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Purpose: 10-year retrospective study to assess burden of illness in individuals with tuberous sclerosis complex (TSC) identified from German healthcare data. Methods: Patients with TSC were identified by International Classification of Diseases code Q85.1. Patients with epilepsy were identified by epilepsy diagnosis or antiseizure medication (ASM) prescription after TSC diagnosis. Results: Using data from 2016 (final study year), 100 patients with TSC were identified (mean [range] age: 38 [1–86] years; male: 40%); prevalence: 7.9 per 100,000 (TSC), 2.2 per 100,000 (TSC with epilepsy). During the 10-year study period (2007–2016), 256 patients with TSC were identified and followed up for 1,784 patient- years (epilepsy: 36%, 616 patient-years). TSC manifestations/comorbidities (apart from epilepsy) were identi- fied more frequently in patients with epilepsy than without. Mean annual healthcare costs for patients with TSC were €6,139 per patient-year (PPY), mostly attributable to medication (35%) and inpatient care (29%). Patients with epilepsy incurred costs more than double those without. Mean (standard deviation [SD]) annual hospi- talisation rate (AHR) and length of stay (LOS) PPY: 0.5 (1.0) and 5.9 (18.6) days for TSC. AHR and LOS were greater in patients with epilepsy than without. Mean (SD) number of ASMs prescribed (TSC with epilepsy): 3.0 (2.3) over the entire observable time per patient. Mortality rates (vs. control): 5.08% (vs. 1.69%, p<0.001) for TSC, 7.53% (vs. 0.98%, p<0.001) for TSC with epilepsy, 3.68% (vs. 2.03%, p = 0.003) for TSC without epilepsy. Conclusion: Healthcare costs, resource utilisation, and mortality were greater in patients with TSC and epilepsy than those without epilepsy.
Comprehensive analysis of tumour sub-volumes for radiomic risk modelling in locally advanced HNSCC
(2020)
Simple Summary: Radiomic risk models are usually based on imaging features, which are extracted from the entire gross tumour volume (GTV entire ). This approach does not explicitly consider the complex biological structure of the tumours. Therefore, in this retrospective study, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma who were treated with primary radio-chemotherapy. The GTV entire was cropped by different margins to define the rim and corresponding core sub-volumes of the tumour. Furthermore, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. As a result, the models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed an improved performance compared to models based on the corresponding tumour core. This indicates that the consideration of tumour sub-volumes may help to improve radiomic risk models.
Abstract: Imaging features for radiomic analyses are commonly calculated from the entire gross tumour volume (GTVentire). However, tumours are biologically complex and the consideration of different tumour regions in radiomic models may lead to an improved outcome prediction. Therefore, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma. The GTVentire was cropped by different margins to define the rim and the corresponding core sub-volumes of the tumour. Subsequently, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. Radiomic risk models were developed and validated using a retrospective cohort consisting of 291 patients in one of the six Partner Sites of the German Cancer Consortium Radiation Oncology Group treated between 2005 and 2013. The validation concordance index (C-index) averaged over all applied learning algorithms and feature selection methods using the GTVentire achieved a moderate prognostic performance for loco-regional tumour control (C-index: 0.61 ± 0.04 (mean ± std)). The models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed higher median performances (C-index: 0.65 ± 0.02 and 0.64 ± 0.05, respectively), while models based on the corresponding tumour core volumes performed less (C-index: 0.59 ± 0.01). The difference in C-index between the 5 mm tumour rim and the corresponding core volume showed a statistical trend (p = 0.10). After additional prospective validation, the consideration of tumour sub-volumes may be a promising way to improve prognostic radiomic risk models.
Purpose: To develop and validate a CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG).
Material and methods: Pre-treatment CT images of 318 patients with locally advanced HNSCC were collected. Four-hundred forty-six features were extracted from each primary tumour volume and then filtered through stability analysis and clustering. First, a baseline signature was developed from demographic and tumour-associated clinical parameters. This signature was then supplemented by CT imaging features. A final signature was derived using repeated 3-fold cross-validation on the discovery cohort. Performance in external validation was assessed by the concordance index (C-Index). Furthermore, calibration and patient stratification in groups with low and high risk for loco-regional recurrence were analysed.
