Development and validation of a nomogram for survival benefit of lymphadenectomy in resected gallbladder cancer
Original Article

Development and validation of a nomogram for survival benefit of lymphadenectomy in resected gallbladder cancer

Mingyu Chen1,2#, Jian Lin3#, Jiasheng Cao1#, Hepan Zhu1, Bin Zhang1, Angela Wu4, Xiujun Cai1,2

1Department of General Surgery, 2Key Laboratory of Endoscopic Technique Research of Zhejiang Province, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou 310016, China; 3Longyou People’s Hospital, Quzhou 324400, China; 4Medicine, University of Melbourne, Melbourne, VIC, Australia

Contributions: (I) Conception and design: M Chen, J Lin, X Cai; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: J Lin, H Zhu; (V) Data analysis and interpretation: B Zhang, A Wu; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Dr. Xiujun Cai. Department of General Surgery, Sir Run-Run Shaw Hospital, and Key Laboratory of Endoscopic Technique Research of Zhejiang Province, Zhejiang University, No. 3 East Qingchun Road, Hangzhou 310016, China. Email: srrsh_cxj@zju.edu.cn.

Background: Due to absence of large, prospective, randomized, clinical trial data, the potential survival benefit of lymphadenectomy with different number of regional lymph nodes (LNs) remains controversial. We aim to create a predicting model to help estimate individualized potential survival benefit of lymphadenectomy with more regional LNs for patients with resected gallbladder cancer (GBC).

Methods: Patients with resected GBC were selected from the Surveillance, Epidemiology, and End Results database who were diagnosed between 2004 and 2014. Covariates included age, race, sex, grade, histological stage, tumor sizes and receipt of non-primary surgery. Two types of multivariate survival regression models were constructed and compared. The best model performance was tested by the external validation data from our hospital.

Results: A total of 1,669 patients met the inclusion criteria for this study. The lognormal survival model showed the best performance and was tested by the external validation data, including 193 patients with resected GBC from our hospital. Nomograms, which based on the accelerated failure time parametric survival model, were built to estimate individualized survival. C-index, was up to 0.754 and 0.710 in internal validation for more and less regional LNs removed, respectively. Both of internal and external calibration curves showed good agreement between predicted and observed outcomes in the 1-, 3-, and 5-year overall survival (OS).

Conclusions: A predicting model can be used as a decision model to predict which patients may obtain benefit from lymphadenectomy with more regional LNs.

Keywords: Gallbladder cancer (GBC); nomogram; lymphadenectomy; predicting model; overall survival (OS)


Submitted Dec 03, 2018. Accepted for publication Feb 28, 2019.

doi: 10.21037/hbsn.2019.03.02


Introduction

Gallbladder cancer (GBC) is one of the most common biliary tract malignancies (1,2). It presents with a low annual incidence (3), poor prognosis (1,3,4) and high mortality, because of a high proportion of early lymph node (LN) metastases (5). LN status plays an important role in prognosis (6-8), i.e., positive LN status indicates a poor prognosis. Surgery remains the first line therapy for patients with resected GBC (9). There is much variation in literatures about what composes a “radical cholecystectomy” and/or an “appropriate lymphadenectomy” (10). For complete resection, extended surgical procedures, such as major hepatectomy and adequate extensive lymphadenectomy, even common bile duct resection or pancreatoduodenectomy, are often required (11). Although lymphadenectomy enables to remove more regional LNs and facilitate accurate staging of cancer, it also increases the operative difficulty and risk. Furthermore, even after extensive lymphadenectomy, not all patients with GBC can benefit from it. Therefore, whether lymphadenectomy with more regional LNs for a risk of metastatic disease could enhance or contribute to this curative potential remains debated and unproven.

