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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 Jiang^1*, Yanhong Su^2*, Yutong Chen^2*, 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.

✉ Corresponding author: Zhiyong Li, 651 Dong Feng Road East, Guangzhou 510060, China; Tel and Fax: +86-20-8734 3088; E-mail: lizhiyorg.cn.

Abstract

Purpose: It remains unclear whether the recently proposed 8^th edition of the American Joint Committee on Cancer (AJCC) staging scheme for pancreatic ductal adenocarcinoma (PDAC) outperforms the 7^th edition. We assessed the prognostic performance of both these schemes and performed recursive partitioning analysis (RPA) to objectively regroup the 7^th and 8^th 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 7^th and 8^th 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 (8^th T1N0 limited to the pancreas), RPA-IB (8^th T1N0 extending beyond the pancreas, or 8^th T2-T3N0 limited to the pancreas), RPA-IIA (8^th T2N0 extending beyond the pancreas, or 8^th T1N1-N2), RPA-IIB (8^th T3N0 extending beyond the pancreas, or 8^th T2-T3N1), and RPA-III stages (8^th 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 7^th and 8^th 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 7^th and 8^th 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.

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is the fifteenth most common malignancy and is the seventh most common cause of cancer-related deaths worldwide [1]. Radical resection is the only curative option, but patients with resectable PDAC have a high risk of postsurgical recurrence and a poor overall prognosis [2].

In the 7^th edition of the American Joint Committee on Cancer (AJCC) staging scheme [3], extrapancreatic extension is considered a more important prognostic factor than tumor size because resectable PDAC with extrapancreatic extension is categorized as T3 regardless of tumor size. Additionally, patients with nodal metastasis are assigned to a single prognostic group—the N1 classification—regardless of the positive lymph node count [3].

Several studies have questioned the clinical relevance and reproducibility of the 7^th AJCC staging for patients with PDAC, especially the 7^th T3 classification which requires the identification of extrapancreatic extension [4]. In the recently proposed 8^th AJCC staging scheme [5], the definitions of T classifications for resectable PDAC were solely based on tumor size (T1, T2, and T3: ≤2 cm, >2 cm and ≤4 cm, and >4 cm, respectively), while the 7^th AJCC N1 classification was further stratified according to the positive lymph node count (N1: 1-3 positive nodes; N2: ≥4 positive nodes). However, in a recent US multi-institutional study, even though the reproducibility of the 8^th AJCC T classification system was found to be superior to that of the 7^th AJCC T classification system, the discriminatory power of the 7^th and 8^th AJCC schemes were still comparable[5].

In the present study, we first assessed the prognostic performance of the 7^th and 8^th AJCC classifications using a large population-based cohort of patients with resectable PDAC. Thereafter, we developed a refined staging scheme through objective regrouping of the 7^th and 8^th T classifications and the 8^th N classifications by using recursive partitioning analysis (RPA).

Methods

Study cohort

Using the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database (18 registries), we included 17379 patients with PDAC (NAACCR Item #400 [primary tumor site], codes: C25.0-C25.4; NAACCR Item #552 [histologic type], codes: 8140, 8150, 8210, 8211, 8251, 8260, 8261, 8263, 8480, 8481, 8490, 8500, and 8503) from January 2004 to December 2012. Exclusion criteria are as following: concurrent or with a history of prior malignancy, locally unresectable tumor (T4 classification), distant metastasis, tumor in situ, and missing information regarding tumor size, 6^th AJCC T and M classifications, and the number of positive nodes. The final study cohort comprised 8542 patients. PDAC in all cases was restaged on the basis of the 7^th and 8^th AJCC staging schemes.

Statistical analysis

Overall survival (OS) was the primary outcome of interest. Stratified survival analyses with the Kaplan-Meier method and log-rank tests were used to evaluate the prognostic impact of the 7^th T classification within each of the 8^th T classifications and the prognostic impact of the 8^th T classification within each of the 7^th T classifications. Multivariate Cox regression was used to examine the association between the 7^th and 8^th T classifications and hazard ratios (HRs) for death after adjustment for the clinicopathologic factors. Additionally, the capacity of the 7^th and 8^th T classification systems to distinguish patients at low and high risk of death was quantified using the concordance index (C-index) [6]. The value of the C-index ranges from 0.5 to 1.0, with 0.5 indicating a random chance and 1.0 indicating a perfect ability to correctly determine the outcome. Thus, the higher the C-index, the greater is the discriminatory capacity of the scheme.

