scholarly journals Construction of immune-related lncRNA signature to predict aggressiveness, immune landscape, and drug resistance of colorectal cancer

2021 ◽  
Author(s):  
Yonggan Xue ◽  
Bobin Ning ◽  
Hongyi Liu ◽  
Baoqing JIa
Keyword(s):  
Colorectal Cancer ◽  
Survival Data ◽  
Clinical Characteristics ◽  
Risk Model ◽  
Expression Patterns ◽  
Risk Groups ◽  
Survival Outcomes ◽  
Lasso Regression ◽  
Optimal Cutoff ◽  
Treatment Regimens

Abstract Background Colorectal cancer (CRC) remains one of the most common malignancies across the world, threatening almost millions of lives every year and increasingly adding the social-economical burden. Thus far, a biomarker, which can comprehensively predict the survival outcomes, clinical characteristics, and therapeutic sensitivity, is still lacking. Results This study established a pair-risk model, together with, an exp-risk model to predict biological characteristics of CRC based on immune-related lncRNA (irlncRNA) expression patterns. We retrieved transcriptomic data of CRC, including 473 tumor samples and 41 normal samples, and identified 739 irlncRNA through co-expression analysis, and constructed irlncRNA pairs. After integrating with clinical survival data, we established an 11 irlncRNA pairs signature using Lasso regression analysis. We next drew the 1-, 5-, 10-year curve line of receiver operating characteristic (ROC), calculated the areas under the curve (AUC), and recognized the optimal cutoff point. Patients with CRC were stratified into high- and low-risk groups based on the optimal cutoff value. Then, we validated the pair-risk model in terms of the survival outcomes of the patients. Moreover, we tested the reliability of the pair-risk model for predicting tumor aggressiveness and therapeutic responsiveness of CRC. Additionally, we reemployed the 11 of irlncRNAs involved in the pair-risk model to constructed an expression risk model that was also highly predictive of prognostic outcomes of CRC patients. Importantly, combining the pair-risk model and exp-risk model yielded a more robust approach for predicting the survival outcomes of patients with CRC. Conclusions We suggest that the irlncRNA-based risk models can be utilized as prognostic tools to predict survival outcomes and clinical characteristics and guide treatment regimens of CRC.

scholarly journals Construction of immune-related lncRNA signature to predict aggressiveness, immune landscape, and drug resistance of colorectal cancer

2021 ◽  
Author(s):  
Yonggan Xue ◽  
Bobin Ning ◽  
Hongyi Liu ◽  
Baoqing Jia
Keyword(s):  
Colorectal Cancer ◽  
Survival Data ◽  
Clinical Characteristics ◽  
Risk Model ◽  
Survival Outcomes ◽  
Lasso Regression ◽  
Differential Analysis ◽  
Operating Characteristics ◽  
Treatment Regimens ◽  
Hr Model

Abstract Background:Colorectal cancer (CRC) remains one of the most common malignancies across the world. Thus far, a biomarker, which can comprehensively predict the survival outcomes, clinical characteristics, and therapeutic sensitivity, is still lacking. Methods: We leveraged retrieved transcriptomic data of CRC from the public database, and constructed irlncRNA pairs. After integrating with clinical survival data, we performed differential analysis and constructed 11 irlncRNA pairs signature using Lasso regression analysis. We next drew the 1-, 5-, 10-year curve line of receiver operating characteristics, calculated the areas under the curve, and recognized the optimal cutoff point. Then, we validated the pair-risk model in terms of the survival outcomes of the patients. Moreover, we tested the reliability of the pair-risk model for predicting tumor aggressiveness and therapeutic responsiveness of CRC. Additionally, we reemployed the 11 of irlncRNAs involved in the pair-risk model to construct an expression risk model that was also highly predictive of prognostic outcomes of CRC patients. Results:We recognized a total of 377 DEirlcRNAs, including 28 low-expressed and 349 high-expressed irlncRNAs in CRC patients. After performing a univariant Cox analysis, we identified 115 risk irlncRNAs that were significantly correlated with survival outcomes of patients with CRC. By taking the intersection of the DEirlcRNAs and the risk irlncRNAs, we ultimately recognized 55 irlncRNA as core irlncRNAs. Then, we established a Cox HR model (pair-risk model) as well as an expression HR model (exp-risk model). We found that both of the two models significantly outperformed the common-used clinical characteristics, including age, T, N, and M stages, in terms of predicting survival outcomes. Moreover, we validated the pair-risk model can serve as a potential tool for studying the tumor microenvironment of CRC and drug response. Additionally, we noticed that combining the pair-risk model and exp-risk model yielded a more robust approach for predicting the survival outcomes of patients with CRC.Conclusions:We suggest that the irlncRNA-based risk models can be utilized as prognostic tools to predict survival outcomes and clinical characteristics and guide treatment regimens of CRC.

