scholarly journals Validation of a Prediction Tool for Chemotherapy Toxicity in Older Adults With Cancer

2016 ◽  
Vol 34 (20) ◽  
pp. 2366-2371 ◽  
Author(s):  
Arti Hurria ◽  
Supriya Mohile ◽  
Ajeet Gajra ◽  
Heidi Klepin ◽  
Hyman Muss ◽  
...  
Keyword(s):  
Older Adults ◽  
High Risk ◽  
Prediction Model ◽  
Receiver Operating Characteristic Curve ◽  
Predictive Model ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Chemotherapy Toxicity ◽  
Operating Characteristic Curve ◽  
Grade 3

Purpose Older adults are at increased risk for chemotherapy toxicity, and standard oncology assessment measures cannot identify those at risk. A predictive model for chemotherapy toxicity was developed (N = 500) that consisted of geriatric assessment questions and other clinical variables. This study aims to externally validate this model in an independent cohort (N = 250). Patients and Methods Patients age ≥ 65 years with a solid tumor, fluent in English, and who were scheduled to receive a new chemotherapy regimen were recruited from eight institutions. Risk of chemotherapy toxicity was calculated (low, medium, or high risk) on the basis of the prediction model before the start of chemotherapy. Chemotherapy-related toxicity was captured (grade 3 [hospitalization indicated], grade 4 [life threatening], and grade 5 [treatment-related death]). Validation of the prediction model was performed by calculating the area under the receiver-operating characteristic curve. Results The study sample (N = 250) had a mean age of 73 years (range, 65 to 94 [standard deviation, 5.8]). More than one half of patients (58%) experienced grade ≥ 3 toxicity. Risk of toxicity increased with increasing risk score (36.7% low, 62.4% medium, 70.2% high risk; P < .001). The area under the curve of the receiver-operating characteristic curve was 0.65 (95% CI, 0.58 to 0.71), which was not statistically different from the development cohort (0.72; 95% CI, 0.68 to 0.77; P = .09). There was no association between Karnofsky Performance Status and chemotherapy toxicity (P = .25). Conclusion This study externally validated a chemotherapy toxicity predictive model for older adults with cancer. This predictive model should be considered when discussing the risks and benefits of chemotherapy with older adults.

scholarly journals A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children

2020 ◽  
Vol 31 (6) ◽  
pp. 1348-1357 ◽  
Author(s):  
Ibrahim Sandokji ◽  
Yu Yamamoto ◽  
Aditya Biswas ◽  
Tanima Arora ◽  
Ugochukwu Ugwuowo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
External Validation ◽  
Health Record ◽  
Hospitalized Children ◽  
Operating Characteristic Curve ◽  
Electronic Health

BackgroundTimely prediction of AKI in children can allow for targeted interventions, but the wealth of data in the electronic health record poses unique modeling challenges.MethodsWe retrospectively reviewed the electronic medical records of all children younger than 18 years old who had at least two creatinine values measured during a hospital admission from January 2014 through January 2018. We divided the study population into derivation, and internal and external validation cohorts, and used five feature selection techniques to select 10 of 720 potentially predictive variables from the electronic health records. Model performance was assessed by the area under the receiver operating characteristic curve in the validation cohorts. The primary outcome was development of AKI (per the Kidney Disease Improving Global Outcomes creatinine definition) within a moving 48-hour window. Secondary outcomes included severe AKI (stage 2 or 3), inpatient mortality, and length of stay.ResultsAmong 8473 encounters studied, AKI occurred in 516 (10.2%), 207 (9%), and 27 (2.5%) encounters in the derivation, and internal and external validation cohorts, respectively. The highest-performing model used a machine learning-based genetic algorithm, with an overall receiver operating characteristic curve in the internal validation cohort of 0.76 [95% confidence interval (CI), 0.72 to 0.79] for AKI, 0.79 (95% CI, 0.74 to 0.83) for severe AKI, and 0.81 (95% CI, 0.77 to 0.86) for neonatal AKI. To translate this prediction model into a clinical risk-stratification tool, we identified high- and low-risk threshold points.ConclusionsUsing various machine learning algorithms, we identified and validated a time-updated prediction model of ten readily available electronic health record variables to accurately predict imminent AKI in hospitalized children.

