scholarly journals Development and validation of a risk prediction model for radiotherapy-related esophageal fistula in esophageal cancer

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Yiyue Xu ◽  
Linlin Wang ◽  
Bo He ◽  
Wanlong Li ◽  
Qiang Wen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Esophageal Cancer ◽  
Risk Prediction ◽  
External Validation ◽  
Individual Risk ◽  
Esophageal Fistula ◽  
Multivariable Analyses ◽  
Independent Risk Factors ◽  
Ecog Ps ◽  
Development And Validation

Abstract Objectives We aimed to identify the risk factors and provide a nomogram for the prediction of radiotherapy-related esophageal fistula in patients with esophageal cancer (EC) using a case-control study. Patients and methods Patients with esophageal fistula who received radiotherapy or chemoradiotherapy between 2003 and 2017 were retrospectively collected in two institutions. In the training cohort (TC), clinical, pathologic, and serum data of 136 patients (cases) who developed esophageal fistula during or after radiotherapy were enrolled and compared with 272 controls (1:2 matched with the diagnosis time of EC, sex, marriage, and race). After the univariable and multivariable logistic regression analyses, the independent risk factors were identified and incorporated into a nomogram. Then the nomogram for the risk prediction was externally validated in the validation cohort (VC; 47 cases and 94 controls) using bootstrap resampling. Results Multivariable analyses demonstrated that ECOG PS, BMI, T4, N2/3 and re-radiotherapy were independent factors for esophageal fistula. Then a nomogram was constructed with the C-index of 0.805 (95% CI, 0.762–0.848) for predicting the risk of developing esophageal fistula in EC patients receiving radiotherapy. Importantly, the C-index maintained 0.764 (95% CI, 0.683–0.845) after the external validation. Conclusions We created and externally validated the first risk nomogram of esophageal fistula associated with radiotherapy. This will aid individual risk stratification of patients with EC developing esophageal fistula.

scholarly journals Risk Prediction Models for Melanoma: A Systematic Review on the Heterogeneity in Model Development and Validation

2020 ◽  
Vol 17 (21) ◽  
pp. 7919
Author(s):  
Isabelle Kaiser ◽  
Annette B. Pfahlberg ◽  
Wolfgang Uter ◽  
Markus V. Heppt ◽  
Marit B. Veierød ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Model Development ◽  
Risk Prediction Models ◽  
Screening Programs ◽  
Development And Validation ◽  
Selection And Assessment

The rising incidence of cutaneous melanoma over the past few decades has prompted substantial efforts to develop risk prediction models identifying people at high risk of developing melanoma to facilitate targeted screening programs. We review these models, regarding study characteristics, differences in risk factor selection and assessment, evaluation, and validation methods. Our systematic literature search revealed 40 studies comprising 46 different risk prediction models eligible for the review. Altogether, 35 different risk factors were part of the models with nevi being the most common one (n = 35, 78%); little consistency in other risk factors was observed. Results of an internal validation were reported for less than half of the studies (n = 18, 45%), and only 6 performed external validation. In terms of model performance, 29 studies assessed the discriminative ability of their models; other performance measures, e.g., regarding calibration or clinical usefulness, were rarely reported. Due to the substantial heterogeneity in risk factor selection and assessment as well as methodologic aspects of model development, direct comparisons between models are hardly possible. Uniform methodologic standards for the development and validation of risk prediction models for melanoma and reporting standards for the accompanying publications are necessary and need to be obligatory for that reason.

90 Socio-Demographic and Medical Factors in A Multi-Ethnic Cohort of COVID Deaths

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
M Patel ◽  
U Umasankar ◽  
B McCall
Keyword(s):  
Risk Factors ◽  
South Asian ◽  
Multivariable Analysis ◽  
Uneventful Recovery ◽  
Asian Ethnicity ◽  
Black African ◽  
Medical Factors ◽  
Multivariable Analyses ◽  
Independent Risk Factors ◽  
Medical Wards

