Abstract 3060
Background
We aimed to establish a risk model using computed tomography-based compactness to predict overall survival (OS) and progression-free survival (PFS) after multimodal treatment for esophageal squamous cell carcinoma (ESCC).
Methods
We extracted pre-treatment CT-based tumor data (volume, surface area, and compactness) for 512 cases of ESCC that were treated at 3 centers. A risk model based on compactness was trained using Cox regression analyses of 83 cases, and then the model was validated using two independent cohorts (98 patients and 283 patients). The largest cohort (283 patients) was then evaluated using the risk model to predict response to radiotherapy with or without chemotherapy.
Results
In the three datasets, the pre-treatment compactness risk model provided good accuracy for predicting OS (P = 0.012, P = 0.022, and P = 0.003) and PFS (P < 0.001, P = 0.003, and P = 0.005). Patients in the low-risk group did not experience a significant OS benefit from concurrent chemoradiotherapy (P = 0.099). Furthermore, after pre-operation concurrent chemoradiotherapy, the OS outcomes were similar among patients in the low-risk group who did and did not achieve a pathological complete response (P = 0.127). Compactness was correlated with clinical T stage but was more accurate for predicting prognosis after treatment for ESCC, based on higher C-index values in all three datasets.
Conclusions
Our compactness-based risk model was effective for predicting OS and PFS after multimodal treatment for ESCC. Therefore, it may be useful for guiding personalized treatment.
Clinical trial identification
Legal entity responsible for the study
Sichuan Cancer Hospital.
Funding
This work was supported by the National Key Projects of Research and Development of China [grant number 2016YFC0904600], the National Natural Science Foundation of China [grant number 81272512], the Capital Clinical Characteristic Application Research of China [grant number Z121107001012004], and the Capital Health Research and Development of Special of China [grant number 2016-2-4021].
Editorial Acknowledgement
Michelle Doctorate/Evolutionary Biology/University of Exeter/Exeter, UK/2008.
Disclosure
All authors have declared no conflicts of interest.