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Predictive Factors for Long-Term Survival in Patients with Advanced Non-Small Cell Lung Cancer Treated with Immunotherapy


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Title: Predictive Factors for Long-Term Survival in Patients with Advanced Non-Small Cell Lung Cancer Treated with Immunotherapy

Authors: Ahmadi E. Omar, Kamran V. Aziz, Waseem N. Tariq

Journal: Academic journal of clinicians

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Year: 2024

Volume: 6

Issue: 4

Language: en

Keywords: Non-Small Cell Lung CancerImmunotherapyPredictive FactorsLong-Term SurvivalRetrospective Study

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Abstract

BackgroundAdvanced non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality. Immunotherapy has emerged as a promising treatment, but identifying predictive factors for long-term survival remains crucial.
ObjectiveThis study aims to identify predictive factors associated with long-term survival in patients with advanced NSCLC treated with immunotherapy.
MethodsA retrospective cohort study was conducted involving 300 patients diagnosed with advanced NSCLC who received immunotherapy between 2018 and 2023. Clinical data, including demographics, tumor characteristics, treatment response, and survival outcomes, were analyzed. Long-term survival was defined as survival beyond 24 months. Logistic regression analysis was performed to determine significant predictive factors.
ResultsOf the 300 patients, 60 (20%) achieved long-term survival. Significant predictive factors for long-term survival included; Performance status (ECOG 0-1) (OR 3.2, p < 0.01), Tumor PD-L1 expression ≥50% (OR 2.5, p < 0.01), Absence of liver metastases (OR 2.3, p < 0.05), Initial treatment response (partial or complete response) (OR 4.0, p < 0.01), Patients with these factors had a higher likelihood of achieving long-term survival compared to those without.
ConclusionsPerformance status, high PD-L1 expression, absence of liver metastases, and positive treatment response are significant predictive factors for long-term survival in patients with advanced NSCLC treated with immunotherapy. These findings can assist clinicians in identifying patients who may benefit most from immunotherapy and guide treatment strategies.


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