scholarly journals Overall survival in patients with metastatic pancreatic cancer after surgically primary tumor resected: a SEER-based nomogram analysis

2020 ◽  
Author(s):  
Maoen Pan ◽  
Yuanyuan Yang ◽  
Xiaoting Wu ◽  
Heguang Huang
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Primary Tumor ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Tumor Resection ◽  
Training Group ◽  
Metastatic Pancreatic Cancer ◽  
Cox Regression Analysis

Abstract Background This study aimed to establish and validate a nomogram to predict overall survival in patients with metastatic pancreatic cancer (mPC) after surgically primary tumor resected. Methods All mPC patients who underwent primary tumor resection at SEER database between 2004 and 2016 were identified. We randomly assigned two-thirds of the patients to the training group and one third to the validation group. In the training group, the Kaplan–Meier survival analysis was used to analyze survival outcomes. A univariate and multivariate cox regression analysis was used to identify significant prognostic factors for establishing a nomogram. The predictive accuracy and discriminative ability were measured by the concordance index (C-index) and risk group stratification. Results A total of 742 patients were included for analysis. Four significant prognostic factors were obtained and included in the nomogram. The nomogram showed an acceptable discrimination ability (C- index:0.711) and good calibration and was further validated in the validation cohort (C- index: 0.727). The nomogram total points (NTP) had the potential to stratify patients into 2-risk groups with a median OS of 11 and 4.5 months (P < 0.001), respectively. Conclusions The nomogram can provide considerable accuracy individual prediction OS outcomes in patients with metastatic pancreatic cancer undergone primary tumor surgery and it can guide clinicians to make decisions in the clinical therapies.

scholarly journals Subdivision of metastatic colorectal cancer for identifying patients who benefit more from primary tumor resection

2021 ◽  
Author(s):  
Dakui Luo ◽  
Zezhi Shan ◽  
Zhiqiang Li ◽  
Simin Chen ◽  
Sanjun Cai ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Factors ◽  
Primary Tumor ◽  
Cox Regression ◽  
Tumor Resection ◽  
Signet Ring Cell ◽  
Normal Serum ◽  
Primary Tumor Resection ◽  
Cox Regression Analysis ◽  
Serum Cea

Abstract Background Stage IV colorectal cancer (CRC) patients are heterogeneous with distinctive clinicopathologic features and prognosis. Radical resection of primary tumor and distant metastases is associated with improved survival outcomes in metastatic CRC. The value of palliative primary tumor resection is controversial. The present study explored which subgroups benefited more from primary tumor resection in metastatic CRC. Methods Between 2004 and 2015, patients with metastatic CRC were identified using the surveillance, epidemiology, and end results (SEER) database. Uni- and multivariable Cox regression analysis were performed to identify factors associated with decreased cancer-specific mortality. The subgroups were divided based on the independent prognostic factors. Results Age, marital status, race, serum CEA, histologic type, differentiation, tumor location, surgery of primary or metastatic lesion, site of metastases, number of metastatic sites, chemotherapy and radiotherapy were identified as independent prognostic factors. Patients with non-white race, normal serum CEA, non-signet ring cell carcinoma, well or moderate differentiation, surgery of metastases, isolated liver metastasis, single metastasis, receiving chemotherapy or radiotherapy presented more survival benefit from primary tumor resection. Conclusion Subgroup of metastatic CRC optimizes decision-making and selected patients will benefit more from primary tumor resection.

scholarly journals Subdivision of metastatic colorectal cancer for identifying patients who benefit more from primary tumor resection

2020 ◽  
Author(s):  
Dakui Luo ◽  
Zezhi Shan ◽  
Qi Liu ◽  
Sanjun Cai ◽  
Qingguo Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Factors ◽  
Primary Tumor ◽  
Cox Regression ◽  
Tumor Resection ◽  
Signet Ring Cell ◽  
Normal Serum ◽  
Primary Tumor Resection ◽  
Cox Regression Analysis ◽  
Serum Cea

Abstract Background Stage IV colorectal cancer (CRC) patients are heterogeneous with distinctive clinicopathologic features and prognosis. Radical resection of primary tumor and distant metastases is associated with improved survival outcomes in metastatic CRC. The value of palliative primary tumor resection is controversial. The present study explored which subgroups benefited more from primary tumor resection in metastatic CRC. Methods Between 2004 and 2015, patients with metastatic CRC were identified using the surveillance, epidemiology, and end results (SEER) database. Uni- and multivariable Cox regression analysis were performed to identify factors associated with decreased cancer-specific mortality. The subgroups were divided based on the independent prognostic factors. Results Age, marital status, race, serum CEA, histologic type, differentiation, tumor location, surgery of primary or metastatic lesion, site of metastases, number of metastatic sites, chemotherapy and radiotherapy were identified as independent prognostic factors. Patients with non-white race, normal serum CEA, non-signet ring cell carcinoma, well or moderate differentiation, surgery of metastases, isolated liver metastasis, single metastasis, receiving chemotherapy or radiotherapy presented more survival benefit from primary tumor resection. Conclusion Subgroup of metastatic CRC optimizes decision-making and selected patients will benefit more from primary tumor resection.

