scholarly journals A Prognostic Nomogram of Colon Cancer With Liver Metastasis: A Study of the US SEER Database and a Chinese Cohort

2021 ◽  
Vol 11 ◽  
Author(s):  
Chuan Liu ◽  
Chuan Hu ◽  
Jiale Huang ◽  
Kanghui Xiang ◽  
Zhi Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Liver Metastasis ◽  
Bone Metastasis ◽  
Lung Metastasis ◽  
Tumor Size ◽  
External Validation ◽  
Histological Type ◽  
Seer Database ◽  
Training Set ◽  
Internal Validation

BackgroundAmong colon cancer patients, liver metastasis is a commonly deadly phenomenon, but there are few prognostic models for these patients.MethodsThe clinicopathologic data of colon cancer with liver metastasis (CCLM) patients were downloaded from the Surveillance, Epidemiology and End Results (SEER) database. All patients were randomly divided into training and internal validation sets based on the ratio of 7:3. A prognostic nomogram was established with Cox analysis in the training set, which was validated by two independent validation sets.ResultsA total of 5,700 CCLM patients were included. Age, race, tumor size, tumor site, histological type, grade, AJCC N status, carcinoembryonic antigen (CEA), lung metastasis, bone metastasis, surgery, and chemotherapy were independently associated with the overall survival (OS) of CCLM in the training set, which were used to establish a nomogram. The AUCs of 1-, 2- and 3-year were higher than or equal to 0.700 in the training, internal validation, and external validation sets, indicating the favorable effects of our nomogram. Besides, whether in overall or subgroup analysis, the risk score calculated by this nomogram can divide CCLM patients into high-, middle- and low-risk groups, which suggested that the nomogram can significantly determine patients with different prognosis and is suitable for different patients.ConclusionHigher age, the race of black, larger tumor size, higher grade, histological type of mucinous adenocarcinoma and signet ring cell carcinoma, higher N stage, RCC, lung metastasis, bone metastasis, without surgery, without chemotherapy, and elevated CEA were independently associated with poor prognosis of CCLM patients. A nomogram incorporating the above variables could accurately predict the prognosis of CCLM.

scholarly journals Bone Metastasis in Esophageal Adenocarcinoma and Squamous Cell Carcinoma: A SEER-Based Study

2021 ◽  
Author(s):  
Ya Qin ◽  
Xiao Liang ◽  
Nanyao Wang ◽  
Ming Yuan ◽  
Jiamin Zhu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prognostic Factors ◽  
Liver Metastasis ◽  
Bone Metastasis ◽  
Lung Metastasis ◽  
Risk Model ◽  
Cox Regression ◽  
Seer Database ◽  
Univariable Analysis ◽  
Worse Prognosis

Abstract Background: Esophageal cancer (EC) is a common worldwide disease with a higher mortality rate. Studies on EC patients with bone metastasis (BM) are rare. Our study focused on the clinicopathological features of EC patients with BM using the Surveillance, Epidemiology and End Results (SEER) database to further explore the risk factors and survival for BM.Methods: According to the inclusion and exclusion criteria, EC patients with BM were extracted from the SEER database from 2010 to 2016. Univariable analysis and multivariable logistic regression were used to study the risk factors for BM. Univariable analysis and multivariable Cox regression were performed to reveal the survival and prognostic factors for BM. The competitive risk model was made to compare the association with BM among causes of death. Propensity score matching (PSM) was used to reduce the bias.Results: A total of 5314 patients were included in this study. Patients with BM had a worse prognosis before and after PSM. Male, middle esophagus, with brain metastasis, without lung metastasis, without liver metastasis were major independent risk factors of BM. Poorly differentiated and undifferentiated, with liver metastasis, with lung metastasis and without chemotherapy were major independent prognostic factors of BM.Conclusions: Compared to patients with other metastatic sites such as liver, brain and lung, patients with BM had a worse prognosis. Our findings provide recommendations about clinical guidelines including examination and treatment for EC patients with BM.

scholarly journals Relationship between tumor size and metastatic site in patients with stage IV non-small cell lung cancer: A large SEER-based study