Two-thirds of the patients in the study cohort were randomly assigned to a training set (n = 5710) and the remaining one-third were assigned to a validation set (n = 2832) to develop and validate a refined staging system which combined the prognostic information of the 7^th and 8^th T classifications together with the 8^th N classifications using RPA. RPA can divide patients at each step into two groups based on the covariate that provided maximum separation with respect to prognosis and accounted for interactions between factors [7, 8].

In both the training and validation sets, the performance of the RPA staging scheme was compared with the 7^th and 8^th AJCC staging schemes in terms of prognostic stratification, discriminatory ability, and prognostic homogeneity. Prognostic stratification was assessed using stratified survival analyses, which evaluated the prognostic effect of a staging scheme within each substage of the other staging scheme. The discriminatory abilities of the three staging schemes were quantified using the C-index and Akaike's information criterion (AIC) [9]. The higher the C-index or the lower the AIC value, the greater was the discriminatory ability of the staging scheme. The likelihood ratio χ² test was used to measure the prognostic homogeneity of the staging schemes [10]. The higher the likelihood ratio χ² value, the greater was the prognostic homogeneity of the staging scheme.

Statistical significance was set at P <0.05 in a two-tailed test. Statistical analyses were performed using SAS v. 9.3 (SAS Institute, Cary, NC, USA), IBM SPSS Statistics for Windows v. 19.0 (IBM Corp., Armonk, NY, USA), and R v. 3.3.1 (http://www.r-project.org). The authenticity of this article has been validated by uploading the key raw data onto the Research Data Deposit public platform (www.researchdata.org.cn), with the approval RDD number as RDDA2017000221.

Results

Table 1 summarizes the characteristics of the study cohort (8542 cases). Most patients were diagnosed as having tumor extending beyond the pancreas (79.3%) and tumor with the greatest dimension >2cm and ≤4cm (59.3%). Most patients had lymph node metastasis (64.3%), and the median positive and examined lymph node counts were 1 (interquartile range [IQR]: 0-3) and 13 (IQR: 7-19), respectively. The median survival period was 18 months.

Survival by T classification of the 7^th and 8^th AJCC schemes is presented in Figure 1A and 1B, respectively. In both systems, each T classification represented a distinct prognosis. After adjustment for race, year of diagnosis, age, sex, marital status, SEER region tumor site, tumor grade, and examined node count, higher 7^th and 8^th T classifications were associated with an increased risk of death (7^th edition: T2 vs. T1: HR, 1.49; P <0.001; T3 vs. T1: HR, 1.79; P <0.001; 8^th edition: T2 vs. T1: HR, 1.37; P <0.001; T3 vs. T1: HR, 1.61; P <0.001). Significant heterogeneity in median survival was identified in patients within the 7^th T3 classification when stratified by the 8^th T classification, and among patients within each of the 8^th T classifications when stratified by the 7^th T classification (Table 2). For patients with 7^th T3N0 disease, the OS differed significantly between the 8^th T1, T2, and T3 classifications (median survival: 26, 20, and 16 months, respectively; P <0.001); within each 8^th T classification, the OS was significantly different between patients with and without tumor extending beyond the pancreas (P <0.01, P <0.001, and P <0.01 in the 8^th T1, T2, and T3 classifications, respectively). Of note, within the 8^th T1N0 classification, a 21-month difference in median survival was found between patients with 7^th T1 and T3 disease (Table 2). Moreover, the 7^th and 8^th T classification systems exhibited similar discriminatory capacity among patients with node-negative disease (C-indices: 0.558 vs. 0.556, P =0.42).

