Journal of gastroenterology and hepatology · 2019
Development and validation of a prognostic nomogram to predict survival in patients with advanced pancreatic cancer receiving second-line palliative chemotherapy.
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Hsu Chih-Chung, Liu Keng-Hao, Chang Pei-Hung, Chen Ping-Tsung, Hung Chia-Yen, Hsueh Shun-Wen, Yeh Kun-Yun, Chen Yen-Yang, Lu Chang-Hsien, Hung Yu-Shin, Chou Wen-Chi
Аннотация
BACKGROUND AND AIM: Given that a wide variation in tumor response rates and survival times suggests heterogeneity among the patients with advanced pancreatic cancer (APC) who underwent second-line (L2) chemotherapy, it is a challenge in clinical practice to identify patients who will receive the most benefit from L2 treatment.
METHODS: We selected 183 APC patients who received L2 palliative chemotherapy between 2010 and 2016 from a medical center as the development cohort. A Cox proportional hazard model was used to identify the prognostic factors and construct the nomogram. An independent cohort of 166 patients from three other hospitals was selected for external validation.
RESULTS: The nomogram was based on eight independent prognostic factors from the multivariate Cox model: sex, Eastern Cooperative Oncology Group performance status, reason for first-line treatment discontinuation, duration of first-line treatment, neutrophil-to-lymphocyte ratio, tumor stage, body mass index, and serum carbohydrate antigen 19-9 levels at the beginning of L2 treatment. The model exhibited good discrimination ability, with a C-index of 0.733 (95% confidence interval, 0.681-0.785) and 0.724 (95% confidence interval, 0.661-0.787) in the development and validation cohorts, respectively. The calibration plots of the development and validation cohorts showed optimal agreement between model prediction and actual observation in predicting survival probability at 6 months, 1 year, and 2 years.
CONCLUSIONS: This study developed and externally validated a prognostic model that accurately predicts the survival outcome of APC patients before L2 palliative chemotherapy, which could assist in clinical decision-making, counseling for treatment, and most importantly, prognostic stratification of patients.
METHODS: We selected 183 APC patients who received L2 palliative chemotherapy between 2010 and 2016 from a medical center as the development cohort. A Cox proportional hazard model was used to identify the prognostic factors and construct the nomogram. An independent cohort of 166 patients from three other hospitals was selected for external validation.
RESULTS: The nomogram was based on eight independent prognostic factors from the multivariate Cox model: sex, Eastern Cooperative Oncology Group performance status, reason for first-line treatment discontinuation, duration of first-line treatment, neutrophil-to-lymphocyte ratio, tumor stage, body mass index, and serum carbohydrate antigen 19-9 levels at the beginning of L2 treatment. The model exhibited good discrimination ability, with a C-index of 0.733 (95% confidence interval, 0.681-0.785) and 0.724 (95% confidence interval, 0.661-0.787) in the development and validation cohorts, respectively. The calibration plots of the development and validation cohorts showed optimal agreement between model prediction and actual observation in predicting survival probability at 6 months, 1 year, and 2 years.
CONCLUSIONS: This study developed and externally validated a prognostic model that accurately predicts the survival outcome of APC patients before L2 palliative chemotherapy, which could assist in clinical decision-making, counseling for treatment, and most importantly, prognostic stratification of patients.