Construction and verification of prognostic nomogram for early-onset esophageal cancer

This study aimed to build up nomogram models to evaluate overall survival (OS) and cancer-specific survival (CSS) in early-onset esophageal cancer (EOEC). Patients diagnosed with esophageal cancer (EC) from 2004 to 2015 were extracted from the Surveillance Epidemiology and End Results (SEER) database. Clinicopathological characteristics of younger versus older patients were compared, and survival analysis was performed in both groups. Independent related factors influencing the prognosis of EOEC were identified by univariate and multivariate Cox analysis, which were incorporated to construct a nomogram. The predictive capability of the nomogram was estimated by the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). A total of 534 younger and 17,243 older patients were available from the SEER database. Younger patients were randomly segmented into a training set (n=266) and a validation set (n=268). In terms of the training set, the C-index of the OS nomogram was 0.740 (95% CI: 0.707-0.773), and that of the CSS nomogram was 0.752 (95% CI: 0.719-0.785). In view of the validation set, the C-index of OS and CSS were 0.706 (95% CI: 0.671-0.741) and 0.723 (95%CI: 0.690-0.756), respectively. Calibration curves demonstrated the consistent degree of fit between actual and predicted values in nomogram models. From the perspective of DCA, the nomogram models were more beneficial than the tumor-node-metastasis (TNM) and the SEER stage for EOEC. In brief, the nomogram model can be considered as an individualized quantitative tool to predict the prognosis of EOEC patients to assist clinicians in making treatment decisions.

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Establishment and verification of a nomogram for predicting survival in patients with small intestinal gastrointestinal stromal tumors

Digestive Diseases ◽

10.1159/000516022 ◽

2021 ◽

Author(s):

Guangrong Lu ◽

Jiajia Li ◽

Limin Wu ◽

Yuning Shi ◽

Xuchao Zhang ◽

...

Keyword(s):

Tnm Staging ◽

Calibration Plot ◽

Survival Prediction ◽

Imatinib Treatment ◽

Seer Database ◽

Training Set ◽

Cancer Specific Survival ◽

Discrimination Power ◽

Ajcc Stage ◽

Small Intestinal

Background: This study aimed to develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in small intestinal gastrointestinal stromal tumours (SI GISTs). Methods: Patients diagnosed with SI GISTs were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly divided into the training and validating cohorts. Univariate and multivariate cox analyses were conducted in the training set to determine independent prognostic factors to build nomograms for predicting 3- and 5-year OS and CSS. The performance of the nomograms was assessed by concordance index (C-index), calibration plot and the area receiver operating characteristic (ROC) curve (AUC). Results: A total of 776 patients with SI GISTs were retrospectively collected from the SEER database. OS nomogram was constructed based on age, surgery, imatinib treatment and AJCC stage, while CSS nomogram incorporated age, surgery, tumor grade and AJCC stage. In the training set, C-index for the OS nomogram was 0.773 [95% confidence intervals (95% CI): 0.722–0.824], CSS nomogram 0.806 (95% CI: 0.757–0.855). In internal validation cohort, the C-index for the OS nomogram was 0.741, while for the CSS nomogram 0.819. Well-corresponded calibration plots both in OS and CSS nomogram models were noticed. The comparisons of AUC values showed that the established nomograms exhibited superior discrimination power than 7th TNM staging system. Conclusion: Our nomogram can effectively predict 3- and 5-year OS and CSS in patients with SI GISTs, and its use can help improve the accuracy of personalized survival prediction and facilitate to provide constructive therapeutic suggestions.

