%). The distribution according to treatment intent was as follows: palliative (n = 266; 23.0%), adjuvant curative (335; 28.9%), radical without adjuvant treatment (229; 19.8%), radical with concomitant treatment (188; 16.2%), curative neoadjuvant (70; 6.0%), salvage radiotherapy (61; 5.3%); and reirradiation (9; 0.8%). The most common treatment techniques were IMRT/VMAT with IGRT (n = 468; 40.4%), 3D-CRT with IGRT (421; 36.4%), SBRT (127; 11.0%), 2DRT (57; 4.9%), and SFRT (56; 4.8%). A mean of 15.9 fractions were administered per treatment. Hypofractionated schemes were used in 100% of radical intent breast and prostate cancer treatments.
Conclusions: The RENORT application facilitates data retrieval from oncology information systems to allow for a comprehensive determination of the real role of radiotherapy in the treatment of cancer patients. This application is valuable to identify patterns of care and to assess treatment efficacy.
Keywords: Cancer; Pattern of care; RENORT; Radiotherapy.