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.

Outcome of patients with colorectal cancer undergoing lung metastases resection: a single-institution retrospective analysis

2020 ◽  
pp. 030089162093079
Author(s):  
Marco Mammana ◽  
Francesca Bergamo ◽  
Letizia Procaccio ◽  
Marco Schiavon ◽  
Fotios Loupakis ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Multivariable Analysis ◽  
Postoperative Chemotherapy ◽  
Single Institution ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Lung Metastasectomy

Introduction: This study was undertaken to review a single-institution cohort of patients with metastatic colorectal cancer undergoing lung resection after a multidisciplinary evaluation and to investigate the main prognostic factors for survival. Methods: Medical records of 129 patients undergoing lung metastasectomy for colorectal cancer with curative intent from 2001 to 2017 were reviewed. Tissue samples from the primary tumor were analyzed with a multiplex genotyping system for the detection of mutations in RAS and BRAF genes. Survival analyses were carried out by the Kaplan-Meier method. Univariate and multivariable analyses were performed using the log-rank test and the Cox regression model. Results: Postoperative morbidity and mortality were 13.2% and 0%, respectively. At a median follow-up time of 62.5 months, median overall survival was 90.5 months and median relapse-free survival was 42.8 months. Multivariable analysis for overall survival identified synchronous versus metachronous metastatic presentation as the only prognostic factor, whereas relapse-free survival was independently associated with synchronous versus metachronous metastatic presentation, number of metastases, and postoperative chemotherapy. Conclusions: This study shows particularly favorable survival outcomes for patients undergoing lung metastasectomy. The validity of some of the main prognostic factors was confirmed and a positive effect of postoperative chemotherapy on relapse-free survival was shown. Contrary to other reports, the presence of KRAS mutations was not associated with significant survival differences. Further studies are needed in order to clarify the interactions between molecular, clinical, and pathologic characteristics and treatment-related factors.

Survival among colorectal cancer patients with a history of previous cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16146-e16146
Author(s):  
Sandi Pruitt ◽  
David E. Gerber ◽  
Hong Zhu ◽  
Daniel Heitjan ◽  
Bhumika Maddineni ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Population Based ◽  
Competing Risk ◽  
Cancer Specific Survival ◽  
Risk Of Death ◽  
Number Of Patients ◽  
Significant Difference ◽  
The Impact

e16146 Background: A growing number of patients with colorectal cancer (CRC) have survived a previous cancer. Although little is known about their prognosis, this population is frequently excluded from clinical trials. We examined the impact of previous cancer on overall and cancer-specific survival in a population-based cohort of patients diagnosed with incident CRC. Methods: We identified patients aged ≥66 years and diagnosed with CRC between 2005-2015 in linked SEER-Medicare data. For patients with and without previous cancer, we estimated overall survival using Cox regression and cause-specific survival using competing risk regression, separately by CRC stage, while adjusting for numerous covariates and competing risk of death from previous cancer, other causes, or the incident CRC. Results: Of 112,769 CRC patients diagnosed with incident CRC, 15,935 (14.1%) had a previous cancer – most commonly prostate (32.9%) or breast (19.4%) cancer, with many 7505 (47.1%) diagnosed ≤5 years of CRC. For all CRC stages except IV in which there was no significant difference in survival, patients with previous cancer had modestly worse overall survival (hazard ratios from fully adjusted models range from 1.11-1.28 across stages; see Table). This survival disadvantage was driven by deaths due to previous cancer and other causes. Notably, most patients with previous cancer had improved CRC-specific survival. Conclusions: CRC patients who have survived a previous cancer have generally worse overall survival but superior CRC-specific survival. This evidence should be considered concurrently with concerns about trial generalizability, low accrual, and heterogeneity of participants when determining exclusion criteria. [Table: see text]

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 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 Development and Validation of a Prognostic Model for Transplant-Associated Thrombotic Microangiopathy Following Allogeneic Hematopoietic Stem Cell Transplantation