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7822
Author(s):  
Qinge Shan ◽  
Yanling Fan ◽  
Jun Guo ◽  
Xiao Han ◽  
Haiyong Wang ◽  
...  
Keyword(s):  
Liver Metastasis ◽  
Bone Metastasis ◽  
Lung Metastasis ◽  
Tumor Size ◽  
Statistical Significance ◽  
Stage Iv ◽  
Metastatic Site ◽  
Nsclc Patients ◽  
The Relationship ◽  
Develop Liver Metastasis

Objective To analyze the relationship between tumor size and metastatic site in stage IV NSCLC patients. Methods A total of 40,196 stage IV NSCLC patients from 2010 to 2015 were screened by SEER database. Chi-square test was used to compare the characteristics of clinical variables. At the same time, multivariate Logistic regression analysis was used to evaluate the relationship between tumor size and organ metastasis. Results Regardless of tumor size, the proportion of bone metastasis and lung metastasis was higher and similar in patients with squamous cell carcinoma, while in patients with adenocarcinoma, bone metastasis accounted for the highest proportion. We found that whether the metastatic site was bone, brain, liver or lung, the proportion of patients with a tumor size of 3–7 cm was the highest. Multivariate regression analysis demonstrated that patients with a tumor size of 3–7 cm and a tumor size ≥7 cm were more likely to develop brain metastasis and lung metastasis compared with patients with a tumor size ≤3 cm (all P < 0.001), which meant the larger the tumor, the greater the risk of brain or lung metastasis. At the same time, the results indicated that patients with a tumor size of 3–7 cm had a tendency to develop liver metastasis (P = 0.004), while the statistical significance was not found for patients with a tumor size ≥7 cm (P = 0.524). The results also revealed that patients with a tumor size of 3–7cm had no significant difference to develop bone metastasis (P = 0.116), while the statistical significance was found for patients with a tumor size ≥7 cm (P < 0.001). Conclusions There was statistical significance between tumor size and metastatic site in patients with stage IV NSCLC. For brain or lung metastasis, the larger the tumor, the higher the risk of brain or lung metastasis. For liver metastasis, patients with a tumor size of 3–7 cm were more prone to develop liver metastasis. For bone metastasis, patients with a tumor size ≥7 cm were more likely to have bone metastasis.

scholarly journals Clinical Characteristics and Survival Outcomes in Neuroblastoma With Bone Metastasis Based on SEER Database Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Bin He ◽  
Jianshui Mao ◽  
Leyi Huang
Keyword(s):  
Risk Factors ◽  
Survival Analysis ◽  
Bone Metastasis ◽  
Clinical Features ◽  
Lung Metastasis ◽  
Tumor Size ◽  
Treatment Modalities ◽  
Seer Database ◽  
Primary Tumor Site ◽  
Cox Regression Analysis

PurposeClinical features and survival analysis of neuroblastoma (NB) are well explored. However, clinical research of NB patients with bone metastasis is rarely reported. Thus, the current study was performed to analyze the clinical features, survival outcome, and risk factors in those patients.Materials and MethodsWe reviewed the Surveillance, Epidemiology, and End Results (SEER) database to select cases diagnosed with NB with bone metastasis from 2010 to 2016. Overall survival (OS) and cancer-specific survival (CSS) were analyzed through univariate Cox regression analysis. Subsequently, we performed multivariate analysis to determine independent predictors of survival. The Kaplan–Meier method was applied to intuitively show differences in prognostic value between independent risk factors.ResultsWe finally identified 393 NB patients with bone metastasis who were selected for survival analysis. Nearly half of the patients (47.3%) were aged &gt;3 years. The adrenal gland was the primary tumor site, accounting for approximately two thirds of cases (66.2%). The 5-year OS and CSS rates of all patients were 62.1% and 64.1%, respectively. The univariate analysis indicated that age, lung metastasis, and tumor size were significantly associated with OS and CSS. Based on the multivariable analysis, age at 2 and 3 years, lung metastasis, and tumor size &gt;10 cm remained significant negative predictors of OS and CSS.ConclusionFor NB patients with bone metastasis, three independent prognostic risk factors (age, lung metastasis, and tumor size) are helpful to clinicians for predicting prognosis and guiding treatment. Reasonable treatment modalities for these patients should be further investigated to prolong survival.