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Nomograms for predicting overall survival and cancer-specific survival in young patients with pancreatic cancer in the US based on the SEER database

PeerJ ◽

10.7717/peerj.8958 ◽

2020 ◽

Vol 8 ◽

pp. e8958 ◽

Cited By ~ 2

Author(s):

Min Shi ◽

Biao Zhou ◽

Shu-Ping Yang

Keyword(s):

Pancreatic Cancer ◽

Overall Survival ◽

Young Patients ◽

Seer Database ◽

Training Set ◽

Cancer Specific Survival ◽

Factors Affecting ◽

Ajcc Stage ◽

Validation Set ◽

Cox Analysis

Background The incidence of young patients with pancreatic cancer (PC) is on the rise, and there is a lack of models that could effectively predict their prognosis. The purpose of this study was to construct nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of young patients with PC. Methods PC patients younger than 50 years old from 2004 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were selected and randomly divided into training set and validation set. Univariable and forward stepwise multivariable Cox analysis was used to determine the independent factors affecting OS. The Fine and Gray competing risk regression model was used to determine the independent factors affecting CSS. We used significant variables in the training set to construct nomograms predicting prognosis. The discrimination and calibration power of models were evaluated by concordance index (C-index), calibration curve and 10-flod cross-validation. Results A total of 4,146 patients were selected. Multivariable Cox analysis showed that gender, race, grade, pathological types, AJCC stage and surgery were independent factors affecting OS. The C-index of the nomogram predicting OS in training and validation was 0.733 (average = 0.731, 95% CI [0.724–0.738]) and 0.742 (95% CI [0.725–0.759]), respectively. Competing risk analysis showed that primary site, pathological types, AJCC stage and surgery were independent factors affecting CSS. The C-index of the nomogram predicting CSS in training and validation set was 0.792 (average = 0.765, 95% CI [0.742–0.788]) and 0.776 (95% CI [0.773–0.779]), respectively. C-index based on nomogram was better in training and validation set than that based on AJCC stage. Calibration curves showed that these nomograms could accurately predict the 1-, 3- and 5-year OS and CSS both in training set and validation set. Conclusions The nomograms could effectively predict OS and CSS in young patients with PC, which help clinicians more accurately and quantitatively judge the prognosis of individual patients.

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Clinical Characteristics and Prognostic Factors of Early-Onset Pancreatic Neuroendocrine Tumors

Cancer Control ◽

10.1177/1073274820986827 ◽

2021 ◽

Vol 28 ◽

pp. 107327482098682

Author(s):

Min Shi ◽

Biao Zhou

Keyword(s):

Prognostic Factors ◽

Neuroendocrine Tumors ◽

Early Onset ◽

Older Patients ◽

Clinical Characteristics ◽

Clinicopathological Characteristics ◽

Pancreatic Neuroendocrine Tumors ◽

Chi Square ◽

Younger Patients ◽

Significant Difference

Background: The incidence of pancreatic neuroendocrine tumors (PNETs) has increased significantly. The purpose of this study was to analyze the clinical characteristics and prognosis of patients under 50 years old. Methods: Patients with PNETs recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 were analyzed. The clinical characteristics were analyzed by Chi-square test. The Kaplan-Meier method was used to estimate overall survival (OS). Multivariate Cox proportional risk regression analysis was used to determine independent prognostic factors. Results: 2,303 patients included, of which 547 (23.8%) patients were younger than 50 years old. The number of younger patients has increased steadily, while the proportion in total PNETs decreased recently. Compared with older group, the proportion of the Black, grade I/II, and surgery were higher in early-onset PNETs. Liver was the most frequent metastatic site. There was no significant difference in the incidence of different metastatic sites between younger and older PNETs patients, while younger patients had better OS (P < 0.05). Grade, N stage, M stage, and surgery were independent prognostic factors for OS in early-onset PNETs. Conclusions: Younger patients have unique clinicopathological characteristics compared with older patients in PNETs. Better OS was observed in younger patients which might due to the higher proportion of well-differentiated tumor and surgery than older patients.

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A Nomogram From The SEER Database For Predicting The Prognosis of Small Cell Lung Cancer With Different Patterns of Metastases

10.21203/rs.3.rs-801014/v1 ◽

2021 ◽

Author(s):

Hongli Ruan ◽

Yanmei Liu ◽

Huali Sun ◽

Yan Ding ◽

Shenpeng Ying ◽

...

