scholarly journals Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study

2021 ◽  
Vol 18 (15) ◽  
pp. 7734
Author(s):  
Nasrin Borumandnia ◽  
Hassan Doosti ◽  
Amirhossein Jalali ◽  
Soheila Khodakarim ◽  
Jamshid Yazdani Charati ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Family History ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Clinical Decision ◽  
Tumor Stage ◽  
Cox Proportional Hazards ◽  
National Study ◽  
Historical Cohort

Background: Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRC patients. Materials and methods: A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran’s three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve. Results: The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRC patients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650–0.734), as well as 0.627 (0.670, 0.686) in the test data. Conclusion: We improved a novel nomogram diagram according to factors for predicting OS in CRC patients, which could assist clinical decision-making and prognosis predictions in patients with CRC.

scholarly journals Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinjie Wu ◽  
Yanlei Wang ◽  
Wei Sun ◽  
Mingsheng Tan
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Training Group ◽  
Clinical Decision ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Predictive Values

Introduction. We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. Methods. The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes ( C -indexes) and calibration plots. Results. All 813 patients were randomly divided into a training group ( n = 572 ) and a validation group ( n = 241 ). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C -indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. Conclusions. The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making.

Association between primary tumor site, perioperative CEA ratio, smoking status, and overall survival in patients with colorectal cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15156-e15156
Author(s):  
Thomas A Odeny ◽  
Nicole Farha ◽  
Hannah Hildebrand ◽  
Jessica Allen ◽  
Wilfred Vazquez ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Multivariate Analysis ◽  
Proportional Hazards ◽  
Smoking Status ◽  
Tumor Stage ◽  
Tumor Location ◽  
Cox Proportional Hazards ◽  
P Value ◽  
Primary Tumor Site

e15156 Background: There are differences in the incidence, clinical presentation, molecular pathogenesis and outcome of colorectal cancer (CRC) based on tumor location. Emerging research suggests that perioperative carcinoembryonic antigen (CEA) ratio (post-op/pre-op CEA) is a prognostic factor for CRC patients. We aimed to determine the association between tumor location, CEA ratio, smoking status and overall survival (OS) among patients with CRC. Methods: We analysed 323 patients who underwent resection for CRC at KUMC. After excluding those without pre- or post-operative CEA data, 162 patients were classified as either high ( > = 0.5) or low ( < 0.5) ratio. Primary outcomes were: 1) OS stratified by tumor location; 2) OS stratified by CEA ratio; and 3) whether the association between CEA ratio and OS differed by tumor location, after adjusting for stage and smoking status. Kaplan-Meier method was used to estimate survival rates, and Cox proportional hazards models for multivariate analysis. Results: The median age was 63 years (inter-quartile range 53-72), 61% male, 43% smokers, 73% left-sided tumors, median pre-operative CEA was 3.0 (IQR 1.5-7), and 64% had CEA ratio > = 0.5. The OS rates were 85.7% and 91.9% in patients with left-sided vs right-sided tumors respectively (log-rank p-value = 0.9). The OS rates were 83.5% and 91.5% in patients with high vs low CEA ratios respectively (log-rank p-value = 0.3). The effect of CEA ratio on OS was significantly different when stratified by tumor location (p-value for interaction < 0.001). However, in the stratified analysis, the n was too small to permit further inferential analysis. In multivariate analysis, both tumor location (HR 0.6; p = 0.5) and CEA ratio (HR 1.5; p = 0.5) were not significantly associated with OS after adjusting for smoking status and tumor stage. Smoking was significantly associated with higher rates of death (HR 3.9; p = 0.04) when adjusted for tumor location, CEA ratio, and tumor stage. Conclusions: There was no difference in OS between left versus right-sided tumors. The association between CEA ratio and OS was significantly modified by tumor location. However, to attribute this modification to left vs right warrants validation in a larger cohort as our sample size was limited. Smoking increases mortality irrespective of right vs left sided CRC.

scholarly journals Are there sex differences among colorectal cancer patients in treatment and survival? A Swiss cohort study