scholarly journals Smaller tumor size is associated with poor survival in stage II colon cancer: An analysis of 7,719 patients in the SEER database

2016 ◽  
Vol 33 ◽  
pp. 157-163 ◽  
Author(s):  
Ben Huang ◽  
Yang Feng ◽  
Liang Zhu ◽  
Tianhong Xu ◽  
Liyong Huang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Tumor Size ◽  
Stage Ii ◽  
Seer Database ◽  
Poor Survival ◽  
Stage Ii Colon Cancer

scholarly journals Use of serum biomarkers in staging of canine hepatic fibrosis

2019 ◽  
Vol 31 (5) ◽  
pp. 665-673 ◽  
Author(s):  
Maud Menard ◽  
Alexis Lecoindre ◽  
Jean-Luc Cadoré ◽  
Michèle Chevallier ◽  
Aurélie Pagnon ◽  
...  
Keyword(s):  
Liver Biopsy ◽  
Hepatic Fibrosis ◽  
External Validation ◽  
Model Performance ◽  
Area Under The Curve ◽  
Gamma Glutamyl Transferase ◽  
Training Set ◽  
Internal Validation ◽  
Validation Set ◽  
Glutamyl Transferase

Accurate staging of hepatic fibrosis (HF) is important for treatment and prognosis of canine chronic hepatitis. HF scores are used in human medicine to indirectly stage and monitor HF, decreasing the need for liver biopsy. We developed a canine HF score to screen for moderate or greater HF. We included 96 dogs in our study, including 5 healthy dogs. A liver biopsy for histologic examination and a biochemistry profile were performed on all dogs. The dogs were randomly split into a training set of 58 dogs and a validation set of 38 dogs. A HF score that included alanine aminotransferase, alkaline phosphatase, total bilirubin, potassium, and gamma-glutamyl transferase was developed in the training set. Model performance was confirmed using the internal validation set, and was similar to the performance in the training set. The overall sensitivity and specificity for the study group were 80% and 70% respectively, with an area under the curve of 0.80 (0.71–0.90). This HF score could be used for indirect diagnosis of canine HF when biochemistry panels are performed on the Konelab 30i (Thermo Scientific), using reagents as in our study. External validation is required to determine if the score is sufficiently robust to utilize biochemical results measured in other laboratories with different instruments and methodologies.

scholarly journals Biliary Neuroendocrine Neoplasms: Analysis of Prognostic Factors and Development and Validation of a Nomogram

2021 ◽  
Vol 11 ◽  
Author(s):  
Shengnan Zhou ◽  
Shitao Jiang ◽  
Weijie Chen ◽  
Haixin Yin ◽  
Liangbo Dong ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Survival Time ◽  
Tumor Size ◽  
External Validation ◽  
Ampulla Of Vater ◽  
Validation Dataset ◽  
Neuroendocrine Neoplasms ◽  
Seer Database ◽  
Pathological Classification ◽  
Individual Survival

BackgroundFor this study, we explored the prognostic profiles of biliary neuroendocrine neoplasms (NENs) patients and identified factors related to prognosis. Further, we developed and validated an effective nomogram to predict the overall survival (OS) of individual patients with biliary NENs.MethodsWe included a total of 446 biliary NENs patients from the SEER database. We used Kaplan-Meier curves to determine survival time. We employed univariate and multivariate Cox analyses to estimate hazard ratios to identify prognostic factors. We constructed a predictive nomogram based on the results of the multivariate analyses. In addition, we included 28 biliary NENs cases from our center as an external validation cohort.ResultsThe median survival time of biliary NENs from the SEER database was 31 months, and the value of gallbladder NENs (23 months) was significantly shorter than that of the bile duct (45 months) and ampulla of Vater (33.5 months, p=0.023). Multivariate Cox analyses indicated that age, tumor size, pathological classification, SEER stage, and surgery were independent variables associated with survival. The constructed prognostic nomogram demonstrated good calibration and discrimination C-index values of 0.783 and 0.795 in the training and validation dataset, respectively.ConclusionAge, tumor size, pathological classification, SEER stage, and surgery were predictors for the survival of biliary NENs. We developed a nomogram that could determine the 3-year and 5-year OS rates. Through validation of our central database, the novel nomogram is a useful tool for clinicians in estimating individual survival among biliary NENs patients.