We further assessed the consistency of predicted OS among patients with node-negative tumor extending beyond the pancreas across different SEER regions. We found that survival was homogeneous when stratified by SEER region in these patients (P =0.14; Figure 1C).

Patient and tumor characteristics were comparable among the training set and the validation set (Table 3). The RPA algorithm classified the patients in the training set into the following five groups (Figure 2): RPA-IA (8^th T1N0 limited to the pancreas), RPA-IB (8^th T1N0 extending beyond the pancreas or 8^th T2-T3N0 limited to the pancreas), RPA-IIA (8^th T2N0 extending beyond the pancreas or 8^th T1N1-N2), RPA-IIB (8^th T3N0 extending beyond the pancreas or 8^th T2-T3N1), and RPA-III (8^th T2-T3N2). The RPA-IA, RPA-IB, RPA-IIA, RPA-IIB, and RPA-III stage groups included 226 (4.0%), 646 (11.3%), 1310 (22.9%), 2412 (42.2%), and 1116 (19.5%) of the patients in the training set, respectively. The corresponding median survival was 47, 28, 20, 16, and 14 months, respectively (P <0.001; Figure 3A). A higher RPA stage was associated with an increased risk of death after adjusted for clinicopathologic factors (RPA-IB vs. RPA-IA: HR, 1.40; P <0.01; RPA-IIA vs. RPA-IA: HR, 2.04; P <0.001; RPA-IIB vs. RPA-IA: HR, 2.73; P <0.001; RPA-III vs. RPA-IA: HR, 3.30; P <0.001).

 Figure 1 

Overall survival for the study cohort comprising 8564 patients with resectable pancreatic ductal adenocarcinoma. (A) Overall survival of patients with node-negative disease stratified by the 7^th AJCC T classification system. (B) Overall survival of patients with node-negative disease stratified by the 8^th AJCC T classification system. (C) Overall survival of patients with 7^th T3N0 disease stratified by SEER region.

As shown in Figure 3B and 3C, each 7^th AJCC and 8^th AJCC stage represented a distinct prognosis in the training set. Using RPA staging, patients with each 8^th AJCC stage of disease and 7^th stage IIA and IIB disease could be further stratified into subgroups with remarkably different OS rates; in contrast, OS was homogeneous when the patients with each RPA stage of disease were re-stratified by the 7^th or 8^th AJCC systems (Table 4). Of note, patients with 8^th stage IA disease (median survival: 36 months) could be further stratified into RPA-IIA and RPA-IA subgroups depending on the presence or absence of extrapancreatic extension, and a 21-month difference in median survival was found between patients classified as having RPA-IA and those classified as having RPA-IIA disease (47 vs. 26 months, P <0.01). Additionally, patients with 8^th T3N0 tumors extending beyond the pancreas and 8^th T2-T3N1 tumors, who were classified into 8^th stage IIA and IIB groups, respectively, actually had similar survival (median survival: 16 months for both; P =0.43) and were both re-classified into RPA-IIB according to the RPA staging system. The findings in stratified analyses were consistent when applied to the validation set (Table 5).

Table 6 lists the parameters used to measure the discriminatory ability and prognostic homogeneity of the RPA staging and the 7^th and 8^th AJCC staging schemes. For both the training and validation sets, the RPA staging system showed significantly greater discriminatory power than the 7^th and 8^th AJCC staging systems (training set: C-indices, 0.574 vs. 0.559; P <0.001; validation set: C-indices, 0.575 vs. 0.558; P <0.01) and the 8^th AJCC staging system (training set: C-indices, 0.574 vs. 0.564; P =0.03; validation set: C-indices, 0.575 vs. 0.562; P =0.04). The RPA staging scheme also outperformed the 7^th and 8^th AJCC staging schemes in terms of the AIC and the likelihood ratio χ² value in both the training and validation sets.

Discussion

The recently proposed 8^th AJCC staging scheme [5] has notable modifications in the T and N classifications compared to the 7^th staging scheme. Tumor size was the only factor considered to determine the 8^th T classification for resectable PDAC regardless of the involvement of peripancreatic soft tissue, whereas node-positive disease was further classified into N1 (1-3 positive nodes) and N2 classification (≥4 positive nodes) in the 8^th staging.

