scholarly journals Development and Validation of a New Risk Scoring System for Cancer Patients with Suspected Infection

2021 ◽  
Author(s):  
Bora Chae ◽  
Seonok Kim ◽  
Yoon-Seon Lee
Keyword(s):  
Cancer Patients ◽  
Scoring System ◽  
Validation Cohort ◽  
Performance Status ◽  
Eastern Cooperative Oncology Group ◽  
Peripheral Oxygen Saturation ◽  
Suspected Infection ◽  
Risk Scoring ◽  
Risk Scoring System ◽  
New Scoring

Abstract Purpose: This study aimed to develop a new prognostic model for predicting 30-day mortality in cancer patients with suspected infection.Methods: This study is a retrospective cohort study and was conducted from August 2019 to December 2019 at a single center. Adult active cancer patients with suspected infection were enrolled among visitors to the emergency room (ER). Logistic regression analysis was used to identify potential predictors for a new model. Results: A total of 899 patients were included; 450 in the development cohort and 449 in the validation cohort. Six independent variables predicted 30-day mortality: Eastern Cooperative Oncology Group (ECOG) performance status (PS), peripheral oxygen saturation (SpO2), creatinine, bilirubin, C-reactive protein (CRP), and lactate. The C-statistic of the new scoring system was 0.799 in the development cohort and 0.793 in the validation cohort. The C-statistics in the development cohort was significantly higher than those of SOFA [0.723 (95% CI: 0.663–0.783)], qSOFA [0.596 (95% CI: 0.537–0.655)], and SIRS [0.547 (95% CI: 0.483–0.612)]. Conclusions: The discriminative capability of the new cancer-specific risk scoring system was good in cancer patients with suspected infection. The new scoring system was superior to SOFA, qSOFA, and SIRS in predicting mortality.

scholarly journals Accuracy of risk scoring system to determine delayed chemotherapy induced nausea and vomiting (CINV) in cancer patients

2019 ◽  
Vol 30 ◽  
pp. ix146
Author(s):  
H. Reddy ◽  
V.V. Maka ◽  
A. D ◽  
M. Krishna Murthy ◽  
A. Mandepudi ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Scoring System ◽  
Nausea And Vomiting ◽  
Risk Scoring ◽  
Risk Scoring System

Novel risk scoring system for metastatic renal cell carcinoma (mRCC) patients (pts) treated with cabozantinib (C).

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 734-734
Author(s):  
Meredith R Kline ◽  
Dylan J. Martini ◽  
Yuan Liu ◽  
Julie M. Shabto ◽  
Bradley Curtis Carthon ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Scoring System ◽  
Group Performance ◽  
Eastern Cooperative Oncology Group ◽  
Risk Scoring ◽  
Ecog Ps ◽  
Risk Scoring System

734 Background: Cabozantinib (C) is an effective treatment for metastatic renal cell carcinoma (mRCC) patients (pts). The international mRCC database consortium (IMDC) criteria is the gold standard for mRCC risk stratification. We created a risk scoring system for mRCC pts treated with C. Methods: We performed a retrospective review of 87 mRCC pts treated with C at Winship Cancer Institute from 2015-19. Overall survival (OS) and progression free survival (PFS) were defined as months from C initiation. The baseline characteristics and inflammation biomarkers included were monocyte, neutrophil, and platelet-to-lymphocyte ratios (MLR, NLR, and PLR respectively), RCC histology, body mass index (BMI), metastatic sites (mets), and Eastern Cooperative Oncology Group performance status (ECOG PS). Upon variable selection in multivariable analysis (MVA), elevated baseline MLR (≥0.71), presence of sarcomatoid histology, ECOG PS > 1, and absence of bone metastases were assigned 1 point. A three-level risk scoring system was created: low (score = 0-1), intermediate (score = 2), and high risk (score = 3-4). The Kaplan-Meier method, Cox proportional hazard model, and Uno’s C-statistics were used to examine performance. Results: The majority of pts were males (71%) with clear-cell RCC (75%). Most pts (67%) received 1+ prior line of therapy. High and intermediate risk pts had significantly shorter OS and PFS compared to low risk pts (Table). The C-statistics for our risk scoring system were higher than IMDC in predicting OS (0.7 vs. 0.62) and PFS (0.65 vs 0.57). Conclusions: Pts treated with C may benefit from risk scoring using RCC histology, ECOG PS, mets, and MLR. These results are hypothesis-generating and should be validated in a larger study.[Table: see text]

scholarly journals Development And Validation of a Risk Scoring System to Predict Pneumothorax in CT-Guided Percutaneous Transthoracic Needle Biopsy