Keyword(s):

Lung Cancer ◽

Liver Metastases ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Distant Metastases ◽

Small Cell ◽

Seer Database ◽

Small Cell Lung ◽

Training Set ◽

Validation Set

Abstract Backgroud: Distant metastases are one of the leading causes of high mortality in small cell lung cancer (SCLC). This research is aimed to investigate the different patterns of metastases in SCLC patients and their impact on prognosis based on the data from the Surveillance, Epidemiology, and End Results (SEER) database. Methods: The 2010-2015 SEER database of 15637 SCLC patients diagnosed from January to August were used as a training set for development of a nomogram. 7310 SCLC patients diagnosed from September to December were used as the validation set. Results: The overall survival (OS) of SCLC patients with no distant metastases, bone metastases, brain metastases, and liver metastases were 16.6, 9.1, 8.8 and 6.0 months, respectively. Patients with solitary liver metastases have the worst prognosis in the cases with single metastatic site. In the patients with multi-site metastases, the clinical outcomes of the cases combined with liver metastases were the worst. Our Cox model indicated that age, gender, American Joint Committee on Cancer (AJCC) stage, metastases, chemotherapy, radiation and surgery were independent predictors for OS in SCLC patients. The c-index value of nomogram was 7.52 in training set and 7.48 in of validation set for predicting OS in SCLC, indicating that the predictive ability of our nomogram model was of great superiority.Conclusion: The prognosis of SCLC patients with liver metastases alone or combined with other metastatic sites were worse than other metastatic models. Our nomogram model that integrated significant factors can aid as an individualized clinical predictive tool in SCLC patients.

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Establishment and Validation of a Clinically Predictive Nomogram Model for Thyroid Carcinoma Patients

10.21203/rs.3.rs-123528/v1 ◽

2020 ◽

Author(s):

Ruyi Zhang ◽

Mei Xu ◽

Xiangxiang Liu ◽

Miao Wang ◽

Qiang Jia ◽

...

Keyword(s):

Thyroid Carcinoma ◽

External Validation ◽

Cancer Staging ◽

Curve Analysis ◽

Calibration Plot ◽

Net Benefit ◽

Training Set ◽

Decision Curve Analysis ◽

Validation Set ◽

Good Calibration

Abstract Objectives To develop a clinically predictive nomogram model which can maximize patients’ net benefit in terms of predicting the prognosis of patients with thyroid carcinoma based on the 8th edition of the AJCC Cancer Staging method. MethodsWe selected 134,962 thyroid carcinoma patients diagnosed between 2004 and 2015 from SEER database with details of the 8th edition of the AJCC Cancer Staging Manual and separated those patients into two datasets randomly. The first dataset, training set, was used to build the nomogram model accounting for 80% (94,474 cases) and the second dataset, validation set, was used for external validation accounting for 20% (40,488 cases). Then we evaluated its clinical availability by analyzing DCA (Decision Curve Analysis) performance and evaluated its accuracy by calculating AUC, C-index as well as calibration plot.ResultsDecision curve analysis showed the final prediction model could maximize patients’ net benefit. In training set and validation set, Harrell’s Concordance Indexes were 0.9450 and 0.9421 respectively. Both sensitivity and specificity of three predicted time points (12 Months,36 Months and 60 Months) of two datasets were all above 0.80 except sensitivity of 60-month time point of validation set was 0.7662. AUCs of three predicted timepoints were 0.9562, 0.9273 and 0.9009 respectively for training set. Similarly, those numbers were 0.9645, 0.9329, and 0.8894 respectively for validation set. Calibration plot also showed that the nomogram model had a good calibration.ConclusionThe final nomogram model provided with both excellent accuracy and clinical availability and should be able to predict patients’ survival probability visually and accurately.