scholarly journals Prognostic Nomogram for Liver Metastatic Colon Cancer Based on Histological Type, Tumor Differentiation, and Tumor Deposit: A TRIPOD Compliant Large-Scale Survival Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Le Kuai ◽  
Ying Zhang ◽  
Ying Luo ◽  
Wei Li ◽  
Xiao-dong Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Large Scale ◽  
Prediction Models ◽  
External Validation ◽  
Histological Type ◽  
Metastatic Colon Cancer ◽  
Tumor Differentiation ◽  
Tnm System ◽  
Prognostic Predictors ◽  
Tumor Deposit

ObjectiveA proportional hazard model was applied to develop a large-scale prognostic model and nomogram incorporating clinicopathological characteristics, histological type, tumor differentiation grade, and tumor deposit count to provide clinicians and patients diagnosed with colon cancer liver metastases (CLM) a more comprehensive and practical outcome measure.MethodsUsing the Transparent Reporting of multivariable prediction models for individual Prognosis or Diagnosis (TRIPOD) guidelines, this study identified 14,697 patients diagnosed with CLM from 1975 to 2017 in the Surveillance, Epidemiology, and End Results (SEER) 21 registry database. Patients were divided into a modeling group (n=9800), an internal validation group (n=4897) using computerized randomization. An independent external validation cohort (n=60) was obtained. Univariable and multivariate Cox analyses were performed to identify prognostic predictors for overall survival (OS). Subsequently, the nomogram was constructed, and the verification was undertaken by receiver operating curves (AUC) and calibration curves.ResultsHistological type, tumor differentiation grade, and tumor deposit count were independent prognostic predictors for CLM. The nomogram consisted of age, sex, primary site, T category, N category, metastasis of bone, brain or lung, surgery, and chemotherapy. The model achieved excellent prediction power on both internal (mean AUC=0.811) and external validation (mean AUC=0.727), respectively, which were significantly higher than the American Joint Committee on Cancer (AJCC) TNM system.ConclusionThis study proposes a prognostic nomogram for predicting 1- and 2-year survival based on histopathological and population-based data of CLM patients developed using TRIPOD guidelines. Compared with the TNM stage, our nomogram has better consistency and calibration for predicting the OS of CLM patients.

scholarly journals Development and Validation of a Scoring System for Early Diagnosis of Malignant Pleural Effusion Based on a Nomogram

2021 ◽  
Vol 11 ◽  
Author(s):  
Aihua Wu ◽  
Zhigang Liang ◽  
Songbo Yuan ◽  
Shanshan Wang ◽  
Weidong Peng ◽  
...  
Keyword(s):  
Pleural Effusion ◽  
Diagnostic Accuracy ◽  
Prediction Model ◽  
Scoring System ◽  
Malignant Pleural Effusion ◽  
Diagnostic Performance ◽  
External Validation ◽  
Training Set ◽  
Internal Validation ◽  
Validation Set

