Diamantis I Tsilimigras1, Kota Sahara1, Anghela Z Paredes1, Amika Moro1, Rittal Mehta1, Dimitrios Moris1, Alfredo Guglielmi2, Luca Aldrighetti3, Matthew Weiss4, Todd W Bauer5, Sorin Alexandrescu6, George A Poultsides7, Shishir K Maithel8, Hugo P Marques9, Guillaume Martel10, Carlo Pulitano11, Feng Shen12, Olivier Soubrane13, Bas Groot Koerkamp14, Itaru Endo15, Timothy M Pawlik16. 1. Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA. 2. Department of Surgery, University of Verona, Verona, Italy. 3. Department of Surgery, Ospedale San Raffaele, Milano, Italy. 4. Department of Surgery, Johns Hopkins Hospital, Baltimore, MD, USA. 5. Department of Surgery, University of Virginia, Charlottesville, VA, USA. 6. Department of Surgery, Fundeni Clinical Institute, Bucharest, Romania. 7. Department of Surgery, Stanford University, Stanford, CA, USA. 8. Department of Surgery, Emory University, Atlanta, GA, USA. 9. Department of Surgery, Curry Cabral Hospital, Lisbon, Portugal. 10. Department of Surgery, University of Ottawa, Ottawa, Canada. 11. Department of Surgery, Royal Prince Alfred Hospital, University of Sydney, Sydney, Australia. 12. Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China. 13. Department of Hepatobiliopancreatic Surgery and Liver Transplantation, AP-HP, Beaujon Hospital, Clichy, France. 14. Department of Surgery, Erasmus University Medical Centre, Rotterdam, Netherlands. 15. Department of Gastroenterological Surgery, Yokohama City University School of Medicine, Yokohama, Japan. 16. Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA. tim.pawlik@osumc.edu.
Abstract
BACKGROUND: The objective of the current study was to develop a model to predict the likelihood of occult lymph node metastasis (LNM) prior to resection of intrahepatic cholangiocarcinoma (ICC). METHODS: Patients who underwent hepatectomy for ICC between 2000 and 2017 were identified using a multi-institutional database. A novel model incorporating clinical and preoperative imaging data was developed to predict LNM. RESULTS: Among 980 patients who underwent resection of ICC, 190 (19.4%) individuals had at least one LNM identified on final pathology. An enhanced imaging model incorporating clinical and imaging data was developed to predict LNM ( https://k-sahara.shinyapps.io/ICC_imaging/ ). The performance of the enhanced imaging model was very good in the training data set (c-index 0.702), as well as the validation data set with bootstrapping resamples (c-index 0.701) and outperformed the preoperative imaging alone (c-index 0.660). The novel model predicted both 5-year overall survival (OS) (low risk 48.4% vs. high risk 18.4%) and 5-year disease-specific survival (DSS) (low risk 51.9% vs. high risk 25.2%, both p < 0.001). When applied among Nx patients, 5-year OS and DSS of low-risk Nx patients was comparable with that of N0 patients, while high-risk Nx patients had similar outcomes to N1 patients (p > 0.05). CONCLUSION: This tool may represent an opportunity to stratify prognosis of Nx patients and can help inform clinical decision-making prior to resection of ICC.
BACKGROUND: The objective of the current study was to develop a model to predict the likelihood of occult lymph node metastasis (LNM) prior to resection of intrahepatic cholangiocarcinoma (ICC). METHODS:Patients who underwent hepatectomy for ICC between 2000 and 2017 were identified using a multi-institutional database. A novel model incorporating clinical and preoperative imaging data was developed to predict LNM. RESULTS: Among 980 patients who underwent resection of ICC, 190 (19.4%) individuals had at least one LNM identified on final pathology. An enhanced imaging model incorporating clinical and imaging data was developed to predict LNM ( https://k-sahara.shinyapps.io/ICC_imaging/ ). The performance of the enhanced imaging model was very good in the training data set (c-index 0.702), as well as the validation data set with bootstrapping resamples (c-index 0.701) and outperformed the preoperative imaging alone (c-index 0.660). The novel model predicted both 5-year overall survival (OS) (low risk 48.4% vs. high risk 18.4%) and 5-year disease-specific survival (DSS) (low risk 51.9% vs. high risk 25.2%, both p < 0.001). When applied among Nx patients, 5-year OS and DSS of low-risk Nx patients was comparable with that of N0 patients, while high-risk Nx patients had similar outcomes to N1 patients (p > 0.05). CONCLUSION: This tool may represent an opportunity to stratify prognosis of Nx patients and can help inform clinical decision-making prior to resection of ICC.
Authors: Joshua S Jolissaint; Kevin C Soares; Kenneth P Seier; Ritika Kundra; Mithat Gönen; Paul J Shin; Thomas Boerner; Carlie Sigel; Ramyasree Madupuri; Efsevia Vakiani; Andrea Cercek; James J Harding; Nancy E Kemeny; Louise C Connell; Vinod P Balachandran; Michael I D'Angelica; Jeffrey A Drebin; T Peter Kingham; Alice C Wei; William R Jarnagin Journal: Clin Cancer Res Date: 2021-05-07 Impact factor: 12.531
Authors: Tin May Aung; Mang Ngaih Ciin; Atit Silsirivanit; Apinya Jusakul; Worachart Lert-Itthiporn; Tanakorn Proungvitaya; Sittiruk Roytrakul; Siriporn Proungvitaya Journal: Front Public Health Date: 2022-03-22