Immune Characteristics-Related Typing of Colorectal Cancer and the Establishment of 14-Gene Prognostic Model

2021 ◽  
Author(s):  
Jianxing Ma ◽  
Chen Wang
Keyword(s):  
Colorectal Cancer ◽  
Risk Model ◽  
Cox Regression ◽  
Nonnegative Matrix ◽  
Test Group ◽  
Progression Free Survival ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Lasso Regression ◽  
Immune Related Genes

Abstract This study is to establish NMF (nonnegative matrix factorization) typing related to the tumor microenvironment (TME) of colorectal cancer (CRC) and to construct a gene model related to prognosis to be able to more accurately estimate the prognosis of CRC patients. NMF algorithm was used to classify samples merged clinical data of differentially expressed genes (DEGs) of TCGA that are related to the TME shared in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, and survival differences between subtype groups were compared. By using createData Partition command, TCGA database samples were randomly divided into train group and test group. Then the univariate Cox analysis, Lasso regression and multivariate Cox regression models were used to obtain risk model formula, which is used to score the samples in the train group, test group and GEO database, and to divide the samples of each group into high-risk and low-risk groups, according to the median score of the train group. After that, the model was validated. Patients with CRC were divided into 2, 3, 5 subtypes respectively. The comparison of patients with overall survival (OS) and progression-free survival (PFS) showed that the method of typing with the rank set to 5 was the most statistically significant (p=0.007, p<0.001, respectively). Moreover, the model constructed containing 14 immune-related genes (PPARGC1A, CXCL11, PCOLCE2, GABRD, TRAF5, FOXD1, NXPH4, ALPK3, KCNJ11, NPR1, F2RL2, CD36, CCNF, DUSP14) can be used as an independent prognostic factor, which is superior to some previous models in terms of patient prognosis. The 5-type typing of CRC patients and the 14 immune-related genes model constructed by us can accurately estimate the prognosis of patients with CRC.

scholarly journals Risk classification as the basis for clinical staging of diffuse large- cell lymphoma derived from 10-year survival data

Blood ◽  
1989 ◽  
Vol 74 (2) ◽  
pp. 551-557 ◽  
Author(s):  
WS Velasquez ◽  
S Jagannath ◽  
SL Tucker ◽  
LM Fuller ◽  
LB North ◽  
...  
Keyword(s):  
Survival Data ◽  
Risk Model ◽  
Survival Rates ◽  
Staging System ◽  
Large Cell ◽  
Risk Groups ◽  
Lactic Dehydrogenase ◽  
Tumor Burden ◽  
Clinical Staging ◽  
Ann Arbor

Two hundred and fifty previously untreated adult patients with diffuse large-cell lymphomas were treated with a chemotherapy combination of cyclophosphamide, adriamycin, vincristine, prednisone, and low-dose bleomycin (CHOP-Bleo) with or without radiotherapy between 1974 and 1984. The 10-year survival rates for patients with Ann Arbor stages II, III, or IV disease of 55%, 42%, and 40%, respectively, were not significantly different. However, the survival rate of 76% for patients with stage I disease was clearly better. Factors more indicative of prognosis than stage, as found by univariant analysis, were tumor burden, serum lactic dehydrogenase level (LDH), age, and constitutional symptoms. From these, a multivariant analysis selected tumor burden, LDH level, and age as major independent factors for predicting survival (P less than .001). A prognostic risk model constructed on the basis of tumor burden and LDH levels identified four distinct risk groups (A, B, C, D) with 10-year survival rates of 85%, 66%, and 43% for A, B, and C. No patient in group D survived 10 years. These risk groups also had a strong correlation with complete remission rates and with relapse rates. Thus this model proved more effective for identifying patient populations according to their expected responses, durations of remission, and survivals than the Ann Arbor staging system. Detailed information supporting the use of this system for predicting prognosis and for treatment selection for patients with diffuse large-cell lymphomas is provided.