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Prognostic Nomogram and a Risk Classification System for Predicting Overall Survival of Elderly Patients with Fibrosarcoma: A Population-Based Study

Journal of Oncology ◽

10.1155/2021/9984217 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Fengkai Yang ◽

Hangkai Xie ◽

Yucheng Wang

Keyword(s):

Overall Survival ◽

Elderly Patients ◽

Classification System ◽

Cox Regression ◽

Predictive Accuracy ◽

Risk Classification ◽

Seer Database ◽

Training Set ◽

Decision Curve Analysis ◽

Validation Set

Background. The objective of this study was to develop a nomogram model and risk classification system to predict overall survival in elderly patients with fibrosarcoma. Methods. The study retrospectively collected data from the Surveillance, Epidemiology, and End Results (SEER) database relating to elderly patients diagnosed with fibrosarcoma between 1975 and 2015. Independent prognostic factors were identified using univariate and multivariate Cox regression analyses on the training set to construct a nomogram model for predicting the overall survival of patients at 3, 5, and 10 years. The receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the discrimination and predictive accuracy of the model. Decision curve analysis was used for assessing the clinical utility of the model. Result. A total of 357 elderly fibrosarcoma patients from the SEER database were included in our analysis, randomly classified into a training set (252) and a validation set (105). The multivariate Cox regression analysis of the training set demonstrated that age, surgery, grade, chemotherapy, and tumor stage were independent prognostic factors. The ROC showed good model discrimination, with AUC values of 0.837, 0.808, and 0.806 for 3, 5, and 10 years in the training set and 0.769, 0.779, and 0.770 for 3, 5, and 10 years in the validation set, respectively. The calibration curves and decision curve analysis showed that the model has high predictive accuracy and a high clinical application. In addition, a risk classification system was constructed to differentiate patients into three different mortality risk groups accurately. Conclusion. The nomogram model and risk classification system constructed by us help optimize patients’ treatment decisions to improve prognosis.

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Incidence of early-onset gastric and esophagus cancers has changed over time with disproportionate impact on Black and Hispanic patients.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.3_suppl.171 ◽

2021 ◽

Vol 39 (3_suppl) ◽

pp. 171-171

Author(s):

Nataly Valeria Torrejon ◽

Suneel Deepak Kamath ◽

Wei Wei ◽

Katherine Tullio ◽

Alok A. Khorana

Keyword(s):

Esophageal Cancer ◽

Early Onset ◽

Older Patients ◽

Young Patients ◽

Disease Stage ◽

P Value ◽

Black Patients ◽

Stage 4 ◽

Poorly Differentiated ◽

Over Time

171 Background: The increased incidence of gastro-esophageal junction adenocarcinoma has been well-described, but how the proportion of early versus older onset cancer has changed over time remains incompletely understood. This study characterized the socioeconomic and pathologic characteristics of early-onset gastro-esophageal malignancies. Methods: All patients with gastric cancer (GC) and esophageal cancer (EC) from 2004-2015 in the National Cancer Database were included and categorized by age under or over 60 years. Differences in demographics, disease stage, treatment characteristics and socioeconomic factors between young and older patients were assessed by Chi-square test. The effect of age, race, insurance status, community median income and community educational attainment on overall survival (OS) were assessed using uni- and multivariable Cox models with Bonferonni correction when indicated. Results: The study population comprised 158,599 patients with GC and 139,210 patients with EC. For GC, 43,146 patients (27.2%) were under age 60. The proportion of patients diagnosed under 60 increased over time: 26.7% in 2004-2006, 26.9% in 2007-2009, 27.6% in 2010-2012 and 27.5% in 2013-2015. Compared to older patients, young patients were more likely to be Black (16.7% vs. 13.2%), Asian (7.6% vs. 6.1%) or Hispanic (15.5% vs. 7.7%), diagnosed with stage 4 disease (43.5% vs. 31.3%) and to have poorly differentiated grade (61% vs. 51.7%), p value < 0.0001 for all. For EC, 38,801 patients (27.8%) were under age 60. The proportion of patients diagnosed under 60, decreased over time: 29.6% in 2004-2006, 28.3% in 2007-2009, 27.6% in 2010-2012 and 26.2 % in 2013-2015. Compared to older patients, young patients were more likely to be Black (12.6% vs. 8.2%) or Hispanic (4.2% vs. 3.1%), diagnosed with stage 4 disease (34.3% vs. 26.1%), p value < 0.0001 for all. There was no difference in histologic grade between younger and older patients (41.1% vs. 40.3%, p = 0.85). Age < 60 years was associated with improved OS in both GC and EC. After adjusting for other demographic, socioeconomic, disease stage and treatment-related factors, Black patients had the worst median OS compared to other races in both malignancies as shown in the Table. Conclusions: Early-onset GC has increased over time while early-onset EC has decreased. Patients with early-onset gastric and esophageal cancer are more likely to be Black or Hispanic and to present with stage 4 cancer. Younger patients with GC are also more likely to have poorly differentiated histology. Most concerning, Black patients have the worst OS compared to other races for both GC and EC. [Table: see text]

