Composite grading algorithm for the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE)

Background: The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events is an item library designed for eliciting patient-reported adverse events in oncology. For each adverse event, up to three individual items are scored for frequency, severity, and interference with daily activities. To align the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events with other standardized tools for adverse event assessment including the Common Terminology Criteria for Adverse Events, an algorithm for mapping individual items for any given adverse event to a single composite numerical grade was developed and tested. Methods: A five-step process was used: (1) All 179 possible Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events score combinations were presented to 20 clinical investigators to subjectively map combinations to single numerical grades ranging from 0 to 3. (2) Combinations with <75% agreement were presented to investigator committees at a National Clinical Trials Network cooperative group meeting to gain majority consensus via anonymous voting. (3) The resulting algorithm was refined via graphical and tabular approaches to assure directional consistency. (4) Validity, reliability, and sensitivity were assessed in a national study dataset. (5) Accuracy for delineating adverse events between study arms was measured in two Phase III clinical trials (NCT02066181 and NCT01522443). Results: In Step 1, 12/179 score combinations had <75% initial agreement. In Step 2, majority consensus was reached for all combinations. In Step 3, five grades were adjusted to assure directional consistency. In Steps 4 and 5, composite grades performed well and comparably to individual item scores on validity, reliability, sensitivity, and between-arm delineation. Conclusion: A composite grading algorithm has been developed and yields single numerical grades for adverse events assessed via the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events, and can be useful in analyses and reporting

Stimulation of vascularization of a subcutaneous scaffold applicable for pancreatic islet-transplantation enhances immediate post-transplant islet graft function but not long-term normoglycemia

Nephrolog

Ethnic and gender differences in applicants' decision-making processes: An application of the theory of reasoned action

Contains fulltext : 54483.pdf (publisher's version ) (Closed access)11 p

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

Measuring and comparing descend in elite race cycling with a perspective on real-time feedback for improving individual performance

Descend technique and performance vary among elite racing cyclists and it is not clear what slower riders should do to improve their performance. An observation study was performed of the descending technique of members of a World Tour cycling team and the technique of each member was compared with the fastest descender amongst them. The obtained data gives us guidelines for rider specific feedback in order to improve his performance. The bicycles were equipped with a system that could measure: velocity, cadence, pedal power, position, steer angle, 3D orientation, rotational speeds and linear accelerations of the rear frame and brake force front and rear. From our observation study, the brake point and apex position turned out to be distinctive indicators of a fast cornering technique in a descent for a tight, hairpin corner. These two indicators can be used as feedback for a slower rider to improve his descend performance.Biomechatronics & Human-Machine ControlResearch Funding Nationa

A Modelling Study to Examine Threat Assessment Algorithms Performance in Predicting Cyclist Fall Risk in Safety Critical Bicycle-Automatic Vehicle lnteractions

Falls are responsible for a large proportion of serious injuries and deaths among cyclists [1-4]. A common fall scenario is loss of balance during an emergency braking maneuver to avoid another vehicle [5-7]. Automated Vehicles (AV) have the potential to prevent these critical scenarios between bicycle and cars. However, current Threat Assessment Algorithms (TAA) used by AVs only consider collision avoidance to decide upon safe gaps and decelerations when interacting wih cyclists and do not consider bicycle specific balance-related constraints. To date, no studies have addressed this risk of falls in safety critical scenarios. Yet, given the bicycle dynamics, we hypothesized that the existing TAA may be inaccurate in predicting the threat of cyclist falls and misclassify unsafe interactions. To test this hypothesis, this study developed a simple Newtonian mechanics-based model that calculates the performance of two existing TAAs in four critical scenarios with two road conditions. Tue four scenarios are: (1) a crossing scenario and a bicycle following lead car scenario in which the car either (2) suddenly braked, (3) halted or (4) accelerated from standstill. These scenarios have been identified by bicycle-car conflict studies as common scenarios where the car driver elicits an emergency braking response of the cyclist [8-11] and are illustrated in Figure 1. The two TAAs are Time-to-Collision (TTC) and Headway (H). These TAAs are commonly used by AVs in the four critical scenarios that will be modelled. The two road conditions are a flat dry road and also a downhill wet road, which serves as a worst-case condition for loss of balance during emergency braking [12]

A Modelling Study to Examine Threat Assessment Algorithms Performance in Predicting Cyclist Fall Risk in Safety Critical Bicycle-Automatic Vehicle lnteractions

Falls are responsible for a large proportion of serious injuries and deaths among cyclists [1-4]. A common fall scenario is loss of balance during an emergency braking maneuver to avoid another vehicle [5-7]. Automated Vehicles (AV) have the potential to prevent these critical scenarios between bicycle and cars. However, current Threat Assessment Algorithms (TAA) used by AVs only consider collision avoidance to decide upon safe gaps and decelerations when interacting wih cyclists and do not consider bicycle specific balance-related constraints. To date, no studies have addressed this risk of falls in safety critical scenarios. Yet, given the bicycle dynamics, we hypothesized that the existing TAA may be inaccurate in predicting the threat of cyclist falls and misclassify unsafe interactions. To test this hypothesis, this study developed a simple Newtonian mechanics-based model that calculates the performance of two existing TAAs in four critical scenarios with two road conditions. Tue four scenarios are: (1) a crossing scenario and a bicycle following lead car scenario in which the car either (2) suddenly braked, (3) halted or (4) accelerated from standstill. These scenarios have been identified by bicycle-car conflict studies as common scenarios where the car driver elicits an emergency braking response of the cyclist [8-11] and are illustrated in Figure 1. The two TAAs are Time-to-Collision (TTC) and Headway (H). These TAAs are commonly used by AVs in the four critical scenarios that will be modelled. The two road conditions are a flat dry road and also a downhill wet road, which serves as a worst-case condition for loss of balance during emergency braking [12].Biomechatronics & Human-Machine Contro