Ten-year patient journey of stage III non-small cell lung cancer patients: A single-center, observational, retrospective study in Korea (Realtime autOmatically updated data warehOuse in healTh care; UNIVERSE-ROOT study)

医学 观察研究 单中心 阶段(地层学) 回顾性队列研究 医疗保健 肺癌 中心(范畴论) 急诊医学 内科学 结晶学 经济增长 生物 古生物学 经济 化学
作者
Hyun Ae Jung,Jong‐Mu Sun,Se‐Hoon Lee,Jin Seok Ahn,Myung‐Ju Ahn,Keunchil Park
出处
期刊:Lung Cancer [Elsevier]
卷期号:146: 112-119 被引量:12
标识
DOI:10.1016/j.lungcan.2020.05.033
摘要

Abstract 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.
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