Diamantis I Tsilimigras1, Kota Sahara1,2, Lu Wu1,3, Dimitrios Moris1, Fabio Bagante4, Alfredo Guglielmi4, Luca Aldrighetti5, Matthew Weiss6, Todd W Bauer7, Sorin Alexandrescu8, George A Poultsides9, Shishir K Maithel10, Hugo P Marques11, Guillaume Martel12, Carlo Pulitano13, Feng Shen3, Olivier Soubrane14, B Groot Koerkamp15, Amika Moro1,16, Kazunari Sasaki16, Federico Aucejo16, Xu-Feng Zhang17, Ryusei Matsuyama2, Itaru Endo2, Timothy M Pawlik1,18. 1. James Comprehensive Cancer Center, Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus. 2. Department of Gastroenterological Surgery, Yokohama City University School of Medicine, Yokohama, Japan. 3. Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China. 4. Department of Surgery, University of Verona, Verona, Italy. 5. Department of Surgery, Ospedale San Raffaele, Milano, Italy. 6. Department of Surgery, Johns Hopkins Hospital, Baltimore, Maryland. 7. Department of Surgery, University of Virginia, Charlottesville. 8. Department of Surgery, Fundeni Clinical Institute, Bucharest, Romania. 9. Department of Surgery, Stanford University, Stanford, California. 10. Department of Surgery, Emory University, Atlanta, Georgia. 11. Department of Surgery, Curry Cabral Hospital, Lisbon, Portugal. 12. Department of Surgery, University of Ottawa, Ottawa, Canada. 13. Department of Surgery, Royal Prince Alfred Hospital, University of Sydney, Sydney, Australia. 14. Department of Hepatobiliopancreatic Surgery and Liver Transplantation, AP-HP, Beaujon Hospital, Clichy, France. 15. Department of Surgery, Erasmus University Medical Centre, Rotterdam, the Netherlands. 16. Digestive Disease and Surgery Institute, Department of General Surgery, Cleveland Clinic, Cleveland, Ohio. 17. Institute of Advanced Surgical Technology and Engineering, Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China. 18. Deputy Editor, JAMA Surgery .
Abstract
Importance: Although surgery offers the best chance of a potential cure for patients with localized, resectable intrahepatic cholangiocarcinoma (ICC), prognosis of patients remains dismal largely because of a high incidence of recurrence. Objective: To predict very early recurrence (VER) (ie, recurrence within 6 months after surgery) following resection for ICC in the pre- and postoperative setting. Design, Setting, and Participants: Patients who underwent curative-intent resection for ICC between May 1990 and July 2016 were identified from an international multi-institutional database. The study was conducted at The Ohio State University in collaboration with all other participating institutions. The data were analyzed in December 2019. Main Outcomes and Measures: Two logistic regression models were constructed to predict VER based on pre- and postoperative variables. The final models were used to develop an online calculator to predict VER and the tool was internally and externally validated. Results: Among 880 patients (median age, 59 years [interquartile range, 51-68 years]; 388 women [44.1%]; 428 [50.2%] white; 377 [44.3%] Asian; 27 [3.2%] black]), 196 (22.3%) developed VER. The 5-year overall survival among patients with and without VER was 8.9% vs 49.8%, respectively (P < .001). A preoperative model was able to stratify patients relative to the risk for VER: low risk (6-month recurrence-free survival [RFS], 87.7%), intermediate risk (6-month RFS, 72.3%), and high risk (6-month RFS, 49.5%) (log-rank P < .001). The postoperative model similarly identified discrete cohorts of patients based on probability for VER: low risk (6-month RFS, 90.0%), intermediate risk (6-month RFS, 73.1%), and high risk (6-month RFS, 48.5%) (log-rank, P < .001). The calibration and predictive accuracy of the pre- and postoperative models were good in the training (C index: preoperative, 0.710; postoperative, 0.722) as well as the internal (C index: preoperative, 0.715; postoperative, 0.728; bootstrapping resamples, n = 5000) and external (C index: postoperative, 0.672) validation data sets. Conclusion and Relevance: An easy-to-use online calculator was developed to help clinicians predict the chance of VER after curative-intent resection for ICC. The tool performed well on internal and external validation. This tool may help clinicians in the preoperative selection of patients for neoadjuvant therapy as well as during the postoperative period to inform surveillance strategies.
Importance: Although surgery offers the best chance of a potential cure for patients with localized, resectable intrahepatic cholangiocarcinoma (ICC), prognosis of patients remains dismal largely because of a high incidence of recurrence. Objective: To predict very early recurrence (VER) (ie, recurrence within 6 months after surgery) following resection for ICC in the pre- and postoperative setting. Design, Setting, and Participants: Patients who underwent curative-intent resection for ICC between May 1990 and July 2016 were identified from an international multi-institutional database. The study was conducted at The Ohio State University in collaboration with all other participating institutions. The data were analyzed in December 2019. Main Outcomes and Measures: Two logistic regression models were constructed to predict VER based on pre- and postoperative variables. The final models were used to develop an online calculator to predict VER and the tool was internally and externally validated. Results: Among 880 patients (median age, 59 years [interquartile range, 51-68 years]; 388 women [44.1%]; 428 [50.2%] white; 377 [44.3%] Asian; 27 [3.2%] black]), 196 (22.3%) developed VER. The 5-year overall survival among patients with and without VER was 8.9% vs 49.8%, respectively (P < .001). A preoperative model was able to stratify patients relative to the risk for VER: low risk (6-month recurrence-free survival [RFS], 87.7%), intermediate risk (6-month RFS, 72.3%), and high risk (6-month RFS, 49.5%) (log-rank P < .001). The postoperative model similarly identified discrete cohorts of patients based on probability for VER: low risk (6-month RFS, 90.0%), intermediate risk (6-month RFS, 73.1%), and high risk (6-month RFS, 48.5%) (log-rank, P < .001). The calibration and predictive accuracy of the pre- and postoperative models were good in the training (C index: preoperative, 0.710; postoperative, 0.722) as well as the internal (C index: preoperative, 0.715; postoperative, 0.728; bootstrapping resamples, n = 5000) and external (C index: postoperative, 0.672) validation data sets. Conclusion and Relevance: An easy-to-use online calculator was developed to help clinicians predict the chance of VER after curative-intent resection for ICC. The tool performed well on internal and external validation. This tool may help clinicians in the preoperative selection of patients for neoadjuvant therapy as well as during the postoperative period to inform surveillance strategies.
Authors: Liang-Shuo Hu; Xu-Feng Zhang; Matthew Weiss; Irinel Popescu; Hugo P Marques; Luca Aldrighetti; Shishir K Maithel; Carlo Pulitano; Todd W Bauer; Feng Shen; George A Poultsides; Oliver Soubrane; Guillaume Martel; B Groot Koerkamp; Endo Itaru; Timothy M Pawlik Journal: Ann Surg Oncol Date: 2019-04-24 Impact factor: 5.344
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Authors: Kota Sahara; Diamantis I Tsilimigras; Yutaro Kikuchi; Cecilia G Ethun; Shishir K Maithel; Daniel E Abbott; George A Poultsides; Ioannis Hatzaras; Ryan C Fields; Matthew Weiss; Charles Scoggins; Chelsea A Isom; Kamran Idrees; Perry Shen; Yasuhiro Yabushita; Ryusei Matsuyama; Itaru Endo; Timothy M Pawlik Journal: Ann Surg Oncol Date: 2020-09-05 Impact factor: 5.344