Peripheral Blood Biomarkers Predict Outcomes in Advanced Cancers Treated With Anti‐PD‐1 Therapy

OBJECTIVE: PD-1 inhibitors are increasingly used in advanced cancers, but reliable biomarkers for predicting treatment response remain limited. METHODS: In this retrospective cohort study, we analyzed 335 patients with stage IV cancers treated with anti-PD-1 therapy (The First People's Hospital of Kunshan, 2019-2025). A predictive model integrating peripheral blood markers and clinical factors was developed using logistic and Cox regression. RESULTS: Histologic subtype, dNLR ≤ 3.18, AMC ≤ 0.48, and IL-6 ≤ 12.35 were independent prognostic factors for OS and PFS (multivariate HRs reported). Patients with ≥ 3 favorable factors had significantly better outcomes. The model showed high accuracy for 1-year survival prediction (AUC = 0.83) but limited performance beyond 3 years. CONCLUSION: This study proposes a clinically feasible biomarker-based tool to stratify PD-1 inhibitor responders, though further validation in prospective cohorts is needed.

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Publication Details

Journal
Immunity Inflammation and Disease
Published
2026-05-01
DOI
https://doi.org/10.1002/iid3.70402
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
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article

Peripheral Blood Biomarkers Predict Outcomes in Advanced Cancers Treated With Anti‐PD‐1 Therapy

P L Li, Jinhua Gu, Qianhui Gu, M B Chen et al.
Immunity Inflammation and Disease
Cancer Immunotherapy and Biomarkers
article

Peripheral Blood Biomarkers Predict Outcomes in Advanced Cancers Treated With Anti‐PD‐1 Therapy

P L Li, Jinhua Gu, Qianhui Gu, M B Chen, Chunxia Feng
article en

Abstract

OBJECTIVE: PD-1 inhibitors are increasingly used in advanced cancers, but reliable biomarkers for predicting treatment response remain limited. METHODS: In this retrospective cohort study, we analyzed 335 patients with stage IV cancers treated with anti-PD-1 therapy (The First People's Hospital of Kunshan, 2019-2025). A predictive model integrating peripheral blood markers and clinical factors was developed using logistic and Cox regression. RESULTS: Histologic subtype, dNLR ≤ 3.18, AMC ≤ 0.48, and IL-6 ≤ 12.35 were independent prognostic factors for OS and PFS (multivariate HRs reported). Patients with ≥ 3 favorable factors had significantly better outcomes. The model showed high accuracy for 1-year survival prediction (AUC = 0.83) but limited performance beyond 3 years. CONCLUSION: This study proposes a clinically feasible biomarker-based tool to stratify PD-1 inhibitor responders, though further validation in prospective cohorts is needed.

Immunity Inflammation and DiseaseVol. 14(5)
Jiangsu University (CN), First People's Hospital of Kunshan (CN)
Good health and well-being
Openalex Percentile: Top 8%
Cancer Immunotherapy and Biomarkers
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