TY - JOUR
T1 - Ten-year patient journey of stage III non-small cell lung cancer patients
T2 - A single-center, observational, retrospective study in Korea (Realtime autOmatically updated data warehOuse in healTh care; UNIVERSE-ROOT study)
AU - Jung, Hyun Ae
AU - Sun, Jong Mu
AU - Lee, Se Hoon
AU - Ahn, Jin Seok
AU - Ahn, Myung Ju
AU - Park, Keunchil
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/8
Y1 - 2020/8
N2 - Introduction: Until the recent approval of immunotherapy after completing concurrent chemoradiotherapy (CCRT), there has been little progress in treating unresectable stage III non-small cell lung cancer (NSCLC). This prompted us to search real-world data (RWD) to better understand diagnosis and treatment patterns, and outcomes. Methods: This non-interventional observational study used a unique, novel algorithm for big data analysis to collect and assess anonymized patient electronic medical records from a clinical data warehouse (CDW) over a 10-year period to capture real-world patterns of diagnosis, treatment, and outcomes of stage III NSCLC patients. We describe real-world patterns of diagnosis and treatment of patients with newly-diagnosed stage III NSCLC, and patients’ characteristics, and assessment of treatment outcomes. Results: We analyzed clinical variables from 23,735 NSCLC patients. Stage III patients (N = 4138, 18.2 %) were diagnosed as IIIA (N = 2,547, 11.2 %) or IIIB (N = 1,591. 7.0 %). Treated stage III patients (N = 2530, 61.1 %) had a median age of 64.2 years, were mostly male (78.5 %) and had an ECOG performance status of 1 (65.2 %). Treatment comprised curative-intent surgery (N = 1,254, 49.6 %) with 705 receiving neoadjuvant therapy; definitive CRT (N = 648, 25.6 %); palliative CT (N = 270, 10.7 %), or thoracic RT (N = 170, 6.7 %). Median OS (range) for neoadjuvant, surgery, CRT, palliative chemotherapy, lung RT alone, and supportive care was 49.2 (42.0–56.5), 52.5 (43.1–61.9), 30.3 (26.6–34.0), 14.7 (13.0–16.4), 8.8 (6.2–11.3), and 2.0 (1.0–3.0) months, respectively. Conclusions: This unique in-house algorithm enabled a rapid and comprehensive analysis of big data through a CDW, with daily automatic updates that documented real-world PFS and OS consistent with the published literature, and real-world treatment patterns and clinical outcomes in stage III NSCLC patients.
AB - Introduction: Until the recent approval of immunotherapy after completing concurrent chemoradiotherapy (CCRT), there has been little progress in treating unresectable stage III non-small cell lung cancer (NSCLC). This prompted us to search real-world data (RWD) to better understand diagnosis and treatment patterns, and outcomes. Methods: This non-interventional observational study used a unique, novel algorithm for big data analysis to collect and assess anonymized patient electronic medical records from a clinical data warehouse (CDW) over a 10-year period to capture real-world patterns of diagnosis, treatment, and outcomes of stage III NSCLC patients. We describe real-world patterns of diagnosis and treatment of patients with newly-diagnosed stage III NSCLC, and patients’ characteristics, and assessment of treatment outcomes. Results: We analyzed clinical variables from 23,735 NSCLC patients. Stage III patients (N = 4138, 18.2 %) were diagnosed as IIIA (N = 2,547, 11.2 %) or IIIB (N = 1,591. 7.0 %). Treated stage III patients (N = 2530, 61.1 %) had a median age of 64.2 years, were mostly male (78.5 %) and had an ECOG performance status of 1 (65.2 %). Treatment comprised curative-intent surgery (N = 1,254, 49.6 %) with 705 receiving neoadjuvant therapy; definitive CRT (N = 648, 25.6 %); palliative CT (N = 270, 10.7 %), or thoracic RT (N = 170, 6.7 %). Median OS (range) for neoadjuvant, surgery, CRT, palliative chemotherapy, lung RT alone, and supportive care was 49.2 (42.0–56.5), 52.5 (43.1–61.9), 30.3 (26.6–34.0), 14.7 (13.0–16.4), 8.8 (6.2–11.3), and 2.0 (1.0–3.0) months, respectively. Conclusions: This unique in-house algorithm enabled a rapid and comprehensive analysis of big data through a CDW, with daily automatic updates that documented real-world PFS and OS consistent with the published literature, and real-world treatment patterns and clinical outcomes in stage III NSCLC patients.
KW - Big data
KW - NSCLC
KW - Real-time updated system
KW - Real-world data
KW - Treatment
UR - https://www.scopus.com/pages/publications/85085914983
U2 - 10.1016/j.lungcan.2020.05.033
DO - 10.1016/j.lungcan.2020.05.033
M3 - Article
C2 - 32526601
AN - SCOPUS:85085914983
SN - 0169-5002
VL - 146
SP - 112
EP - 119
JO - Lung Cancer
JF - Lung Cancer
ER -