Development and external validation of a prognostic nomogram to predict survival in patients aged ≥60 years with pancreatic ductal adenocarcinoma

Introduction

Pancreatic cancer (PC) is a highly aggressive malignant tumor characterized by metastatic susceptibility, poor therapeutic effect and poor prognosis (1,2). Early diagnosis is difficult, and as the disease progresses to advanced stages, most patients have no obvious symptoms. Due to its late-stage and poor prognosis, and difficulties in developing effective treatments, the mortality of the disease is increasing, and it is projected to become the second most common cause of cancer death in developed countries by 2040 (3). Surgical resection remains the only curative method for PC patients. However, the majority of patients were diagnosed at an advanced stage and only 20–30% had the opportunity to undergo surgical resection (4,5). Chemotherapy is the primary treatment option for most patients with metastatic PC, but the objective response rate of first-line chemotherapy is less than 50% (6,7). Immunotherapy, which has obtained satisfactory effects in other cancers, has not achieved desirable results in PC (8,9), mainly due to its immunosuppressive tumor microenvironment (10). The 5-year relative overall survival (OS) rate of the disease is approximately 11%, with a median survival time of less than 1 year (11).

Age is considered to be an independent prognostic factor for many cancers, including PC (12-14). Previous studies have shown that the clinical features and prognosis of elderly PC patients differ from those of younger patients (12,15,16). It is commonly believed that older patients are less tolerant to surgery, chemotherapy and radiation, leading to poorer adherence to anti-tumor treatment and increased side effects. Besides, aging is accompanied by cellular senescence, including homeostasis changes, protein and nuclear genome instability, which may be involved in the occurrence and development of tumors (17-19). Currently, the American Joint Committee on Cancer (AJCC) TNM (tumor-node-metastasis) staging system is widely used in clinical practice to predict prognoses and develop treatment plans (20). However, it only incorporates some pathological factors and ignores other potential variables, such as age, gender, obesity, smoking status, alcohol use, comorbidities and tumor differentiation etc. (21). Notably, survival can vary greatly among patients with the same TNM stage of disease (22). Thus, a more accurate and specific prediction model than AJCC staging is needed for prognostic analysis of elderly patients with PC.

Nomograms are a valuable tool to determine statistical prognostic models using different clinicopathological variables to produce probabilities of clinical outcomes for individual patients (23). Nomograms have been used in a variety of cancers, showing superior results when compared to the traditional AJCC staging system (24-26). Pancreatic ductal adenocarcinoma (PDAC), which accounts for the vast majority of PC, shows the lowest OS and worst prognosis in patients with PC (27). For patients with metastatic PDAC, the 5-year OS rate is less than 3% (28). Few studies have reported the clinical characteristics and prognosis of elderly patients with PDAC (12,29). As far as we know, there are no specific nomograms considering both OS and cancer-specific survival (CSS) for elderly PDAC patients. Zhong et al. developed a web-based prediction model for predicting OS in PC patients aged ≥65 years. However, the study included all pathological types of PC and the nomogram was not externally validated (12). Our study aimed to investigate the prognostic factors for OS and CSS in PDAC patients aged ≥60 years and further develop a population-based survival-predicting model with external validation. We present this article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-5/rc).

Methods

Patient selection

The Surveillance, Epidemiology, and End Results (SEER) database is the largest publicly available cancer database in the United States and collects patient information including demographics, clinicopathological features, treatment regimen, and survival. We used SEER*Stat software (v 8.3.5) to identify PC patients in the database between 1975 and 2017. Patients with primary PDAC and aged ≥60 years were included using histological types [International Classification of Diseases for Oncology, Third Edition (ICD-O-3): 8140 and 8500] and from the corresponding locations [Site recode ICD-O-3/World Health Organization (WHO) 2008: pancreas]. The following baseline characteristics of PDAC patients were collected: age, gender, marital status, race, tumor location, tumor size, histology grade, liver metastasis, lung metastasis, bone metastasis, the 7th TNM stage (published in 2010), radiation, chemotherapy, surgery, vital status, cause of death and survival months. Patients with missing or incomplete information on the above variables were excluded. CSS was defined as the time interval between initial diagnosis of PC to death. OS was defined as the time from first diagnosis to death from any cause or data from the last follow-up.

We retrospectively gathered data from 432 PDAC patients aged ≥60 years in The First Affiliated Hospital of Wenzhou Medical University from 2007 to 2017 as an external validation cohort for this study. The inclusion and exclusion criteria for external validation cohort were the same as for internal cohort. We further collected information on independent prognostic variables based on the training cohort. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics board of The First Affiliated Hospital of Wenzhou Medical University (No. YS2022-241) and individual consent for this retrospective analysis was waived. The flow chart of our study is shown in Figure S1.