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 16-17
Author(s):  
Peng Zhao ◽  
Ye-Jun Wu ◽  
Qing-Yuan Qu ◽  
Shan Chong ◽  
Xiao-Wan Sun ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Model ◽  
Validation Cohort ◽  
Risk Group ◽  
External Validation ◽  
Internal Validation ◽  
Hematopoietic Stem ◽  
Derivation Cohort ◽  
Peking University ◽  
Score Model

Introduction Transplant-associated thrombotic microangiopathy (TA-TMA) is a potentially life-threatening complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT), which can result in multiorgan injury and increased risk for mortality. Renewed interest has emerged in the prognostication of TA-TMA with the development of novel diagnostic and management algorithms. Our previous study reported an adverse outcome in patients with TA-TMA and concomitant acute graft-versus-host disease (Eur J Haematol, 2018). However, information on markers for the early identification of severe cases remains limited. Therefore, this study is concentrated on the development and validation of a prognostic model for TA-TMA, which might facilitate risk stratification and contribute to individualized management. Methods Patients receiving allo-HSCT in Peking University People's Hospital with 1) a diagnosis of microangiopathic hemolytic anemia (MAHA) or 2) evidence of microangiopathy were retrospectively identified from 2010 to 2018. The diagnosis of TA-TMA was reviewed according to the Overall-TMA criteria (Transplantation, 2010). Patients without fulfillment of the diagnostic criteria or complicated with other causes of MAHA were excluded from analysis. Prognostic factors for TA-TMA were determined among patients receiving HSCT between 2010 and 2014 (derivation cohort). Candidate predictors (univariate P < 0.1) were included in the multivariate analysis using a backward stepwise logistic regression model. A risk score model was then established according to the regression coefficient of each independent prognostic factor. The performance of this predictive model was evaluated through internal validation (bootstrap method with 1000 repetitions) and external temporal validation performed on data from those who received HSCT between 2015 and 2018 (validation cohort). Results 5337 patients underwent allo-HSCT at Peking University Institute of Hematology from 2010 to 2018. A total of 1255 patients with a diagnosis of MAHA and/or evidence of microangiopathy were retrospectively identified, among whom 493 patients met the inclusion criteria for this analysis (269 in the derivation cohort and 224 in the validation cohort). The median age at the time of TA-TMA diagnosis was 28 (IQR: 17-41) years. The median duration from the time of transplantation to the diagnosis of TA-TMA was 63 (IQR: 38-121) days. The 6-month overall survival rate was 42.2% (208/493), and the 1-year overall survival rate was 45.0% (222/493). In the derivation cohort, patient age (≥35 years), anemia (hemoglobin <70 g/L), severe thrombocytopenia (platelet count <15,000/μL), elevated lactic dehydrogenase (serum LDH >800 U/L) and elevated total bilirubin (TBIL >1.5*ULN) were identified by multivariate analysis as independent prognostic factors for the 6-month outcome of TA-TMA. A risk score model was constructed according to the regression coefficients (Table 1), and patients were stratified into a low-risk group (0-1 points), an intermediate-risk group (2-4 points) and a high-risk group (5-6 points). The Kaplan-Meier estimations of overall survival separated well between these risk groups (Figure 1). The prognostic model showed significant discriminatory capacity, with a cross-validated c-index of 0.770 (95%CI, 0.714-0.826) in the internal validation and 0.768 (95%CI, 0.707-0.829) in the external validation cohort. The calibration plots also indicated a good correlation between model-predicted and observed probabilities. Conclusions A prognostic model for TA-TMA incorporating several baseline laboratory factors was developed and evaluated, which demonstrated significant predictive capacity through internal and external validation. This predictive model might facilitate prognostication of TA-TMA and contribute to early identification of patients at higher risk for adverse outcomes. Further study may focus on whether these high-risk patients could benefit from early application of specific management. Disclosures No relevant conflicts of interest to declare.

scholarly journals Predicting Survival Outcome of Patients With Colorectal Cancer and Only Lung Metastasis: A Population-Based Real-World Study

