Ann Surg Treat Res.  2020 Aug;99(2):118-126. 10.4174/astr.2020.99.2.118.

Nomogram for predicting overall survival in children with neuroblastoma based on SEER database

Affiliations
  • 1Department of Pediatric Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
  • 2Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China

Abstract

Purpose
This study was performed to establish and validate a nomogram for predicting the overall survival in children with neuroblastoma.
Methods
The latest clinical data of neuroblastoma in Surveillance, Epidemiology, and End Results (SEER) database was extracted from 2000 to 2016. The cases included were randomly divided into training and validation cohorts. The survival curves were drawn with a Kaplan-Meier estimator to investigate the influences of certain single factors on overall survival. Also, least absolute shrinkage and selection operator regression was applied to further select the prognostic variables for neuroblastoma. Additionally, receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the accuracy of the nomogram.
Results
In total, 1,262 patients were collected and 8 independent prognostic factors were achieved, including patients’ age, sex, race, tumor grade, radiotherapy, chemotherapy, tumor site, and tumor size. Then we constructed a nomogram by using the data of the training cohort with 886 cases. Subsequently, the nomogram was validated internally and externally with 886 and 376 cases, respectively. The internal validation revealed that the area under the curves (AUC) of ROC curves of 1-, 3-, and 5-year overall survival were 0.69, 0.78, and 0.81, respectively. Accordingly, the external validation also showed that the AUC of 1-, 3-, and 5-year overall survival were all ≥0.69. Both methods of validation demonstrated that the predictive calibration curves were consistent with standard curves.
Conclusion
The nomogram possess the potential to be a new tool in predicting the survival rate of neuroblastoma patients.

Keyword

Neuroblastoma; Nomograms; Prognosis; Risk factors; SEER program

Figure

  • Fig. 1 The process of data selection.

  • Fig. 2 The influence of each independent predictive factor on overall survival by Kaplan-Meier survival analysis. (A–H) The survival curves of age, sex, race, radiation, grade, tumor size, tumor site, and chemotherapy, respectively. Annotation in (G): A, adrenal gland; B, soft tissue including heart; C, retroperitoneum; D, mediastinum and other respiratory organs; E, other.

  • Fig. 3 The selection of predictive factors by least absolute shrinkage and selection operator (LASSO) regression. (A) LASSO coefficient profiles of the 8 variables. Predictors were chosen according to the minimum criteria, where optimal λ resulted in 8 nonzero coefficients. (B) The left and right dotted lines stand for the minimum criteria and 1 standard error criterion, respectively.

  • Fig. 4 (A) The nomogram of neuroblastoma. (B) The scores of an example. A, adrenal gland; B, soft tissue including heart; C, retroperitoneum; D, mediastinum and other respiratory organs; E, other.

  • Fig. 5 The assessment of the predictive modelling by receiver operating characteristic curve. (A) Internal validation. (B) External validation. AUC, area under the curve.

  • Fig. 6 The diagonal lines (dotted) were standard curves, and the colored lines were calibration lines of prediction. When the calibration lines get closer to the standard lines, the nomogram would have greater prognostic potential. (A) The calibration curves of internal validation for 1- , 3- , 5-year probabilities of survival. (B) The calibration curves of external validation for 1- , 3- , 5-year probabilities of survival.


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