2021 ◽  
Vol 147 (5) ◽  
pp. 1407-1419
Author(s):  
Manuela Limam ◽  
Katarina Luise Matthes ◽  
Giulia Pestoni ◽  
Eleftheria Michalopoulou ◽  
Leonhard Held ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regression Models ◽  
Proportional Hazards ◽  
Treatment Decision ◽  
Tumor Stage ◽  
Primary Treatment ◽  
Cox Proportional Hazards ◽  
Men And Women ◽  
Logistic Regression Models ◽  
Comorbidity Index

Abstract Background Colorectal cancer (CRC) is among the three most common incident cancers and causes of cancer death in Switzerland for both men and women. To promote aspects of gender medicine, we examined differences in treatment decision and survival by sex in CRC patients diagnosed 2000 and 2001 in the canton of Zurich, Switzerland. Methods Characteristics assessed of 1076 CRC patients were sex, tumor subsite, age at diagnosis, tumor stage, primary treatment option and comorbidity rated by the Charlson Comorbidity Index (CCI). Missing data for stage and comorbidities were completed using multivariate imputation by chained equations. We estimated the probability of receiving surgery versus another primary treatment using multivariable binomial logistic regression models. Univariable and multivariable Cox proportional hazards regression models were used for survival analysis. Results Females were older at diagnosis and had less comorbidities than men. There was no difference with respect to treatment decisions between men and women. The probability of receiving a primary treatment other than surgery was nearly twice as high in patients with the highest comorbidity index, CCI 2+, compared with patients without comorbidities. This effect was significantly stronger in women than in men (p-interaction = 0.010). Survival decreased with higher CCI, tumor stage and age in all CRC patients. Sex had no impact on survival. Conclusion The probability of receiving any primary treatment and survival were independent of sex. However, female CRC patients with the highest CCI appeared more likely to receive other therapy than surgery compared to their male counterparts.

scholarly journals Eps15 Homology Domain-Containing Protein 3 Hypermethylation as a Prognostic and Predictive Marker for Colorectal Cancer

Biomedicines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 453
Author(s):  
Yu-Han Wang ◽  
Shih-Ching Chang ◽  
Muhamad Ansar ◽  
Chin-Sheng Hung ◽  
Ruo-Kai Lin
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Mrna Expression ◽  
Proportional Hazards ◽  
Uterine Cancer ◽  
Colonic Polyps ◽  
Predictive Marker ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Eps15 Homology Domain

Colorectal cancer (CRC) arises from chromosomal instability, resulting from aberrant hypermethylation in tumor suppressor genes. This study identified hypermethylated genes in CRC and investigated how they affect clinical outcomes. Methylation levels of specific genes were analyzed from The Cancer Genome Atlas dataset and 20 breast cancer, 16 esophageal cancer, 33 lung cancer, 15 uterine cancer, 504 CRC, and 9 colon polyp tissues and 102 CRC plasma samples from a Taiwanese cohort. In the Asian cohort, Eps15 homology domain-containing protein 3 (EHD3) had twofold higher methylation in 44.4% of patients with colonic polyps, 37.3% of plasma from CRC patients, and 72.6% of CRC tissues, which was connected to vascular invasion and high microsatellite instability. Furthermore, EHD3 hypermethylation was detected in other gastrointestinal cancers. In the Asian CRC cohort, low EHD3 mRNA expression was found in 45.1% of patients and was connected to lymph node metastasis. Multivariate Cox proportional-hazards survival analysis revealed that hypermethylation in women and low mRNA expression were associated with overall survival. In the Western CRC cohort, EHD3 hypermethylation was also connected to overall survival and lower chemotherapy and antimetabolite response rates. In conclusion, EHD3 hypermethylation contributes to the development of CRC in both Asian and Western populations.