scholarly journals A nomogram for predicting overall survival in patients with Merkel cell carcinoma: A population-based analysis

2021 ◽  
Author(s):  
Miao Wang ◽  
Ye Qiu ◽  
Fang Tang ◽  
Yi-Xin Liu ◽  
Yi Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Staging System ◽  
Merkel Cell ◽  
Cox Regression Analysis

Abstract Background: Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with increasing incidence and poor prognosis. We sought to develop and validate a nomogram to estimate overall survival (OS) of MCC patients. Methods: 1863 MCC patients between 2010-2015 from the Surveillance, Epidemiology and End Results (SEER) database were randomly divided into the training and validation cohort. Independent prognostic factors determined by Cox regression analysis in the training cohort were used to establish a nomogram. We evaluated prognostic performance using the concordance index (C-index), area under receiver operating characteristic curve (AUC) and calibration curves. Decision curve analysis (DCA), net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compared the the nomogram’s clinical utility with that of the staging system.Results: eight independent prognostic factors were incorporated in the nomogram. The C-index of the nomogram was 0.744, which was superior to the C-index of AJCC TNM Stage (0.659). The AUC was greater than 0.75 and the calibration plots of this model exhibited good performance. Additionally, the positive NRI and IDI of nomogram versus the staging system illustrated that the nomogram had better predictive accuracy than the staging system (P<0.001) and the DCA showed great clinical usefulness of the nomogram. MCC patients were perfectly classified into three risk groups by the nomogram, showing better discrimination than the staging system.Conclusions: We developed and validated a nomogram to assist clinicians in evaluating prognosis of MCC patients.

scholarly journals A nomogram predicting overall survival in patients with non-metastatic pancreatic head adenocarcinoma after surgery: a population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenbo Zou ◽  
Zizheng Wang ◽  
Fei Wang ◽  
Gong Zhang ◽  
Rong Liu
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Pancreatic Head ◽  
Staging System ◽  
Seer Database ◽  
Cox Regression Analysis ◽  
Net Reclassification Improvement ◽  
Calibration Curves

Abstract Background Pancreatic head adenocarcinoma (PHAC), a malignant tumour, has a very poor prognosis, and the existing prognostic tools lack good predictive power. This study aimed to develop a better nomogram to predict overall survival after resection of non-metastatic PHAC. Methods Patients with non-metastatic PHAC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided randomly into training and validation cohorts at a ratio of 7:3. Cox regression analysis was used to screen prognostic factors and construct the nomogram. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the performance of the model. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results From 2010 to 2016, 6419 patients with non-metastatic PHAC who underwent surgery were collected from the SEER database. A model including T stage, N stage, grade, radiotherapy, and chemotherapy was constructed. The concordance index of the nomogram was 0.676, and the AUCs of the model assessing survival at multiple timepoints within 60 months were significantly higher than those of the American Joint Committee on Cancer (AJCC) 8th staging system in the training cohort. Calibration curves showed that the nomogram had ability to predict the actual survival. The NRI, IDI, and DCA curves also indicated that our nomogram had higher predictive capability and clinical utility than the AJCC staging system. Conclusions Our nomogram has an ability to predict overall survival after resection of non-metastatic PHAC and includes prognostic factors that are easy to obtain in clinical practice. It would help assist clinicians to conduct personalized medicine.

scholarly journals Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Shaojie Chen ◽  
Feifei Huang ◽  
Shangxiang Chen ◽  
Yinting Chen ◽  
Jiajia Li ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Time Dependent ◽  
Concordance Index ◽  
Cox Regression Analysis ◽  
Score Model

ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.

scholarly journals Incidence, Survival, and Associated Factors Estimation in Osteosarcoma Patients with Lung Metastasis: A Single-center Experience of 11 Years in Tianjin, China

2021 ◽  
Author(s):  
Chao Zhang ◽  
Haixiao Wu ◽  
Guijun Xu ◽  
Wenjuan Ma ◽  
Lisha Qi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Lung Metastasis ◽  
Associated Factors ◽  
Cox Regression ◽  
Cancer Center ◽  
Single Center ◽  
Cox Regression Analysis