Several different LN staging/scoring systems, such as tumor-node-metastasis, LN ratio, the log odds of positive LN, have been proposed to stratify the prognosis of patients with GBC. Unfortunately, none of them focuses on this debate. Moreover, it is not easy and convenient to make decision on who need to be performed with more regional lymphadenectomy during operation, according to the results of frozen-sections alone. Due to the rarity of GBC and the lack of large-scale prospective randomized clinical trials, the actual benefit for removing more and/or less regional LNs at risk of GBC has not been well established. As a result, there is little evidence for clinicians to rely on to determine which patients will obtain benefit from more regional LNs.

The primary aim of this study was to create a decision model to estimate individualized potential survival benefit of lymphadenectomy with more and/or less regional LNs for patients with resected GBC.


Methods

Study population

Surveillance, Epidemiology and End Results (SEER) database, which covers approximately 26% of the U.S. population, provides patients’ data, including patient demographics, tumor morphology, staging, treatment detail, follow-up and so on. Patients who underwent resection for GBC between 2004 and 2014 were identified in the SEER database of the National Cancer Institute. GBC was identified using the International Classification of Diseases (ICD-O-3) (C23.9) codes, and patients diagnosed at autopsy, or none of regional LNs removed were excluded. Standard patient demographic and clinicopathologic data, including size, grade, and histological stage, was collected. In addition, one to three regional LNs removed was defined as “lymphadenectomy with less regional LNs”, while four or more regional LNs removed was defined as “lymphadenectomy with more regional LNs”. Patients who underwent resection for GBC from January 2007 to December 2012 at author’s institution were included in the study as external validation data.

Statistical analysis

Statistical analyses were performed using the SPSS 24.0 or R software packages. The primary end point of interest in this study was overall survival (OS). Observed covariates were age, sex, race, grade, tumor size, American Joint Commotion Cancer of T stage according to 7th edition and receipt of non-primary surgery and so on. A propensity score 1:1 matching method was performed to balance observed covariates in two groups using the SPSS 24.0. By assigning propensity score weights to each patient and incorporating these weights into model construction, we can reduce inherent biases in retrospective non-randomized regression analyses. Multivariate regression survival analysis was performed to identify significant factors. Then, two survival modeling methods such as Semiparametric model (Cox proportional hazards) and accelerated failure time parametric model (lognormal) were compared using Akaike’s Information Criterion. The best model was selected and tested by the internal data form SEER database and external validation data from authors’ hospital using both discrimination and calibration. Discrimination was evaluated using the Harrell’s concordance index (C-index). Calibration, which compares predicted with actual survival, was evaluated with a calibration curve. Except that, the analysis of subgroup (1 LNs and 2–3 LNs) from less regional LNs group was performed. When P value less than 0.05, it means significant. In addition, STROBE and TRIPOD guidelines are performed in the observational study to consult for prediction model.


Results

Patient and tumor characteristics

A total of 1,669 coming from SEER were summered in Table 1. There were some differences in two groups, such as patients undergoing lymphadenectomy with more regional LNs group tended to be younger, had lower histological differentiated grade, smaller tumor size, higher T-stages and percent of non-primary. Of these, after propensity score weighting applied to balance covariates in two groups, all covariates were balanced and no longer had statistically significant difference. In addition, the characteristics of 193 patients from our hospital were shown in Table 2.

Table 1
Table 1 Patient and tumor characteristics before and after PS weighting applied to balance covariates between less and more regional LNs groups
Full table
Table 2
Table 2 Patient and tumor characteristics between less and more regional LNs groups from SRRSH database
Full table

Independent factors and two nomograms

The multivariate survival regression analysis was performed. There were four statistically significant factors for the group of less regional LNs removed, including age (P=0.001), tumor size (P<0.001), T-stages (P<0.001) and receipt of non-primary surgery (P=0.004), which were listed in Table 3. At the meantime, five factors for that of more regional LNs, consisting of age (P=0.020), sex (P=0.044), grade (P=0.043), tumor size (P=0.015) and T-stages (P<0.001), was identified and summered in Table 3. Two nomograms were built on basis of each independent factor. In order to compare the performance of survival models, the lognormal model had the lowest Akaike’s Information Criterion of 9032, indicating a better overall fit than the Cox proportional hazards models (9546). According to the coefficients from this model, two nomograms (Figure 1A,B) were constructed to estimate the survival benefit for lymphadenectomy with less and more regional LNs, respectively. To use the nomogram, first draw a vertical line up to the top point row to assign points for each variable. Then, add up the total points and drop a vertical line from the total point row to obtain the 1-year OS, 3-year OS, and 5-year OS.

