scholarly journals Metastasis Pattern and Survival Analysis in Primary Small Bowel Adenocarcinoma: A SEER-Based Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Yanmei Gu ◽  
Haixiao Deng ◽  
Daijun Wang ◽  
Yumin Li
Keyword(s):  
Risk Factors ◽  
Survival Analysis ◽  
Prognostic Factor ◽  
Small Bowel ◽  
Tnm Staging ◽  
Curve Analysis ◽  
Small Bowel Adenocarcinoma ◽  
Decision Curve Analysis ◽  
Kaplan Meier ◽  
Metastasis Patterns

Background: Small bowel adenocarcinoma (SBA) is a rare gastrointestinal tumor with high malignancy. The aim of this study was to comprehensively evaluate the distant metastasis pattern and establish nomograms predicting survival for SBA.Methods: From 2010 to 2015, patients diagnosed with SBA were identified based on the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan–Meier survival analysis was applied to compare survival differences between metastasis patterns. Then, univariate and multivariate cox analyses were applied to screened out independent prognostic factors of cancer-specific survival (CSS) and overall survival (OS), and identify the risk factors for metastasis of SBA. To assess the discrimination and calibration of nomograms, the concordance index (C-index), calibration curves, receiver-operating characteristic curve (ROC), and decision curve analysis (DCA) were calculated.Results: Kaplan–Meier curves revealed that metastasis patterns were significantly correlated with CSS (p < 0.001) and OS (p < 0.001). Then, the metastasis pattern was showed to be an independent prognostic factor of OS and CSS in patients with SBA, as well as age, grade, T stage, N stage, surgery, retrieval of regional lymph nodes, and chemotherapy. Combining these factors, we constructed prognostic nomograms, which suggested that the metastasis pattern made the greatest contribution to the survival of patients with SBA. Nomograms for OS and CSS had a C-index of 0.787 and 0.793, respectively. Calibration curves showed an excellent agreement between probability and actual observation in the training and validation cohort. Decision curve analysis also exhibited its clinical value with an improved net benefit. In addition, the models we constructed had better prognostic accuracy and clinical utility than traditional TNM staging based on C-index and ROC. Further, Cox regression analysis showed that old age, poor differentiation, N2, and not receiving chemotherapy were the risk factors for prognosis in patients with metastatic SBA.Conclusion: As an independent prognostic factor, the metastasis pattern exhibited the greatest predictive effect on OS and CSS for patients with SBA. Adjuvant chemotherapy had a positive effect on the survival of patients with SBA. Nomograms for predicting 3-and 5-year OS and CSS of patients with SBA were constructed, which could identify patients with higher risk and might be superior in predicting the survival of patients with SBA than TNM staging.

scholarly journals Established the first clinical prediction model regarding the risk of hyperuricemia in IgA nephropathy

2021 ◽  
Author(s):  
Yin-Hong Geng ◽  
Zhe Zhang ◽  
Jun-Jun Zhang ◽  
Bo Huang ◽  
Zui-Shuang Guo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Iga Nephropathy ◽  
Interstitial Fibrosis ◽  
Characteristic Curve ◽  
Univariate Analysis ◽  
Curve Analysis ◽  
University Hospital ◽  
Prediction Ability ◽  
Decision Curve Analysis ◽  
Incidence Risk

Abstract Objective. To construct a novel nomogram model that predicts the risk of hyperuricemia incidence in IgA nephropathy (IgAN) . Methods. Demographic and clinicopathological characteristics of 1184 IgAN patients in the First Affiliated Hospital of Zhengzhou University Hospital were collected. Univariate analysis and multivariate logistic regression were used to screen out hyperuricemia risk factors. The risk factors were used to establish a predictive nomogram model. The performance of the nomogram model was evaluated using an area under the receiver operating characteristic curve (AUC), calibration plots, and a decision curve analysis. Results. Independent predictors for hyperuricemia incidence risk included sex, hypoalbuminemia, hypertriglyceridemia, blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), 24-hour urinaryprotein (24h TP), Gross and tubular atrophy/interstitial fibrosis (T). The nomogram model exhibited moderate prediction ability with an AUC of 0.834 ((95% CI 0.804–0.864)). The AUC from validation reached 0.787 (95% CI 0.736-0.839). The decision curve analysis displayed that the hyperuricemia risk nomogram was clinically applicable.Conclusion. Our novel and simple nomogram containing 8 factors may be useful in predicting hyperuricemia incidence risk in IgAN.