Phenotypic expression of Bax is a predictive marker of 5-fluorouracil treatment in colorectal cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 3605-3605
Author(s):  
U. Manne ◽  
C. Suarez-Cuervo ◽  
N. C. Jhala ◽  
J. Posey ◽  
C. B. Herring ◽  
...  
Keyword(s):  
Overall Survival ◽  
Predictive Value ◽  
Proportional Hazards ◽  
Phenotypic Expression ◽  
Tumor Stage ◽  
Cox Proportional Hazards ◽  
Nuclear Accumulation ◽  
Adjuvant Therapies ◽  
Post Surgery ◽  
Significant Difference

3605 Background: The anti-tumor activity of 5-fluorouracil (5-FU) has been related to its ability to induce apoptosis. Therefore, we assessed the predictive value of phenotypic expression of key apoptotic molecules in colorectal adenocarcinomas (CRC) of patients treated with 5-FU-based adjuvant therapies. Methods: Archival tissues of CRCs from 56 patients who received a complete regimen of 5-FU-based chemotherapy after surgery, and 56 age, gender, ethnicity, tumor stage, tumor location, and tumor differentiation matched patients who had undergone only surgery (without any pre- or post-surgery chemo- or radiation therapy), were evaluated for immunophenotypic expression of Bax, Bcl-2 and nuclear accumulation of p53 (p53nac). Immunophenotypic expression of these markers was categorized into low and high expressors and cut-point values were determined based on their expression in benign epithelium. These tumors Ability of these markers in predicting the efficacy of 5-FU-based treatment was assessed by estimating overall survival utilizing the Kaplan-Meier and Cox proportional hazards methods. Results: There was no significant difference in overall survival rates between the two patient categories (logrank P=0.487). However, a better survival was observed for patients who received chemotherapy when their CRCs lacked Bax expression; in contrast, patients with high Bax expression CRCs had worse survival when they received chemotherapy (logrank P=0.016). Surgically treated patients with CRCs lacked Bax expression had 5.33 times higher mortality than those with high Bax expression (HR, 5.33; CI: 1.78–15.94), when controlled for tumor stage and other confounding variables. Bcl-2 or p53nac had no predictive value in either patient group. Conclusions: These preliminary findings are the first to provide good evidence to suggest that patients with CRCs lacking Bax phenotypic expression benefit from 5-FU-based adjuvant therapies but not those with high Bax expression (Supported by NIH/NCI R01-CA98932–01). No significant financial relationships to disclose.

Discovery and validation of a cross-platform 21-gene prognostic signature in neuroblastoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10035-10035
Author(s):  
Mehul Gupta ◽  
Sunand Nageswaran Kannappan ◽  
Aru Narendran ◽  
Pinaki Bose
Keyword(s):  
Machine Learning ◽  
Risk Stratification ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Risk Model ◽  
Learning Algorithm ◽  
Clinical Decision ◽  
Gene Signature ◽  
Cox Proportional Hazards ◽  
Transcriptomic Signature

10035 Background: Neuroblastoma (NB) is the most common extracranial solid tumor in children. Despite the development of risk stratification tools to improve prognostication, prediction of patient survival outcomes in NB remains poor. In this study we used an unbiased machine-learning algorithm to develop and validate a transcriptomic signature capable of predicting 5-year overall (OS) and event-free survival (EFS) in these patients. Methods: The TARGET-Neuroblastoma dataset (n = 243) was used as the training set. Two independent NB cohorts, E-MTAB-179 (n = 478) and GSE85047 (n = 266) were used as validation sets. Elastic net regression was employed to identify transcripts associated with EFS. Association of the developed signature with EFS and OS was evaluated using univariate Cox proportional hazards (CoxPH), Kaplan-Meier, and 5-year receiver-operator characteristic curves in validation cohorts. Further, the independent prognostic value of the signature was assessed using multivariate CoxPH models with relevant clinicopathologic variables including age, INSS stage, and N-Myc amplification status in both validation sets. Finally, a nomogram was developed to integrate the signature with prognostic clinicopathologic variables to evaluate their combined efficacy for prediction of 5-year EFS and OS. Results: We identified a 21-gene signature that demonstrates significant association with EFS and OS in both E-MTAB-178 and GSE49710 validation cohorts. Moreover, the signature is independent of clinicopathological variables and can be effectively incorporated into a risk model, improving the prognostic performance. Several genes within the signature have been previously implicated in NB, including ECEL1, HOXC9 and ARAF1. Conclusions: To the best of our knowledge, we are the first to use an unbiased machine learning approach to generate a transcriptomic gene signature for neuroblastoma prognosis externally validated in multiple cohorts across platforms. This 21-gene transcriptomic signature significantly associated with EFS and OS in this disease. Combining this signature with current prognostic clinicopathologic variables will improve risk stratification of affected patients and may inform effective clinical decision-making.[Table: see text]