BackgroundThe diagnostic value of clinical and laboratory features to differentiate between malignant pleural effusion (MPE) and benign pleural effusion (BPE) has not yet been established.ObjectivesThe present study aimed to develop and validate the diagnostic accuracy of a scoring system based on a nomogram to distinguish MPE from BPE.MethodsA total of 1,239 eligible patients with PE were recruited in this study and randomly divided into a training set and an internal validation set at a ratio of 7:3. Logistic regression analysis was performed in the training set, and a nomogram was developed using selected predictors. The diagnostic accuracy of an innovative scoring system based on the nomogram was established and validated in the training, internal validation, and external validation sets (n = 217). The discriminatory power and the calibration and clinical values of the prediction model were evaluated.ResultsSeven variables [effusion carcinoembryonic antigen (CEA), effusion adenosine deaminase (ADA), erythrocyte sedimentation rate (ESR), PE/serum CEA ratio (CEA ratio), effusion carbohydrate antigen 19-9 (CA19-9), effusion cytokeratin 19 fragment (CYFRA 21-1), and serum lactate dehydrogenase (LDH)/effusion ADA ratio (cancer ratio, CR)] were validated and used to develop a nomogram. The prediction model showed both good discrimination and calibration capabilities for all sets. A scoring system was established based on the nomogram scores to distinguish MPE from BPE. The scoring system showed favorable diagnostic performance in the training set [area under the curve (AUC) = 0.955, 95% confidence interval (CI) = 0.942–0.968], the internal validation set (AUC = 0.952, 95% CI = 0.932–0.973), and the external validation set (AUC = 0.973, 95% CI = 0.956–0.990). In addition, the scoring system achieved satisfactory discriminative abilities at separating lung cancer-associated MPE from tuberculous pleurisy effusion (TPE) in the combined training and validation sets.ConclusionsThe present study developed and validated a scoring system based on seven parameters. The scoring system exhibited a reliable diagnostic performance in distinguishing MPE from BPE and might guide clinical decision-making.

scholarly journals Effect of Aging-Related Genes on the Prognosis of Colon Cancer

2021 ◽  
Author(s):  
Yushu Liu ◽  
Jiantao Gong ◽  
Yanyi Huang ◽  
Qunguang Jiang
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Validation Cohort ◽  
External Validation ◽  
Predictive Ability ◽  
Lasso Regression ◽  
Internal Validation ◽  
Cox Regression Analysis

Abstract Background:Colon cancer is a common malignant cancer with high incidence and poor prognosis. Cell senescence and apoptosis are important mechanisms of tumor occurrence and development, in which aging-related genes(ARGs) play an important role. This study aimed to establish a prognostic risk model based on ARGs for diagnosis and prognosis prediction of colon cancer .Methods: We downloaded transcriptome data and clinical information of colon cancer patients from the Cancer Genome Atlas(TCGA) database and the microarray dataset(GSE39582) from the Gene Expression Omnibus(GEO) database. Univariate COX, least absolute shrinkage and selection operator(LASSO) regression algorithm and multivariate COX regression analysis were used to construct a 6-ARG prognosis model and calculated the riskScore. The prognostic signatures is validated by internal validation cohort and external validation cohort(GSE39582).In addition, functional enrichment pathways and immune microenvironment of aging-related genes(ARGs) were also analyzed. We also analyzed the correlation between rsikScore and clinical features and constructed a nomogram based on riskScore. We are the first to construct prognostic nomogram based on ARGs.Results: Through univariate COX,LASSO regression algorithm and multivariate COX regression analysis,6 prognostic ARGs (PDPK1,RAD52,GSR,IL7,BDNF and SERPINE1) were screened out and riskScore was constructed. We have verified that riskScore has good prognostic value in both internal validation cohort and external validation cohort. Pathway enrichment and immunoanalysis of ARGs provide a direction for the treatment of colon cancer patients. We also found that riskScore was closely related to the clinical characteristics of patients. Based on riskScore and related clinical features, we constructed a nomogram, which has good predictive performance.Conclusion: The 6-ARG prognostic signature we constructed has a certain clinical predictive ability. Its riskScore is also closely related to clinical characteristics, and nomogram based on this has stronger predictive ability than a single indicator. ARGs and the nomogram we constructed may provide a promising treatment for colon cancer patients.

scholarly journals Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244693
Author(s):  
Lingchen Wang ◽  
Wenhua Wang ◽  
Shaopeng Zeng ◽  
Huilie Zheng ◽  
Quqin Lu
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Lung Metastasis ◽  
Cancer Metastasis ◽  
External Validation ◽  
Breast Cancer Patients ◽  
Training Set ◽  
Validation Set ◽  
Robust Likelihood ◽  
Six Genes

Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What’s more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs.

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