• Muqing Wang, Xubin Jing, Weihua Cao, Yicheng Zeng, Chaofen Wu, Weilong Zeng, Wenxia Chen, Xi Hu, Yanna Zhou, and Xianbin Cai.
• Department of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, 57 Changping Road, Shantou, Guangdong, 515041, People's Republic of China.
• BMC Palliat Care. 2020 Dec 7; 19 (1): 185.

BackgroundPatients suffering from gastrointestinal cancer comprise a large group receiving home hospice care in China, however, little is known about the prediction of their survival time. This study aimed to develop a gastrointestinal cancer-specific non-lab nomogram predicting survival time in home-based hospice.MethodsWe retrospectively studied the patients with gastrointestinal cancer from a home-based hospice between 2008 and 2018. General baseline characteristics, disease-related characteristics, and related assessment scale scores were collected from the case records. The data were randomly split into a training set (75%) for developing a predictive nomogram and a testing set (25%) for validation. A non-lab nomogram predicting the 30-day and 60-day survival probability was created using the least absolute shrinkage and selection operator (LASSO) Cox regression. We evaluated the performance of our predictive model by means of the area under receiver operating characteristic curve (AUC) and calibration curve.ResultsA total of 1618 patients were included and divided into two sets: 1214 patients (110 censored) as training dataset and 404 patients (33 censored) as testing dataset. The median survival time for overall included patients was 35 days (IQR, 17-66). The 5 most significant prognostic variables were identified to construct the nomogram among all 28 initial variables, including Karnofsky Performance Status (KPS), abdominal distention, edema, quality of life (QOL), and duration of pain. In training dataset validation, the AUC at 30 days and 60 days were 0.723 (95% CI, 0.694-0.753) and 0.733 (95% CI, 0.702-0.763), respectively. Similarly, the AUC value was 0.724 (0.673-0.774) at 30 days and 0.725 (0.672-0.778) at 60 days in the testing dataset validation. Further, the calibration curves revealed good agreement between the nomogram predictions and actual observations in both the training and testing dataset.ConclusionThis non-lab nomogram may be a useful clinical tool. It needs prospective multicenter validation as well as testing with Chinese clinicians in charge of hospice patients with gastrointestinal cancer to assess acceptability and usability.

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