In the present study of patients with resectable PDAC from the SEER database, we first compared the performance of the 7^th and 8^th AJCC T classifications using stratified survival analyses. For patients with N0 disease, both the 7^th and 8^th AJCC T classification systems showed significant heterogeneity in survival when assessed against each other, suggesting that there is scope to improve both these schemes. Therefore, we performed RPA to develop a new staging scheme for resectable PDAC that incorporated the 7^th and 8^th T classifications along with the 8^th N classifications.

RPA is a kind of nonparametric multivariable analysis that can repeatedly dichotomize the study population into smaller and smaller subsets [7]. The process of binary stratification is repeated based on covariates that maximize the change in an index of diversity, which accounts for prior probabilities and penalties for misclassification [11, 12]. Additionally, RPA is able to identify synergistic interactions among covariates [11]. Moreover, Kattan et al. reported that the RPA-based model exhibited a superior predictive accuracy to the traditional Cox proportional hazards regression model [13].

RPA has been widely used in other malignancies [14-17]. One of the most common applications and advantages is that it is able to objectively and intuitively generate several risk-groups for a desired endpoint. For instance, Huang et al. performed RPA to regroup the current AJCC T and N classifications and proposed a RPA staging system for human papilloma virus (HPV)-related cancer [16]. Compared with the current AJCC staging for oropharyngeal cancer, the RPA staging significantly improved survival prediction for patients with HPV-related oropharyngeal cancer, without increasing complexity [16]. Another common application and advantage of RPA is that it is capable of identifying optimal cutoff values for continuous covariates of interests. For instance, by using RPA among patients with chronic lymphocytic leukemia, Cui et al. defined a threshold for ROR1 surface expression that could categorize the cohort into ROR1-High vs. ROR1-Low subgroups with significantly different survival outcomes [15].

 Figure 2 

Refined stage grouping for resectable PDAC on the basis of RPA. MS, median survival.

 Figure 3 

Overall survival of patients with resectable pancreatic ductal adenocarcinoma from the training set. (A) Overall survival of patients stratified by RPA stage. (B) Overall survival of patients stratified by the 7^th AJCC stage. (C) Overall survival of the patients stratified by the 8^th AJCC stage.

For the training set, the RPA staging scheme outperformed the 7^th and 8^th AJCC staging schemes in terms of discriminatory power and in stratified survival analyses. Even though the RPA staging was only slightly better in terms of discrimination, it was considerably superior to the 7^th and 8^th AJCC schemes in stratified survival analyses. With the additional ability to distinguish survival between patients with PDAC of diameter ≤4 cm and those with PDAC of diameter >4 cm, the RPA staging scheme was able to further stratify patients within the 7^th stage IIA and IIB group into different risk groups. Additionally, it is noteworthy that each 8^th AJCC stage group could be classified by the RPA system into subgroups with remarkably different OS rates. For example, the 8^th stage IA disease (8^th T1N0) was further stratified into RPA-IIA and RPA-IA disease depending on the presence or absence of extrapancreatic extension, and the difference in median survival between patients in these two groups exceeded 20 months. In contrast, OS was homogeneous within each RPA stage regardless of the 7^th and 8^th AJCC staging. For example, 8^th T3N0 tumors extending beyond the pancreas and 8^th T2-T3N1 tumors, which were classified into different prognostic subgroups on the basis of the 8^th AJCC staging (8^th stage IIA and IIB, respectively), actually had similar survival and were both classified into RPA-IIB. The results of the likelihood ratio χ² tests also support the findings from stratified survival analyses. Moreover, the predictive superiority of the RPA staging scheme was further verified using the validation set, which indicates minimal evidence of model overfit and the potential generalizability of the RPA staging scheme.

Currently, adjuvant chemotherapy followed by curative surgery is a standard treatment for PDAC [18, 19]. However, the OS benefits of adjuvant chemotherapy are modest (difference in median OS: <5 months) in view of the results of the CONKO-001[20] and ESPAC-1 trials [21]. In this context, the RPA staging scheme will be clinically useful for treatment planning for the decision-making regarding adjuvant chemotherapy, which may help improve survival in selected patients and avoid overtreatment in others.