Abstract Background: Osteosarcoma is the most common primary malignant bone tumor. The current study was conducted to describe the general condition of patients with primary osteosarcoma in a single cancer center in Tianjin, China and to investigate the associated factors in osteosarcoma patients with lung metastasis. Methods: From February 2009 to October 2020, patients from Tianjin Medical University Cancer Institute and Hospital, China were retrospectively analyzed. The Kaplan–Meier method was used to evaluate the overall survival of osteosarcoma patients. Prognostic factors of patients with osteosarcoma were identified by the Cox proportional hazard regression analysis. Risk factor of lung metastasis in osteosarcoma were investigated by the logistic regression model. Results: A total of 203 patients were involved and 150 patients were successfully followed up for survival status. The 5-year survival rate of osteo-sarcoma patients was 70.0%. Surgery, bone and lung metastasis were the significant prognostic factors in multivariable Cox regression analysis. Twenty-one (10.3%) patients showed lung metastasis at the diagnosis of osteosarcoma and 67 (33%) lung metastases during the later course. T3 stage (OR=11.415, 95%CI 1.362-95.677, P=0.025) and synchronous bone metastasis (OR=6.437, 95%CI 1.69-24.51, P=0.006) were risk factors of synchronous lung metastasis occurrence. Good necrosis (≥90%, OR=0.097, 95%CI 0.028-0.332, P=0.000) and elevated Ki-67 (≥50%, OR=4.529, 95%CI 1.241-16.524, P=0.022) were proved to be significantly associated with metachronous lung metastasis occurrence. Conclusion: The overall survival, prognostic factors and risk factors for lung metastasis in this single center provided insight about osteosarcoma management.

Study of genotypic variations and protein expression of the xCT subunit of cystine/glutamate transporter in pancreatic cancer.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 210-210
Author(s):  
T. J. Huang ◽  
D. Li ◽  
Y. Li ◽  
S. P. Kar ◽  
S. Krishnan ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Protein Expression ◽  
Cox Regression ◽  
Performance Status ◽  
Glutamate Transporter ◽  
Supporting Evidence ◽  
Cox Regression Analysis ◽  
Risk Of Death ◽  
Increased Risk

210 Background: The plasma membrane xCT cystine-specific subunit of the cystine/glutamate transporter contributes to chemotherapy resistance in pancreatic cancer by regulating intracellular glutathione levels and protecting cancer cells against oxidative stress. We previously noted that the rs7674870 single nucleotide polymorphism (SNP) of xCT correlated with overall survival in pancreatic cancer and may be predictive of platinum resistance. There are no data regarding xCT protein expression in pancreatic cancer or the functional significance of this SNP. Methods: Paraffin-embedded core and surgical biopsy tumor specimens from 49 patients with metastatic pancreatic adenocarcinoma were analyzed by immunohistochemistry (IHC) using an xCT specific antibody (Novus Biologicals). xCT protein IHC expression scores (product of intensity and percentage of staining cells) were analyzed in relation to overall survival and genotype of the patients using the one factor ANOVA test, Kaplan-Meier plot, log-rank test, and Cox regression analysis. Overall survival was measured from the date of diagnosis to the date of death or last follow-up. Results: Positive xCT expression was detected in 38 (78%) of the 49 samples, and 9 (18%) patients had high levels of expression. High xCT expression was associated with lower overall survival as compared with low expression (5.1 months versus 8.8 months; p = 0.119). In a multivariate Cox regression model with adjustment for prognostic parameters of age, sex, performance status and CA19-9 level, high xCT expression was associated with a 2.1-fold increased risk of death (p = 0.096). Performance status also correlated with overall survival (p = 0.027). Preliminary analysis on the genotype-phenotype association (n = 12) indicated that xCT expression was higher with the TT genotype than the TC/CC genotype (p = 0.115), which is consistent with the previous observation that the TT genotype was associated with reduced survival. Conclusions: These data provide supporting evidence for a possible role of cystine/glutamate transporter xCT subunit in pancreatic cancer progression and survival. Further pharmacogenomic and clinicopathologic studies are ongoing. No significant financial relationships to disclose.

Modified IPCW model: A method for adjusting for bias in the estimation of overall survival due to the use of second and third line therapies in locally advanced or metastatic pancreatic cancer patients.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e15787-e15787
Author(s):  
N. E. Iznaga Escobar ◽  
Patricia Lorenzo Luaces ◽  
Lizet Sanchez Valdes ◽  
Carmen Valenzuela Silva ◽  
Tania Crombet Ramos ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Cox Regression ◽  
Locally Advanced ◽  
Secondary Analysis ◽  
Metastatic Pancreatic Cancer ◽  
Fixed Dose ◽  
Line Treatment ◽  
Newly Diagnosed