scholarly journals Causes and Prognosis of Intestinal Failure in Crohn’s Disease: An 18-year Experience From a National Centre

2020 ◽  
Vol 14 (11) ◽  
pp. 1558-1564 ◽  
Author(s):  
Mattias Soop ◽  
Haroon Khan ◽  
Emma Nixon ◽  
Antje Teubner ◽  
Arun Abraham ◽  
...  
Keyword(s):  
Risk Factors ◽  
Crohn’S Disease ◽  
Small Bowel ◽  
Crohn's Disease ◽  
Abdominal Surgery ◽  
Parenteral Nutrition ◽  
Intestinal Failure ◽  
Anastomotic Dehiscence ◽  
Septic Complication ◽  
Kaplan Meier

Abstract Background and Aims Intestinal failure [IF] is a feared complication of Crohn’s disease [CD]. Although cumulative loss of small bowel due to bowel resections is thought to be the dominant cause, the causes and outcomes have not been reported. Methods Consecutive adult patients referred to a national intestinal failure unit over 2000–2018 with a diagnosis of CD, and subsequently treated with parenteral nutrition during at least 12 months, were included in this longitudinal cohort study. Data were extracted from a prospective institutional clinical database and patient records. Results A total of 121 patients were included. Of these, 62 [51%] of patients developed IF as a consequence of abdominal sepsis complicating abdominal surgery; small bowel resection, primary disease activity, and proximal stoma were less common causes [31%, 12%, and 6%, respectively]. Further, 32 had perianastomotic sepsis, and 15 of those had documented risk factors for anastomotic dehiscence. On Kaplan-Meier analysis, 40% of all patients regained nutritional autonomy within 10 years and none did subsequently; 14% of patients developed intestinal failure-associated liver disease. On Kaplan-Meier analysis, projected mean age of death was 74 years.2 Conclusions IF is a severe complication of CD, with 60% of patients permanently dependent on parenteral nutrition. The most frequent event leading directly to IF was a septic complication following abdominal surgery, in many cases following intestinal anastomosis in the presence of significant risk factors for anastomotic dehiscence. A reduced need for abdominal surgery, an increased awareness of perioperative risk factors, and structured pre-operative optimisation may reduce the incidence of IF in CD.

Retrospective analysis of first-line chemotherapy in 132 patients with advanced small-bowel adenocarcinoma.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 260-260
Author(s):  
T. Tsushima ◽  
N. Boku ◽  
Y. Honma ◽  
H. Takahashi ◽  
S. Ueda ◽  
...  
Keyword(s):  
Small Bowel ◽  
Univariate Analysis ◽  
Objective Response ◽  
Progression Free Survival ◽  
Ampullary Carcinoma ◽  
Small Bowel Adenocarcinoma ◽  
Kaplan Meier ◽  
Group A ◽  
Group B ◽  
Ecog Ps

260 Background: No standard care has been established for advanced small-bowel adenocarcinoma (SBA). The aim of this study is to explore a most promising chemotherapy regimen for advanced SBA. Methods: All data were collected from medical records of patients with advanced or recurrent SBA who received chemotherapy between April 1999 and March 2009 at 41 hospitals in Japan. Selection criteria were as follows: 1) histologically proven SBA, excluding ampullary carcinoma, 2) no previous chemotherapy or radiotherapy, 3) ECOG PS 0-2, 4) adequate bone marrow, hepatic and renal functions, 5) no concomitant malignancy. Patients were divided into the five groups by regimens: group A, fluoropyrimidine alone; group B, fluoropyrimidine + cisplatin; group C, fluoropyrimidine + oxaliplatin; group D, fluoropyrimidine + irinotecan; group E, others. Progression-free survival (PFS) and overall survival (OS) were calculated by Kaplan-Meier method. Results: Demographics of selected 132 patients were: median age (range), 59 (23-78) years; male/female, 87/45; location of primary tumor, duodenum/jejunum/ileum/unknown, 80/32/17/3; advanced/recurrent disease, 91/41. The numbers of the patients in group A, B, C, D and E were 60, 17, 22, 11 and 22, and objective response rates (ORR) in the patients with target lesions were 20% (9/46), 38% (5/13), 42% (8/19), 25% (2/8), 21% (4/19), respectively. Median PFS and OS were 6.0 and 14.0 months for the whole population, and those in each group are shown in the Table.In comparison with fluoropyrimidine alone (A), oxaliplatin-combined regimens (C) associated with better PFS (HR=0.53 [0.31-0.93], p=0.03) and OS (HR=0.64 [0.33-1.25], p=0.19), while cisplatin-combined regimens (B) did not (HR=1.54 [0.88-2.68], p=0.13 for PFS and HR=1.67 [0.94-2.97], p=0.08 for OS) by univariate analysis. Conclusions: It is suggested that oxaliplatin-combined regimens might be the most promising regimen for advanced SBA. [Table: see text] No significant financial relationships to disclose.