Table 3
Table 3 Multivariate survival regression analysis results after PS weighting
Full table
Figure 1 Nomograms for estimating benefit of lymphadenectomy for individual patient (A, less regional lymph nodes removed; B, more regional lymph nodes removed).

Performance of nomogram

Model performance was internally and externally validated for discrimination and calibration. Discrimination, as measured by the bootstrap corrected C-index, was 0.754 and 0.7103 in internal validation and 0.710 and 0.687 in external validation for more and less regional LNs, respectively. Both of internal calibration curves (Figure 2A,B) and the external calibration curves (Figure 2C,D) showed good agreement between predicted and observed outcomes in the 1-year OS, 3-year OS, and 5-year OS respectively.

Figure 2 Internal and external calibration curve demonstrating how survival predictions from the model compare to the actual observed survival (A: internal calibration curve for 1-, 3-, 5-year OS at more regional group; B: internal calibration curve for 1-, 3-, 5-year OS at less regional group; C: external calibration curve for 1-, 3-, 5-year OS at more regional group; D: external calibration curve for 1-, 3-, 5-year OS at less regional group). OS, overall survival.

Difference on the status of LNs and each T-stages

Lymphadenectomy with more regional LNs showed a higher percent of positive LNs (P<0.001), according to the data from SEER (Figure 3A). what’s more, the percentage of positive LNs increased with higher T-staged in the less regional LNs group, while that of more regional LNs remained steady (Figure 3B). The same result based on hospital data were shown in Figure 3C,D.

Figure 3 Difference of proportion of patients with positive LNs (A: difference between less and more regional removed in training set; B: difference in each T-stage in training set; C: difference between less and more regional removed in validation set; D: difference in each T-stage in validation set). LN, lymph node.

Discussion

GBC is one of the most common and aggressive biliary tract malignancy (2). Because early GBCs are not always with specific symptoms, and the majority (50–70%) of them are detected as incidental findings after cholecystectomy performed for other indications (12-14). Although the incidental gallbladder cancer (IGBC) is the most common form of GBC diagnosed today (15), many patients present with lymphatic metastases involvement (5). LN status is referred as one of the strongest prognostic factors (6). The early LNs metastasis is a characteristic of GBC (5). Fahim et al. (16) reported that the collecting trunks from the lymphatic plexuses in the medial and lateral wall of the gallbladder terminate in the cystic and peri-choledochal LNs and follow one of three pathways (cholecysto-mesenteric pathways, cholecysto-retropancreatic pathways and cholecysto-coeliac pathways) to converge at the para-aortic LNs between left renal vein and inferior mesenteric artery (Figures S1,S2,S3). Patients with LN metastasis will have a shorter survival time and 30–40% increased risk of death, comparing to patients without LNs metastasis (17,18). However, LNs status may be inaccurate without extensive lymphadenectomy. In our study, we showed that more regional LNs removed have a higher rate of positive LNs, and a more stable accuracy in patients with different T-stage. Some studies also showed same results that it presented with LN metastases in a high proportion of patients, up to 60–80% of T3–4 tumors (7). Although the extensive lymphadenectomy was beneficial for accurately evaluating the nodal basin (19), the operative difficulty and risk was higher. Due to difficulty for surgeons to obtain the LN status directly during surgery, it is very necessary to assist clinicians in decision-making.

Figure S1 Pathway of lymphatic metastasis related GBC. GBC, gallbladder cancer.
Figure S2 TRIPOD checklist: prediction model development and validation.
Figure S3 STROBE statement—checklist of items that should be included in reports of cohort studies.