Abstract Introduction Whilst most patients during the COVID pandemic made an uneventful recovery,there was a significant minority in whom the disease was severe and unfortunately fatal. This survey aims to examine and evaluate risk factors for those patients who died of COVID and to identify any markers for improvement in the management of such patients during future COVID surges. Methods Medical records of all patients who died within a multi-ethnic, inner city acute district general hospital over a 6-week period in 2020 were examined. Data collected included demographic details, medical comorbidities, and type of ward where they received care. Multivariable analysis using stepwise backward logistic regression was conducted to examine independent risk factors for these patients. Results Of 275 deaths,204 were related to COVID. Compared to non-COVID deaths(n = 71), there were no age differences. There were significantly more deaths in males (58%vs39%,P < 0.001)) and in Black African and South Asian groups. 18% of COVID deaths were those who were not frail (Frailty Rockwood Scale 1–3) whereas there were no non-COVID deaths in this group(P < 0.001). 69% of COVID deaths occurred in general medical wards whereas 19% in critical care units (90% and 7% for non-COVID deaths,p < 0.001). COVID patients died more quickly compared to non-COVID patients (length of stay mean, 11vs21,p < 0.001). Medical factors prevalent in >20% of COVID deaths included Diabetes, Hypertension, Chronic Heart Disease, Chronic Kidney Disease,and Dementia. Multivariable analyses showed males (OR 1.9), age > 70(OR 2.0), frailty (OR 2.3) were independent risk factors for COVID deaths. Discussion Compared to non-COVID deaths,COVID deaths were more common in previously well individuals,males,Black African and South Asian ethnicity, but multivariable analyses showed males, age > 70 and frailty were independent risk factors for COVID deaths. This survey indicates that greater psychological support may be required for healthcare workers on general medical wards who looked after greater proportion of COVID deaths.

scholarly journals A New Rapid Approach for Predicting Death in Coronavirus Patients: The Development and Validation of the COVID-19 Risk-Score in Fars Province (CRSF)

2022 ◽  
Author(s):  
Mehrdad Sharifi ◽  
Mohammad Hossein Khademian ◽  
Razieh Sadat Mousavi-Roknabadi ◽  
Vahid Ebrahimi ◽  
Robab Sadegh
Keyword(s):  
Risk Factors ◽  
Risk Score ◽  
Predictive Value ◽  
Assessment Tool ◽  
Fars Province ◽  
Risk Of Mortality ◽  
Risk Patients ◽  
Independent Risk Factors ◽  
Development And Validation ◽  
Underlying Diseases

Background:Patients who are identified to be at a higher risk of mortality from COVID-19 should receive better treatment and monitoring. This study aimed to propose a simple yet accurate risk assessment tool to help decision-making in the management of the COVID-19 pandemic. Methods: From Jul to Nov 2020, 5454 patients from Fars Province, Iran, diagnosed with COVID-19 were enrolled. A multiple logistic regression model was trained on one dataset (training set: n=4183) and its prediction performance was assessed on another dataset (testing set: n=1271). This model was utilized to develop the COVID-19 risk-score in Fars (CRSF). Results: Five final independent risk factors including gender (male: OR=1.37), age (60-80: OR=2.67 and >80: OR=3.91), SpO2 (≤85%: OR=7.02), underlying diseases (yes: OR=1.25), and pulse rate (<60: OR=2.01 and >120: OR=1.60) were significantly associated with in-hospital mortality. The CRSF formula was obtained using the estimated regression coefficient values of the aforementioned factors. The point values for the risk factors varied from 2 to 19 and the total CRSF varied from 0 to 45. The ROC analysis showed that the CRSF values of ≥15 (high-risk patients) had a specificity of 73.5%, sensitivity of 76.5%, positive predictive value of 23.2%, and negative predictive value (NPV) of 96.8% for the prediction of death (AUC=0.824, P<0.0001). Conclusion:This simple CRSF system, which has a high NPV,can be useful for predicting the risk of mortality in COVID-19 patients. It can also be used as a disease severity indicator to determine triage level for hospitalization.

Abstract 196: Development and Validation of Machine Learning-based Race-specific Models to Predict 10-year Risk of Heart Failure: A Multi-cohort Analysis

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Matthew W Segar ◽  
Byron Jaeger ◽  
Kershaw V Patel ◽  
Vijay Nambi ◽  
Chiadi E Ndumele ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Heart Failure ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Superior Performance ◽  
Risk Models ◽  
Black And White ◽  
White Adults

