Dataset Information

Development of predictive prognostic nomogram for NECs of rectum on population-based exploration.

ABSTRACT: We aim to investigate the clinical characteristics of the rectal NECs and the prognosis-related factors and construct a nomogram for prognosis prediction. The data of 41 patients and 1028 patients with rectal NEC were retrieved respectively from our institution and SEER database. OS or PFS were defined as the major study outcome. Variables were compared by Chi2 test, t-test when appropriate. Kaplan-Meier analysis with log-rank test was used for survival analysis and the cox regression analysis were applied. The nomogram integrating risk factors for predicting OS was constructed by R to achieve superior discriminatory ability. Predictive utility of the nomogram was determined by concordance index (C-index) and calibration curve. In the univariate and multivariate analysis, tumor differentiation, N stage, M stage and resection of primary site were identified as independent prognostic indicators. The linear regression relationship was found between the value of Ki-67 index and the duration of OS (P<0.05). Furthermore, the independent prognostic factors were added to formulate prognostic nomogram. The constructed nomogram showed good performance according to the C-index. Contrary to WHO classification guideline, we found that the rectal NEC disease are heterogeneous and should be divided as different categories according to the pathological differentiation. Besides, the nomogram formulated in this study showed excellent discriminative capability to predict OS for those patients. More advanced predictive model for this disease is required to assist risk stratification via the formulated nomogram.

SUBMITTER: Lv Y

PROVIDER: S-EPMC6215795 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Development of predictive prognostic nomogram for NECs of rectum on population-based exploration.

Lv Yang Y Pu Ning N Mao Wei-Lin WL Chen Wen-Qi WQ Wang Huan-Yu HY Han Xu X Ji Yuan Y Zhang Lei L Jin Da-Yong DY Lou Wen-Hui WH Xu Xue-Feng XF

Endocrine connections 20181101 11

<h4>Aim</h4>We aim to investigate the clinical characteristics of the rectal NECs and the prognosis-related factors and construct a nomogram for prognosis prediction.<h4>Methods</h4>The data of 41 patients and 1028 patients with rectal NEC were retrieved respectively from our institution and SEER database. OS or PFS was defined as the major study outcome. Variables were compared by chi-square test and t-test when appropriate. Kaplan-Meier analysis with log-rank test was used for survival analysi ...[more]

PMID: 30352397

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Project description:BackgroundBone is one of the most common metastatic sites of advanced lung cancer, and the median survival time is significantly shorter than that of patients without metastasis. This study aimed to identify prognostic factors associated with survival and construct a practical nomogram to predict overall survival (OS) in lung cancer patients with bone metastasis (BM).MethodsWe extracted the patients with BM from lung cancer between 2011 and 2015 from the Surveillance, Epidemiology, and End Result (SEER) database. Univariate and multivariate Cox regressions were performed to identify independent prognostic factors for OS. The variables screened by multivariate Cox regression analysis were used to construct the prognostic nomogram. The performance of the nomogram was assessed by receiver operating characteristic (ROC) curve, concordance index (C-index), and calibration curves, and decision curve analysis (DCA) was used to assess its clinical applicability.ResultsA total of 7861 patients were included in this study and were randomly divided into training (n=5505) and validation (n=2356) cohorts using R software in a ratio of 7:3. Cox regression analysis showed that age, sex, race, grade, tumor size, histological type, T stage, N stage, surgery, brain metastasis, liver metastasis, chemotherapy and radiotherapy were independent prognostic factors for OS. The C-index was 0.723 (95% CI: 0.697-0.749) in the training cohorts and 0.738 (95% CI: 0.698-0.778) in the validation cohorts. The AUC of both the training cohorts and the validation cohorts at 3-month (0.842 vs 0.859), 6-month (0.793 vs 0.814), and 1-year (0.776 vs 0.788) showed good predictive performance, and the calibration curves also demonstrated the reliability and stability of the model.ConclusionsThe nomogram associated with the prognosis of BM from lung cancer was a reliable and practical tool, which could provide risk assessment and clinical decision-making for individualized treatment of patients.

Project description:BackgroundAlthough some studies have explored prognostic factors of myxofibrosarcoma (MFS), the sample sizes were small, generally fewer than 100 patients. There is still no effective prognostic model for MFS patients based on a large population and comprehensive factors. The present study was designed to establish and validate a large population-based, clinically relevant prognostic nomogram for predicting 3- and 5-year overall survival (OS) in patients with MFS.MethodsWe identified patients with MFS (ICD-O-3 code: 8811/3) who were diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database and separated them into training and validation cohorts (7:3 ratio). Survival was described using the Kaplan-Meier method. Univariate and multivariate Cox regression analyses were used to identify prognostic factors of survival. An individual nomogram was established to predict OS at 3 and 5 years in MFS patients. The discriminative ability and predictive accuracy of the nomogram were compared to those of the traditional American Joint Committee on Cancer (AJCC) staging system in the training and validation cohorts. Finally, MFS patients were divided into two subgroups based on the prognostic index (PI) score of the nomogram, and the survival outcomes of the subgroups were compared.ResultsA total of 1,270 patients were included. Age at diagnosis, total number of in situ or malignant tumors, tumor size, tumor site, tumor extension, AJCC stage, surgical status, chemotherapy, and radiotherapy were the independent predictors of survival and were included in the nomogram. The nomogram had C-indexes of 0.806 in the training cohort and 0.783 in the validation cohort, which were greater than those of the sixth edition of the AJCC staging system (training cohort, 0.669 and validation cohort, 0.674). Decision curve analysis (DCA) revealed that the nomogram was useful with high clinical net benefits. Survival outcomes were significantly different between the different risk subgroups (P<0.001).ConclusionsA novel nomogram based on a large population was constructed to evaluate survival outcomes for MFS. Its predictive efficacy was markedly superior than that of the traditional sixth edition of the AJCC staging system.

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Development of predictive prognostic nomogram for NECs of rectum on population-based exploration.

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Development of predictive prognostic nomogram for NECs of rectum on population-based exploration.

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