Patients characteristics and survival outcomes
In total, this study involved 363 eligible patients diagnosed with PCCA as the sole primary cancer and underwent surgical resection in SEER database from 2004-2015. The descriptive and clinical characteristics of these patients are provided in Table1. In the training cohort, the median follow-up periods were 23.87 (range, 1-83) months with 70.8% patients being over age of 60 years. Notably, in this study, we combined the variables ("regional nodes examined" and "regional nodes positive", which were included in Collaborative Stage Data Collection System) into regional lymph nodes status, which was divided into four subgroups: regional nodes examined and not positive, regional nodes examined and <4 nodes positive, regional nodes examined and ³4 nodes positive, and regional nodes not examined or regional nodes unknown. 78% resected PCCA patients had less than 4 positive regional lymph nodes. We also noticed that 86.6% patients without vascular invasion, which was seem as the important factor in prognosis of PCCA. In general, in terms of prognosis, the 1-,3- and 5- year CSS rates were stratified by age, sex, tumor grade, T stage, and M stage (7th edition), regional lymph nodes status, vascular invasion and tumor size.
Identification of optimal tumor-size cutoff value with prognosis
The cutoff value, 20 mm and 34 mm, of tumor size was identified by X-tile plot based on minimal P-value approach and the maximum of chi-square log-rank values was 24.1 according to cancer-specific survival (Fig.2A). To investigate the impact of tumor-size cutoff value on CSS, we first reclassified patients into three risk groups, 1-19 mm, 20-33 mm and ³34 mm, using 20 mm and 34 mm as the cutoff value. The tumor size is an important prognosis factor for PCCA and patients with 34mm or more had significant poor prognosis and 20 mm or less group showed better survival outcome than other groups in CSS (p<0.001, Fig2B). In the external validation cohort, we also found that tumor size less than 20 mm in PCCA patients has a better survival outcome, and tumor size larger than 34mm is a significant negative factor implying a worse prognosis (Fig2C). Then, to further confirm the impact of different tumor size on CSS of resected PCCA, we treated the size of PCCA as a continuous variable and analyzed the size of PCCA from 18 to 40 mm (Table.2). The tumor size is the independent factor for PCCA, and patients with tumor size more than 34 mm had significant worse 5-year survival outcome and shorter mean survival time than other groups. Notably, when the tumor size was 33mm and less, the difference in the prognosis of patients was reduced compared with others. Until the cut-off value was 20 mm, the prognosis of patients with tumor size greater than 20mm was significantly worse than that with tumor size less than 20mm. To better reveal the clinical value of this tumor-size cutoff value, we compared the differences in tumor characteristics among the three groups. Of these, we noticed that more larger tumor size group had worse tumor grade, advanced T stage, more positive regional lymph nodes and more frequency vascular invasion (Table.3, all p<0.05).
Effect of tumor size counts on survival outcome of PCCA
Initially, univariate analysis revealed that, besides of tumor size, other clinicopathologic characteristics strongly correlated with CSS with tumor grade, T stage and regional lymph nodes status (Table.4). Multivariate analysis with cox regression demonstrated that more larger tumor size showed survival disadvantage in CSS (tumor size: 20-33mm hazard ratio (HR) 1.525; ³ 34 mm HR 2.354). Notably, we noticed that tumor size less than 20 mm in PCCA patients indicated a better prognosis, and for patients with tumor size larger than 34mm is a significant negative factor affecting prognosis. Of other variables, tumor grade, T stage and regional lymph nodes status remained significantly associated with CSS in the multivariate cox regression model (all P < 0.05), suggesting they were also the independent predictors for CSS in resected PCCA patients (Table.4).
Construction and Validation of Nomogram for CSS
With the independent predictors of CSS derived from multivariate analysis, we established a nomogram to predict the 1-,3- and 5-year CSS in patients with PCCA. Tumor grade, regional lymph nodes status and tumor size were included into the nomogram (Fig.3A). Notably, the tumor size contributed the most to prognosis follow by regional lymph nodes status and tumor grade in the novel nomogram. Each variable in nomogram was assigned a risk score on the point scale. And we were able to calculated the total risk point to estimate the 1-,3- and 5-year survival rate according to the survival probability scales in the nomogram. The nomogram based on tumor size showed good accuracy with c-index of 0.626 for CSS model in the training cohort. Calibration plots for the probabilities of 1-, 3-, and 5-year CSS showed an optimal agreement between prediction by the nomogram and the actual observation regarding both training and external validation sets (Fig.3). To further explore the discriminatory accuracy of the nomogram with that of 7th edition TNM staging systems in the training set. The nomogram discriminatory accuracy of the nomogram for CSS prediction was superior to that of either the 7th edition TNM stage systems (C-index: 0.626 vs 0.608). The external prognostic validation using the above cut-points revealed that prognosis of patients with tumor size less than 20 mm had more better survival outcome, and the calibration plots also performed the good correlations between the nomogram prediction and actual observation for 1-, 3- and 5-year CSS and C-index of the nomogram was also higher than the 7th edition TNM stage systems (C-index: 0.606 vs 0.541, Fig.3).
Comparison of the Values of Area Under the ROC Curve
Comparisons of the novel nomogram and the 7th edition TNM staging system was performed using the AUC values. For the whole study cohort, the AUC values of the nomogram for predicting 1-,3- and 5- year CSS were 0.680, 0.691 and 0.727. These results were significantly better than the corresponding 1- and 5-year AUC values of CSS in TNM staging system (AUC value: 1-year 0.609, 3-year 0.671 and 5-year 0.628, Fig.4A, B&C). In the external cohort, the1-, 3- and 5-year AUC value of the nomogram also showed better accuracy for predicting the CSS than that with the 7th TNM stage system (0.632 vs 0.572, 0.655 vs 0.527 and 0.709 vs 0.540, Fig.4 D, E&F). DCA was performed to compare the clinical usability and benefits of the nomogram with that of the traditional AJCC stage. As shown in Figure 4G&H, compared to the AJCC stage model, the new nomogram’s 5-year DCA curves showed larger net benefits across a range of death risk in the training and external validation cohort.