Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test f...Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test for predicting the outcome of a radiation treatment. We determine the foresight capability of prostate tumour erradication (cure) from Monte Carlo simulations of the Dawson-Hillen TCP model. We construct the receiver operating characteristic (ROC) curves of the test from the probability distributions of the fraction of remaining tumour cells for simulated experiments that evolve either to cure or non-cure. Simulations show that a similar procedure may be applicable to clinical data. Results suggest that the evaluation of tumour sizes after the treatment has started may be used for short-term prognosis.展开更多
The oral glucose tolerance test(OGTT)has been widely used both in clinics and in basic research for a long time.It is applied to diagnose impaired glucose tolerance and/or type 2 diabetes mellitus in individuals.Addit...The oral glucose tolerance test(OGTT)has been widely used both in clinics and in basic research for a long time.It is applied to diagnose impaired glucose tolerance and/or type 2 diabetes mellitus in individuals.Additionally,it has been employed in research to investigate glucose utilization and insulin sensitivity in animals.The main aim of each was quite different,and the details are also somewhat varied.However,the time or duration of the OGTT was the same,using the 2-h post-glucose load glycemia in both,following the suggestions of the American Diabetes Association.Recently,the use of 30-min or 1-h post-glucose load glycemia in clinical practice has been recommended by several studies.In this review article,we describe this new view and suggest perspectives for the OGTT.Additionally,quantification of the glucose curve in basic research is also discussed.Unlike in clinical practice,the incremental area under the curve is not suitable for use in the studies involving animals receiving repeated treatments or chronic treatment.We discuss the potential mechanisms in detail.Moreover,variations between bench and bedside in the application of the OGTT are introduced.Finally,the newly identified method for the OGTT must achieve a recommendation from the American Diabetes Association or another official unit soon.In conclusion,we summarize the recent reports regarding the OGTT and add some of our own perspectives,including machine learning and others.展开更多
This study evaluates the effects of a fall experience caused by tripping during the repetitive stepping movements over an obstacle [obstacle-single leg forward step (OSFS) test]. The study included 147 participants wh...This study evaluates the effects of a fall experience caused by tripping during the repetitive stepping movements over an obstacle [obstacle-single leg forward step (OSFS) test]. The study included 147 participants who were divided into 2 groups: 25 fallers caused by tripping and 122 nonfallers. The subjects were asked to step forward over a 10-cm-high obstacle with 1 leg and then return to their original position, as quickly as possible, and this test was repeated for 5 times. The OSFS test was evaluated in 2 phases: the OSFS-F phase, wherein the participants stepped forward on one leg, and the OSFS-R phase, wherein they returned to their original position. Significant differences were observed in both phases of the OSFS test between the two groups, and the fallers by tripping were significantly inferior to the nonfallers. The area under the curve [AUC;area under the receiver operating characteristic (ROC) curve] was more than 0.63 for all the parameters, which was statistically significant. In conclusion, the fallers by tripping were inferior to the nonfallers in the obstacle step movement.展开更多
Objective： To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score（MEWS） system and the Acute Physiology and Chronic Health Evaluation（APACHE Ⅱ） system ...Objective： To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score（MEWS） system and the Acute Physiology and Chronic Health Evaluation（APACHE Ⅱ） system in the Emergency Department.Methods： Using a prospective study method, the APACHE Ⅱ and MEWS data for 640 patients hospitalized in the Emergency Internal Medicine Department were collected. The prognoses, two scores to predict the corresponding prediction index of sensitivity, specificity and positive predictive value for the prognosis,the negative predictive value and the ROC curve for predicting the prognosis were analyzed for all patients.Results： In the prediction of the risk of mortality, the MEWS system had a high resolution. The MEWS area under the ROC curve was 0.93. The area under the ROC curve for the APACHE score was 0.79, and the difference was statistically significant（Z =4.348, P 〈 0.01）.Conclusions： Both the MEWS and APACHE Ⅱ systems can be used to determine the severity of emergency patients and have a certain predictive value for the patient＇s mortality risk. However, the MEWS system is simple and quick to operate, making it a useful supplement for APACHE Ⅱ score.展开更多
In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. Within-cluster correlations need to be taken into account when analyzing such clustered data. A nonparametric m...In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. Within-cluster correlations need to be taken into account when analyzing such clustered data. A nonparametric method has been proposed by Obuchowski (1997) to estimate the Receiver Operating Characteristic curve area (AUC) for such clustered data. However, Obuchowski’s estimator gives equal weight to all pairwise rankings within and between cluster. In this paper, we modify Obuchowski’s estimate by allowing weights for the pairwise rankings vary across clusters. We consider the optimal weights for estimating one AUC as well as two AUCs’ difference. Our results in this paper show that the optimal weights depends on not only the within-patient correlation but also the proportion of patients that have both unaffected and affected units. More importantly, we show that the loss of efficiency using equal weight instead of our optimal weights can be severe when there is a large within-cluster correlation and the proportion of patients that have both unaffected and affected units is small.展开更多
Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species...Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species are thought to be a major threat to endemism.In this study,by examining the key variables that influence Acacia mearnsii,we sought to understand its potential invasion in eastern Zimbabwe.We used the maximum entropy(MaxEnt)method against a set of environmental variables to predict the potential invasion front of A.mearnsii.Our study showed that the predictor variables,i.e.,aspect,elevation,distance from streams,soil type and distance from the nearest A.mearnsii plantation adequately explained(training AUC=0.96 and test AUC=0.93)variability in the spatial distribution of invading A.mearnsii.The front of invasion by A.mearnsii seemed also to occur next to existing A.mearnsii plantations.Results from our study could be useful in identifying priority areas that could be targeted for controlling the spread of A.mearnsii in Zimbabwe and other areas under threat from A.mearnsii invasion.We recommend that the plantation owners pay for the control of A.mearnsii invasion about their plantations.展开更多
The lack of validated tools to predict how long sow farms will remain PRRS virus-free following successful elimination of the virus has deterred veterinarians and producers from attempting to eliminate the PRRS virus ...The lack of validated tools to predict how long sow farms will remain PRRS virus-free following successful elimination of the virus has deterred veterinarians and producers from attempting to eliminate the PRRS virus from sow farms. The aim of this study was to use the database of PRRS Risk Assessments for the Breeding Herd in PADRAP to develop and validate an objective risk scoring system for predicting the likelihood of virus introduction in PRRS virus-free sow farms in the US. To overcome the challenges of dealing with a large number of variables, group lasso for logistic regression (GLLR) was applied to a retrospective dataset of PRRS Risk Assessment for the Breeding Herd surveys completed for 704 farms to develop the risk scoring system. The validity of the GLLR risk scoring system was then evaluated by testing its predictive ability on a dataset from a long-term prospective study of 196 sow farms to assess risk factors associated with how long PRRS virus-free sow farms remained PRRS virus-free. Receiver operator characteristic(ROC) curves were estimated to compare the performance of the GLLR risk scoring system to the risk scoring system based on expert opinion (EO), currently used in the PRRS Risk Assessment for the Breeding Herd, for predicting whether herds remained PRRS virus-free for 130 weeks. The GLLR risk scoring system (AUC, 0.76;95% CI, 0.67 - 0.84) performed significantly better than the EO risk scoring system (AUC, 0.36;95% CI, 0.27 - 0.46) for predicting whether to sow farms in the prospective study survived for 130 weeks (p 0.001). Dividing farms into 3 risk groups (low, medium and high) using a low and high cutoff values for the GLLR risk score was informative as the differences in the KM survival curves for the 3 groups were both clinically meaningful and statistically significant. The GLLR risk scoring system used in conjunction with the PRRS Risk Assessment for the Breeding Herd survey delivered through PADRAP appears to have the potential to help veterinarians predict the likelihood of virus introduction in PRRS virus-free sow farms in the US.展开更多
基金the Brazilian agency CNPq for financial support.
文摘Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test for predicting the outcome of a radiation treatment. We determine the foresight capability of prostate tumour erradication (cure) from Monte Carlo simulations of the Dawson-Hillen TCP model. We construct the receiver operating characteristic (ROC) curves of the test from the probability distributions of the fraction of remaining tumour cells for simulated experiments that evolve either to cure or non-cure. Simulations show that a similar procedure may be applicable to clinical data. Results suggest that the evaluation of tumour sizes after the treatment has started may be used for short-term prognosis.
文摘The oral glucose tolerance test(OGTT)has been widely used both in clinics and in basic research for a long time.It is applied to diagnose impaired glucose tolerance and/or type 2 diabetes mellitus in individuals.Additionally,it has been employed in research to investigate glucose utilization and insulin sensitivity in animals.The main aim of each was quite different,and the details are also somewhat varied.However,the time or duration of the OGTT was the same,using the 2-h post-glucose load glycemia in both,following the suggestions of the American Diabetes Association.Recently,the use of 30-min or 1-h post-glucose load glycemia in clinical practice has been recommended by several studies.In this review article,we describe this new view and suggest perspectives for the OGTT.Additionally,quantification of the glucose curve in basic research is also discussed.Unlike in clinical practice,the incremental area under the curve is not suitable for use in the studies involving animals receiving repeated treatments or chronic treatment.We discuss the potential mechanisms in detail.Moreover,variations between bench and bedside in the application of the OGTT are introduced.Finally,the newly identified method for the OGTT must achieve a recommendation from the American Diabetes Association or another official unit soon.In conclusion,we summarize the recent reports regarding the OGTT and add some of our own perspectives,including machine learning and others.
文摘This study evaluates the effects of a fall experience caused by tripping during the repetitive stepping movements over an obstacle [obstacle-single leg forward step (OSFS) test]. The study included 147 participants who were divided into 2 groups: 25 fallers caused by tripping and 122 nonfallers. The subjects were asked to step forward over a 10-cm-high obstacle with 1 leg and then return to their original position, as quickly as possible, and this test was repeated for 5 times. The OSFS test was evaluated in 2 phases: the OSFS-F phase, wherein the participants stepped forward on one leg, and the OSFS-R phase, wherein they returned to their original position. Significant differences were observed in both phases of the OSFS test between the two groups, and the fallers by tripping were significantly inferior to the nonfallers. The area under the curve [AUC;area under the receiver operating characteristic (ROC) curve] was more than 0.63 for all the parameters, which was statistically significant. In conclusion, the fallers by tripping were inferior to the nonfallers in the obstacle step movement.