scholarly journals A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Shixiong Wu ◽  
Cen Zhang ◽  
Jing Xie ◽  
Shuang Li ◽  
Shuo Huang
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Nasopharyngeal Carcinoma ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Risk Group ◽  
Characteristic Curve ◽  
High Risk Group ◽  
Prognostic Signature ◽  
Operating Characteristic Curve

BackgroundThere is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC).MethodsWe constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (N = 213). We verified its prognostic value using three independent external validation cohorts (GSE36682, N = 62; GSE70970, N = 246; and TCGA-HNSC, N = 523). Through principal component analysis, receiver operating characteristic curve analysis, and C-index calculation, we confirmed the predictive accuracy of this prognostic signature.ResultsWe calculated the risk score based on the LASSO algorithm and divided the patients into high- and low-risk groups according to the calculated optimal cutoff value. The patients in the high-risk group tended to have a worse prognosis outcome and chemotherapy response. The time-dependent receiver operating characteristic curve showed that the 1-year overall survival rate of the five-microRNA signature had an area under the curve of more than 0.83. A functional annotation analysis of the five-microRNA signature showed that the patients in the high-risk group were usually accompanied by activation of DNA repair and MYC-target pathways, while the patients in the low-risk group had higher immune-related pathway signals.ConclusionsWe constructed a five-microRNA prognostic signature, which could accurately predict the prognosis of nasopharyngeal carcinoma, and constructed a nomogram that could conveniently predict the overall survival of patients.

scholarly journals Predicting Risk of Postoperative Lung Injury in High-risk Surgical Patients

2014 ◽  
Vol 120 (5) ◽  
pp. 1168-1181 ◽  
Author(s):  
Daryl J. Kor ◽  
Ravi K. Lingineni ◽  
Ognjen Gajic ◽  
Pauline K. Park ◽  
James M. Blum ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Surgical Patients ◽  
Patients At Risk ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background: Acute respiratory distress syndrome (ARDS) remains a serious postoperative complication. Although ARDS prevention is a priority, the inability to identify patients at risk for ARDS remains a barrier to progress. The authors tested and refined the previously reported surgical lung injury prediction (SLIP) model in a multicenter cohort of at-risk surgical patients. Methods: This is a secondary analysis of a multicenter, prospective cohort investigation evaluating high-risk patients undergoing surgery. Preoperative ARDS risk factors and risk modifiers were evaluated for inclusion in a parsimonious risk-prediction model. Multiple imputation and domain analysis were used to facilitate development of a refined model, designated SLIP-2. Area under the receiver operating characteristic curve and the Hosmer–Lemeshow goodness-of-fit test were used to assess model performance. Results: Among 1,562 at-risk patients, ARDS developed in 117 (7.5%). Nine independent predictors of ARDS were identified: sepsis, high-risk aortic vascular surgery, high-risk cardiac surgery, emergency surgery, cirrhosis, admission location other than home, increased respiratory rate (20 to 29 and ≥30 breaths/min), Fio2 greater than 35%, and Spo2 less than 95%. The original SLIP score performed poorly in this heterogeneous cohort with baseline risk factors for ARDS (area under the receiver operating characteristic curve [95% CI], 0.56 [0.50 to 0.62]). In contrast, SLIP-2 score performed well (area under the receiver operating characteristic curve [95% CI], 0.84 [0.81 to 0.88]). Internal validation indicated similar discrimination, with an area under the receiver operating characteristic curve of 0.84. Conclusions: In this multicenter cohort of patients at risk for ARDS, the SLIP-2 score outperformed the original SLIP score. If validated in an independent sample, this tool may help identify surgical patients at high risk for ARDS.