2020 ◽  
Author(s):  
Hui Tang ◽  
Jian-Feng Zhou ◽  
Chun-Mei Bai
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Factors ◽  
Lung Metastasis ◽  
Clinical Decision Making ◽  
Histological Grade ◽  
External Validation ◽  
Roc Curves ◽  
Survival Outcome ◽  
Cancer Specific Survival ◽  
Tumor Deposit

Abstract Background: Patients with metastatic colorectal cancer (mCRC) have a poor prognosis, but lung metastasis (LM) generally has a relatively desirable survival outcome. However, clinicians have had few tools for estimating the probability of survival in patients with colorectal cancer (CRC) and only LM (OLM). The present study aimed to develop nomograms estimating survival probability for patients with CRC and OLM.Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) database of patients with CRC between 2010 and 2014 were retrieved for retrospective analysis. Patients with OLM diagnosed between 2010 and 2014, except for 2012 (n = 1,118) were used to conduct multivariate Cox analysis to identify independent prognostic factors. Nomograms estimating 1- and 3-year overall survival (OS) and cancer-specific survival (CSS) were developed. The nomograms were internally validated for concordance index (C-index), calibration plots, receiver operating characteristic (ROC) curves, and were also externally validated with independent patients diagnosed in 2012 (n = 261).Results: Age, marital status, tumor location, tumor size, T and N stage, CEA, tumor deposit, histological grade, primary or metastatic tumor surgery, chemotherapy, radiotherapy, and income were found to be independently associated with OS and/or CSS. The nomograms were constructed based on these prognostic factors. The C-index were high in internal validation (0.736 for OS and 0.741 for CSS) and external validation (0.656 for OS and 0.663 for CSS). Internal and external calibration plots and ROC curves demonstrated a good agreement between actual observation and nomogram prediction.Conclusions: The nomograms individually predict OS and CSS of patients with CRC and OLM and could aid in the personalized prognostic evaluation and clinical decision-making.

scholarly journals SURVIVAL OF PATIENTS WITH COLORECTAL CANCER IN A CANCER CENTER

2020 ◽  
Vol 57 (2) ◽  
pp. 172-177
Author(s):  
Samuel AGUIAR JUNIOR ◽  
Max Moura de OLIVEIRA ◽  
Diego Rodrigues Mendonça e SILVA ◽  
Celso Abdon Lopes de MELLO ◽  
Vinicius Fernando CALSAVARA ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Early Stage ◽  
Age Groups ◽  
Rectal Adenocarcinoma ◽  
Disease Stage ◽  
Cancer Center ◽  
Risk Of Death

ABSTRACT BACKGROUND: Hospital-based studies recently have shown increases in colorectal cancer survival, and better survival for women, young people, and patients diagnosed at an early disease stage. OBJECTIVE: To describe the overall survival and analyze the prognostic factors of patients treated for colorectal cancer at an oncology center. METHODS: The analysis included patients diagnosed with colon and rectal adenocarcinoma between 2000 and 2013 and identified in the Hospital Cancer Registry at A.C.Camargo Cancer Center. Overall 5-year survival was estimated using the Kaplan-Meier method, and prognostic factors were evaluated in a Cox regression model. Hazard ratios (HR) are reported with 95% confidence intervals (CI). RESULTS: Of 2,279 colorectal cancer cases analyzed, 58.4% were in the colon. The 5-year overall survival rate for colorectal cancer patients was 63.5% (65.6% and 60.6% for colonic and rectal malignancies, respectively). The risk of death was elevated for patients in the 50-74-year (HR=1.24, 95%CI =1.02-1.51) and ≥75-year (HR=3.02, 95%CI =2.42-3.78) age groups, for patients with rectal cancer (HR=1.37, 95%CI =1.11-1.69) and for those whose treatment was started >60 days after diagnosis (HR=1.22, 95%CI =1.04-1.43). The risk decreased for patients diagnosed in recent time periods (2005-2009 HR=0.76, 95%CI =0.63-0.91; 2010-2013 HR=0.69, 95%CI =0.57-0.83). CONCLUSION: Better survival of patients with colorectal cancer improves with early stage and started treatment within 60 days of diagnosis. Age over 70 years old was an independent factor predictive of a poor prognosis. The overall survival increased to all patients treated in the period 2000-2004 to 2010-2013.