Cancer prediction model has been increasingly popular and important in personalized medicine (20), in which clinicians optimize the patient’s therapeutic recommendations according to their specific and individual information. Recently, cancer prediction model have been used in various cancers, such as lung (21-23), breast (24-26), pancreas (27,28) and prostate cancer (29-31). Cancer prediction model usually consists of many observed covariates. Bai et al. (32) constructed a GBC prediction model based on covariates such as jaundice, CA19-9 and T stage to predict OS after GBC resection. However, they merged stage 0 to IIIA into one category, which made the model not accurate and specific. According to SEER database, Zhang et al. (33) developed a nomogram to predict prognosis in patients of GBC (M0) after surgical resection. Although they found that receipt of LN dissection was a significant variable, they didn’t divide LN removal to lymphadenectomy with less regional LNs and lymphadenectomy with more regional LNs, and therefore, some biased existed in this research.

In the present study, we divided patients into less and more regional LNs removal group, meanwhile, we utilized propensity score methods which were usually used to reduce the impact of treatment selection bias, especially for non-random trails (34), to optimize the allocation of data from SEER database, and compared lognormal and Cox proportional hazards model, before we build a final survival model. Although lognormal model is not as popular as Cox proportional hazards model, it has a long history of usage in cancer survival (35) and has been shown to be a more appropriate survival model in some cancers, such as breast cancer (36), lung cancer (37), extrahepatic cholangiocarcinoma (38). Besides, Wang et al. (35) in current study indicated that the lognormal model also demonstrated a good fit for GBC. In this paper, we chose the accelerated failure time parametric model (lognormal), because its Akaike’s Information Criterion was lower than that of semiparametric model (Cox proportional hazards).

Some factors, such as age, size and T-stage, play an important role in OS between less and more regional LNs removed group, while there were some different factors, including non-primary surgery for less regional LNs group, sex and grade for more regional LNs group. Age has a great influence on survival time in the present study as expected. Generally, the elder patients possess a poorer tolerance of stress and a damaged compensatory mechanism, and higher T-stage usually showed more aggressive of the biological behavior of malignant tumors. We found the younger and/ or lower T-stage patients with GBC, the better OS, which was similar to previous studies. Interestingly, we found non-primary surgery or IGBC also a significant factor in the less regional LNs. Patients who underwent non-primary surgery usually showed lower stage, and less regional LNs removed might be enough. The other factor in more regional LNs was no difference with previous studies.

There are some limitations that need to be considered in the present study. Firstly, although the largest series of GBC cases are available form SEER, some of the known survival predictors are nearly all missing in the SEER data, such as margin status, chemoradiotherapy. Its accuracy may be affected, but this nomogram based on information which clinician can obtain before and during surgery. In addition, we used propensity score methods to reduce the impact of treatment selection bias. Therefore, postoperative treatment, such as chemoradiotherapy, immunotherapy and so on, may have little influence on the accuracy of this nomogram. Secondly, this is a retrospective study. The performance of this nomogram shows good in our hospital data, but whether it is suitable for other centers need more data to be improved and testified. Therefore, in the future, we hope get a large external data to optimize this nomogram. Finally, the details of regional LNs are missing, which increases difficulty to study which regional LNs or how much number of regional LNs are recommended to be removed. If possible, our future study will focus on this point.

In summary, we present a novel prediction model that can estimate individual survival benefit of lymphadenectomy with more and/or less regional LNs for resected GBC patients. It can be regarded as a tool to help clinician estimate which people need more regional LNs removed during surgical resection of GBC.


Acknowledgments

Thanks to Yun Cai help us revise and improve this paper.

Funding: This work was supported by Key Research and Development Plan Projects of Zhejiang Province (No. 2017C01018).


Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.

Ethical Statement: The study was approved by Sir Run Run Shaw Hospital Ethics Committee.


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Cite this article as: Chen M, Lin J, Cao J, Zhu H, Zhang B, Wu A, Cai X. Development and validation of a nomogram for survival benefit of lymphadenectomy in resected gallbladder cancer. Hepatobiliary Surg Nutr 2019;8(5):480-489. doi: 10.21037/hbsn.2019.03.02