scholarly journals Multiparameter MRI Radiomics Model Predicts Preoperative Peritoneal Carcinomatosis in Ovarian Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiao Yu Yu ◽  
Jialiang Ren ◽  
Yushan Jia ◽  
Hui Wu ◽  
Guangming Niu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Ovarian Cancer ◽  
Peritoneal Carcinomatosis ◽  
Calibration Curve ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Imaging Features ◽  
Decision Curve Analysis ◽  
Dce Mri

ObjectivesTo evaluate the predictive value of radiomics features based on multiparameter magnetic resonance imaging (MP-MRI) for peritoneal carcinomatosis (PC) in patients with ovarian cancer (OC).MethodsA total of 86 patients with epithelial OC were included in this retrospective study. All patients underwent FS-T2WI, DWI, and DCE-MRI scans, followed by total hysterectomy plus omentectomy. Quantitative imaging features were extracted from preoperative FS-T2WI, DWI, and DCE-MRI images, and feature screening was performed using a minimum redundancy maximum correlation (mRMR) and least absolute shrinkage selection operator (LASSO) methods. Four radiomics models were constructed based on three MRI sequences. Then, combined with radiomics characteristics and clinicopathological risk factors, a multi-factor Logistic regression method was used to construct a radiomics nomogram, and the performance of the radiomics nomogram was evaluated by receiver operating characteristic curve (ROC) curve, calibration curve, and decision curve analysis.ResultsThe radiomics model from the MP-MRI combined sequence showed a higher area under the curve (AUC) than the model from FS-T2WI, DWI, and DCE-MRI alone (0.846 vs. 0.762, 0.830, 0.807, respectively). The radiomics nomogram (AUC=0.902) constructed by combining radiomics characteristics and clinicopathological risk factors showed a better diagnostic effect than the clinical model (AUC=0.858) and the radiomics model (AUC=0.846). The decision curve analysis shows that the radiomics nomogram has good clinical application value, and the calibration curve also proves that it has good stability.ConclusionRadiomics nomogram based on MP-MRI combined sequence showed good predictive accuracy for PC in patients with OC. This tool can be used to identify peritoneal carcinomatosis in OC patients before surgery.

scholarly journals Predicting the risk of sarcopenia in elderly patients with patellar fracture: Development and assessment of a new predictive nomogram

2019 ◽  
Author(s):  
Chen Yisheng ◽  
Tao Jie
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Elderly Patients ◽  
Prediction Model ◽  
Predictive Model ◽  
Body Mass ◽  
Curve Analysis ◽  
Decision Curve Analysis ◽  
Low Body Mass Index ◽  
Patellar Fractures

AbstractPurposeThis study was aimed at developing a risk prediction model for postoperative dysplasia in elderly patients with patellar fractures in China.Patients and methodsWe conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (Lasso analysis). The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We conducted internal sampling methods for qualitative assessment.ResultWe recruited 61 participants (males: 20, mean age: 68.1 years). Various risk factors were assessed, and low body mass index and diabetes mellitus were identified as the most important risk factors (P<0.05). The model showed a good prediction rate (C-index: 0.909; 95% confidence interval: 0.81–1.00) and good correction effect. The C-index remained high (0.828) even after internal sample verification. Decision curve analysis showed that the risk of sarcopenia was 8.3–80.0%, suggesting good clinical practicability.ConclusionOur prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, longer postoperative hospital stay, no higher education, no postoperative rehabilitation, removal of internal fixation, and less outdoor exercise.

scholarly journals Prediction of 90-day mortality among sepsis patients based on a nomogram integrating diverse clinical indices

