Merging self-reported with technically sensed data for tracking mobility behavior in a naturalistic intervention study. Insights from the GISMO study

Sound exposure data are central for any intervention study. In the case of utilitarian mobility, where studies cannot be conducted in controlled environments, exposure data are commonly self-reported. For short-term intervention studies, wearable devices with location sensors are increasingly employed. We aimed to combine self-reported and technically sensed mobility data, in order to provide more accurate and reliable exposure data for GISMO, a long-term intervention study. Through spatio-temporal data matching procedures, we are able to determine the amount of mobility for all modes at the best possible accuracy level. Self-reported data deviate ±10% from the corrected reference. Derived modal split statistics prove high compliance to the respective recommendations for the control group (CG) and the two intervention groups (IG-PT, IG-C). About 73.7% of total mileage was travelled by car in CG. This share was 10.3% (IG-PT) and 9.7% (IG-C), respectively, in the intervention groups. Commuting distances were comparable in CG and IG, but annual mean travel times differ between  = 8,458 min (σ = 6,427 min) for IG-PT,  = 8,444 min (σ = 5,961 min) for IG-C, and  = 5,223 min (σ = 5,463 min) for CG. Seasonal variabilities of modal split statistics were observable. However, in IG-PT and IG-C no shift toward the car occurred during winter months. Although no perfect single-method solution for acquiring exposure data in mobility-related, naturalistic intervention studies exists, we achieved substantially improved results by combining two data sources, based on spatio-temporal matching procedures.     

Circulating Fibronectin Controls Tumor Growth

Fibronectin is ubiquitously expressed in the extracellular matrix, and experimental evidence has shown that it modulates blood vessel formation. The relative contribution of local and circulating fibronectin to blood vessel formation in vivo remains unknown despite evidence for unexpected roles of circulating fibronectin in various diseases. Using transgenic mouse models, we established that circulating fibronectin facilitates the growth of bone metastases by enhancing blood vessel formation and maturation. This effect is more relevant than that of fibronectin produced by endothelial cells and pericytes, which only exert a small additive effect on vessel maturation. Circulating fibronectin enhances its local production in tumors through a positive feedback loop and increases the amount of vascular endothelial growth factor (VEGF) retained in the matrix. Both fibronectin and VEGF then cooperate to stimulate blood vessel formation. Fibronectin content in the tumor correlates with the number of blood vessels and tumor growth in the mouse models. Consistent with these results, examination of three separate arrays from patients with breast and prostate cancers revealed that a high staining intensity for fibronectin in tumors is associated with increased mortality. These results establish that circulating fibronectin modulates blood vessel formation and tumor growth by modifying the amount of and the response to VEGF. Furthermore, determination of the fibronectin content can serve as a prognostic biomarker for breast and prostate cancers and possibly other cancers.     

Cytogenetic risk grouping by the monosomal karyotype classification is superior in predicting the outcome of acute myeloid leukemia undergoing allogeneic stem cell transplantation in complete remission

We retrospectively analyzed the impact of cytogenetic abnormalities grouped according to the monosomal karyotype (MK) classification or the Southwest Oncology/Eastern Cooperative Oncology Group (SWOG/ECOG) definition in 263 patients with acute myeloid leukemia (AML) who underwent allogeneic stem cell transplantation (alloSCT) in complete remission (CR) at our center. Risk grouping using the MK criteria shows a highly significant difference in 5‐yr overall survival (OS) ranging between 67%, for the most favorable, and 32%, for the poorest risk group (P = 0.001). Although similarly precise in predicting OS, the MK scheme better separates patients with respect to relapse incidence as compared to the SWOG/ECOG grouping (P = 0.0001 vs. P = 0.01). Notably, patients displaying non‐MK abnormalities (MK?) had a 5‐yr relapse incidence identical to those cytogenetically normal (CN), that is 24%. Multivariate analysis revealed that the MK classification is an independent prognosticator and superior in predicting OS (hazard ratios, HR 3.74, P = 0.01) and relapse incidence (HR 3.74, P = 0.005) as compared to the SWOG/ECOG criteria. Finally, subgroup analysis revealed that the prognostic capacity of the MK classification is highly significant in patients treated with standard myeloablative conditioning prior to alloSCT (P = 0.0011 for OS, P = 0.0007 for relapse). In contrast, the MK grouping failed to predict OS or relapse incidence in patients treated with reduced intensity conditioning. Taken together, these results indicate that the MK classification is superior in predicting the overall outcome of patients with AML undergoing alloSCT in CR. Furthermore, our data suggest that the genetic risk profile of MK? and CN patients is mostly overlapping in this setting.