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Hemangiopericytoma: Incidence, Treatment, and Prognosis Analysis Based on SEER Database

BioMed Research International ◽

10.1155/2020/2468320 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Kewei Wang ◽

Fei Mei ◽

Sisi Wu ◽

Zui Tan

Keyword(s):

Retrospective Cohort ◽

Patient Survival ◽

Tumor Grade ◽

Clinicopathological Characteristics ◽

Clinical Usefulness ◽

Treatment Modalities ◽

Study Cohort ◽

Seer Database ◽

Cancer Specific Survival ◽

Patient Prognosis

Background. Hemangiopericytomas are rare tumors derived from pericytes surrounding the blood vessels. The clinicopathological characteristics and prognosis of hemangiopericytoma patients remain mostly unknown. In this retrospective cohort study, we assessed the clinicopathological characteristics of hemangiopericytoma patients, as well as the clinical usefulness of different treatment modalities. Material and Methods. We collected the clinicopathological data (between 1975 and 2016) of hemangiopericytoma and hemangioendothelioma patients from the Surveillance, Epidemiology, and End Results (SEER) database. Incidence, treatment, and patient prognosis were assessed. Results. Data from 1474 patients were analyzed in our study cohort (hemangiopericytoma: n = 1243 ; hemangioendothelioma: n = 231 ). The incidence of hemangiopericytoma in 2016 was 0.060 per 100,000 individuals. The overall survival (OS) and cancer-specific survival (CSS) did not differ between patients with hemangioendothelioma and those with hemangiopericytoma ( P = 0.721 , P = 0.544 ). The tumor grade had no effect on the OS of hemangiopericytoma patients. Multivariate analysis revealed the clinical usefulness of surgery in hemangiopericytoma patients ( HR = 0.15 , 95% confidence interval: 0.05-0.41, P < 0.001 ). In contrast, radiotherapy did not improve OS ( P = 0.497 ) or CSS ( P = 0.584 ), and chemotherapy worsened patient survival ( P < 0.001 ). Additionally, the combination of surgery and radiotherapy had a similar effect with surgery alone on hemangiopericytoma patient survival (OS: P = 0.900 ; CSS: P = 0.156 ). Surgery plus chemotherapy provided a worse clinical benefit than surgery alone ( P < 0.001 ). Conclusions. Our findings suggested that hemangiopericytoma had a similar prognosis with hemangioendothelioma. Surgery was the only effective treatment that provided survival benefits in hemangiopericytoma patients, while the clinical usefulness of adjuvant chemotherapy or radiotherapy was limited.

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Development and validation of a nomogram to predict overall survival for patients with metastatic renal cell carcinoma

10.21203/rs.3.rs-26209/v2 ◽

2020 ◽

Author(s):

Wenwen Zheng ◽

Weiwei Zhu ◽

Shengqiang Yu ◽

Kangqi Li ◽

Yuexia Ding ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Overall Survival ◽

