2023 World Conference on Lung Cancer (Posters)-P2.13. Integrated Clinical and Radiomics Approach to Assess the Treatment Outcome of Combined Chemoimmunotherapy in Extensive-Stage SCLC

P2.13. Integrated Clinical and Radiomics Approach to Assess the Treatment Outcome of Combined Chemoimmunotherapy in Extensive-Stage SCLC - PDF(Slides)

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Researchers conducted a retrospective study to assess the treatment outcomes of combined chemoimmunotherapy in extensive-stage small cell lung cancer (SCLC). The study included SCLC patients treated with atezolizumab or durvalumab with standard chemotherapy and a control group treated with chemotherapy alone. The researchers used machine learning algorithms to derive a radiomics score based on features extracted from chest CT scans taken before treatment. Clinical features such as tumor stage, performance status, and immune prognostic index were also analyzed. The study found that an integrated clinical and radiomics model could accurately predict treatment outcomes in patients receiving chemoimmunotherapy. The model provided a convenient and cost-effective tool for decision-making in patient management. The study demonstrated that the radiomics prediction model had a higher concordance index and time-dependent receiver operating characteristic curve compared to traditional clinical features alone. Additionally, the study showed that patients with high-progression risk receiving chemoimmunotherapy had similar progression-free survival and overall survival rates compared to the control group receiving chemotherapy alone. However, certain clinical features such as tumor stage, performance status, liver metastases, and immune prognostic index were found to be significantly correlated with treatment outcomes. In conclusion, the study suggests that an integrated clinical and radiomics approach can effectively assess the treatment outcomes of combined chemoimmunotherapy in extensive-stage SCLC, providing a valuable tool for predicting patient response and guiding clinical decision-making.

Asset Subtitle

Yang Xia

Meta Tag

Speaker Yang Xia

Topic SCLC & Neuroendocrine Tumors: Biomarkers & Radiomics

Keywords

chemoimmunotherapy

small cell lung cancer

machine learning algorithms

radiomics score

tumor stage

performance status

immune prognostic index

patient management

progression-free survival

clinical decision-making