Academic Editor: Yoh Dobashi
Background: Currently, individual clinical prognostic variables are
used sequentially with risk-stratification after TNM staging in clinical practice
for the prognostic assessment of patients with NSCLC, which is not effective for
estimating the collective impact of multiple individual variables on patient
outcomes. Here, we developed a clinical and PET/CT volumetric prognostic (CPVP)
index that integrates the prognostic power of multiple clinical variables and
metabolic tumor volume from baseline FDG-PET, for use immediately after
definitive therapy. Patients and methods: This retrospective cohort
study included 998 NSCLC patients diagnosed between 2004 and 2017, randomly
assigned to two cohorts for modeling the CPVP index using Cox regression models
examining overall survival (OS) and subsequent validation. Results: The
CPVP index generated from the model cohort included pretreatment variables
(whole-body metabolic tumor volume [MTVwb], clinical TNM stage, tumor histology,
performance status, age, race, gender, smoking history) and treatment type. A
clinical variable (CV) index without MTVwb and PET/CT volumetric prognostic (PVP)
index without clinical variables were also generated for comparison. In the
validation cohort, univariate Cox modeling showed a significant association of
the index with overall survival (OS; Hazard Ratio [HR] 3.14; 95% confidence interval [95% CI] = 2.71 to
3.65, p