Development and Validation of a Nomogram for Predicting Overall Survival in Pancreatic NeuroendocrineTumors

Miao, Dong-liu; Song, Wei; Qian, Jun; Zhu, Zhigang; Wu, Qiong; Lv, Chang-guang; Chen, Lei

doi:10.1016/j.tranon.2018.06.012

Cited by 27 publications

(23 citation statements)

References 29 publications

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“…GBC is an aggressive malignancy associated with multiple etiologies and high mortality rates. [ 1 , 26 ] There have been some studies of the prognosis status of gallbladder carcinoma, but many of the survival analyses have focused on only a single survival end point [ 27 , 28 ] and so have ignored competing events that would lead to inaccurate survival evaluations, especially among older patients. [ 29 ] The present study estimated the probability of death for 3836 patients with GBAC who had been enrolled in the SEER database between 2004 and 2015, and calculated the 1-, 3-, and 5-year CIFs for GBAC-specific mortality.…”

Section: Discussionmentioning

confidence: 99%

Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis

Han

Yang

et al. 2020

Medicine

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A competing-risks model was developed in this study to identify the significant prognostic factors and evaluate the cumulative incidence of cause-specific death in gallbladder adenocarcinoma (GBAC), with the aim of providing guidance on effective clinical treatments. All patients with GBAC in the Surveillance, Epidemiology, and End Results (SEER) database during 1973 to 2015 were identified. The potential prognostic factors were identified using competing-risks analyses implemented using the R and SAS statistical software packages. We calculated the cumulative incidence function (CIF) for cause-specific death and death from other causes at each time point. The Fine-Gray proportional-subdistribution-hazards model was then applied in univariate and multivariate analyses to test the differences in CIF between different groups and identify independent prognostic factors. This study included 3836 eligible patients who had been enrolled from 2004 to 2015 in the SEER database. The univariate analysis indicated that age, race, AJCC stage, RS, tumor size, SEER historic stage, grade, surgery, radiotherapy, chemotherapy and adjuvant therapy (RCT, SRT, SCT and SRCT) were significant factors affecting the probability of death due to GBAC. The multivariate analysis indicated that age, race, AJCC stage, RS status, tumor size, grade and SRT were independent prognostic factors affecting GBAC cancer-specific death. A nomogram model was constructed based on multivariate models for death related to GBAC. We have constructed the first competing-risks nomogram for GBAC. The model was found to perform well. This novel validated prognostic model may facilitate the choosing of beneficial treatment strategies and help when predicting survival.

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Section: Discussionmentioning

confidence: 99%

Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis

Han

Yang

et al. 2020

Medicine

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“…A variety of prognostic factors influences the survival outcome of patients with cancer, and the ability of a single prognostic factor to predict individual survival probability is limited. In addition, relying merely on traditional staging systems is not enough to accurately assess cancer prognosis . Because of the ability to visually show data, accuracy, and individualization, nomograms have been commonly used to predict the survival of patients with cancer .…”

Section: Discussionmentioning

confidence: 99%

“…In addition, relying merely on traditional staging systems is not enough to accurately assess cancer prognosis. 16 Because of the ability to visually show data, accuracy, and individualization, nomograms have been commonly used to predict the survival of patients with cancer. 17 262 cases in the SEER database, which covers 28% of the US population.…”

Section: Discussionmentioning

confidence: 99%

Prognostic nomograms to predict overall survival and cancer‐specific survival in patients with pelvic chondrosarcoma

et al. 2019

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Background The pelvis is the most common site of chondrosarcoma (CS), and the prognosis for patients with pelvic CS is worse than that for patients with CS in the extremities. However, clinicians have had few tools for estimating the likelihood of survival in patients with pelvic CS. Our aim was to develop nomograms to predict survival of patients with pelvic CS. Methods Data from the Surveillance, Epidemiology, and End Results (SEER) database of patients with pelvic CS between 2004 and 2016 were retrieved for retrospective analysis. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. On the basis of the results of the multivariate analyses, nomograms were constructed to predict the likelihood of 3‐ and 5‐year overall survival (OS) and cancer‐specific survival (CSS) of patients with pelvic CS. The concordance index (C‐index) and calibration curves were used to test the models. Results In univariate and multivariate analyses of OS, sex, pathologic grade, tumor size, tumor stage, and surgery were identified as the independent risk factors. In univariate and multivariate analyses of CSS, pathologic grade, tumor size, tumor stage, and surgery were identified as the independent risk factors. These characteristics except surgery were integrated in the nomograms for predicting 3‐ and 5‐year OS and CSS, and the C‐indexes were 0.758 and 0.786, respectively. Conclusion The nomograms precisely and individually predict OS and CSS of patients with pelvic CS and could aid in personalized prognostic evaluation and individualized clinical decision‐making.

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“…Additionally, the nomograms we constructed could not only predict for OS, but also predict for CSS. It improved the level of utility of nomograms for clinical applications compared with the previous study [21].…”

Section: Discussionmentioning

confidence: 87%

WITHDRAWN: Survival Nomograms for Patients with Pancreatic Neuroendocrine Tumors: A Population-based Study

Lin

Chen

et al. 2020

Preprint

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Background: Although Pancreatic neuroendocrine tumors(PNETs) considered as indolent tumors, most patients are diagnosed at an advanced stage. Herein, we aimed to establish a nomogram to predict the survival of PNETs patients for clinical use via Surveillance, Epidemiology, and End Results (SEER) database. Methods: Based on the SEER program, the data of 1103 patients with PNETs were enrolled and randomly divided into training set and validation set. We performed Kaplan-Meier analysis, Cox proportional hazard regression analysis in training set to evaluate the value of prognostic factors. A nomogram was constructed obtained these independent prognostic factors for predicting overall survival(OS) and specific-cancer survival(CSS). C-index, calibration curve, decision curve analysis were used to evaluate the predictive accuracy of the nomogram. Results: Age, primary site, TNM stage, grade, and surgery were associated with OS and CSS in the multivariate models. Nomograms were established depend on these risk factors and had a better discrimination power than TMN stage. The validation technologies showed that the nomogram was able to predict 3- and 5-year OS and CSS accurately, and also proved the superiority. Age, primary site, TNM stage, grade, and surgery were associated with OS and CSS in the multivariate models. Conclusions: Nomograms were established depend on these risk factors and had a better discrimination power than TMN stage. The validation technologies showed that the nomograms were able to predict 3- and 5-year OS and CSS accurately, and also proved the superiority.

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Development and Validation of a Nomogram for Predicting Overall Survival in Pancreatic NeuroendocrineTumors

Cited by 27 publications

References 29 publications

Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis

Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis

Prognostic nomograms to predict overall survival and cancer‐specific survival in patients with pelvic chondrosarcoma

WITHDRAWN: Survival Nomograms for Patients with Pancreatic Neuroendocrine Tumors: A Population-based Study

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