2021 ◽  
Author(s):  
Qiuhong Yang ◽  
Lin cheng Luo ◽  
Xinyi Peng ◽  
Hailong Wei ◽  
Qun Yi ◽  
...  
Keyword(s):  
Scoring System ◽  
Validation Cohort ◽  
Transthoracic Needle Biopsy ◽  
Ct Guided ◽  
Score System ◽  
Derivation Cohort ◽  
Risk Scoring ◽  
Risk Score System ◽  
Risk Scoring System ◽  
Percutaneous Transthoracic Needle Biopsy

Abstract Objective: To develop and validate a risk scoring system using variables easily obtained for the prediction of pneumothorax in CT-guided percutaneous transthoracic needle biopsy (PTNB).Methods: The derivation cohort was comprised of 1001 patients who underwent CT-guided PTNB. Multivariate logistic regression was used to identify risk factors for pneumothorax, which were treated as the foundation to develop the risk scoring system. To validate the system, a validation cohort group of 230 patients was enrolled.Results: Age, puncture times, puncture depth, smoking index, number of specimens, bleeding from the needle path, and lobular lesion were identified as risk factors in the derivation cohort. A risk scoring system (Hosmer-Lemeshow goodness-of-fit test p =0.33) was developed. The area under the receiver operating characteristic curve (AUROC) was 0.601 by using the risk score system. This risk score system demonstrated a better diagnostic effect with increasing age. In the group of patients older than 80 years, the AUROC was 0.76, showing good predictive power. This risk scoring system was confirmed in the validation cohort with an AUROC of 0.736.Conclusion: This scoring system has a good predictive effect in both derivation and validation cohort.

scholarly journals A Risk Scoring System to Predict Progression to Severe Pneumonia in Patients with Covid-19

2020 ◽  
Author(s):  
Ji Yeon Lee ◽  
Byung-Ho Nam ◽  
Mhinjine Kim ◽  
Jongmin Hwang ◽  
Jin Young Kim ◽  
...  
Keyword(s):  
High Risk ◽  
Sensitivity And Specificity ◽  
Scoring System ◽  
Resource Constraints ◽  
Validation Cohort ◽  
Severe Pneumonia ◽  
High Risk Group ◽  
Risk Scores ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Rapid outbreak of coronavirus disease 2019 (Covid-19) raised major concern regarding medical resource constraints. We constructed and validated a scoring system for early prediction of progression to severe pneumonia in patients with Covid-19. A total of 561 patients from a Covid-19 designated hospital in Daegu, South Korea were randomly divided into two cohorts: development cohort (N=421) and validation cohort (N=140). We used multivariate logistic regression to identify four independent risk predictors for progression to severe pneumonia and constructed a risk scoring system by giving each factor a number of scores corresponding to its regression coefficient. We calculated risk scores for each patient and defined two groups: low risk (0 to 8 points) and high risk (9 to 20 points). In the development cohort, the sensitivity and specificity were 83.8% and 78.9%. In the validation cohort, the sensitivity and specificity were 70.8% and 79.3%, respectively. The C-statistics was 0.884 (95% CI, 0.833-0.934) in the development cohort and 0.828 (95% CI, 0.733-0.923) in the validation cohort. This risk scoring system is useful to identify high-risk group for progression to severe pneumonia in Covid-19 patients and can prevent unnecessary overuse of medical care in limited-resource settings.

