Literature DB >> 32526601

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).

Hyun Ae Jung1, Jong-Mu Sun1, Se-Hoon Lee1, Jin Seok Ahn1, Myung-Ju Ahn1, Keunchil Park2.   

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.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Big data; NSCLC; Real-time updated system; Real-world data; Treatment

Mesh:

Year:  2020        PMID: 32526601     DOI: 10.1016/j.lungcan.2020.05.033

Source DB:  PubMed          Journal:  Lung Cancer        ISSN: 0169-5002            Impact factor:   5.705


  2 in total

1.  Real-World Treatment Patterns and Clinical Outcomes in Patients With Stage III Non-Small-Cell Lung Cancer: Results of KINDLE-Vietnam Cohort.

Authors:  Tu Van Dao; Tuan Bao Diep; Tri Le Phuong; Reto Huggenberger; Amit Kumar
Journal:  Front Oncol       Date:  2022-05-23       Impact factor: 5.738

2.  Real-time autOmatically updated data warehOuse in healThcare (ROOT): an innovative and automated data collection system.

Authors:  Hyun Ae Jung; Oksoon Jeong; Dong Kyung Chang; Sehhoon Park; Jong-Mu Sun; Se-Hoon Lee; Jin Seok Ahn; Myung-Ju Ahn; Keunchil Park
Journal:  Transl Lung Cancer Res       Date:  2021-10
  2 in total

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