scholarly journals Nomogram for predicting cancer-specific survival in undifferentiated pleomorphic sarcoma: A Surveillance, Epidemiology, and End Results -based study

2021 ◽  
Vol 28 ◽  
pp. 107327482110367
Author(s):  
Fengshuo Xu ◽  
Fanfan Zhao ◽  
Xiaojie Feng ◽  
Chengzhuo Li ◽  
Didi Han ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Regression Model ◽  
Cox Regression ◽  
External Validation ◽  
Cancer Specific Survival ◽  
Cox Regression Model ◽  
Training Cohort ◽  
Undifferentiated Pleomorphic Sarcoma ◽  
Pleomorphic Sarcoma ◽  
End Results

Introduction The purpose of this study was to construct and validate a nomogram for predicting cancer-specific survival (CSS) in undifferentiated pleomorphic sarcoma (UPS) patients at 3, 5, and 8 years after the diagnosis. Methods Data for UPS patients were extracted from the SEER (Surveillance, Epidemiology, and End Results) database. The patients were randomly divided into a training cohort (70%) and a validation cohort (30%). The backward stepwise Cox regression model was used to select independent prognostic factors. All of the factors were integrated into the nomogram to predict the CSS rates in UPS patients at 3, 5, and 8 years after the diagnosis. The nomogram’ s performance was then validated using multiple indicators, including the area under the time-dependent receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, decision-curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Results This study included 2,009 UPS patients. Ten prognostic factors were identified after analysis of the Cox regression model in the training cohort, which were year of diagnosis, age, race, primary site, histological grade, T, N, M stage, surgery status, and insurance status. The nomogram was then constructed and validated internally and externally. The relatively high C-indexes and AUC values indicated that the nomogram has good discrimination ability. The calibration curves revealed that the nomogram was well calibrated. NRI and IDI values were both improved, indicating that our nomogram was superior to the AJCC (American Joint Committee on Cancer) system. DCA curves demonstrated that the nomogram was clinically useful. Conclusions The first nomogram for predicting the prognosis of UPS patients has been constructed and validated. Its usability and performance showed that the nomogram can be applied to clinical practice. However, further external validation is still needed.

scholarly journals Impact of old age on resectable colorectal cancer outcomes

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6350 ◽  
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.

scholarly journals Development and validation of nomograms for prediction of overall survival and cancer-specific survival of patients of colorectal cancer

2019 ◽  
Vol 50 (3) ◽  
pp. 261-269
Author(s):  
Jieyun Zhang ◽  
Yue Yang ◽  
Xiaojian Fu ◽  
Weijian Guo
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Prognostic Model ◽  
Cox Regression ◽  
External Validation ◽  
Cancer Prognosis ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Development And Validation

Abstract Purpose Nomograms are intuitive tools for individualized cancer prognosis. We sought to develop a clinical nomogram for prediction of overall survival and cancer-specific survival for patients with colorectal cancer. Methods Patients with colorectal cancer diagnosed between 1988 and 2006 and those who underwent surgery were retrieved from the Surveillance, Epidemiology, and End Results database and randomly divided into the training (n = 119 797) and validation (n = 119 797) cohorts. Log-rank and multivariate Cox regression analyses were used in our analysis. To find out death from other cancer causes and non-cancer causes, a competing-risks model was used, based on which we integrated these significant prognostic factors into nomograms and subjected the nomograms to bootstrap internal validation and to external validation. Results The 1-, 3-, 5- and 10-year probabilities of overall survival in patients of colorectal cancer after surgery intervention were 83.04, 65.54, 54.79 and 38.62%, respectively. The 1-, 3-, 5- and 10-year cancer-specific survival was 87.36, 73.44, 66.22 and 59.11%, respectively. Nine independent prognostic factors for overall survival and nine independent prognostic factors for cancer specific survival were included to build the nomograms. Internal and external validation CI indexes of overall survival were 0.722 and 0.721, and those of cancer-specific survival were 0.765 and 0.766, which was satisfactory. Conclusions Nomograms for prediction of overall survival and cancer-specific survival of patients with colorectal cancer. Performance of the model was excellent. This practical prognostic model may help clinicians in decision-making and design of clinical studies.