scholarly journals Application of ensemble clustering and survival tree analysis for identifying prognostic clinicogenomic features in patients with colorectal cancer from the 100,000 Genomes Project

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yuguo Wei ◽  
Nikolaos Papachristou ◽  
Stefanie Mueller ◽  
J. C. Ambrose ◽  
P. Arumugam ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Model ◽  
Cox Model ◽  
Risk Groups ◽  
Rank Test ◽  
Cancer Stage ◽  
Ensemble Clustering ◽  
Stage 4 ◽  
Cluster 2 ◽  
Survival Tree

Abstract Objective The objective of this study was to employ ensemble clustering and tree-based risk model approaches to identify interactions between clinicogenomic features for colorectal cancer using the 100,000 Genomes Project. Results Among the 2211 patients with colorectal cancer (mean age of diagnosis: 67.7; 59.7% male), 16.3%, 36.3%, 39.0% and 8.4% had stage 1, 2, 3 and 4 cancers, respectively. Almost every patient had surgery (99.7%), 47.4% had chemotherapy, 7.6% had radiotherapy and 1.4% had immunotherapy. On average, tumour mutational burden (TMB) was 18 mutations/Mb and 34.4%, 31.3% and 25.7% of patients had structural or copy number mutations in KRAS, BRAF and NRAS, respectively. In the fully adjusted Cox model, patients with advanced cancer [stage 3 hazard ratio (HR)  =  3.2; p  <  0.001; stage 4 HR  =  10.2; p  <  0.001] and those who had immunotherapy (HR  =  1.8; p  <  0.04) or radiotherapy (HR  =  1.5; p  <  0.02) treatment had a higher risk of dying. The ensemble clustering approach generated four distinct clusters where patients in cluster 2 had the best survival outcomes (1-year: 98.7%; 2-year: 96.7%; 3-year: 93.0%) while patients in cluster 3 (1-year: 87.9; 2-year: 70.0%; 3-year: 53.1%) had the worst outcomes. Kaplan–Meier analysis and log rank test revealed that the clusters were separated into distinct prognostic groups (p  <  0.0001). Survival tree or recursive partitioning analyses were performed to further explore risk groups within each cluster. Among patients in cluster 2, for example, interactions between cancer stage, grade, radiotherapy, TMB, BRAF mutation status were identified. Patients with stage 4 cancer and TMB  ≥  1.6 mutations/Mb had 4 times higher risk of dying relative to the baseline hazard in that cluster.

scholarly journals Construction and Validation of an Autophagy-Related Prognostic Model for Osteosarcoma Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Hu Qian ◽  
Ting Lei ◽  
Pengfei Lei ◽  
Yihe Hu
Keyword(s):  
Prognostic Value ◽  
Risk Model ◽  
Cox Regression ◽  
Bone Development ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Low Risk ◽  
Lasso Regression ◽  
Prognostic Accuracy ◽  
Selection Operator

While the prognostic value of autophagy-related genes (ARGs) in OS patients remains scarcely known, increasing evidence is indicating that autophagy is closely associated with the development and progression of osteosarcoma (OS). Therefore, we explored the prognostic value of ARGs in OS patients and illuminate associated mechanisms in this study. When the OS patients in the training/validation cohort were stratified into high- and low-risk groups according to the risk model established using least absolute shrinkage and selection operator (LASSO) regression analysis, we observed that patients in the low-risk group possessed better prognosis ( P < 0.0001 ). Univariate/Multivariate COX regression and subgroup analysis demonstrated that the ARGs-based risk model was an independent survival indicator for OS patients. The nomogram incorporating the risk model and clinical features exhibited excellent prognostic accuracy. GO, KEGG, and GSVA analyses collectively indicated that bone development-associated pathway mediated the contribution of ARGs to the malignance of OS. Immune infiltration analysis suggested the potential pivotal role of macrophage in OS. In summary, the risk model based on 12 ARGs possessed potent capacity in predicting the prognosis of OS patients. Our work may assist clinicians to map out more reasonable treatment strategies and facilitate individual-targeted therapy in osteosarcoma.

