Overview of approaches to estimate real-world disease progression in lung cancer
Menée à partir d'une revue narrative de la littérature publiée entre 2008 et 2022 (40 articles), cette étude identifie 5 approches pour estimer la progression d'un cancer du poumon à partir de données obtenues en contexte réel
Background : Randomized clinical trials (RCTs) of novel treatments for solid tumors normally measure disease progression using the Response Evaluation Criteria in Solid Tumors (RECIST). However, novel, scalable approaches to estimate disease progression using real-world data (RWD) are needed to advance cancer outcomes research. The purpose of this narrative review is to summarize examples from the existing literature on approaches to estimate real world (RW)-disease progression and their relative strengths and limitations, using lung cancer as a case study.
Methods : A narrative literature review was conducted in PubMed to identify articles that used approaches to estimate RW-disease progression in lung cancer patients. Data abstracted included data source, approach used to estimate RW-progression, and comparison to a selected gold standard (if applicable).
Results : A total of 40 articles were identified from 2008-2022. Five approaches to estimate RW-disease progression were identified including: manual abstraction of medical records, natural language processing of clinical notes/radiology reports, treatment-based algorithms, changes in tumor volume, and delta radiomics-based approaches. The accuracy of these progression approaches were assessed using different methods, including correlations between RW-endpoints and OS for manual abstraction (Spearman rank p = .61-0.84) and area under the curve (AUC) for NLP approaches (AUC = 0.86-0.96).
Conclusions : RW-disease progression has been measured in several observational studies of lung cancer. However, comparing the accuracy of methods across studies is challenging, due, in part, to the lack of a gold standard and the different methods used to evaluate accuracy. Concerted efforts are needed to define a gold standard and quality metrics for RWD.
JNCI Cancer Spectrum , article en libre accès, 2022