Objective: We aimed to evaluate the efficacy of neoadjuvant docetaxel, cisplatin, and 5-fluorouracil (DCF) therapy over cisplatin and 5-fluorouracil (CF) in patients with surgically resectable advanced esophageal squamous cell carcinoma (ESCC), using real-world data from 85 esophageal centers. Background: JCOG1109 trial, which assessed the superiority of DCF over CF, and the superiority of chemoradiotherapy with CF over CF alone demonstrated the significant survival advantage of neoadjuvant DCF in overall survival (OS) over CF for ESCC. Methods: The ESCC patients who received neoadjuvant CF or DCF at 85 Japanese esophageal centers certified by the Japan Esophageal Society were retrospectively reviewed. After propensity score (PS) matching, the OS and recurrence-free survival were compared between CF and DCF. Results: We initially enrolled 4781 patients. After data cleaning and PS matching using pretreatment variables, 1074 patients for each group were selected for subsequent analysis. There was no significant difference in the incidence of postoperative pneumonia and anastomotic leakage. In the survival analysis, OS was significantly longer in DCF group than CF group (hazard ratio, 0.868; 95% confidence interval, 0.770–0.978; P=0.02), as well as recurrence-free survival (hazard ratio, 0.850; 95% confidence interval, 0.761–0.949; P=0.004). The survival advantage of DCF was not observed in patients with 76 years old or older. Conclusions: Neoadjuvant DCF therapy showed a remarkable survival advantage in surgically resectable ESCC patients, especially in patients who were 75 years old or younger. The current real-world evidence will encourage recommendations for DCF as a standard regimen in neoadjuvant chemotherapy–based treatment strategy for ESCC.

Background Although machine learning-based prediction models for in-hospital cardiac arrest (IHCA) have been widely investigated, it is unknown whether a model based on vital signs alone (Vitals-Only model) can perform similarly to a model that considers both vital signs and laboratory results (Vitals+Labs model). Methods All adult patients hospitalized in a tertiary care hospital in Japan between October 2011 and October 2018 were included in this study. Random forest models with/without laboratory results (Vitals+Labs model and Vitals-Only model, respectively) were trained and tested using chronologically divided datasets. Both models use patient demographics and eighthourly vital signs collected within the previous 48 hours. The primary and secondary outcomes were the occurrence of IHCA in the next 8 and 24 hours, respectively. The area under the receiver operating characteristic curve (AUC) was used as a comparative measure. Sensitivity analyses were performed under multiple statistical assumptions. Results Of 141,111 admitted patients (training data: 83,064, test data: 58,047), 338 had an IHCA (training data: 217, test data: 121) during the study period. The Vitals-Only model and Vitals +Labs model performed comparably when predicting IHCA within the next 8 hours (Vitals-Only model vs Vitals+Labs model, AUC = 0.862 [95% confidence interval (CI): 0.855-0.868] vs 0.872 [95% CI: 0.867-0.878]) and 24 hours (Vitals-Only model vs Vitals+Labs model,

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