scholarly journals m6A RNA Methylation Regulators Impact Prognosis and Tumor Microenvironment in Renal Papillary Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Lianze Chen ◽  
Baohui Hu ◽  
Xinyue Song ◽  
Lin Wang ◽  
Mingyi Ju ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Patterns ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Lasso Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation

Accumulating evidence has proven that N6-methyladenosine (m6A) RNA methylation plays an essential role in tumorigenesis. However, the significance of m6A RNA methylation modulators in the malignant progression of papillary renal cell carcinoma (PRCC) and their impact on prognosis has not been fully analyzed. The present research set out to explore the roles of 17 m6A RNA methylation regulators in tumor microenvironment (TME) of PRCC and identify the prognostic values of m6A RNA methylation regulators in patients afflicted by PRCC. We investigated the different expression patterns of the m6A RNA methylation regulators between PRCC tumor samples and normal tissues, and systematically explored the association of the expression patterns of these genes with TME cell-infiltrating characteristics. Additionally, we used LASSO regression to construct a risk signature based upon the m6A RNA methylation modulators. Two-gene prognostic risk model including IGF2BP3 and HNRNPC was constructed and could predict overall survival (OS) of PRCC patients from the Cancer Genome Atlas (TCGA) dataset. The prognostic signature-based risk score was identified as an independent prognostic indicator in Cox regression analysis. Moreover, we predicted the three most significant small molecule drugs that potentially inhibit PRCC. Taken together, our study revealed that m6A RNA methylation regulators might play a significant role in the initiation and progression of PRCC. The results might provide novel insight into exploration of m6A RNA modification in PRCC and provide essential guidance for therapeutic strategies.

Risk classification as the basis for clinical staging of diffuse large- cell lymphoma derived from 10-year survival data

Blood ◽  
1989 ◽  
Vol 74 (2) ◽  
pp. 551-557 ◽  
Author(s):  
WS Velasquez ◽  
S Jagannath ◽  
SL Tucker ◽  
LM Fuller ◽  
LB North ◽  
...  
Keyword(s):  
Survival Data ◽  
Risk Model ◽  
Survival Rates ◽  
Staging System ◽  
Large Cell ◽  
Risk Groups ◽  
Lactic Dehydrogenase ◽  
Tumor Burden ◽  
Clinical Staging ◽  
Ann Arbor

Abstract Two hundred and fifty previously untreated adult patients with diffuse large-cell lymphomas were treated with a chemotherapy combination of cyclophosphamide, adriamycin, vincristine, prednisone, and low-dose bleomycin (CHOP-Bleo) with or without radiotherapy between 1974 and 1984. The 10-year survival rates for patients with Ann Arbor stages II, III, or IV disease of 55%, 42%, and 40%, respectively, were not significantly different. However, the survival rate of 76% for patients with stage I disease was clearly better. Factors more indicative of prognosis than stage, as found by univariant analysis, were tumor burden, serum lactic dehydrogenase level (LDH), age, and constitutional symptoms. From these, a multivariant analysis selected tumor burden, LDH level, and age as major independent factors for predicting survival (P less than .001). A prognostic risk model constructed on the basis of tumor burden and LDH levels identified four distinct risk groups (A, B, C, D) with 10-year survival rates of 85%, 66%, and 43% for A, B, and C. No patient in group D survived 10 years. These risk groups also had a strong correlation with complete remission rates and with relapse rates. Thus this model proved more effective for identifying patient populations according to their expected responses, durations of remission, and survivals than the Ann Arbor staging system. Detailed information supporting the use of this system for predicting prognosis and for treatment selection for patients with diffuse large-cell lymphomas is provided.

