A Novel Nomogram Predicting Distant Metastasis in T1 and T2 Gallbladder Cancer: A SEER-based Study

Cai, Yulong; Lin, Yixin; Jiang, Lingjun; Ye, Hui; Li, Fuyu; Cheng, Nan‐Sheng

doi:10.7150/ijms.47073

Cited by 19 publications

(17 citation statements)

References 29 publications

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“…However, nomogram has been applied to predict metastasis in other cancer types. Study by Cai et al combined age, grade, histology, T stage, lymph node metastasis, and tumor size to predict the metastasis in T1 and T2 gallbladder cancer [ 17 ]. In pancreatic ductal adenocarcinoma, demographic and clinicopathological characteristics were used to construct nomogram to evaluate metastasis [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study

Wang

Liu

et al. 2021

J Orthop Surg Res

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Background Osteosarcoma is most common malignant bone tumors. OS patients with metastasis have a poor prognosis. There are few tools to assess metastasis; we want to establish a nomogram to evaluate metastasis of osteosarcoma. Methods Data from the Surveillance, Epidemiology, and End Results (SEER) database of patients with osteosarcoma were retrieved for retrospective analysis. We identify risk factors through univariate logistic regression and multivariate logistic regression analysis. Based on the results of multivariate analysis, we established a nomogram to predict metastasis of patients with osteosarcoma and used the concordance index (C-index) and calibration curves to test models. Results One thousand fifteen cases were obtained from the SEER database. In the univariate and multivariate logistic regression analysis, age, primary site, grade, T stage, and surgery are risk factors. The nomogram for metastasis was constructed based on these factors. The C-index of the training and validation cohort was 0.754 and 0.716. This means that the nomogram predictions of patients with metastasis are correct, and the calibration plots also show the good prediction performance of the nomogram. Conclusion We successfully develop the nomogram which can reliably predict metastasis in different patients with osteosarcoma and it only required basic information of patients. The nomogram that we developed can help clinicians better predict the metastasis with OS and determine postoperative treatment strategies.

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Section: Discussionmentioning

confidence: 99%

Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study

Wang

Liu

et al. 2021

J Orthop Surg Res

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“…Although stage T1 tumors have a shallow depth of infiltration, their outcomes are worse when compared to stage T2 and T3 tumors, and this result is different from the association between the N stage and BM. Cai et al retrospectively analyzed 3,013 patients with gallbladder cancer and concluded that stage T1 has a higher risk of distant metastasis than that associated with stage T2 ( 17 ). Guo et al studied 212,787 patients with colorectal cancer and found that stage T1 is more prone to BM than stages T2, T3, and T4.…”

Section: Discussionmentioning

confidence: 99%

Bone metastasis of esophageal carcinoma diagnosed as a first primary tumor: a population-based study

Wang¹,

Liu²,

Chen³

et al. 2022

Transl Cancer Res TCR

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Background: This study aimed to explore predictors of bone metastasis (BM) of esophageal carcinoma (EC) and factors affecting the prognosis of EC with BM (ECBM). Methods:We retrospectively studied the data of EC patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016. Logistic regression analysis was used to analyze the risk factors of BM. Cox regression and Fine and Gray's competing risk regression were performed to identify prognostic factors associated with all-cause and cancer-specific death, respectively. The Kaplan-Meier method was used to assess survival.Results: After exclusion, 8,916 patients were eligible, of whom 462 (5.2%) had ECBM. Independent risk factors of BM were age <65 years, male sex, stage T1, advanced N stage, and non-bone organ metastases. For EC, the median survival time (MST) was 17 months, and the 3-and 5-year survival rates were 31.6% and 23.3%, respectively; meanwhile, for BM, the MST was 5 months, and the 3-and 5-year survival rates were 2% and 1%, respectively. Adenocarcinoma, stage T2, the absence of non-bone organ metastases, and combined radiotherapy and chemotherapy were associated with a reduced risk of all-cause death in ECBM patients.Stage T2, the absence of non-bone organ metastases, and combined radiotherapy and chemotherapy were associated with a decreased risk of cancer-specific death in ECBM patients.Conclusions: Although rare, BM severely impairs the prognosis of EC. BM predictors and factors influencing the prognosis of ECBM may help distinguish high-risk patients with BM and assess survival in ECBM patients.

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“…Previous studies have shown that the 1-year and 3-year cancer-specific survival rates of non-metastatic GBC were 82.3% and 56.7%, respectively ( 10 ). The GBC with metastasis had a shorter survival time than non-metastatic GBC and was commonly observed in the advanced stage and non-adenocarcinoma type ( 5 ). The three major metastatic pathways of GBC include hematogenous metastasis, lymphatic metastasis, and direct infiltration.…”

Section: Discussionmentioning

confidence: 99%

“…Previous population-based studies investigated that metastasis of lymph nodes and distant organs is prevalent in GBC, with incidence ranging from 17.9% to 64.5% ( 5 , 6 ). The most frequently observed metastatic organs are the liver, lung, and peritoneum ( 7 ).…”

Section: Introductionmentioning

confidence: 99%

Risk factors and prognosis of liver metastasis in gallbladder cancer patients: A SEER-based study

Fang

Wang

et al. 2022

Front. Surg.

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BackgroundLiver metastasis is a common complication in gallbladder cancer (GBC). We design this study to develop models for predicting the development of liver metastasis in GBC patients and evaluate the risk of mortality in these patients with liver metastasis.MethodsGBC patients from Surveillance Epidemiology and End Results (SEER) between 2010 and 2016 were included in this study. Logistic regression was performed to discover risk factors and construct predictive models for liver metastasis in GBC patients. Cox regression was utilized to find risk factors of mortality in GBC patients with liver metastasis. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the constructed predictive models.ResultsMultivariate logistic regression confirmed that T stage, N stage, and tumor grade were risk factors for liver metastasis in GBC patients. Composed of these factors, the model for predicting the development of liver metastasis had AUCs of 0.707 and 0.657 in the training cohort and testing cohort, respectively. Multivariate Cox regression showed that surgery of the primary site and chemotherapy were independently associated with the mortality of GBC patients with liver metastasis. Composed of these two factors, the predictive model for 1-year mortality of GBC patients with liver metastasis had AUCs of 0.734 and 0.776 in the training cohort and testing cohort, respectively.ConclusionThe predictive models that we constructed are helpful for surgeons to evaluate the risk of liver metastasis in GBC patients and the survival condition of those with liver metastasis. Surgery of the primary site and chemotherapy should be provided for GBC with liver metastasis.

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A Novel Nomogram Predicting Distant Metastasis in T1 and T2 Gallbladder Cancer: A SEER-based Study

Cited by 19 publications

References 29 publications

Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study

Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study

Bone metastasis of esophageal carcinoma diagnosed as a first primary tumor: a population-based study

Risk factors and prognosis of liver metastasis in gallbladder cancer patients: A SEER-based study

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