Staging System ◽

Survival Prediction ◽

Seer Database ◽

Training Set ◽

Ajcc Staging System ◽

Validation Set ◽

Ajcc Staging ◽

Metastatic Rcc

Abstract Background: The prognosis of metastatic renal cell carcinoma (RCC) patients vary widely because of clinical and pathological heterogeneity. We aimed to develop a novel nomogram to predict overall survival (OS) for this population. Methods: Metastatic RCC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016. These patients were randomly assigned to a training set and a validation set at a ratio of 1:1. Significant prognostic factors of survival were identified through Cox regression models and then integrated to form a nomogram to predict 1-, 3- and 5-year OS. The nomogram was subsequently subjected to validations via the training and the validation sets. The performance of this model was evaluated by using Harrell’s concordance index (C-index), calibration curve, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). Results: Overall, 2315 eligible metastatic RCC patients were enrolled from the SEER database. A nomogram of survival prediction for patients of newly diagnosed with metastatic RCC was established, in which eight clinical factors significantly associated with OS were involved, including Fuhrman grade, lymph node status, sarcomatoid feature, cancer-directed surgery, bone metastasis, brain metastasis, liver metastasis, and lung metastasis. The new model presented better discrimination power than the American Joint Committee on Cancer (AJCC) staging system (7th edition) in the training set (C-indexes, 0.701 vs. 0.612, P <0.001) and the validation set (C-indexes, 0.676 vs. 0.600, P <0.001). The calibration plots of the nomogram exhibited optimal agreement between the predicted values and the observed values. The results of NRI and IDI also indicated the superior predictive capability of the nomogram relative to the AJCC staging system. The DCA plots revealed higher clinical use of our model in survival prediction. Conclusions: We developed and validated an effective nomogram to provide individual OS prediction for metastatic RCC patients, which would be beneficial to clinical trial design, patient counseling, and therapeutic modality selection.

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Impact of old age on resectable colorectal cancer outcomes

PeerJ ◽

10.7717/peerj.6350 ◽

2019 ◽

Vol 7 ◽

pp. e6350 ◽

Cited By ~ 1

Author(s):

Jianfei Fu ◽

Hang Ruan ◽

Hongjuan Zheng ◽

Cheng Cai ◽

Shishi Zhou ◽

...

Keyword(s):

Colorectal Cancer ◽

Regression Model ◽

Old Age ◽

Older Patients ◽

Cox Regression ◽

External Validation ◽

Seer Database ◽

Cancer Specific Survival ◽

Cox Regression Model ◽

The Impact

Objective This study was performed to identify a reasonable cutoff age for defining older patients with colorectal cancer (CRC) and to examine whether old age was related with increased colorectal cancer-specific death (CSD) and poor colorectal cancer-specific survival (CSS). Methods A total of 76,858 eligible patients from the surveillance, epidemiology, and end results (SEER) database were included in this study. The Cox proportional hazard regression model and the Chow test were used to determine a suitable cutoff age for defining the older group. Furthermore, a propensity score matching analysis was performed to adjust for heterogeneity between groups. A competing risk regression model was used to explore the impact of age on CSD and non-colorectal cancer-specific death (non-CSD). Kaplan–Meier survival curves were plotted to compare CSS between groups. Also, a Cox regression model was used to validate the results. External validation was performed on data from 1998 to 2003 retrieved from the SEER database. Results Based on a cutoff age of 70 years, the examined cohort of patients was classified into a younger group (n = 51,915, <70 years of old) and an older group (n = 24,943, ≥70 years of old). Compared with younger patients, older patients were more likely to have fewer lymph nodes sampled and were less likely to receive chemotherapy and radiotherapy. When adjusted for other covariates, age-dependent differences of 5-year CSD and 5-year non-CSD were significant in the younger and older groups (15.84% and 22.42%, P < 0.001; 5.21% and 14.21%, P < 0.001). Also an age of ≥70 years remained associated with worse CSS comparing with younger group (subdistribution hazard ratio, 1.51 95% confidence interval (CI) [1.45–1.57], P < 0.001). The Cox regression model as a sensitivity analysis had a similar result. External validation also supported an age of 70 years as a suitable cutoff, and this older group was associated with having reduced CSS and increased CSD. Conclusions A total of 70 is a suitable cutoff age to define those considered as having elderly CRC. Elderly CRC was associated with not only increased non-CSD but also with increased CSD. Further research is needed to provide evidence of whether cases of elderly CRC should receive stronger treatment if possible.

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