Somatic mutation landscape of appendiceal cancer.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 671-671 ◽  
Author(s):  
John P. Shen ◽  
Miriam T. Jacobs ◽  
Ingrid L Fuh ◽  
Joel Micah Baumgartner ◽  
Paul T. Fanta ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Somatic Mutation ◽  
Survival Data ◽  
Randomized Clinical Trials ◽  
Clinical Investigation ◽  
Primary Objective ◽  
Lower Prevalence ◽  
Appendiceal Cancer ◽  
Treatment Regimens ◽  
Metastatic Setting

671 Background: Appendiceal cancers are rare, comprising just 0.5% of all intestinal neoplasia, which has prevented the systematic study of these tumors in randomized clinical trials. Given this absence of clinical data, no evidence-based guidelines exist regarding the best management of this disease. Standard treatment generally follows consensus guidelines for colorectal cancer; however, there are currently no standards to guide chemotherapy selection in the adjuvant or metastatic setting. Methods: Somatic mutation profiles covering ~300 frequently mutated genes were obtained for 385 primary appendiceal tumors (Foundation Medicine). A retrospective review was performed to gather clinico-pathologic data. The primary objective was to assess the somatic mutation profile of each subtype of appendiceal cancer and to compare these to colorectal cancer. Colorectal data was obtained from TCGA cohort via cBioPortal. Results: Appendiceal adenocarcinoma (non-mucinous) and mucinous adenocarcinoma had shared somatic mutations albeit with differing frequencies. The most common mutations were KRAS (60.1% and 80.5%, respectively), GNAS (32.4%, 58.5%), TP53 (42.8%, 19.5%), and SMAD4 (14.8%, 14.6%). Tumors with goblet cell (adenocarcinoid) histology had lower prevalence of KRAS (16.0%) and GNAS mutations (8.0%), but similar prevalence of TP53 mutation (24.0%) and a greater prevalence of ARID1A mutation (20.0%). The mutation profiles of all appendiceal histologies differed from colorectal adenocarcinoma with markedly lower prevalence of ATM (7.9% vs. 71.0%). Chemotherapy data was available for 30 metastatic patients; these patients received an average of 1.76 lines of therapy (range 1-4). All 30 were treated with either 5-FU or capecitabine, 11 (36.7%) with oxaliplatin, 23 (76.7%) with irinotecan and 19 (63.3%) with bevacizumab. Analysis of survival data and correlation with molecular and histologic features is ongoing. Conclusions: Despite clear molecular differences between appendiceal and colorectal tumors, appendiceal tumors are primarily treated with colorectal chemotherapy regimens. There remains a pressing need for both pre-clinical and clinical investigation to develop treatment regimens specific to appendix cancer.

Racial and socioeconomic disparities in overall survival in colorectal cancer (CRC) at West Cancer Center & Research Institute (WCCRI), Memphis, TN.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16122-e16122
Author(s):  
Vanessa Wookey ◽  
Gabriella Bufalino ◽  
Gregory A. Vidal ◽  
Bradley G. Somer ◽  
Lee S. Schwartzberg ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Survival Data ◽  
Private Insurance ◽  
Socioeconomic Disparities ◽  
Cancer Center ◽  
Survival Outcomes ◽  
Median Income ◽  
Entire Cohort ◽  
Stage 4

