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Updated: May 28, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
The Association Between Tumor Burden and the Efficacy of Immunotherapy Among Patients With Non-small Cell Lung Cancer
Jia-Jun Hui1, Han-Lu Yan2, Sheng-Jun Ding1
1Department of Medical Oncology, Wuxi Huishan District People' s Hospital, Affiliated Huishan Hospital of Xinglin College, Nantong University, Wuxi, China.
Background:
This cohort study aimed to evaluate the impact of tumor burden (TB) on the efficacy of immunotherapy in patients with advanced non-small cell lung cancer (NSCLC).
Materials And Methods:
Data from the POPLAR and OAK trials were extracted as the training and validation cohorts, respectively. TB was defined as the sum of the longest dimensions (blSLD) of measurable target lesions as per RECIST v1.1. The Kaplan-Meier curves and multivariate Cox regression analyses were performed to assess the association between TB with blood-tested tumor mutation burden (bTMB), PD-L1 expression, and survival outcomes. Additionally, random forest algorithms analysis was performed to evaluate the accuracy of TB in predicting 12-month mortality of NSCLC patients received atezolizumab.
Results:
A total of 105 patients from the POPLAR trial and 322 patients from the OAK trial were recruited in the training and validation sets, respectively. Patients with TB-L have significantly better OS than those with TB-H in the training (mOS: 15.8 months vs 6.93 months) as well as the validation (mOS: 16.0 months vs 7.59 months) cohort. The multivariate Cox regression analysis indicated that TB is an independent biomarker for OS prediction, regardless of bTMB, PD-L1 expression, and number of metastasis sites. The impact of TB on 12-month mortality was expected to be stronger with the increase of TB, suggesting that patients with a high tumor burden experienced a detrimental effect on 12-month mortality.
Conclusion:
TB may act as a prognostic biomarker for clinical benefit in NSCLC patients treated with immunotherapy alone. This may be potentially effective for predicting the efficacy of immunotherapy-based regimens.
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