Nomogram development and statistical analyses

In this study, R software (version 3.4.2) was used to analyze the data. After rigorous screening, a total of 7,212 PDAC patients aged ≥60 years were included from the SEER database. These patients were randomly divided into a training cohort (n=5,052) and an internal validation cohort (n=2,160) at a ratio of 7:3. Statistically significance was considered for two-sided P values <0.05. Categorical data (including age) was shown as numbers and proportions, and chi-square test or Fisher exact test were used between subgroups. In the training group, univariable and multivariable cox proportional hazard regression analyses were used to determine the factors affecting CSS and OS. We constructed nomograms using prognostic factors identified in multivariate analysis and tested its ability to predict 1- and 2-year survival in PDAC patients aged ≥60 years through internal and external validation cohorts.

Calibration curves were plotted to show agreement between observations and estimated survival. The concordance index (C-index) and area under the receiver operator characteristic (ROC) curve (AUC) were used to evaluate the discriminatory ability of the nomogram. Decision curve analysis (DCA) was applied to evaluate the clinical utility of the nomogram, and the DCA curves were plotted to calculate the clinical net benefit rate (30). We divided patients into high and low-risk groups according to nomogram risk scores, the dividing point of which was derived from ROC curve. We used Kaplan-Meier analysis and log-rank tests to compare survival differences between high-risk and low-risk groups.

Results

Patient characteristics

Detailed demographic and clinicopathological information is listed in Table 1. In the training set, there were 2,285 (45.3%) patients aged 60–69 years, 2,566 (50.8%) females, 4,100 (81.2%) White, 3,087 (61.1%) married, and 4,527 (89.6%) insured patients. PDAC was most likely occurring in the head of pancreas (67.3%). Grade II (45.5%) was the most common degree of differentiation. The majority of patients were AJCC stage II (n=2,842, 56.3%). In terms of treatment, 2,881 cases (57.0%) underwent surgery, 3,259 cases (64.5%) underwent chemotherapy, and 1,180 cases (23.4%) underwent radiation. Among the distant metastases of PDAC, 72 cases (1.4%) had bone metastases, 959 cases (19.0%) had liver metastases, and 260 cases (5.1%) had lung metastases. Regarding tumor size, 2.1–4.0 cm accounted for 54.8%. As for the validation cohort, there were slightly more women [1,085 (50.2%)] than men [1,075 (49.8%)]. The most common tumor site was the head of the pancreas (67.7%), followed by the body (12.6%) and the tail (11.3%). As for tumor size, the median size (2.1–4 cm, 57.0%) was the most common, followed by large size (>4 cm, 32.4%) and small size (≤2 cm, 10.6%). There was no statistical significance in the distribution of variables between the two groups (P>0.05).

In addition, 432 patients from The First Affiliated Hospital of Wenzhou Medical University were also included (Table S1). Most patients (40.5%) were aged 70–79 years. The tumors were mostly at histologic grade III (n=173, 40.1%) and AJCC stage II (n=201, 46.5%). Among these patients, 229 (53.0%), 46 (10.6%) and 248 (57.4%) received surgery, radiation and chemotherapy, respectively. The liver was the most common site of metastasis (23.1%).

Independent prognostic factors for PDAC aged ≥60 years

First, we performed a univariate Cox proportional hazards regression analysis in the training cohort. Then, all the variables with P<0.05 were accessed into multivariate Cox proportional hazards regression analysis. Finally, age, grade, AJCC stage, chemotherapy, surgery, radiation, bone metastasis, liver metastasis, lung metastasis and tumor size were identified as independent prognostic factors for both OS and CSS. The results of univariate and multivariate analyses are shown in Table 2.

Nomogram construction for 1- and 2-year OS and CSS

Based on the significant and independent prognostic factors identified by the multivariate analysis, nomograms for predicting OS and CSS of PDAC patients aged ≥60 years were constructed (Figure 1). The nomograms showed that surgery was the most significant variable affecting the prognosis of patients, followed by chemotherapy, AJCC stage, tumor grade and size. Score each level of each variable on the nomogram. By adding the scores of the selected variables, the nomograms could be used to predict 1- and 2-year OS and CSS in PDAC patients aged ≥60 years.

Figure 1 Nomogram predicting 1- and 2-year OS (A) and CSS (B) of patients with pancreatic ductal adenocarcinoma. AJCC, American Joint Committee for Cancer; OS, overall survival; CSS, cancer-specific survival.

