Nomogram model may help predict cancer specific survival in gallbladder cancer patients

By including several risk indicators, a study team led by Chong Wen built a predictive nomogram model to forecast cancer-specific survival (CSS) in older gallbladder cancer (GBC) patients. The findings of the study were published in BMC Gastroenterology.

In older patients, gallbladder cancer is a very aggressive cancer. The study's objective was to develop a new nomogram to forecast cancer-specific survival in older GBC patients.

From the SEER database, researchers retrieved clinicopathological information about older GBC patients. The independent risk factors for older GBC patients were chosen using univariate and multivariate Cox proportional hazard regression analysis. A predictive nomogram model was later built by integrating these risk factors. The accuracy and discrimination of the predictive nomogram model were validated using the C-index, calibration curve, and area under the receiver operating curve (AUC). The clinical utility of the nomogram was assessed using the decision analysis curve (DCA).

The key findings of the study were:

1. 4241 senior GBC patients in total were enrolled.

2. Patients from 2004 to 2015 were divided into the training cohort (n = 2237) and the validation cohort (n = 1000), whereas patients from 2016 to 2018 were divided into the external validation cohort (n = 1004).

3. Age, tumour histological grade, TNM stage, surgical approach, chemotherapy, and tumour size were determined to be independent risk factors for the prognosis of older GBC patients in both univariate and multivariate Cox proportional hazard regression analyses.

4. To predict cancer-specific survival at 1, 3, and 5 years, all independent risk factors that were chosen were incorporated into the nomogram.

5. The C-index of the nomogram was 0.763, 0.756, and 0.786 in the training cohort, internal validation cohort, and external validation cohort, respectively.

6. The calibration curves indicated that the nomogram's anticipated value and the actual observed value are very consistent.

7. AUC further demonstrated the great degree of predictability of the model.

8. The nomogram model's superior predictive power over the traditional TNM staging approach was demonstrated by DCA.

In conclusion, the nomogram can assist doctors in predicting patient prognosis and making more logical clinical decisions with comparatively high accuracy and dependability.

Reference:

Wen, C., Tang, J., Wang, T., & Luo, H. (2022). A nomogram for predicting cancer-specific survival for elderly patients with gallbladder cancer. In BMC Gastroenterology (Vol. 22, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12876-022-02544-y