IMR Press / FBL / Volume 27 / Issue 1 / DOI: 10.31083/j.fbl2701016
Open Access Original Research
Developing a clinical and PET/CT volumetric prognostic index for risk assessment and management of NSCLC patients after initial therapy
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1 Department of Nuclear Medicine, Shanghai Chest Hospital, Shanghai Jiao tong University, 200030 Shanghai, China
2 Clinical and Translational Center in Shanghai Chest Hospital, Shanghai Key Laboratory for Molecular Imaging, Shanghai University of Medicine and Health Sciences, 201318 Shanghai, China
3 Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, 050017 Shijiazhuang, Hebei, China
4 Department of Surgery, Section of Thoracic Surgery, The University of Chicago, Chicago, IL 60637, USA
5 Department of Radiology, The University of Chicago, Chicago, IL 60637, USA
6 Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
*Correspondence: (Yonglin Pu)
Academic Editor: Yoh Dobashi
Front. Biosci. (Landmark Ed) 2022, 27(1), 16;
Submitted: 1 September 2021 | Revised: 16 December 2021 | Accepted: 21 December 2021 | Published: 12 January 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

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 < 0.001). Multivariate Cox regression analysis demonstrated a significant association of the index with OS (HR = 3.13, 95% CI = 2.66 to 3.67, p < 0.001). The index showed greater prognostic power (C-statistic = 0.72) than any of its independent variables including clinical TNM stage (C-statistic ranged from 0.50 to 0.69, all p < 0.003), CV index (C-statistic = 0.68, p < 0.001) and PVP index (C-statistic = 0.70, p = 0.006). Conclusions: The CPVP index for NSCLC patients has moderately strong prognostic power and is more prognostic than its individual prognostic variables and other indices. It provides a practical tool for quantitative prognostic assessment after initial treatment and therefore may be helpful for the development of individualized treatment and monitoring strategy for NSCLC patients.

Prognostic index
Metabolic tumor burden
Non-small cell lung cancer
Survival analysis
TNM stage
Fig. 1.
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