基金supported by Pudong New Area Health System leadership program(No.PWRd2016-11)National Natural Science Foundation of China(No.81360231)
文摘Objective： To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score（MEWS） system and the Acute Physiology and Chronic Health Evaluation（APACHE Ⅱ） system in the Emergency Department.Methods： Using a prospective study method, the APACHE Ⅱ and MEWS data for 640 patients hospitalized in the Emergency Internal Medicine Department were collected. The prognoses, two scores to predict the corresponding prediction index of sensitivity, specificity and positive predictive value for the prognosis,the negative predictive value and the ROC curve for predicting the prognosis were analyzed for all patients.Results： In the prediction of the risk of mortality, the MEWS system had a high resolution. The MEWS area under the ROC curve was 0.93. The area under the ROC curve for the APACHE score was 0.79, and the difference was statistically significant（Z =4.348, P 〈 0.01）.Conclusions： Both the MEWS and APACHE Ⅱ systems can be used to determine the severity of emergency patients and have a certain predictive value for the patient＇s mortality risk. However, the MEWS system is simple and quick to operate, making it a useful supplement for APACHE Ⅱ score.
文摘In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. Within-cluster correlations need to be taken into account when analyzing such clustered data. A nonparametric method has been proposed by Obuchowski (1997) to estimate the Receiver Operating Characteristic curve area (AUC) for such clustered data. However, Obuchowski’s estimator gives equal weight to all pairwise rankings within and between cluster. In this paper, we modify Obuchowski’s estimate by allowing weights for the pairwise rankings vary across clusters. We consider the optimal weights for estimating one AUC as well as two AUCs’ difference. Our results in this paper show that the optimal weights depends on not only the within-patient correlation but also the proportion of patients that have both unaffected and affected units. More importantly, we show that the loss of efficiency using equal weight instead of our optimal weights can be severe when there is a large within-cluster correlation and the proportion of patients that have both unaffected and affected units is small.
文摘Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species are thought to be a major threat to endemism.In this study,by examining the key variables that influence Acacia mearnsii,we sought to understand its potential invasion in eastern Zimbabwe.We used the maximum entropy(MaxEnt)method against a set of environmental variables to predict the potential invasion front of A.mearnsii.Our study showed that the predictor variables,i.e.,aspect,elevation,distance from streams,soil type and distance from the nearest A.mearnsii plantation adequately explained(training AUC=0.96 and test AUC=0.93)variability in the spatial distribution of invading A.mearnsii.The front of invasion by A.mearnsii seemed also to occur next to existing A.mearnsii plantations.Results from our study could be useful in identifying priority areas that could be targeted for controlling the spread of A.mearnsii in Zimbabwe and other areas under threat from A.mearnsii invasion.We recommend that the plantation owners pay for the control of A.mearnsii invasion about their plantations.
文摘The lack of validated tools to predict how long sow farms will remain PRRS virus-free following successful elimination of the virus has deterred veterinarians and producers from attempting to eliminate the PRRS virus from sow farms. The aim of this study was to use the database of PRRS Risk Assessments for the Breeding Herd in PADRAP to develop and validate an objective risk scoring system for predicting the likelihood of virus introduction in PRRS virus-free sow farms in the US. To overcome the challenges of dealing with a large number of variables, group lasso for logistic regression (GLLR) was applied to a retrospective dataset of PRRS Risk Assessment for the Breeding Herd surveys completed for 704 farms to develop the risk scoring system. The validity of the GLLR risk scoring system was then evaluated by testing its predictive ability on a dataset from a long-term prospective study of 196 sow farms to assess risk factors associated with how long PRRS virus-free sow farms remained PRRS virus-free. Receiver operator characteristic(ROC) curves were estimated to compare the performance of the GLLR risk scoring system to the risk scoring system based on expert opinion (EO), currently used in the PRRS Risk Assessment for the Breeding Herd, for predicting whether herds remained PRRS virus-free for 130 weeks. The GLLR risk scoring system (AUC, 0.76;95% CI, 0.67 - 0.84) performed significantly better than the EO risk scoring system (AUC, 0.36;95% CI, 0.27 - 0.46) for predicting whether to sow farms in the prospective study survived for 130 weeks (p 0.001). Dividing farms into 3 risk groups (low, medium and high) using a low and high cutoff values for the GLLR risk score was informative as the differences in the KM survival curves for the 3 groups were both clinically meaningful and statistically significant. The GLLR risk scoring system used in conjunction with the PRRS Risk Assessment for the Breeding Herd survey delivered through PADRAP appears to have the potential to help veterinarians predict the likelihood of virus introduction in PRRS virus-free sow farms in the US.