2021 ◽  
Author(s):  
Qing-Bo Zeng ◽  
Long-Ping He ◽  
Nian-Qing Zhang ◽  
Qing-Wei Lin ◽  
Lin-Cui Zhong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Validation Cohort ◽  
International Normalized Ratio ◽  
Curve Analysis ◽  
Individual Risk ◽  
Decision Curve Analysis ◽  
Training Cohort ◽  
Receiver Operating Characteristic Curves ◽  
Individual Risk Factors

Abstract Background Sepsis is prevalent among intensive care units and is a frequent cause of death. Several studies have identified individual risk factors or potential predictors of sepsis-associated mortality, without defining an integrated predictive model. The present work aimed to define a nomogram for reliably predicting mortality. Methods We carried out a retrospective, single-center study based on 231 patients with sepsis who were admitted to our intensive care unit between May 2018 and October 2020. Patients were randomly split into training and validation cohorts. In the training cohort, multivariate logistic regression and a stepwise algorithm were performed to identify risk factors, which were then integrated into a predictive nomogram. Nomogram performance was assessed against the training and validation cohorts based on the area under receiver operating characteristic curves (AUC), calibration plots and decision curve analysis. Results Among the 161 patients in the training cohort and 70 patients in the validation cohort, 90-day mortality was 31.6%. Older age and higher values for the international normalized ratio, lactate level, and thrombomodulin level were associated with greater risk of 90-day mortality. The nomogram showed an AUC of 0.810 (95% CI 0.739 to 0.881) in the training cohort and 0.813 (95% CI 0.708 to 0.917) in the validation cohort. The nomogram also performed well based on the calibration curve and decision curve analysis. Conclusion This nomogram may help identify sepsis patients at elevated risk of 90-day mortality, which may help clinicians allocate resources appropriately to improve patient outcomes.

scholarly journals A nomogram to predict prognosis after surgery for young patients with hepatocellular carcinoma

2020 ◽  
Author(s):  
Xingchen Li ◽  
Xinyu Bi ◽  
Jianjun Zhao ◽  
Zhiyu Li ◽  
Jianguo Zhou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Young Patients ◽  
Risk Groups ◽  
Curve Analysis ◽  
Rank Test ◽  
Cancer Center ◽  
Cancer Specific Survival ◽  
Decision Curve Analysis ◽  
Log Rank Test ◽  
Kaplan Meier

Abstract Background Only few studies have been evaluated the clinical characteristics and prognosis of hepatocellular carcinoma in young patients. The purpose of this study is to identify prognostic factors and develop an efficient and practical nomogram to predict cancer-specific survival in young patients with hepatocellular carcinoma.Methods Four-hundred-and-forty-one young patients with hepatocellular carcinoma who had undergone surgery from 2004-2015 were selected from the Surveillance, Epidemiology, and End Results database. The competing risk model, Lasso and Cox regression were used to screen prognostic factors for cancer-specific survival, and a prognostic nomogram was established using these factors. Thirty-nine young patients with hepatocellular carcinoma from the National Cancer Center, Cancer Hospital, Chinese Academy of Medical Science were used to validate our model. To further evaluate the predictive performance of our model, the concordance index was calculated and the calibration curves were drawn. The clinical usefulness was evaluated by decision curve analysis(DCA). Finally, all patients were grouped by our nomogram. The survival of different risk groups was analyzed using the Kaplan-Meier method, and the differences among survival curves were compared by the log-rank test.Results The median survival times of the Surveillance, Epidemiology, and End Results training group and the external National Cancer Center validation group were 41 and 52 months, respectively. Histological grade, tumor size, Alpha-fetoprotein, T stage, and M stage were selected as independent factors for cancer-specific survival, and a prognostic nomogram was established. The concordance indices of the training and external validation groups were 0.76 (95% CI, 0.72 to 0.80) and 0.92 (se=0.085), respectively. The calibration plots showed good agreement. Decision curve analysis revealed that our nomogram resulted in a better clinical net benefit than the AJCC 7th edition and Barcelona Clinic Liver Cancer staging systems. Patients were divided into two risk groups according to the cut-off value of 125 of the total points from our nomogram. Kaplan-Meier plots for cancer-specific survival were performed using the log-rank test, the p-value of which was <0.001.Conclusions The practical nomogram resulted in a more-accurate prognostic prediction for young hepatocellular carcinoma patients after curative liver resection.

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