Clinical multi-dimensional prognostic nomogram for predicting the efficacy of immunotherapy in NSCLC

Qian Zhao ^1,2, Xiao Zhong ^2,3, Xiaoqing Wang ⁴

⁰Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430064, China.

Scientific Reports +

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September 13, 2024

View abstract on PubMed

Summary

A new multi-dimensional model integrating clinical, radiomic, and immune data improves prediction of immunotherapy efficacy in non-small cell lung cancer (NSCLC) patients. This approach offers a more personalized treatment strategy for better patient outcomes.

Area Of Science

Oncology
Radiology
Immunology

Background

Immunotherapy has advanced non-small cell lung cancer (NSCLC) treatment, but low response rates necessitate predictive markers.
Tumor heterogeneity requires multi-dimensional models for accurate efficacy prediction.

Purpose Of The Study

To develop and validate a multi-dimensional prediction model for immunotherapy efficacy in NSCLC patients.
To integrate clinical parameters, radiomic features, and immune signatures for enhanced predictive power.

Main Methods

137 NSCLC patients receiving immunotherapy were analyzed.
Clinical data, CT-derived radiomic features, and immunohistochemical immune signatures were collected.
LASSO Cox regression identified predictive features; models (mLIPI, Radioscore, immune score, multi-dimensional) were constructed and evaluated using C-index and AUC.

Main Results

Three radiomic features and three immune signatures were identified as predictive.
The multi-dimensional model demonstrated superior predictive efficacy for progression-free survival (PFS) and overall survival (OS) compared to individual models (C-index: 0.721 for PFS, 0.727 for OS; AUC: 0.771 for PFS, 0.768 for OS).
mLIPI, Radioscore, and immune score were independent predictors of PFS and OS.

Conclusions

A multi-dimensional model integrating clinical, radiomic, and immune data significantly improves immunotherapy efficacy prediction in NSCLC.
This model offers a more precise and personalized approach to NSCLC treatment, potentially improving patient outcomes.
Further validation is warranted for clinical application.

Keywords:

Immunotherapy Nomograms Non-small cell lung cancer Predictive Radiomics