探索改性晚期肺癌炎症指数对晚期非小细胞肺癌患者的治疗结果的影响
Abhishek Mahajan1, Devendra Goyal2, Ujjwal Agarwal2
1Clatterbridge Centre for Oncology NHS Foundation Trust, L7 8YA Liverpool, UK.
Exploration of targeted anti-tumor therapy
|November 16, 2023
概括
麻症和骨肌密度 (SMD) 是高级非小细胞肺癌 (NSCLC) 总生存率 (OS) 和无进展生存率 (PFS) 的显著预测因素. 经过修改的晚期肺癌炎症指数 (mALI) 也显示出预后价值,有助于患者分层获得营养支持.
科学领域:
- 在瘤学瘤学.
- 放射学 放射学是一门学科.
- 营养科学 营养科学
背景情况:
- 麻症和骨肌密度 (SMD) 是癌症中确定的预后标志物.
- 晚期肺癌炎症指数 (ALI) 预测了小细胞肺癌 (SCLC) 的生存率.
- 计算机断层扫描 (CT) 提供客观的身体组成评估,与身体质量指数 (BMI) 不同.
研究的目的:
- 评估使用CT衍生L3骨肌指数在高级非小细胞肺癌 (NSCLC) 中修改ALI (mALI) 的预后效用.
- 为了研究萨尔科佩尼亚,SMD,中性粒细胞-淋巴细胞比率 (NLR),ALI和mALI之间的相互作用.
- 确定这些标记物对化疗前后总生存 (OS) 和无进展生存 (PFS) 的影响.
主要方法:
- 对285名晚期NSCLC患者的回顾性分析.
- 基于CT的SMD,骨肌肉指数 (SMI) 和L3脊椎的无脂肪质量 (FFM) 的量化.
- 计算ALI (BMI × 血清白蛋白/NLR) 和mALI (SMI × 血清白蛋白/NLR).
主要成果:
- 在所有BMI类别中,肉类的流行率 (>70%) 较高.
- 在ALI和mALI治疗前观察到一致性.
- 较差的ALI,化疗前后的mALI与较差的NLR有显著的相关性.
结论:
- 麻症,SMD和mALI是高级NSCLC中OS的显著独立预测因素.
- 麻症和SMD也可以预测PFS.
- 这些基于CT的生物标志物可以指导营养干预措施,以改善患者的治疗结果.
相关概念视频
01:25Chronic Obstructive Pulmonary Disease-III: Symptoms and Complications.
2.8K
Understanding the variety of primary symptoms and systemic complications that characterize chronic obstructive pulmonary disease (COPD) is crucial for healthcare professionals.
Symptoms of COPD can be classified as primary or systemic. Primary symptoms relate to reduced airflow, while systemic or extrapulmonary symptoms relate to COPD's broader impact on the body.
Primary Symptoms of COPD:
Symptoms of COPD can be classified as primary or systemic. Primary symptoms relate to reduced airflow, while systemic or extrapulmonary symptoms relate to COPD's broader impact on the body.
Primary Symptoms of COPD:
2.8K
01:21Cancer Survival Analysis
356
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
356