e16122 Background: WCCRI, a comprehensive regional community oncology center in Memphis, Tennessee and the Mid-South region, serves a racially, geographically and socioeconomically diverse patient cohort. We sought to evaluate disparity of outcomes in survival by race and socioeconomic status, in addition to patient and tumor characteristics. Methods: All consecutive patients referred to and treated at WCCRI with colorectal adenocarcinoma from 2007-2013 were included. Individual chart review was performed to verify diagnosis, stage, and date and cause of death. Kaplan-Meier Overall Survival curves were generated for the entire cohort and by race, sex, tumor location and income derived from zip code. WCCRI survival data were compared to SEER data. Results: From 2007-2013, 1,176 patients were included in the analysis: 405 blacks, 757 whites, 14 others. Median age at diagnosis: Blacks 58 yrs, whites 61 yrs. Stage distribution at diagnosis: stage 1: 100, stage 2: 275, stage 3: 425, stage 4: 376. All stages combined, blacks trended towards shorter OS vs whites (5-year OS: 52.8% vs 58.3%; median survival 71.0 mos vs 98.6 mos; p= 0.095). Blacks presented at later stages (71.4% at stage 3 or 4 vs 66.3% for whites) but no statistically significant OS differences were seen when compared by stage. Patients at or below the median income of $39,590 for WCC had worse 5-year OS (51.6% vs. 61.1%; p= 0.006), as did patients without private insurance (5-year OS: uninsured: 48.0%, Medicare/Medicaid: 50.0%, private: 62.0%; p< 0.001). Adjusted for stage, 5-year OS was statistically significant for stage 4 (private: 18.0%, Medicare/Medicaid: 9.4%, uninsured: 8.3%; p= 0.020). A higher proportion of blacks were below the median income (69% vs 39%) but no statistically significant OS differences were seen when adjusted by race. Overall, cancer survival outcomes were similar to SEER results. Conclusions: At WCCRI, black patients with CRC presented at a later stage than whites, however, adjusted for stage, no significant racial difference in OS was found. Income and insurance status influenced survival outcomes. Overall, our results reveal racial and socioeconomic disparities in colorectal cancer in a diverse US population and further detailed multivariate data analyses are underway.

Racial and socioeconomic disparities in overall survival in colorectal cancer (CRC) at West Cancer Center (WCC), Memphis, TN.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 80-80
Author(s):  
Vanessa Wookey ◽  
Gabriella Bufalino ◽  
Gregory A. Vidal ◽  
Bradley G. Somer ◽  
Lee S. Schwartzberg ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Survival Data ◽  
Private Insurance ◽  
Socioeconomic Disparities ◽  
Cancer Center ◽  
Survival Outcomes ◽  
Median Income ◽  
Entire Cohort ◽  
Stage 4

80 Background: WCC, a comprehensive regional community oncology center in Memphis, Tennessee and the Mid-South region, serves a racially, geographically and socioeconomically diverse patient cohort. We sought to evaluate disparity of outcomes in survival by race and socioeconomic status, in addition to patient and tumor characteristics. Methods: All consecutive patients referred to and treated at WCC with colorectal adenocarcinoma from 2007-2013 were included. Individual chart review was performed to verify diagnosis, stage, and date and cause of death. Kaplan-Meier Overall Survival curves were generated for the entire cohort and by race, sex, tumor location and income derived from zip code. WCC survival data were compared to SEER data. Results: From 2007-2013, 1,176 patients were included in the analysis: 405 blacks, 757 whites, 14 others. Median age at diagnosis: Blacks 58 yrs, whites 61 yrs. Stage distribution at diagnosis: stage 1: 100, stage 2: 275, stage 3: 425, stage 4: 376. All stages combined, blacks trended towards shorter OS vs whites (5-year OS: 52.8% vs 58.3%; median survival 71.0 mos vs 98.6 mos; p= 0.095). Blacks presented at later stages (71.4% at stage 3 or 4 vs 66.3% for whites) but no statistically significant OS differences were seen when compared by stage. Patients at or below the median income of $39,590 for WCC had worse 5-year OS (51.6% vs. 61.1%; p= 0.006), as did patients without private insurance (5-year OS: uninsured: 48.0%, Medicare/Medicaid: 50.0%, private: 62.0%; p< 0.001). Adjusted for stage, 5-year OS was statistically significant for stage 4 (private: 18.0%, Medicare/Medicaid: 9.4%, uninsured: 8.3%; p= 0.020). A higher proportion of blacks were below the median income (69% vs 39%) but no statistically significant OS differences were seen when adjusted by race. Overall, cancer survival outcomes were similar to SEER results. Conclusions: At WCC, black patients with CRC presented at a later stage than whites, however, adjusted for stage, no significant racial difference in OS was found. Income and insurance status affected survival outcomes. Overall, our results reveal racial and socioeconomic disparities in colorectal cancer in a diverse US population.

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