scholarly journals Nomograms Forecasting Long-Term Overall and Cancer Specific Survival of Patients With Head and Neck Neuroendocrine Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Ouying Yan ◽  
Wenji Xie ◽  
Haibo Teng ◽  
Shengnan Fu ◽  
Yanzhu Chen ◽  
...  
Keyword(s):  
Head And Neck ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
External Validation ◽  
Receiver Operating Curve ◽  
Survival Prediction ◽  
Validation Group ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Cancer Hospital

BackgroundThe purpose of this retrospective analysis was to build and validate nomograms to predict the cancer-specific survival (CSS) and overall survival (OS) of head and neck neuroendocrine carcinoma (HNNEC) patients.MethodsA total of 493 HNNEC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and 74 HNNEC patients were collected from the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital (HCH) between 2008 and 2020. Patients from SEER were randomly assigned into training (N=345) and internal validation (N=148) groups, and the independent data group (N=74) from HCH was used for external validation. Independent prognostic factors were collected using an input method in a Cox regression model, and they were then included in nomograms to predict 3‐, 5‐, and 10‐year CSS and OS rates of HNNEC patients. Finally, we evaluated the internal and external validity of the nomograms using the consistency index, while assessing their prediction accuracy using calibration curves. A receiver operating curve (ROC) was also used to measure the performance of the survival models.ResultsThe 3-, 5-, and 10-year nomograms of this analysis demonstrated that M classification had the largest influence on CSS and OS of HNNEC, followed by the AJCC stage, N stage, age at diagnosis, sex/gender, radiation therapy, and marital status. The training validation C-indexes for the CSS and OS models were 0.739 and 0.713, respectively. Those for the internal validation group were 0.726 and 0.703, respectively, and for the external validation group were 0.765 and 0.709, respectively. The area under the ROC curve (AUC) of 3-, 5-, and 10-year CSS and OS models were 0.81, 0.82, 0.82, and 0.78, 0.81, and 0.82, respectively. The C-indexes were all higher than 0.7, indicating the high accuracy ability of our model’s survival prediction.ConclusionsIn this study, prognosis nomograms in HNNEC patients were constructed to predict CSS and OS for the first time. Clinicians can identify patients’ survival risk better and help patients understand their survival prognosis for the next 3, 5, and 10 years more clearly by using these nomograms.

scholarly journals Construction of a Prognostic Model for Predicting Overall Survival of Patients with Colorectal Cancer

2020 ◽  
Author(s):  
Shuwen Han ◽  
Kefeng Ding
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Levulinic Acid ◽  
Prognostic Model ◽  
Cox Regression ◽  
Aminolevulinic Acid ◽  
Risk Group ◽  
Prognostic Models ◽  
Cox Regression Analysis

