Developing a nomogram based on SEER database for predicting prognosis in choroid plexus tumors

Abstract

Choroid plexus tumors (CPT) are rare and highly vascularized neoplasms that have three histologically confirmed diagnoses, including choroid plexus papilloma, atypical choroid plexus papilloma, and choroid plexus carcinoma (CPC). This study aimed to determine the epidemiology and survival of patients with CPTs and develop a nomogram to quantify the prognosis of the patients with CPT. Data of 808 patients who were diagnosed as CPT between 2000 and 2020 was obtained from the surveillance, epidemiology, and end results database. Descriptive analysis was used to assess the distribution and tumor-related characteristics of the patients with CPT. Independent prognostic factors for patients with CPT were identified by univariate and multivariate Cox regression analysis. The nomogram was established and evaluated by receiver operating characteristic curve, and decision curve analysis (DCA), calibration curves. The independent prognostic factors for patients with CPT are age, tumor size, surgery, chemotherapy, tumor number, pathologies, and race. For the prognostic nomogram, the area under the curve (AUC) of 60-, 120-, and 180-months were 0.855, 0.869 and 0.857 in the training set and 0.836, 0.864 and 0.922 in the test set. The DCA and calibration curve indicated the good performance of the nomogram. Patients with CPTs can be diagnosed at any age. Among the three histopathological tumors, patients with CPC had the worst prognosis. The nomogram was established to predict the prognosis of patients with CPT, which had satisfactory accuracy, and clinical utility may benefit for clinical decision-making.

Keywords: Choroid plexus tumor; Epidemiology; Nomogram; Prognosis; SEER program.

Figure 1

The Kaplan–Meier survival analysis for patients with CPT classified based on (A) sex, (B) tumour size, (C) surgery, (D) chemotherapy, (E) marital status, (F) tumour number, (G) pathologies, (H) race, and (I) radiation. (J) Forest plot of multivariate Cox analysis for patients with CPT.

Figure 2

(A) A prognostic nomogram for patients with CPT. The area of the box and the area under the curve represent the distribution of the categorical and numerical variables. (B) Based on the cutoff value of 0.186, we categorized all patients into low-risk and high-risk groups. The Kaplan–Meier survival curve of the training (C) and the testing (D) set.

Figure 3

The receiver operating characteristic curves of nomogram and all independent predictors at 60- (A), 120- (B), and 180-months (C) in the training set and at 60- (D), 120- (E), and 180-months (F) in the testing set. The decision curve analysis of the nomogram at 60- (G), 120- (H), and 180-months (I) in the training set and the testing set (J-L). The calibration curve of the prognostic nomogram for patients with CPT in the training set (M) and the testing set (N).