scholarly journals Predicting Clustered Dental Implant Survival Using Frailty Methods

2006 ◽  
Vol 85 (12) ◽  
pp. 1147-1151 ◽  
Author(s):  
S.-K. Chuang ◽  
T. Cai
Keyword(s):  
Risk Factors ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Smoking Status ◽  
Joint Probability ◽  
Frailty Model ◽  
Clinical Decision ◽  
Cox Proportional Hazards ◽  
Implant Survival ◽  
Survival Status

The purpose of this study was to predict future implant survival using information on risk factors and on the survival status of an individual’s existing implant(s). We considered a retrospective cohort study with 677 individuals having 2349 implants placed. We proposed to predict the survival probabilities using the Cox proportional hazards frailty model, with three important risk factors: smoking status, timing of placement, and implant staging. For a non-smoking individual with 2 implants placed, an immediate implant and in one stage, the marginal probability that 1 implant would survive 12 months was 85.8% (95%CI: 77%, 91.7%), and the predicted joint probability of surviving for 12 months was 75.1% (95%CI: 62.1%, 84.7%). If 1 implant was placed earlier and had survived for 12 months, then the second implant had an 87.5% (95%CI: 80.3%, 92.4%) chance of surviving 12 months. Such conditional and joint predictions can assist in clinical decision-making for individuals.

Prognostic effect of inflammatory genes on stage I-III colorectal cancer – integrative analysis of TCGA data

2020 ◽  
Author(s):  
Eun Kyung Choe ◽  
Sangwoo Lee ◽  
So Yeon Kim ◽  
Manu Shivakumar ◽  
Kyu Joo Park ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Clinical Features ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Integrative Analysis ◽  
Stage I ◽  
The Cancer Genome Atlas ◽  
Integrative Model ◽  
Inflammatory Status

Abstract Background Inflammatory status indicators have been reported as a prognostic biomarker of colorectal cancer (CRC). However, since the inflammatory interactions with colon involve various modes of action, the biological mechanism to link inflammation and CRC prognosis is not fully elucidated. We comprehensively evaluated the predictive role of the expression and methylation level of inflammation-related genes for CRC prognosis and their pathophysiological associations. Method An integrative analysis was conducted on 247 patients of stage I-III CRC from The Cancer Genome Atlas. Lasso-penalized Cox proportional hazards regression (Lasso-Cox) and statistical Cox proportional hazard regression (CPH) were used for analysis. Result Models to predict overall survival were designed with respective combinations of clinical variables, including age, sex, stage, gene expression, and methylation. An integrative model combining expression, methylation, and clinical features had the highest performance (median C-index=0.756), compared to the model with clinical features alone (median C-index=0.726). By multivariate CPH with features from the best model, methylation levels of CEP250, RAB21 and TNPO3 were significantly associated with overall survival. They did not share any biological process in functional networks. The 5-year survival rate was 29.8% in a low methylation group of CEP250 and 79.1% in a high (P <0.001). Conclusion Our study result implicates the importance of integrating the expression and methylation information along with clinical information in prediction of survival. CEP250, RAB21 and TNPO3, in the prediction model might have a crucial role in CRC prognosis and further improve our understanding of potential mechanisms linking inflammatory reaction and CRC progression.

Association between primary tumor site, perioperative CEA ratio, and overall survival in patients with colorectal cancer.