Introduction: Heart failure (HF) risk and the underlying biological risk factors vary by race. Machine learning (ML) may improve race-specific HF risk prediction but this has not been fully evaluated. Methods: The study included participants from 4 cohorts (ARIC, DHS, JHS, and MESA) aged > 40 years, free of baseline HF, and with adjudicated HF event follow-up. Black adults from JHS and white adults from ARIC were used to derive race-specific ML models to predict 10-year HF risk. The ML models were externally validated in subgroups of black and white adults from ARIC (excluding JHS participants) and pooled MESA/DHS cohorts and compared to prior established HF risk scores developed in ARIC and MESA. Harrell’s C-index and Greenwood-Nam-D’Agostino chi-square were used to assess discrimination and calibration, respectively. Results: In the derivation cohorts, 288 of 4141 (7.0%) black and 391 of 8242 (4.7%) white adults developed HF over 10 years. The ML models had excellent discrimination in both black and white participants (C-indices = 0.88 and 0.89). In the external validation cohorts for black participants from ARIC (excluding JHS, N = 1072) and MESA/DHS pooled cohorts (N = 2821), 131 (12.2%) and 115 (4.1%) developed HF. The ML model had adequate calibration and demonstrated superior discrimination compared to established HF risk models (Fig A). A consistent pattern was also observed in the external validation cohorts of white participants from the MESA/DHS pooled cohorts (N=3236; 100 [3.1%] HF events) (Fig A). The most important predictors of HF in both races were NP levels. Cardiac biomarkers and glycemic parameters were most important among blacks while LV hypertrophy and prevalent CVD and traditional CV risk factors were the strongest predictors among whites (Fig B). Conclusions: Race-specific and ML-based HF risk models that integrate clinical, laboratory, and biomarker data demonstrated superior performance when compared to traditional risk prediction models.

O30 NON-RADICAL ESOPHAGECTOMY FOR ESOPHAGEAL CANCER; A NATIONWIDE STUDY ON INCIDENCE, RISK FACTORS AND OUTCOMES IN SWEDEN

2019 ◽  
Vol 32 (Supplement_2) ◽  
Author(s):  
David Edholm ◽  
Petter Hollertz ◽  
Per Sandström ◽  
Bergthor Björnsson ◽  
Dennis Björk ◽  
...  
Keyword(s):  
Risk Factors ◽  
Esophageal Cancer ◽  
Cox Regression ◽  
Regional Lymph Node ◽  
Neoadjuvant Treatment ◽  
Resected Specimen ◽  
Radical Esophagectomy ◽  
Term Survival ◽  
R1 Resection ◽  
Independent Risk Factors

Abstract Aim To identify potential risk factors for a microscopically non-radical esophageal cancer resection (R1) and investigate how such a resection affects long-term survival. Background & Methods Esophageal cancer resections that are considered R1 have been associated with worse survival. The Swedish National Register for Esophageal and Gastric Cancer includes information on all esophageal cancer resections in Sweden. All patients having undergone esophageal resection with curative intent 2006-2017 were included. Risk factors for R1 resection were assessed through logistic regression. Factors predicting five-year survival were assessed through Cox-regression, adjusted for T-stage, N-stage, age and R-status. Results The study included 1,504 patients. The margins were microscopically involved in 146 patients (10%). Of these the circumferential margin was involved in 115 (8%). The proximal margin was involved in 55 patients (4%) and the distal in 30 (2%). In 54 (4%) specimens two margins were involved. Independent risk factors for R1-resection were absence of neoadjuvant treatment and clinical T3 stage or higher. The 5-year survival for the entire cohort was 41%, but only 19% for those with an R1 resection. Independent risk factors for death within 5-year from resection were regional lymph node metastasis (Hazard Ratio (HR) 2.6 (95% CI 2.2-3.1), histopathological stage T3 or higher (HR 1.2 95% CI 1.1-1.5), age above 60 years and R1-resection (HR 1.6 95% CI 1.4-2.0) Conclusion Involved margin in the resected specimen is an independent risk factor predicting worse 5-year survival. Besides striving for adequate surgical margins, the rate of R1-resections could be decreased through neoadjuvant treatment in fit patients.

RA09.07: SURGICAL MANAGEMENT OF EARLY ESOPHAGEAL CANCER BASED ON LYMPH NODE METASTASIS RISK.

2018 ◽  
Vol 31 (Supplement_1) ◽  
pp. 41-41
Author(s):  
Xiaofeng Duan ◽  
Zhentao Yu
Keyword(s):  
Risk Factors ◽  
Esophageal Cancer ◽  
Lymph Node ◽  
Lymph Node Dissection ◽  
Tumor Location ◽  
Individual Risk ◽  
Node Dissection ◽  
Early Esophageal Cancer ◽  
Node Metastasis ◽  
The Individual

