Multi-Omics Prediction of Radiation Pneumonitis Risk in Lung Cancer Patients After Immunotherapy and Thoracic Radiotherapy
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 160
- 试验地点
- 1
- 主要终点
- Area Under the Receiver Operating Characteristic Curve (AUC) of the Multi-Omics Prediction Model for Radiation Pneumonitis
研究概览
简要总结
This prospective study aims to develop a multi-omics-based predictive model for radiation pneumonitis in lung cancer patients receiving sequential immunotherapy and thoracic radiotherapy.
详细描述
The combination of immune checkpoint inhibitors with thoracic radiotherapy has yielded substantial survival gains in lung cancer, yet this dual-modality strategy confers a markedly elevated risk of radiation pneumonitis, particularly when radiotherapy follows immunotherapy. To date, no validated biomarkers exist to stratify patients by this risk, constraining both individualized treatment planning and proactive surveillance. This prospective study addresses this unmet need by systematically collecting blood, urine, and stool samples from patients receiving sequential immunotherapy and thoracic radiotherapy. Employing integrative multi-omics platforms, including genomics, transcriptomics, proteomics, and metabolomics, we aim to discover novel molecular signatures capable of accurately predicting radiation pneumonitis susceptibility. Ultimately, by correlating multi-omic profiles with clinical outcomes, we seek to construct a clinically actionable prediction model to inform risk-adapted monitoring, facilitate patient-clinician shared decision-making, and enhance therapeutic safety and quality of life in this expanding patient population.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients aged 18 or older years with a life expectancy of at least 6 months. Additional inclusion criteria were a Zubrod performance status of 0-1, documentation of baseline chest computed tomography (CT) scans prior to the initiation of immunotherapy, receipt of at least 2 cycles of systemic therapy (PD-1) as either monotherapy or combination therapy within the past six months, voluntary participation with written informed consent, and appropriate baseline biochemical tests. The radiation dose for thoracic radiotherapy was ≥30Gy for all eligible patients in this study. No use of antibiotics within 1 week prior to the initiation of thoracic radiotherapy.
排除标准
- •Participation in other interventional clinical studies or treatments, having received investigational drugs or treatments within 4 weeks prior to the first dose, or prior receipt of a solid organ or hematopoietic stem cell transplant, having an active infection, or pre-existing/active ICI-induced pneumonitis.
结局指标
主要结局
Area Under the Receiver Operating Characteristic Curve (AUC) of the Multi-Omics Prediction Model for Radiation Pneumonitis
时间窗: At 6 months post-radiotherapy
The area under the ROC curve (AUC) will be calculated to evaluate the predictive performance of a multi-omics-based model-integrating genomic, transcriptomic, proteomic, and metabolomic data-for distinguishing lung cancer patients who develop grade ≥2 radiation pneumonitis from those who do not, following sequential immunotherapy and thoracic radiotherapy. Model performance will be assessed using bootstrap internal validation with 1,000 resamples to estimate optimism-corrected AUC.
次要结局
未报告次要终点
研究者
HAN GUANG
Clinical Professor
Hubei Cancer Hospital