scholarly journals Nomogram for Predicting the Overall Survival and Cancer-Specific Survival of Patients with Occult Breast Cancer: A Population-Based Study

2021 ◽  
Author(s):  
Yang-Yu Huang ◽  
Guowei Ma ◽  
Shen-Hua Liang ◽  
Lei-Lei Wu ◽  
Xuan Liu
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Cancer Patients ◽  
Subgroup Analysis ◽  
External Validation ◽  
Breast Cancer Patients ◽  
Cancer Specific Survival ◽  
Occult Breast Cancer ◽  
Training Cohort

Abstract Background: Occult breast cancer is a rare breast tumor, whose prognostic nomogram model has not been established. Thus, we aim to develop and validate a nomogram for evaluating the overall survival (OS) and cancer-specific survival (CSS) of patients with occult breast cancer. Methods: Between 2004 and 2015, 704 eligible occult breast cancer patients were screened from the Surveillance, Epidemiology, and End Results (SEER) database using specific inclusion and exclusion criteria and then included in the surveillance. They were randomly divided into a training cohort (n = 494) and a validation cohort (N = 210). Univariate and multivariate Cox analyses were performed to explore independent prognostic factors and establish two survival-related nomograms. Area under the curve (AUC), consistency index (C index), internal and external validation calibration curve, decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analysis were used to evaluate the nomogram. Results: A total of seven variables were considered to be independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS): age, chemotherapy, radiotherapy, Progesterone receptor (PR) status, N stage, number of lymph node examinations, and number of positive lymph nodes. In the training cohort, the OS nomogram-predicted AUC for three, five, and ten years were 0.792, 0.775, and 0.783, respectively, while those of the CSS nomogram were 0.807, 0.817, and 0.812, respectively. The calibration chart showed excellent agreement between the actual and the nomogram-predicted survival rates in both the training and validation cohorts. The C-index values ​​of the OS nomogram in the training and validation cohorts were 0.762 and 0.782, respectively, while those ​​of the CSS nomogram were 0.786 and 0.816, respectively. DCA and subgroup analysis proved the usefulness of nomograms. Conclusion: The developed nomogram provided a comprehensive visual model of the risk of each prognostic factor. It can be conveniently used as a personalized prediction tool for the prognosis of occult breast cancer patients.

scholarly journals External Validation of a Nomogram and Risk Grouping System for Predicting Individual Prognosis of Patients With Medulloblastoma

2020 ◽  
Vol 11 ◽  
Author(s):  
Chengcheng Guo ◽  
Dunchen Yao ◽  
Xiaoping Lin ◽  
He Huang ◽  
Ji Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Treatment Plan ◽  
External Validation ◽  
Risk Groups ◽  
Cancer Center ◽  
Training Cohort ◽  
Cox Regression Analysis ◽  
Risk Grouping

Background: Medulloblastoma (MB) is one of the most malignant neuroepithelial tumors in the central nervous system. This study aimed to establish an effective prognostic nomogram and risk grouping system for predicting overall survival (OS) of patients with MB.Materials and Methods: The nomogram was constructed based on data from the database of Surveillance, Epidemiology, and End Results (SEER). This database consisted of 2,824 patients with medulloblastoma and was used as the training cohort. The data of another additional 161 patients treated at the Sun Yat-sen University Cancer Center (SYSUCC) were used as the external validation cohort. Cox regression analysis was used to select independent prognostic factors. Concordance index (C-index) and calibration curve were used to predict the prognostic effect of the nomogram for overall survival.Results: In the training cohort, Cox regression analyses showed that the prognostic factors included histopathology, surgery, radiotherapy, chemotherapy, tumor size, dissemination, and age at diagnosis. The internal and external validated C-indexes were 0.681 and 0.644, respectively. Calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year OS for patients with MB precisely. Using the training cohort, a risk grouping system was built, which could perfectly classify patients into four risk nomogroups with a 5-year survival rate of 83.9%, 76.5%, 64.5%, and 46.8%, respectively.Conclusion: We built and validated a nomogram and risk grouping system that can provide individual prediction of OS and distinguish MB patients from different risk groups. This nomogram and risk grouping system could help clinicians making better treatment plan and prognostic assessment.