Abstract Background Esophagectomy and lymph node dissection is still the main treatment for esophageal cancer. Endoscopic mucosal resection and submucosal dissection are increasingly becoming a treatment of choice to preserve the integrity of the esophagus and decrease the surgical trauma in early esophageal cancer. However, lymph node metastasos (LNM) risk is still a debate focus for the decision of treatment selection. Our objective was to evaluate the prevalence, pattern and risk factors of LNM in early stage esophageal cancer to improve surgical treatment allocation. Methods We identified patients with pathological T1 stage esophageal cancer who underwent esophagectomy and lymph node dissection. The pattern of LNM was analyzed and the risk factors related to LNM were assessed by univariate and multivariable logistic regression analysis.The nomogram model was used to estimate the individual risk of lymph node metastasis. Results In 143 patients, LNM rates were: all patients 17.5%, T1a 8.0%, and T1b 22.5% for T1b. Depth of tumor infiltration (P < 0.05), tumor size (P < 0.01), tumor location (P < 0.05), and tumor differentiation (P < 0.01) were independent risk factors related to LNM. These four parameters allowed the compilation of a nomogram to estimate the individual risk of LNM. Fig. Nomogram to estimate the individual risk of LNM. Each characteristic of the included parameters scores a specific number of points (points per parameter). The summarized total points score indicates the probability of LNM. For a middle esophageal cancer with middle differentiated (G2), 3 cm tumor (> 2.5cm) that invades the submucosa (pT1b), the calculated total scores is 129.5 = 87.5 + 21 + 0 + 21, hence the corresponding LNM risk is 20%. Conclusion T1 esophageal cancer has a relatively high LNM rate, and the depth of tumor infiltration, tumor size, tumor location and tumor differentiation are correlated with LNM. Nomograms that include factors can be used to predict individual LNM risk. The LNM risk and extent must be considered comprehensively in decision-making of a better surgical treatment and lymph node dissection strategy. Disclosure All authors have declared no conflicts of interest.

scholarly journals Risk Factors for Esophageal Fistula Associated With Chemoradiotherapy for Locally Advanced Unresectable Esophageal Cancer

Medicine ◽  
2016 ◽  
Vol 95 (20) ◽  
pp. e3699 ◽  
Author(s):  
Takahiro Tsushima ◽  
Junki Mizusawa ◽  
Kazuki Sudo ◽  
Yoshitaka Honma ◽  
Ken Kato ◽  
...  
Keyword(s):  
Risk Factors ◽  
Esophageal Cancer ◽  
Locally Advanced ◽  
Esophageal Fistula

scholarly journals Serum MMP-9 and SAA in the Diagnosis of Severe Pneumonia Caused by Radiotherapy of Esophageal Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yu Zhou ◽  
Li Liu ◽  
Wenjun Gu
Keyword(s):  
Risk Factors ◽  
Esophageal Cancer ◽  
Lung Function ◽  
White Blood Cells ◽  
Severe Pneumonia ◽  
Diagnostic Value ◽  
Control Group ◽  
Radiation Group ◽  
Severe Group ◽  
Independent Risk Factors

Objective. To explore the relationship and diagnostic value of serum MMP-9 and SAA in severe pneumonia (sCAP) caused by radiotherapy of esophageal cancer. Methods. A total of 144 esophageal cancer patients who underwent radiotherapy in our hospital from April 2016 to February 2018 were collected. Among them, 58 patients without radiation pneumonitis (RP) were in the control group, 49 patients with grade 1∼2 RP were in the radiation group, and 37 patients with sCAP were in the severe group. The levels of serum MMP-9 and SAA in every group of patients were detected. The ROC curve was used to determine the diagnostic value of serum MMP-9 and SAA in the diagnosis of RP and sCAP. The correlation between serum MMP-9 and SAA and the patient’s lung function indexes was analyzed, and the logistic single-factor and multivariate analyses were performed to analyze the factors of sCAP in esophageal cancer radiotherapy. Results. PaO2, FVC, and FEV1 decreased in RP and sCAP, and PaCO2, white blood cells, serum MMP-9, and SAA levels increased ( P < 0.05 ); serum MMP-9 and SAA were negatively correlated with lung function ( P < 0.05 ); the AUC of serum MMP-9 and SAA in RP was 0.833 and 0.823, respectively, and the AUC of the two combined diagnosis of RP was 0.919. The AUC of serum MMP-9 and SAA in sCAP was 0.809 and 0.797, respectively, and the AUC of both combined diagnosis of sCAP was 0.873; logistics multivariate analysis found that serum MMP-9, serum SAA, double lung V5, and V20 were independent risk factors for sCAP caused by radiotherapy for esophageal cancer ( P < 0.05 ). Conclusion. Serum MMP-9 and SAA increase in RP and sCAP and are negatively correlated with lung function in patients with pneumonia. They are independent risk factors for severe pneumonia caused by radiotherapy of esophageal cancer and have good diagnostic value.

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