TY - JOUR
T1 - A novel clinically based staging system for gallbladder cancer
AU - Yadav, Siddhartha
AU - Tella, Sri Harsha
AU - Kommalapati, Anuhya
AU - Mara, Kristin
AU - Prasai, Kritika
AU - Mady, Mohamed Hamdy
AU - Hassan, Mohamed
AU - Smoot, Rory L.
AU - Cleary, Sean P.
AU - Truty, Mark J.
AU - Roberts, Lewis R.
AU - Mahipal, Amit
N1 - Publisher Copyright:
© 2020 Harborside Press. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Background: Current staging systems for gallbladder cancer (GBC) are primarily based on surgical pathology and therefore are not relevant for unresectable patients and those undergoing neoadjuvant chemotherapy. Methods: Patients with a confirmed diagnosis of GBC managed at a tertiary referral center (2000–2016) were included. Independent predictors of overall survival (OS) were identified using multivariable analysis (MVA). A combination of these variables was then assessed to identify a set of factors that provided maximal accuracy in predicting OS, and a nomogram and a new staging system were created based on these factors. Harrell’s C-statistic was calculated to evaluate the predictive accuracy of the nomogram and staging system. Results: A total of 528 patients were included in the final analysis. On MVA, factors predictive of poor OS were older age, ECOG performance status, hemoglobin level,9 g/dL, presence of metastases, and alkaline phosphatase (ALP) level .200 U/L. A nomogram and a 4-tier staging system predictive of OS were created using age at diagnosis, ECOG status, tumor size, presence or absence of metastasis, and ALP level. The C-statistic for this novel staging system was 0.71 compared with 0.69 for the TNM staging system (P5.08). In patients who did not undergo surgery, the C-statistics of the novel and TNM staging systems were 0.60 and 0.51, respectively (P,.001). Conclusions: We created a novel, clinically based staging system for GBC based on nonoperative information at the time of diagnosis that was superior to the TNM staging system in predicting OS in patients who did not undergo surgery, and that performed on par with TNM staging in surgical patients.
AB - Background: Current staging systems for gallbladder cancer (GBC) are primarily based on surgical pathology and therefore are not relevant for unresectable patients and those undergoing neoadjuvant chemotherapy. Methods: Patients with a confirmed diagnosis of GBC managed at a tertiary referral center (2000–2016) were included. Independent predictors of overall survival (OS) were identified using multivariable analysis (MVA). A combination of these variables was then assessed to identify a set of factors that provided maximal accuracy in predicting OS, and a nomogram and a new staging system were created based on these factors. Harrell’s C-statistic was calculated to evaluate the predictive accuracy of the nomogram and staging system. Results: A total of 528 patients were included in the final analysis. On MVA, factors predictive of poor OS were older age, ECOG performance status, hemoglobin level,9 g/dL, presence of metastases, and alkaline phosphatase (ALP) level .200 U/L. A nomogram and a 4-tier staging system predictive of OS were created using age at diagnosis, ECOG status, tumor size, presence or absence of metastasis, and ALP level. The C-statistic for this novel staging system was 0.71 compared with 0.69 for the TNM staging system (P5.08). In patients who did not undergo surgery, the C-statistics of the novel and TNM staging systems were 0.60 and 0.51, respectively (P,.001). Conclusions: We created a novel, clinically based staging system for GBC based on nonoperative information at the time of diagnosis that was superior to the TNM staging system in predicting OS in patients who did not undergo surgery, and that performed on par with TNM staging in surgical patients.
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U2 - 10.6004/jnccn.2019.7353
DO - 10.6004/jnccn.2019.7353
M3 - Article
C2 - 32023528
AN - SCOPUS:85079034623
SN - 1540-1405
VL - 18
SP - 151
EP - 159
JO - JNCCN Journal of the National Comprehensive Cancer Network
JF - JNCCN Journal of the National Comprehensive Cancer Network
IS - 2
ER -