Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years

Liu, Qunlong; Li, Wenxia; Xie, Mixue; Yang, Minghui; Xu, Meiqing; Yang, Lei; Bing, Sheng; Peng, Yanna; Gao, Li

doi:10.17305/bjbms.2020.5271

Cited by 13 publications

(18 citation statements)

References 17 publications

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“…We calculated the concordance index (C-index) and the area under the receiver operating characteristic curve (AUC) of the training and validation groups to evaluate the discrimination ability of the nomograms ( 15 ). Calibration curves were plotted to assess the calibration ability ( 16 ). In addition, we used decision curve analysis (DCA) to evaluate the clinical usefulness of the nomograms ( 17 ).…”

Section: Methodsmentioning

confidence: 99%

Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery

Shi

Liu²,

Cao³

et al. 2022

Front. Oncol.

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BackgroundThe prediction models for primary duodenal adenocarcinoma (PDA) are deficient. This study aimed to determine the predictive value of the lymph node ratio (LNR) in PDA patients and to establish and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) for PDAs after surgical resection.MethodsWe extracted the demographics and clinicopathological information of PDA patients between 2004 and 2018 from the Surveillance, Epidemiology and End Results database. After screening cases, we randomly divided the enrolled patients into training and validation groups. X-tile software was used to obtain the best cut-off value for the LNR. Univariate and multivariate Cox analyses were used in the training group to screen out significant variables to develop nomograms. The predictive accuracy of the nomograms was evaluated by the concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). Finally, four risk groups were created based on quartiles of the model scores.ResultsA total of 978 patients were included in this study. The best cut-off value for the LNR was 0.47. LNR was a negative predictive factor for both OS and CSS. Age, sex, grade, chemotherapy and LNR were used to construct the OS nomogram, while age, grade, chemotherapy, the number of lymph nodes removed and LNR were incorporated into the CSS nomogram. The C-index, calibration curves and AUC of the training and validation sets revealed their good predictability. DCA showed that the predictive value of the nomograms was superior to that of the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition). In addition, risk stratification demonstrated that patients with higher risk correlated with poor survival.ConclusionsThe LNR was an adverse prognostic determinant for PDAs. The nomograms provided an accurate and applicable tool to evaluate the prognosis of PDA patients after surgery.

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Section: Methodsmentioning

confidence: 99%

Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery

Shi

Liu²,

Cao³

et al. 2022

Front. Oncol.

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“…By constructing a two-dimensional projection, X-tile tool can illustrate potential subsets (cutoff) [ 16 ]. As a powerful graphic method, this tool has been widely used in many previous investigations [ 7 , 12 , 13 , 29 ]. To date, the role of tumor size in prognosis prediction of CRC has been intensively investigated [ 30 ].…”

Section: Discussionmentioning

confidence: 99%

“…Clinically, the tumor lymph node metastasis (TNM) staging system, proposed by the American Joint Commission on Cancer (AJCC), is widely used to predict the prognosis of various cancers, but has some shortcomings and is deficient in predicting prognosis accurately [ 7 ]. In recent years, some studies have suggested that other factors, including primary site, tumor size, and marital status, may also influence the outcome of CRC patients [ 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…Based on a multivariable linear regression model, nomograms integrate multiple clinical predictors and show quantitative relationships between these individual predictors, which can accurately predict the overall survival (OS) and cancer-specific survival (CSS) for a single patient, assisting clinicians to optimize individualized therapeutic options and assess treatment outcomes [ 11 ]. Such studies have recently been reported in various types of cancers [ 7 , 11 - 13 ], but the research focusing on the OS and CSS prognosis of VEO-CRC is rarely reported.…”

Section: Introductionmentioning

confidence: 99%

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Prognostic nomograms for predicting overall survival and cancer-specific survival of patients with very early onset colorectal cancer: a population‑based analysis

Dong

Lyu

2022

Bosn J of Basic Med Sci

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In contrast to the declining incidence in older populations, the incidence of very early onset colorectal cancer (VEO-CRC) patients (aged ≤40 years) has been increasing in different regions of the world. In this study, we aimed to establish nomogram models for the prognostic prediction of patients with VEO-CRC for both overall survival (OS) and cancer-specific survival (CSS). Patients diagnosed with VEO-CRC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomly assigned to the training cohort and validation cohort at a ratio of 7:3 for model construction and internal validation. Using univariate and multivariate Cox regression analysis to screen important variables, which were then used to construct a nomogram. The nomogram was evaluated using calibration curves and the receiver operating characteristic (ROC) curves. A total of 3061 patients were included and randomly divided into the training cohort (n = 2145) and validation cohort (n = 916). Five independent prognostic factors, including race, grade, tumor size, AJCC stage, and AJCC T stage were all significantly identified in OS multivariate Cox regression analysis. Meanwhile in CSS, multivariate Cox regression analysis demonstrated that race, grade, tumor size, AJCC stage, AJCC T stage, AJCC N stage, and SEER stage were independent prognostic factors. The calibration plots of the established nomograms indicated high correlations between the predicted and observed results. C-index and ROC analysis implied that our nomogram model has a strong predictive ability. Moreover, nomograms also showed higher C-index values compared to tumor-node-metastasis (TNM) and SEER stages. We established and validated a simple-to-use nomogram to evaluate the 1-, 3-, and 5-year OS and CSS prognosis of patients with VEO-CRC. This tool can assist clinicians to optimize individualized treatment plans.

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“…A nomogram can simplify and visualise complex regression equations, integrate data with a model, comprehensively consider the influential variables in the analysis, and graphically display the probability of the predicted outcome 68 . Therefore, we used the rms package in R software to plot the nomogram of the logistic regression model constructed in this study.…”

Section: Methodsmentioning

confidence: 99%

Establishment and evaluation of a risk-prediction model for hypertension in elderly patients with NAFLD from a health management perspective

Zhang

Luo

Pan

et al. 2022

Sci Rep

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Elderly patients with nonalcoholic fatty liver disease are at a higher risk of developing. This study established an effective, individualised, early Hypertension risk-prediction model and proposed health management advice for patients over 60 years of age with NAFLD. Questionnaire surveys, physical examinations, and biochemical tests were conducted in 11,136 participants. The prevalence of NAFLD among 11,136 participants was 52.1%. Risk factors were screened using the least absolute shrinkage and selection operator model and random forest model. A risk-prediction model was established using logistic regression analysis and a dynamic nomogram was drawn. The model was evaluated for discrimination, calibration, and clinical applicability using receiver operating characteristic curves, calibration curves, decision curve analysis, net reclassification index (NRI), and external validation. The results suggested that the model showed moderate predictive ability. The area under curve (AUC) of internal validation was 0.707 (95% CI: 0.688–0.727) and the AUC of external validation was 0.688 (95% CI: 0.672–0.705). The calibration plots showed good calibration, the risk threshold of the decision curve was 30–56%, and the NRI value was 0.109. This Hypertension risk factor model may be used in clinical practice to predict the Hypertension risk in NAFLD patients.

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Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years

Cited by 13 publications

References 17 publications

Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery

Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery

Prognostic nomograms for predicting overall survival and cancer-specific survival of patients with very early onset colorectal cancer: a population‑based analysis

Establishment and evaluation of a risk-prediction model for hypertension in elderly patients with NAFLD from a health management perspective

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