A quantified risk-scoring system and rating model for postsurgical gastroparesis syndrome in gastric cancer patients

2017 ◽  
Vol 116 (4) ◽  
pp. 533-544 ◽  
Author(s):  
Xiao-dong Chen ◽  
Chen-chen Mao ◽  
Wei-teng Zhang ◽  
Ji Lin ◽  
Rui-sen Wu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
Scoring System ◽  
Risk Scoring ◽  
Gastric Cancer Patients ◽  
Rating Model ◽  
Risk Scoring System

scholarly journals IL17a and IL21 combined with surgical status predict the outcome of ovarian cancer patients

2015 ◽  
Vol 22 (5) ◽  
pp. 703-711 ◽  
Author(s):  
Yu-Li Chen ◽  
Cheng-Yang Chou ◽  
Ming-Cheng Chang ◽  
Han-Wei Lin ◽  
Ching-Ting Huang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Patients ◽  
Scoring System ◽  
Disease Free Survival ◽  
Validation Group ◽  
Immunological Parameters ◽  
Interleukin 17A ◽  
Risk Scoring ◽  
Immunological Factors ◽  
Risk Scoring System

Aside from tumor cells, ovarian cancer-related ascites contains the immune components. The aim of this study was to evaluate whether a combination of clinical and immunological parameters can predict survival in patients with ovarian cancer. Ascites specimens and medical records from 144 ovarian cancer patients at our hospital were used as the derivation group to select target clinical and immunological factors to generate a risk-scoring system to predict patient survival. Eighty-two cases from another hospital were used as the validation group to evaluate this system. The surgical status and expression levels of interleukin 17a (IL17a) and IL21 in ascites were selected for the risk-scoring system in the derivation group. The areas under the receiver operating characteristic (AUROC) curves of the overall score for disease-free survival (DFS) of the ovarian cancer patients were 0.84 in the derivation group, 0.85 in the validation group, and 0.84 for all the patients. The AUROC curves of the overall score for overall survival (OS) of cases were 0.78 in the derivation group, 0.76 in the validation group, and 0.76 for all the studied patients. Good correlations between overall risk score and survival of the ovarian cancer patients were demonstrated by sub-grouping all participants into four groups (P for trend <0.001 for DFS and OS). Therefore, acombination of clinical and immunological parameters can provide a practical scoring system to predict the survival of patients with ovarian carcinoma. IL17a and IL21 can potentially be used as prognostic and therapeutic biomarkers.

scholarly journals Development and Validation of a Risk Score for Predicting 1-Year Mortality Risk of STEMI Based on a Nationwide Cohort in China

2021 ◽  
Author(s):  
Si Chen ◽  
Qianzi Che ◽  
Yan Zhang ◽  
Jia Jia ◽  
Yiqun Wu ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Risk Score ◽  
Mortality Risk ◽  
Scoring System ◽  
Validation Cohort ◽  
Predictive Score ◽  
Inferior Wall ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract BackgroundA risk assessment for identifying long-term risk of post-discharge mortality in Chinese STEMI patients remains a concern. The aim of this study is to establish a bedside available risk scoring system for predicting 1-year mortality risk among Chinese STEMI patients. Methods STEMI patients(n=12611) were enrolled from the China STEMI Care Project Phase 2(CSCAP-2) collected between 2015 and 2016. Confounding bias was controlled using propensity score matching. Epidemiological, clinical, laboratory, and imaging variables, treatment strategy and medicine records were screened using extreme gradient boosting and nomogram according to the hazard ratio of Cox regression analysis to construct a predictive score. A validation cohort included 7342 patients collected in 2017 from CSCAP-2 was analyzed using receiver ROC and expectation (E)/observation (O) ratio to validate the risk scoring system. Results From 39 potential predictors, 8 variables were independent predictive factor and were included in the risk score: Killip class, early reperfusion strategy, Non-PCI intraoperative anticoagulants, heart rate, gender, age, anterior-wall myocardial infarction (AWMI) and inferior-wall myocardial infarction (IWMI). The new model demonstrated an excellent discrimination and calibration. The c-statistic and E/O ratio were 0.87(95%CI, 0.80-0.93) and 1.14(95%CI, 0.93-1.39) in the train set, 0.88 (95%CI, 0.78-0.96) and 1.15(95%CI, 0.85-1.56) in the test set, meanwhile, 0.89(95%CI, 0.82-0.95) and 1.00(95%CI, 0.81-1.23) in the validation cohort. The score has better sensitivity than the GRACE score and can recognize risk stratification among STEMI patients (P<0.001).Conclusions We developed a risk scoring system for predicting 1-year mortality risk of STEMI in a large Chinese population. The new score is easy-to-use and demonstrating a good discriminatory accuracy in predicting both short-term and long-term mortality risk in Chinese patients with STEMI.

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