scholarly journals Prognostic and Predictive Value of m6A “Eraser” Related Gene Signature in Gastric Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Xin Xu ◽  
En Zhou ◽  
Jun Zheng ◽  
Chihao Zhang ◽  
Yinghua Zou ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Factors ◽  
Regression Model ◽  
Cox Regression ◽  
Risk Group ◽  
Critical Role ◽  
Predictive Tool ◽  
Cox Regression Model ◽  
Risk Genes ◽  
Related Risk

BackgroundN6-methyladenosine (m6A) RNA modification plays a critical role in gastric cancer (GC). However, the relationship between the m6A “eraser”, FTO, and ALKBH5, and the prognosis of GC still remains unclear. This study aimed to evaluate the effect of FTO and ALKBH5 on the prognosis of patients and their potential roles in GC.Materials and MethodsA total of 738 GC samples with clinical information obtained from two independent datasets were included and divided into training set and testing set. Differential expression analysis of the m6A “eraser” related genes was performed. The LASSO Cox regression model was constructed to analyze the m6A “eraser” related risk genes. The univariate and multivariate Cox regression model were employed to identify the independent prognostic factors. Kaplan-Meier method was used for survival analysis. A nomogram model was then carried out to predict the prognosis of GC patients. Additionally, GO and KEGG analyses were conducted to identify the potential role of the m6A “eraser” related genes in GC. The relative proportion of 22 different genotypes in immune infiltrating cells was calculated by CIBERSORT algorithm.ResultsIn total, nine m6A “eraser” related risk genes and risk scores were obtained and calculated. Patients in high-risk group demonstrated significantly worse prognosis than those in low-risk group. Age, stage, and risk score were considered as independent prognostic factors. The nomogram model constructed accurately predicted the 3-year and 5-year overall survival (OS) of patients. Furthermore, m6A “eraser” might play a functional role in GC. The expression of m6A “eraser” leads to changes in tumor immune microenvironment.ConclusionsFTO and ALKBH5 showed association with the prognosis of GC. The m6A “eraser” related genes, which is considered as a reliable prognostic and predictive tool, assists in predicting the OS in GC patients.

scholarly journals Prognostic Factors in Non-Occlusive Mesenteric Ischemia: A Pragmatic Pre-Operative Score for the Prediction of 28-day Mortality

2021 ◽  
Author(s):  
PAUL CALAME ◽  
Hadrien Winiszewski ◽  
Alexandre Doussot ◽  
Zaher Lakkis ◽  
Pierre Verdot ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Regression Model ◽  
Mesenteric Ischemia ◽  
Cox Regression ◽  
Cox Regression Model ◽  
Factors Associated ◽  
Icu Admission ◽  
Enhanced Ct ◽  
Occlusive Mesenteric Ischemia ◽  
Preoperative Factors