Prognostic nomograms that combine various prognostic factors, such as the one created by the Memorial Sloan-Kettering Cancer Center, have been proposed to refine survival prediction among patients with PDAC [22]. However, nomograms have not been widely used by patients and clinicians, probably due to their cumbersome nature and inherent complexities. In contrast, the proposed RPA staging scheme is based on the objective regrouping of the existing 7^th and 8^th AJCC stages, which are simple and widely accepted. Thus, it is important to note that the proposed RPA staging not only has a favorable prognostic performance but also is a convenient tool for treatment-related decision-making.

Previous studies investigating the prognostic impact of extrapancreatic extension have shown inconsistent findings [5, 22-28]. One possible explanation for this may be differences in the clinicopathologic characteristics of the included cases. Most studies that failed to detect a significant correlation between extrapancreatic extension and survival included patients with T4 disease [22, 23, 25, 28], which was regarded as unresectable, while all three studies that reported a negative correlation between extrapancreatic extension and survival excluded patients with T4 disease [5, 24, 27]. In the present study after excluding patients with T4 disease, we also identified prominent differences in survival between patients with and without tumor extending beyond the pancreas across all the 8^th T classifications.

The reproducibility of detecting extrapancreatic extension is a challenge for pathologists, because of the histologic complexity of the pancreas, including its lack of encapsulation and its complicated invaginations into peripancreatic soft tissue [4]. Allen et al. [5] reported that patients from different institutions classified as having 7^th T3N0 disease showed varying survival rates. However, in the present study of patients from the SEER database, survival rates were uniform among patients with 7^th T3N0 disease across different SEER regions. Although further studies to investigate the reproducibility of pathologic evaluation of extrapancreatic extension are necessary, our finding does support the stability of the 7^th AJCC T3 classification for prognosis in the general population.

The present study has some limitations. First, the measurement of tumor size was partially dependent on the percentage of tumor mesenchyme and the experience of the pathologist and may not always be accurate. Additionally, several important patient-level data were not available in the SEER data. For instance, because information regarding adjuvant chemotherapy was not reported, we could not evaluate how the proposed RPA staging may influence patient selection for adjuvant chemotherapy. Finally, this study was US-centric and patient cohorts from other countries are required to validate the RPA staging scheme.

In summary, we demonstrated that the prognostic accuracy of both the 7^th and 8^th AJCC T classification schemes needed improvement. Thus, we used population-based data and RPA to develop and validate a refined staging scheme for patients with resectable PDAC. The RPA staging system outperformed the 7^th and 8^th AJCC classification systems but was not substantially more complex. We expect that this newly proposed staging system will aid in decision-making regarding treatment and surveillance, as well as risk stratification in future prospective trials for patients with resectable PDAC.

Abbreviation

PDAC: Pancreatic ductal adenocarcinoma; AJCC: American Joint Committee on Cancer; RPA: recursive partitioning analysis; SEER: Surveillance, Epidemiology, and End Results; OS: Overall survival; HR: hazard ratio; C-index: concordance index; AIC: Akaike's information criterion; HPV: human papilloma virus.

Acknowledgements

We thank the staff members of the National Cancer Institute and their colleagues across the United States and at Information Management Services, Inc., who have been involved with the Surveillance, Epidemiology, and End Results (SEER) Program.

Ethical approval

Because SEER is public-use data, this study was deemed exempt from institutional review board approval by Sun Yat-Sen University Cancer Center.

Informed consent

Because SEER is public-use data, informed consent was waived.

Competing Interests

The authors have declared that no competing interest exists.

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Author contact

Corresponding author: Zhiyong Li, 651 Dong Feng Road East, Guangzhou 510060, China; Tel and Fax: +86-20-8734 3088; E-mail: lizhiyorg.cn.

Received 2017-2-6
Accepted 2017-5-19
Published 2017-8-23

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