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Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram

BACKGROUND: Robotic pancreaticoduodenectomy (RPD) is a novel type of minimally invasive surgery to treat tumors located at the head of the pancreas. This study aimed to construct a novel prediction model for predicting selection preference for RPD in a Chinese single medical center population. MATER...

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Autores principales: Huo, Zhen, Shi, Zhihao, Zhai, Shuyu, Li, Jingfeng, Qian, Hao, Tang, Xiaomei, Weng, Yuanchi, Shi, Yusheng, Wang, Liwen, Wang, Yue, Deng, Xiaxing, Shen, Baiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827327/
https://www.ncbi.nlm.nih.gov/pubmed/31654999
http://dx.doi.org/10.12659/MSM.917446
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author Huo, Zhen
Shi, Zhihao
Zhai, Shuyu
Li, Jingfeng
Qian, Hao
Tang, Xiaomei
Weng, Yuanchi
Shi, Yusheng
Wang, Liwen
Wang, Yue
Deng, Xiaxing
Shen, Baiyong
author_facet Huo, Zhen
Shi, Zhihao
Zhai, Shuyu
Li, Jingfeng
Qian, Hao
Tang, Xiaomei
Weng, Yuanchi
Shi, Yusheng
Wang, Liwen
Wang, Yue
Deng, Xiaxing
Shen, Baiyong
author_sort Huo, Zhen
collection PubMed
description BACKGROUND: Robotic pancreaticoduodenectomy (RPD) is a novel type of minimally invasive surgery to treat tumors located at the head of the pancreas. This study aimed to construct a novel prediction model for predicting selection preference for RPD in a Chinese single medical center population. MATERIAL/METHODS: The clinical data from 451 pancreatic ductal adenocarcinoma patients were collected and analyzed from January 2013 to December 2016. Twenty-three items affecting clinical strategies were optimized by LASSO (least absolute shrinkage and selection operator) regression analysis and then were incorporated in multivariable logistic regression analysis. C-index was used for evaluating the discriminative ability. Decision curve was applied to determine clinical application of this model and the calibration of this nomogram was evaluated by calibration plot. The model was internally validated through bootstrapping validation. RESULTS: Clinicopathological factors included in the model were age, history of diabetes mellitus, history of hypertension, history of heart, brain and kidney disease, history of abdominal surgery, symptoms (jaundice, accidental discovery and weight loss), anemia, elevated carcinoembryonic antigen (CEA), smoking, alcohol intake, American Society of Anesthesiologists (ASA) scores, vascular invasion, overweight, preoperative lymph node metastasis and tumor size >3.5 cm. A C-index of 0.831 indicated good discrimination and calibration of this model. Interval validation generated an acceptable C-index of 0.787. When surgical approach was determined at the threshold of preference possibility less than 63%, decision curve analysis indicated that this model had good clinical application value in this range. CONCLUSIONS: This new nomogram could be conveniently used to predict the selection preference of robotic surgery for patients with pancreatic head cancer.
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spelling pubmed-68273272019-11-14 Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram Huo, Zhen Shi, Zhihao Zhai, Shuyu Li, Jingfeng Qian, Hao Tang, Xiaomei Weng, Yuanchi Shi, Yusheng Wang, Liwen Wang, Yue Deng, Xiaxing Shen, Baiyong Med Sci Monit Clinical Research BACKGROUND: Robotic pancreaticoduodenectomy (RPD) is a novel type of minimally invasive surgery to treat tumors located at the head of the pancreas. This study aimed to construct a novel prediction model for predicting selection preference for RPD in a Chinese single medical center population. MATERIAL/METHODS: The clinical data from 451 pancreatic ductal adenocarcinoma patients were collected and analyzed from January 2013 to December 2016. Twenty-three items affecting clinical strategies were optimized by LASSO (least absolute shrinkage and selection operator) regression analysis and then were incorporated in multivariable logistic regression analysis. C-index was used for evaluating the discriminative ability. Decision curve was applied to determine clinical application of this model and the calibration of this nomogram was evaluated by calibration plot. The model was internally validated through bootstrapping validation. RESULTS: Clinicopathological factors included in the model were age, history of diabetes mellitus, history of hypertension, history of heart, brain and kidney disease, history of abdominal surgery, symptoms (jaundice, accidental discovery and weight loss), anemia, elevated carcinoembryonic antigen (CEA), smoking, alcohol intake, American Society of Anesthesiologists (ASA) scores, vascular invasion, overweight, preoperative lymph node metastasis and tumor size >3.5 cm. A C-index of 0.831 indicated good discrimination and calibration of this model. Interval validation generated an acceptable C-index of 0.787. When surgical approach was determined at the threshold of preference possibility less than 63%, decision curve analysis indicated that this model had good clinical application value in this range. CONCLUSIONS: This new nomogram could be conveniently used to predict the selection preference of robotic surgery for patients with pancreatic head cancer. International Scientific Literature, Inc. 2019-10-26 /pmc/articles/PMC6827327/ /pubmed/31654999 http://dx.doi.org/10.12659/MSM.917446 Text en © Med Sci Monit, 2019 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Clinical Research
Huo, Zhen
Shi, Zhihao
Zhai, Shuyu
Li, Jingfeng
Qian, Hao
Tang, Xiaomei
Weng, Yuanchi
Shi, Yusheng
Wang, Liwen
Wang, Yue
Deng, Xiaxing
Shen, Baiyong
Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram
title Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram
title_full Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram
title_fullStr Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram
title_full_unstemmed Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram
title_short Predicting Selection Preference of Robotic Pancreaticoduodenectomy (RPD) in a Chinese Single Center Population: Development and Assessment of a New Predictive Nomogram
title_sort predicting selection preference of robotic pancreaticoduodenectomy (rpd) in a chinese single center population: development and assessment of a new predictive nomogram
topic Clinical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827327/
https://www.ncbi.nlm.nih.gov/pubmed/31654999
http://dx.doi.org/10.12659/MSM.917446
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