Shin Young Seob, Jang Jeong Yun, Yoo Ye Jin, Yu Jesang, Song Kye Jin, Jo Yoon Young, Kim Sung-Bae, Park Sook Ryun, Song Ho June, Kim Yong-Hee, Kim Hyeong Ryul, Kim Jong Hoon
Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Department of Radiation Oncology, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Korea.
Gastroenterol Rep (Oxf). 2024 Jul 6;12:goae060. doi: 10.1093/gastro/goae060. eCollection 2024.
In patients with esophageal squamous cell carcinoma (ESCC), accurately predicting a pathologic complete response (pCR) to preoperative chemoradiotherapy (PCRT) has the potential to enable an active surveillance strategy without esophagectomy. We aimed to establish a reliable multiparameter nomogram model that combines tumor characteristics, imaging modalities, and hematologic markers to predict pCR in patients with ESCC who underwent PCRT and esophagectomy.
We retrospectively reviewed the medical records of 457 patients with ESCC who received PCRT followed by esophagectomy between January 2005 and October 2020. The nomogram model was developed using logistic regression analysis with a training cohort and externally validated with a validation cohort.
In the training and validation cohorts, 44.2% (126/285) and 48.3% (83/172) of patients, respectively, achieved pCR after PCRT. The 5-year rates of overall survival, progression-free survival, and freedom from local progression in the training cohort were 51.6%, 48.5%, and 77.6%, respectively. The parameters included in the nomogram were histologic grade, clinical N stage, maximum standardized uptake value on positron emission tomography, and post-PCRT biopsy. Hematologic markers were significantly associated with survival outcomes but not with pCR. The area under the receiver operating characteristic curve of the nomogram was 0.717, 0.704, and 0.707 for the training cohort, internal validation cohort, and external validation cohort, respectively.
Our nomogram model based on four parameters obtained from standard clinical practice demonstrated good performance in both the training and validation cohorts and could be useful to aid clinical decision-making to determine whether surgery or active surveillance strategy should be pursued.
在食管鳞状细胞癌（ESCC）患者中，准确预测术前放化疗（PCRT）后的病理完全缓解（pCR），有可能使患者在不进行食管切除术的情况下采取积极监测策略。我们旨在建立一个可靠的多参数列线图模型，该模型结合肿瘤特征、影像学检查方法和血液学标志物，以预测接受PCRT和食管切除术的ESCC患者的pCR。
我们回顾性分析了2005年1月至2020年10月期间457例接受PCRT后行食管切除术的ESCC患者的病历。列线图模型采用逻辑回归分析在训练队列中构建，并在验证队列中进行外部验证。
在训练队列和验证队列中，分别有44.2%（126/285）和48.3%（83/172）的患者在PCRT后达到pCR。训练队列中5年总生存率、无进展生存率和无局部进展生存率分别为51.6%、48.5%和77.6%。列线图纳入的参数包括组织学分级、临床N分期、正电子发射断层扫描最大标准化摄取值和PCRT后活检。血液学标志物与生存结局显著相关，但与pCR无关。列线图在训练队列、内部验证队列和外部验证队列中的受试者工作特征曲线下面积分别为0.717、0.704和0.707。
我们基于标准临床实践获得的四个参数构建的列线图模型在训练队列和验证队列中均表现良好，有助于临床决策，以确定应采取手术还是积极监测策略。