Calibration and internal validation

The calibration plots for the training cohort and the internal validation cohort used to predict OS showed good agreement between the actual observation and nomogram predicted survival (Figure 2). A similar result for CSS was demonstrated in Figure S2. In the training cohort, nomograms of OS and CSS showed strong prediction capabilities, with C-indexes of 0.759 [95% confidence interval (CI): 0.751–0.767] and 0.760 (95% CI: 0.752–0.768), respectively. Additionally, the established nomograms demonstrated higher values of C-indexes compared with the 7th TNM stage system, indicating improved discriminatory ability in predicting OS and CSS (Table 3). For the internal validation cohort, similar results were observed in both OS and CSS nomograms (Table 3).

Figure 2 Calibration plots of the nomogram for 1- and 2-year OS prediction of the training cohort (A,B) and internal validation cohort (C,D). OS, overall survival.

Comparison of the nomogram and 7th TNM staging system

The AUC values of the OS nomogram were superior to the 7th TNM staging in both the training set (1-year: 0.829 vs. 0.678, 2-year: 0.802 vs. 0.679) and internal validation set (1-year: 0.821 vs. 0.678, 2-year: 0.809 vs. 0.681) (Figure 3, Table 4). For the CSS nomogram, the AUC values also outperformed the traditional TNM model (Figure S3, Table 4). The DCAs are commonly used to evaluate the clinical value of OS and CSS nomograms. As shown in Figure 4 and Figure S4, comparisons between nomograms and 7th TNM staging system showed that the net benefit of nomograms consistently improved, indicating that our nomograms were superior to the traditional TNM stage in predicting OS and CSS in PDAC patients aged ≥60 years.

Figure 3 The ROC curves of the nomograms for 1- and 2-year OS prediction of the training cohort (A,B) and internal validation cohort (C,D). AUC, area under the curve; ROC, receiver operating characteristic; OS, overall survival.

Figure 4 DCA of the nomogram and 7th AJCC TNM staging system for 1-year (A,C) and 2-year (B,D) overall survival in the training cohort (A,B) and internal validation cohort (C,D). AJCC, American Joint Committee for Cancer; DCA, decision curve analyses; TNM, tumor-node-metastasis.

External validation of nomogram

The established nomograms were externally validated to further illustrate the clinical application. The C-indexes of OS and CSS nomograms were 0.800 (95% CI: 0.773–0.827) and 0.799 (95% CI: 0.771–0.826), respectively, which were both higher than those of the 7th TNM staging system. Also, the AUC values of the nomograms for predicting 1- and 2-year survival were 0.843 and 0.860, and 0.849 and 0.862 for OS and CSS, respectively, indicating a high predictive ability in external validation (Figure 5). The calibration curves (Figure 6) still showed that the nomograms had good agreement. Additionally, we developed a risk stratification system according to patients’ total scores on the nomogram. The Kaplan-Meier curves demonstrated that there were significant differences in survival between high and low risk groups (P<0.001) (Figure 7).

Figure 5 The ROC curves of the nomograms for 1- and 2-year OS (A,B) and CSS (C,D) prediction in external validation cohort. AUC, area under the curve; ROC, receiver operating characteristic; OS, overall survival; CSS, cancer-specific survival.

Figure 6 Calibration plots of the nomogram for 1- and 2-year OS (A,B) and CSS (C,D) prediction in external validation cohort. OS, overall survival; CSS, cancer-specific survival.

Figure 7 Kaplan-Meier curves of OS (A) and CSS (B) to test the risk stratification system in the external validation cohort. OS, overall survival; CSS, cancer-specific survival.

Discussion

PDAC accounts for approximately 90% of all pancreatic tumors and is usually diagnosed at a late stage, with systemic therapy being the primary treatment. Chemotherapy, which is now increasingly being used as a neoadjuvant therapy, has evolved to improve survival. The growing use of genomic testing in advanced PC has led to a better understanding of its biology, allowing doctors to consider potential targeted treatment (2,31). Despite the development of novel therapies, survival remains limited, usually of less than 1 year (32). Many studies have shown that age is an independent variable affecting OS in PDAC patients (26,33-35). Since the clinical features and prognosis of elderly PDAC patients are different from those of younger patients (12,15,16), it is not accurate to rely solely on the traditional stage systems to estimate the prognosis of these patients. In the current study, we constructed a nomogram model based on a combination of independent prognostic factors to predict survival in PDAC patients aged ≥60 years. The new nomogram included ten variables including age, grade, AJCC staging, chemotherapy, surgery, radiation, lung metastases, bone metastases, liver metastases and tumor size, which could comprehensively predict survival prognosis and fill the gap in applying this model in elderly PDAC.