Abstract Background The prognosis of critical ill patients with non-occlusive mesenteric ischemia (NOMI) is poor and not fully understood. Preoperative prognostic factors are needed. The aim of this study was to determine preoperative factors associated with 28-day mortality in a cohort of ICU patients requiring laparotomy for NOMI. The secondary objective was to determine general prognostic factors associated with NOMI. Methods This retrospective observational study was performed in a University Hospital among critically ill patients 18 years old or older who underwent a laparotomy for NOMI from January 1, 2009 to December 31, 2019, and who had an available contrast enhanced CT with at least one portal venous phase. Variables were collected at the time of the CT. All variables associated with 28-day mortality were entered into a multivariate cox regression model and were used to compute a NOMI mortality score. Results During the study period, 154 patients underwent laparotomy for NOMI after having benefited from an abdominal enhanced CT. The 28-day mortality rate was 56%. Variable at the time of ICU admission and at the time of the CT were collected. Surgical and histopathologic findings were recorded. Multivariable analyses on 28-day mortality including variables at the time of the CT identified three independent variables (i.e. lactates > 7mmol/l, prothrombin rate < 60% and kidney infarction), included in a simple mortality score. For each variable associated with 28 days mortality, 1 point was attributed. Among the study population, the probability of 28-day mortality was 26% (11/42), 54% (26/48), 77% (23/30) and 100% (21/21) for a survival score of 0, 1, 2 and 3, respectively. A second explorative multivariate cox regression model including the variables at the time of ICU admission showed that jejunal transmural necrosis was the only operative finding associated with death (HR = 2.26 CI95%[1.14–4.71]). Conclusion We identified three preoperative factors independently associated with short-

scholarly journals A Robust Seven-Gene Signature Associated With Tumor Microenvironment to Predict Survival Outcomes of Patients With Stage III–IV Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Hao Zhao ◽  
Xuening Zhang ◽  
Lan Guo ◽  
Songhe Shi ◽  
Ciyong Lu
Keyword(s):  
High Risk ◽  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Regression Model ◽  
Cox Regression ◽  
Risk Group ◽  
External Validation ◽  
Gene Signature ◽  
Survival Outcomes ◽  
Cox Regression Model

BackgroundDue to the relatively insidious early symptoms of lung adenocarcinoma (LUAD), most LUAD patients are at an advanced stage at the time of diagnosis and lose the best chance of surgical resection. Mounting evidence suggested that the tumor microenvironment (TME) was highly correlated with tumor occurrence, progress, and prognosis. However, TME in advanced LUAD remained to be studied and reliable prognostic signatures based on TME in advanced LUAD also had not been well-established. This study aimed to understand the cell composition and function of TME and construct a gene signature associated with TME in advanced LUAD.MethodsThe immune, stromal, and ESTIMATE scores of each sample from The Cancer Genome Atlas (TCGA) database were, respectively, calculated using an ESTIMATE algorithm. The LASSO and Cox regression model were applied to select prognostic genes and to construct a gene signature associated with TME. Two independent datasets from the Gene Expression Omnibus (GEO) were used for external validation. Twenty-two subsets of tumor-infiltrating immune cells (Tiics) were analyzed using the CIBERSORT algorithm.ResultsFavorable overall survival (OS) and progression-free survival (PFS) were found in patients with high immune score (p = 0.048 and p = 0.028; respectively) and stromal score (p = 0.024 and p = 0.025; respectively). Based on the immune and stromal scores, 453 differentially expressed genes (DEGs) were identified. Using the LASSO and Cox regression model, a seven-gene signature containing AFAP1L2, CAMK1D, LOXL2, PIK3CG, PLEKHG1, RARRES2, and SPP1 was identified to construct a risk stratification model. The OS and PFS of the high-risk group were significantly worse than that of the low-risk group (p &lt; 0.001 and p &lt; 0.001; respectively). The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the seven-gene signature. Similar findings were validated in two independent cohorts. In addition, the proportion of macrophages M2 and Tregs was higher in high-risk patients (p = 0.041 and p = 0.022, respectively).ConclusionOur study established and validated a seven-gene signature associated with TME, which might serve as a prognosis stratification tool to predict survival outcomes of advanced LUAD patients. In addition, macrophages M2 polarization may lead to worse prognosis in patients with advanced LUAD.

Sign in / Sign up

Export Citation Format

Share Document