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 518-518
Author(s):  
Thomas A Odeny ◽  
Nicole Farha ◽  
Wilfred Vazquez ◽  
Amna Batool ◽  
Anwaar Saeed ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Multivariate Analysis ◽  
Smoking Status ◽  
Tumor Stage ◽  
Tumor Location ◽  
Effect Modification ◽  
Cox Proportional Hazards ◽  
P Value ◽  
Primary Tumor Site

518 Background: There are differences in the incidence, clinical presentation, molecular pathogenesis and outcome of colorectal cancer (CRC) based on the tumor location. Emerging research suggests that the perioperative carcinoembryonic antigen (CEA) ratio is a prognostic factor for CRC patients. We aimed to determine the association between tumor location, perioperative CEA ratio, and 5-year survival among patients with CRC. Methods: We analyzed 111 patients who underwent resection for CRC at KUMC. After excluding patients without pre- or post-operative CEA data, 62 patients for whom we could calculate a CEA ratio (post-op/pre-op CEA) were classified as either high ( ≥ 0.5) or low ( < 0.5) ratio. The primary outcomes were: 1) overall survival (OS) stratified by tumor location; 2) OS stratified by CEA ratio; and 3) whether there was effect modification by tumor location, of the association between perioperative CEA ratio and OS, after adjusting for tumor stage and smoking status. Kaplan-Meier method was used to estimate survival rates, and Cox proportional hazards models for multivariate analysis. Results: The median age was 61 years, 54% male, 31% smokers, 74% left-sided tumors, median pre-operative CEA was 3.3, and 60% had CEA ratio ≥ 0.5. The OS rates were 89.1% and 81.3% in patients with left-sided versus right-sided tumors respectively (p-value = 0.4). The OS rates were 83.8% and 92.0% in patients with high versus low CEA ratios respectively (p-value = 0.3). There was effect modification by tumor location on association between CEA ratio and OS, after adjusting for smoking status and tumor stage (p-value < 0.001). However, in the stratified analysis, the n was too small to permit inferential analysis. In multivariate analysis, both tumor location (HR 0.4; p = 0.3) and perioperative CEA ratio (HR 2.7; p = 0.3) were not significantly associated with OS after adjusting for smoking status and tumor stage. Conclusions: There was no difference in OS between left versus right-sided tumors. The association between perioperative CEA ratio and OS was significantly modified by tumor location. However, to attribute this modification to left versus right warrants validation in a larger cohort as our sample size was limited.

scholarly journals Predictors of colorectal cancer survival using cox regression and random survival forests models based on gene expression data

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261625
Author(s):  
Mohanad Mohammed ◽  
Innocent B. Mboya ◽  
Henry Mwambi ◽  
Murtada K. Elbashir ◽  
Bernard Omolo
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Missing Values ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Predictive Performance ◽  
Cox Proportional Hazards ◽  
Rank Score ◽  
Detection And Diagnosis ◽  
Better Than

Understanding and identifying the markers and clinical information that are associated with colorectal cancer (CRC) patient survival is needed for early detection and diagnosis. In this work, we aimed to build a simple model using Cox proportional hazards (PH) and random survival forest (RSF) and find a robust signature for predicting CRC overall survival. We used stepwise regression to develop Cox PH model to analyse 54 common differentially expressed genes from three mutations. RSF is applied using log-rank and log-rank-score based on 5000 survival trees, and therefore, variables important obtained to find the genes that are most influential for CRC survival. We compared the predictive performance of the Cox PH model and RSF for early CRC detection and diagnosis. The results indicate that SLC9A8, IER5, ARSJ, ANKRD27, and PIPOX genes were significantly associated with the CRC overall survival. In addition, age, sex, and stages are also affecting the CRC overall survival. The RSF model using log-rank is better than log-rank-score, while log-rank-score needed more trees to stabilize. Overall, the imputation of missing values enhanced the model’s predictive performance. In addition, Cox PH predictive performance was better than RSF.

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