J Cancer 2017; 8(14):2765-2773. doi:10.7150/jca.19515 This issue Cite

Research Paper

Refining the American Joint Committee on Cancer Staging Scheme For Resectable Pancreatic Ductal Adenocarcinoma Using Recursive Partitioning Analysis

Yiquan Jiang1*, Yanhong Su2*, Yutong Chen2*, Zhiyong Li3✉

1. Department of Hepatobiliary and Pancreatic Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China;
2. Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China;
3. Department of Urology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China.
* These authors contributed equally as first authors.

Citation:
Jiang Y, Su Y, Chen Y, Li Z. Refining the American Joint Committee on Cancer Staging Scheme For Resectable Pancreatic Ductal Adenocarcinoma Using Recursive Partitioning Analysis. J Cancer 2017; 8(14):2765-2773. doi:10.7150/jca.19515. https://www.jcancer.org/v08p2765.htm
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Abstract

Purpose: It remains unclear whether the recently proposed 8th edition of the American Joint Committee on Cancer (AJCC) staging scheme for pancreatic ductal adenocarcinoma (PDAC) outperforms the 7th edition. We assessed the prognostic performance of both these schemes and performed recursive partitioning analysis (RPA) to objectively regroup the 7th and 8th AJCC stages and derive a refined staging scheme.

Methods: We examined 8542 patients with resectable PDAC from the 2004-2012 Surveillance, Epidemiology, and End Results database. The dataset was randomly divided into training and validation sets. The performance of different staging schemes was evaluated in terms of prognostic stratification, discriminatory ability, and prognostic homogeneity.

Results: The 7th and 8th T classifications showed prominent heterogeneity within each subcategory when assessed against each other in the case of node-negative disease. RPA divided resectable PDAC into RPA-IA (8th T1N0 limited to the pancreas), RPA-IB (8th T1N0 extending beyond the pancreas, or 8th T2-T3N0 limited to the pancreas), RPA-IIA (8th T2N0 extending beyond the pancreas, or 8th T1N1-N2), RPA-IIB (8th T3N0 extending beyond the pancreas, or 8th T2-T3N1), and RPA-III stages (8th T2-T3N2) (median survival in the training set: 47, 28, 20, 16, and 14 months, respectively; P < 0.001). The RPA staging scheme outperformed the 7th and 8th AJCC classifications in terms of prognostic stratification, discriminatory ability, and prognostic homogeneity for both the training and validation sets.

Conclusions: The proposed RPA staging is a superior risk-stratified tool to the 7th and 8th AJCC classifications and is not substantially more complex.

Keywords: pancreatic ductal adenocarcinoma (PDAC), American Joint Committee on Cancer staging (AJCC), Surveillance, Epidemiology, and End Results (SEER), staging, survival.


Citation styles

APA
Jiang, Y., Su, Y., Chen, Y., Li, Z. (2017). Refining the American Joint Committee on Cancer Staging Scheme For Resectable Pancreatic Ductal Adenocarcinoma Using Recursive Partitioning Analysis. Journal of Cancer, 8(14), 2765-2773. https://doi.org/10.7150/jca.19515.

ACS
Jiang, Y.; Su, Y.; Chen, Y.; Li, Z. Refining the American Joint Committee on Cancer Staging Scheme For Resectable Pancreatic Ductal Adenocarcinoma Using Recursive Partitioning Analysis. J. Cancer 2017, 8 (14), 2765-2773. DOI: 10.7150/jca.19515.

NLM
Jiang Y, Su Y, Chen Y, Li Z. Refining the American Joint Committee on Cancer Staging Scheme For Resectable Pancreatic Ductal Adenocarcinoma Using Recursive Partitioning Analysis. J Cancer 2017; 8(14):2765-2773. doi:10.7150/jca.19515. https://www.jcancer.org/v08p2765.htm

CSE
Jiang Y, Su Y, Chen Y, Li Z. 2017. Refining the American Joint Committee on Cancer Staging Scheme For Resectable Pancreatic Ductal Adenocarcinoma Using Recursive Partitioning Analysis. J Cancer. 8(14):2765-2773.

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