e15787 Background: Nimotuzumab, a unique and affinity differentiated anti-EGFR antibody had been used in combination with gemcitabine on the treatment of pancreatic cancer patients. The aim of the study was to evaluate overall survival. Methods: Patients with newly diagnosed, locally advanced or metastatic pancreatic cancer, KPS ≥ 70 %, 18-72 years old, with adequate renal and liver function were included. Pts received gemcitabine 1000 mg/m2and nimotuzumab or placebo fixed dose of 400 mg once a wk, for 3 wks, followed by a 1-wk rest (d1, 8, 15, q28) until disease progression or unacceptable toxicity. The primary endpoint was OS and secondary PFS, ORR, CBR, safety and QoL. For OS determination, a KM log-rank test was used and a modified IPCW with a cox regression as a secondary analysis. On this evaluation using a modified IPCW model, 41.7% of pts from treatment arm and 42.7% from control arm who received 2nd and 3rd line treatment were censored after progression, while pts that did not receive 2nd and 3rd line treatment were weighted to compensate for the bias created by censoring switchers to 2nd and 3rd line treatment. Results: 192 pancreatic cancer pts were recruited. Ninety-six pts (62 male and 34 female) with a median age of 67 years, range (31, 83) were randomized to treatment arm and 96 pts (57 male and 39 female) with a median age of 64 years, range (41, 82) were randomized to control arm. In the primary analysis, median OS [95% CI] in the treatment arm was 8.57 mo [5.93, 10.90] vs 6.03 mo [4.97, 7.60] in the control arm. The HR [95% CI], 0.83 [0.62, 1.12] and p = 0.23 and when a modified IPCW model as a secondary analysis was used to remove the effect of 2nd and 3rd line therapies, the median OS was statistically significant with a HR [95% CI], 0.81 [0.67, 0.98] and a p = 0.030. The median PFS [95% CI] was 4.43 mo [3.67, 6.00] in the treatment arm vs 3.47 mo [2.60, 4.03] in the control arm with a HR [95% CI] 0.68 [0.51, 0.92] and p = 0.012. Conclusions: A modified IPCW model had proven that addition of nimotuzumab to gemcitabine increases median overall survival of newly diagnosed chemotherapy-naïve locally advanced or metastatic pancreatic cancer patients. Clinical trial information: NCT00561990.

Correlation of neutrophil lymphocyte ratio, platelet lymphocyte ratio and rate of change of CA 19.9 in predicting outcome for metastatic pancreatic cancer.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 326-326
Author(s):  
Andrew Peter Dean ◽  
Dom Higgs ◽  
Adarsh Das ◽  
Madeline Rogers-Seeley ◽  
Sean Fennessy ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Rate Of Change ◽  
Cox Proportional Hazards Model ◽  
Metastatic Pancreatic Cancer ◽  
Lymphocyte Ratio ◽  
Daily Rate ◽  
Ca 19.9

326 Background: CA19.9, NLR and PLR have all been proposed as prognostic in pancreatic cancer. We analysed correlation between NLR, PLR and rate of change of CA19.9. Methods: A total of 63 metastatic pancreatic cancer patients were identified from our database and evaluated retrospectively for blood count, NLR, PLR and serial CA19.9 levels during treatment. Daily Rate of Change of CA19.9 levels were calculated for the first 90 days (DRC90) of the patient’s treatment. Kaplan-Meir curves, univariate and multivariate Cox-regression analyses were calculated to assess the effects of these 3 markers on overall survival. Results: In a univariate analysis, PLR > 240, NLR > 5 and DRC90 > 0.4% were all significantly associated with deceased overall survival. The Cox proportional hazards model showed that NLR < 5 (HR 0.475, 95% CI 0.259 to 0.873, P = 0.017), PLR < 240 (HR 0.444, 95% CI 0.229 to 0.861, P = 0.016), and a DRC90 < 0.4% (HR 0.294, 95% CI 0.102 to 0.851, P = 0.024) were independent predictors of good prognosis (22.6 months vs. 9.6 months, 22.3 months vs 12.4 months and 23.9 months vs. 9.3 months respectively). In multivariate analysis, only a DRC90 < 0.4% was independently associated with a longer survival (HR 0.239, 95% CI 0.076 to 0.752, P = 0.014). The formula (F) {PLR + (NLRxNLR) + (DRC90 x 100)} was predictive for survival, as patients with F > 190 (HR 3.295, 95% CI 1.232 to 8.807, P = 0.017), having a significantly lower survival rate than patients with F < 190 (25.1 months vs. 10.6 months, log-rank P = 0.009). Conclusions: These findings indicate the prognostic utility of the rate of CA 19.9 decline - measured as a standardised daily percentage change in value over 90 days. Our data validates daily rate of change of CA 19.9 over 90 days as an independent variable that correlates with prognosis, independent of PLR and NLR. We also identified a novel formula - PLR + (NLRxNLR) + (DRC90 x 100) - as being predictive for survival. We would like to increase the sample size to further validate our initial findings and investigate possible relationships in combining these variables for better prognostication in metastatic pancreatic cancer.

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.

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