In our study, the majority of PDAC patients were white, 60–69 years old. Most tumors were located in the head of the pancreas. The majority of patients were in AJCC stage II with histological grade II and III. More than half of the patients were treated with chemotherapy and surgery. These were some of the disease characteristics for PDAC patients aged ≥60 years. Additionally, ten independent prognostic variables were identified for OS and CSS, which are in accordance with previous studies (12,15,35,36). Our model showed that surgery had the greatest impact on OS and CSS, followed by chemotherapy, AJCC stage and grade. Consistent with our findings, Zhong et al. established a prediction model for OS in elderly PC patients, in which surgery contributed the most to the final risk score (12). At present, surgery is usually considered the dominant modality in PDAC treatment. Over the past few decades, surgery for PC has become safer and the risk of postoperative mortality has dropped to 3% (37). Even in stage IV patients, some patients with distant isolated metastases treated with neoadjuvant chemotherapy may undergo surgical evaluation after tumor shrinkage (38). However, suitability of patient for surgery is also dependent upon patient’s health condition and the presence of comorbidities. We were unable to take these factors into account due to the lack of information in the SEER database. Future studies with more comprehensive data will be conducted to address these issues. Chemotherapy is considered to be the standard treatment for resected PDAC and primary first-line treatment for metastatic PC (39,40). Despite poor tolerance and compliance of chemotherapy in elderly patients, more than half of the patients in our study received chemotherapy, and its impact on OS and CSS was even greater than AJCC staging. Tumor grade or AJCC TNM staging system is a routine method used by physicians to assess cancer prognosis and select treatment strategies, but remains inaccurate due to its relative heterogeneity (41). Consistent with our study, several studies also attempted to combine these factors with other prognostic variables, thereby improving the predictive ability of their models (15,42).

In addition to the abovementioned factors, tumor size was also proven to be a significant parameter and included in our prognostic model, which is in accordance with other similar studies (25,43). The liver is the most common site of metastasis for PC, followed by the lungs. However, bone metastases are as rare as brain metastases (44,45). Yao et al. (46) found that liver and bone metastases were not only risk factors for lung metastasis of PC, but also independent prognostic factors for OS in these patients. Our study also found that liver and bone metastases significantly affected the prognosis of PDAC patients aged ≥60 years. Therefore, clinicians should be aware of screening for metastases at these sites to accurately assess prognosis.

In our study, the nomograms were constructed with a large sample size from the SEER database, which guaranteed the reliability and stability of the results. The calibration plots showed that the 1- and 2-year survival probabilities predicted by nomograms were in good agreement with the actual observation. The C-indexes and AUC values of our nomograms were higher than those of the 7th AJCC staging system, indicating better discriminatory power to predict OS and CSS. Moreover, our model still demonstrated relatively higher C-index and AUC value in the external validation cohort, compared to the elderly PC nomogram data reported by Zhong et al. (12) (C-index: 0.800 vs. 0.797, AUC: 0.843 vs. 0.828). The results of DCA analyses further proved that our nomograms were superior to the AJCC staging system in terms of clinical application. Finally, we applied one Chinese center to externally verify the nomograms. Kaplan-Meier curves showed significant differences in survival of patients in the high and low risk groups. As far as we know, this is the first nomogram based on a large multicenter dataset and an external validation cohort to effectively predict prognosis in PDAC patients aged ≥60 years. The nomograms, which consist of a few easily obtained variables, can be used to estimate the individualized survival probabilities and guide personalized treatment for elderly patients with PDAC.

There were several limitations in our study. First, it was a retrospective study with inevitable selection bias. Second, detailed information on radiation, chemotherapy, targeted therapy and surgical methods was incompletely recorded. In addition, other potential risk factors, such as family history, comorbidities, alcohol consumption, obesity or smoking, were also difficult to obtain from the SEER database, and these factors might confound the actual association. Finally, the sample size of external validation cohort was small, so future multi-center prospective studies should be conducted to further increase the number of cases, so as to improve the accuracy and reliability of the prediction model.

Conclusions

We established and externally validated a reliable nomogram specifically for predicting 1- and 2-year survival in PDAC patients aged ≥60 years, which showed superiority over the traditional TNM staging system. This new nomogram could help clinicians personalize survival prediction and risk assessment. Further prospective studies with larger sample sizes and more detailed clinical information are warranted to improve the accuracy and applicability of our model.

Acknowledgments

Funding: This work was supported by grants from Basic Public Welfare Research Program of Zhejiang Province (No. LQ21C080002).

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-5/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-5/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-5/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-5/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics board of the First Affiliated Hospital of Wenzhou Medical University (No. YS2022-241) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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