Four Square Step Test With Foam Is More Accurate Than Those Without Foam for Discriminating Between Older Adults With and Without Fall History

2018 ◽  
Vol 26 (4) ◽  
pp. 624-628 ◽  
Author(s):  
Phakkanut Mathurapongsakul ◽  
Akkradate Siriphorn
Keyword(s):  
Older Adults ◽  
Receiver Operating Characteristic Curve ◽  
Alternative Assessment ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Step Test ◽  
Cutoff Score ◽  
Operating Characteristic Curve ◽  
Four Square

Objective:The aim was to compare the use of the four square step test (FSST) and the FSST with foam surface (FSST + foam) scores for discriminating between adults, faller older adults, and nonfaller older adults.Methods:Fifty-four participants (18 for each group) were assessed using the FSST and FSST + foam. The area under the curve (AUC) of receiver operating characteristic curve was calculated and used to compare the accuracy of the tests.Results:The FSST + foam was more accurate than FSST for discriminating between faller and nonfaller older adults (area under the curves were 0.765 and 0.725, respectively) and between nonfaller older adults and adults (area under the curves were 0.99 and 0.95, respectively). The cutoff score for discriminating between faller and nonfaller older adults was 11.21, with a sensitivity and specificity of 0.889 and 0.611, respectively.Conclusion:FSST + foam could be used as an alternative assessment for discriminating between adults, faller, and nonfaller older adults.

A validated novel preoperative index to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology: A cohort study

2019 ◽  
Vol 30 (7-8) ◽  
pp. 221-228
Author(s):  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
Nicholas Hobbs ◽  
Jigar Shah ◽  
Matthew Harris ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Emergency Laparotomy ◽  
Contamination Index ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.

scholarly journals Evaluation of factors that predict the success rate of trial of labor after the cesarean section

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yang Mi ◽  
Pengfei Qu ◽  
Na Guo ◽  
Ruimiao Bai ◽  
Jiayi Gao ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cesarean Section ◽  
Receiver Operating Characteristic Curve ◽  
Success Rate ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Predictive Ability ◽  
Training Set ◽  
History Of ◽  
Operating Characteristic Curve

Abstract Background For most women who have had a previous cesarean section, vaginal birth after cesarean section (VBAC) is a reasonable and safe choice, but which will increase the risk of adverse outcomes such as uterine rupture. In order to reduce the risk, we evaluated the factors that may affect VBAC and and established a model for predicting the success rate of trial of the labor after cesarean section (TOLAC). Methods All patients who gave birth at Northwest Women’s and Children’s Hospital from January 2016 to December 2018, had a history of cesarean section and voluntarily chose the TOLAC were recruited. Among them, 80% of the population was randomly assigned to the training set, while the remaining 20% were assigned to the external validation set. In the training set, univariate and multivariate logistic regression models were used to identify indicators related to successful TOLAC. A nomogram was constructed based on the results of multiple logistic regression analysis, and the selected variables included in the nomogram were used to predict the probability of successfully obtaining TOLAC. The area under the receiver operating characteristic curve was used to judge the predictive ability of the model. Results A total of 778 pregnant women were included in this study. Among them, 595 (76.48%) successfully underwent TOLAC, whereas 183 (23.52%) failed and switched to cesarean section. In multi-factor logistic regression, parity = 1, pre-pregnancy BMI < 24 kg/m2, cervical score ≥ 5, a history of previous vaginal delivery and neonatal birthweight < 3300 g were associated with the success of TOLAC. The area under the receiver operating characteristic curve in the prediction and validation models was 0.815 (95% CI: 0.762–0.854) and 0.730 (95% CI: 0.652–0.808), respectively, indicating that the nomogram prediction model had medium discriminative power. Conclusion The TOLAC was useful to reducing the cesarean section rate. Being primiparous, not overweight or obese, having a cervical score ≥ 5, a history of previous vaginal delivery or neonatal birthweight < 3300 g were protective indicators. In this study, the validated model had an approving predictive ability.

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