Development and validation of a nomogram for prognosis of bone metastatic disease in patients with esophageal squamous cell carcinoma: A retrospective study in the SEER database and China cohort

Abstract

Purpose: Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor worldwide, and individuals with ESCC and bone metastasis (BM) often face a challenging prognosis. Our objective was to identify the risk and prognostic factors associated with BM in patients with ESCC and develop a nomogram for predicting Cancer-Specific Survival (CSS) which following the occurrence of BM.

Methods: We conducted a retrospective analysis of data pertaining to ESCC patients with BM registered in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015, as well as those treated at a Chinese institution from 2006 to 2020. Significant prognostic factors for CSS were assessed through univariate and multivariate Cox regression analyses. Subsequently, a nomogram was developed utilizing the SEER database and externally validated using real-world evidence from a Chinese cohort.

Results: A total of 266 patients from the SEER database and 168 patients from the Chinese cohort were included in the analysis. In the SEER cohort, multivariate analysis indicated that chemotherapy, radiotherapy, liver metastasis, brain metastasis, and sex were independent prognostic factors for ESCC with BM. The prognostic nomogram demonstrated areas under the ROC curve (AUCs) of 0.823, 0.796, and 0.800, respectively, for predicting 3-, 6-, and 12-month CSS. In the Chinese validation cohort, the nomogram exhibited acceptable discrimination (AUCs: 0.822, 0.763, and 0.727) and calibration ability.

Conclusion: The study developed a prognostic nomogram to predict CSS in ESCC patients with BM, which can help clinicians assess survival and make individualized treatment decisions.

Keywords: Bone metastasis; Esophageal squamous cell carcinoma; Nomogram; Prognosis.

Fig. 1

Flow chart of the study.

Fig. 2

Nomogram for 3-, 6-, and 12-month CSS prediction of the ESCC patients with bone metastasis. Each prognostic factor was assigned a point on the scale, and the sum of the total points projected on the bottom scale represent the probabilities of 3-, 6-, and 12-month CSS.

Fig. 3

Receiver operating characteristic (ROC) curves of 3-, 6-, and 12-month in the SEER database(A) and Chinese cohorts (B), respectively. The area under the ROC curve (AUC) was 0.823, 0.796, and 0.800 in the SEER database, and 0.822, 0.763, and 0.727 in the Chinese cohorts, respectively.

Fig. 4

The calibration curves of the prognostic nomogram for the 3-, 6-, and 12-month CSS prediction of the SEER database (A–C) and Chinese cohort (D–F). The calibration curves suggested that the predictive outcome have good accordance with the actual 3-, 6-, and 12-month CSS in both groups.

Fig. 5

DCA of the nomogram for the survival prediction of ESCC patients with bone metastasis in the SEER database and Chinese cohort. (A-C) 3-, 6-, and 12-month survival benefit in SEER database; (D-F) 3-, 6-, and 12-month survival benefit in Chinese cohorts. The “ALL”, “None” and “Nomogram” lines are represented as “intervention for all” (orange line), “intervention for none” (blackish green line), and “result for the nomogram or validation” (pink line). The “None” and “ALL” lines would show the expected net benefit without and with the intervention development respectively. DCA curves showed that nomogram manifested a higher net clinical benefit than “None” and “All”. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 6

Kaplan-Meier curve of risk stratification for CSS based on nomogram in SEER database. The low-risk and high-risk meant prognostic scores < 128 and ≥ 128 for CSS, respectively. Log-rank test was applied to estimate the significant difference.

Fig. 7

Kaplan-Meier curve of risk stratification for CSS based on nomogram in Chinese cohort. The low-risk and high-risk meant prognostic scores < 128 and ≥ 128 for CSS, respectively. Log-rank test was applied to estimate the significant difference.