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies. The purpose of this study is to construct a prognostic model for predicting the overall survival (OS) in patients with CRC. Methods: The mRNA-seq and miRNA-seq data of colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) were downloaded from The Cancer Genome Atlas (TCGA) database. The differentially expressed RNAs (DE-RNAs) between tumor and normal tissues were screened. The Kaplan-Meier and univariate Cox regression analysis were used to screen the survival-related genes. Functional enrichment analysis of survival-related genes was conducted, followed by protein-protein interaction (PPI) analysis. Subsequently, the potential drugs targeting differentially expressed mRNAs (DE-mRNAs) were investigated. Multivariate Cox regression analysis was then conducted to screen the independent prognostic factors, and these genes were used to establish a prognostic model. A receiver operator characteristic (ROC) curve was constructed, and the area under the curve (AUC) value of ROC was calculated to evaluate the specificity and sensitivity of the model. Results: A total of 855 survival-related genes were screened. These genes were mainly enriched in Gene Ontology (GO) terms, such as methylation, synapse organization, and methyltransferase activity; and pathway analysis showed that these genes were significantly involved in N-Glycan biosynthesis and the calcium signaling pathway. PPI analysis showed that aminolevulinate dehydratase (ALAD) and cholinergic receptor muscarinic 2 (CHRM2) served vital roles in the development of CRC. Aminolevulinic acid, levulinic acid, and loxapine might be potential drugs for CRC treatment. The prognostic models were built and the patients were divided into high-risk and low-risk groups based on the median of risk score (RS) as screening threshold. The OS for patients in the high-risk group was markedly shorter than that for patients in the low-risk group. Meanwhile, kazal type serine peptidase inhibitor domain 1 (KAZALD1), hippocalcin like 4 (HPCAL4), cadherin 8 (CDH8), synaptopodin 2 (SYNPO2), cyclin D3 (CCND3), and hsa_mir_26b may be independent prognostic factors that could be considered as therapeutic targets for CRC.Conclusion: We established prognostic models that could predict the OS for CRC patients and may assist clinicians in providing personalized and precision treatment in this patient population.Highlights:1. ALAD served a vital role in the development of CRC.2. CHRM2 played a role in CRC development by affecting the calcium signaling pathway.3. Aminolevulinic acid, levulinic acid, and loxapine might be potential drugs for treating CRC.4. KAZALD1 and HPCAL4 were associated with the OS of CRC.5. CDH8, SYNPO2, CCND3, and hsa-mir-26b were closely related to the prognostic of CRC staging.

Prognostic model for survival in patients with advanced pancreatic cancer receiving palliative chemotherapy.

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 248-248
Author(s):  
Yu Uneno ◽  
Tadayuki Kou ◽  
Masashi Kanai ◽  
Michio Yamamoto ◽  
Peng Xue ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Poor Prognosis ◽  
Prognostic Model ◽  
Palliative Chemotherapy ◽  
Cox Regression ◽  
Advanced Pancreatic Cancer ◽  
Prognostic Index ◽  
Prognostic Models

248 Background: The prognosis of patients with advanced pancreatic cancer (APC) is extremely poor. Several clinical and laboratory factors have been known to be associated with prognosis of APC patients. However, there are few clinically available prognostic models predicting survival in APC patients receiving palliative chemotherapy. Methods: To construct a prognostic model to predict survival in APC patients receiving palliative chemotherapy, we analyzed the clinical data from 306 consecutive patients with pathologically confirmed APC who received palliative chemotherapy. We selected six independent prognostic factors which remained independent prognostic factors after multivariate analysis. Thereafter, we rounded the regression coefficient (β) for each independent prognostic factor derived from the Cox regression equation (HR = eβ) and developed a prognostic index (PI). Results: Developed prognostic index (PI) was as follows: PI = 2 (if performance status score 2–3) + 1 (if metastatic disease) + 1 (if initially unresectable disease) + 1 (if carcinoembryonic antigen level ≥5.0 ng/ml) + 1 (if carbohydrate antigen 19-9 level ≥1000 U/ml) + 2 (if neutrophil–lymphocyte ratio ≥5). The patients were classified into three prognostic groups: favorable (PI 0–1, n = 73), intermediate (PI 2–3, n = 145), and poor prognosis (PI 4–8, n = 88). The median overall survival for each prognostic group was 16.5, 12.3 and 6.2 months, respectively, and the 1-year survival rates were 67.3%, 51.3%, and 19.1%, respectively (P < 0.01). The c index of the model was 0.658. This model was well calibrated to predict 1-year survival, in which overestimation (2.4% and 0.2% in the favorable and poor prognosis groups, respectively) and underestimation (3.6% in the intermediate prognosis group) were observed. Conclusions: This prognostic model based on readily available clinical factors would help clinicians in estimating the overall survival in APC patients receiving palliative chemotherapy.

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