Applying Evidence Synthesis Constructing Directed Acyclic Graphs (Esc-Dags) for Early Stage Non-Small Cell Lung Cancer Determining Causal Pathways Informing Epidemiologic Statistical Modelling

Abstract

Background: Directed Acyclic Graphs (DAGs) inform the epidemiologic statistical modelling confounders to determine close to true causal relationship in a study context. They inform inclusion of the predictive model variables that affect the causal relationship. Non-Small Cell Lung Cancer (NSCLC) is the frequently diagnosed, aggressive, and second leading cause of cancer deaths in the United States. Determining factors affecting both the guideline concordant treatment receipt and survival outcomes will help inform future epidemiologic models aiming to achieve close-to true causal relationship. Method: Peer-reviewed original research published during 2002-2023 were identified through PubMed, Embase, Web of Sciences, Clinical trials registry, and gray literature. DAGitty, an online software program, developed implied DAGs and integrated DAGs graphics. Evidence Synthesis for Constructing Directed Acyclic Graphs (ESC-DAGs) is utilized to guide DAG development. Conceptual models utilized were Andersen and Aday for factors affecting treatment receipt, and Shi and Steven’s for survival outcomes factors. Results: A total of 36 studies were included in the DAG synthesis out of 9421 retrieved across databases. Eight studies served in synthesis of treatment receipt DAG, while 28 studies for survival outcomes DAG. There were 10 causal paths and 13 covariates for treatment receipt, while two causal pathways and 32 covariates for survival outcomes. Conclusion : There are very few studies reporting on factors affecting early stage NSCLC guideline concordant care receipt compared to factors affecting its survival outcomes. Future investigations can utilize data extracted in current study to develop a meta-analysis informing effect size.

Note:
Funding declaration: No funding was received by any authors of this study.

Conflict of Interests: Authors of the paper have no competing interests.

Ethical Approval: The University of Louisville (UofL) Institutional Review Board (IRB) approved this study (IRB number 22.0281). The study is exempt according to 45 CFR 46.101(b) under Category 4: Secondary research, for which consent is not required.

Keywords: directed acyclic graphs, Causal inference, epidemiology, lung neoplasm, survival outcomes, treatment