Results: For the clinical baseline signature, only the primary tumour volume was selected. The final signature combined the tumour volume with two independent radiomics features. It achieved moderately good discriminatory performance (C-Index [95% confidence interval]: 0.66 [0.55–0.75]) on the validation cohort along with significant patient stratification (p = 0.005) and good calibration.
Conclusion: We identified and validated a clinical-radiomics signature for LRC of locally advanced HNSCC using a multi-centric retrospective dataset. Prospective validation will be performed on the primary cohort of the HNprädBio trial of the DKTK-ROG once follow-up is completed.
Highlights
• German patients with LGS identified using most specific algorithm to date.
• Prevalence of probable LGS with epilepsy diagnosis before age 6 was 6.5 per 100,000.
• High healthcare costs of €22,787 PPY; mostly due to inpatient and home nursing care.
• Costs were greater in patients prescribed rescue medications.
• Over 10 years, LGS patients had significant mortality vs. controls (2.88 vs. 0.01%).
Abstract
Objective: This retrospective study examined patients with probable Lennox-Gastaut syndrome (LGS) identified from German healthcare data.
Methods: This 10-year study (2007–2016) assessed healthcare insurance claims information from the Vilua Healthcare research database. A selection algorithm considering diagnoses and drug prescriptions identified patients with probable LGS. To increase the sensitivity of the identification algorithm, two populations were defined: all patients with probable LGS (broadly defined) and only those with a documented epilepsy diagnosis before 6 years of age (narrowly defined). This specific criterion was used as LGS typically has a peak seizure onset between age 3 and 5 years. Primary analyses were prevalence and demographics; secondary analyses included healthcare costs, hospitalization rate and length of stay (LOS), medication use, and mortality.
Results: In the final year of the study, 545 patients with broadly defined probable LGS (mean [range] age: 31.4 [2–89] years; male: 53%) were identified. Using the narrowly defined probable LGS definition, the number of patients was reduced to 102 (mean [range] age: 7.4 [2–14] years; male: 52%). Prevalence of broadly defined and narrowly defined probable LGS was 39.2 and 6.5 per 100,000 people. During the 10-year study, 208 patients with narrowly defined probable LGS were identified and followed up for 1379 patient-years. The mean annual cost of healthcare was €22,787 per patient-year (PPY); greatest costs were attributable to inpatient care (33%), home nursing care (13%), and medication (10%). Mean annual healthcare costs were significantly greater for those with prescribed rescue medication (45% of patient-years) versus those without (€33,872 vs. €13,785 PPY, p < 0.001). Mean (standard deviation [SD]) annual hospitalization rate was 1.6 (2.0) PPY with mean (SD) annual LOS of 22.7 (46.0) days. Annual hospitalization rate was significantly greater in those who were prescribed rescue medication versus those who were not (2.2 [2.3] vs. 1.1 [1.6] PPY, p < 0.001). The mean (SD) number of different medications prescribed was 11.3 (7.3) PPY and 33.8 (17.0) over the entire observable time per patient (OET); antiepileptic drugs only accounted for 2.1 (1.1) of the medications prescribed PPY and 3.8 (2.0) OET. Over the 10-year study period, mortality in patients with narrowly defined probable LGS was significantly higher than the matched control population (six events [2.88%] vs. one event [0.01%], p < 0.001).
Conclusion: Annual healthcare costs incurred by patients with probable LGS in Germany were substantial, and mostly attributable to inpatient care, home nursing care, and medication. Patients prescribed with rescue medication incurred significantly greater costs than those who were not. Patients with narrowly defined probable LGS had a higher mortality rate versus control populations.
Highlights
• Prevalence of probable DS identified from German healthcare data: 4.7 per 100,000.
• Healthcare costs: €11,048 per patient-year, mostly inpatient care 47%, medication 26%.
• Costs and hospitalizations greater in patients with rescue medication than without.
• Mean (SD) of 5.0 (2.5) different ASMs prescribed per patient over study period.
• Patients with probable DS had significantly higher mortality risk vs. controls (11.88% vs. 1.19%).
Abstract
Objective: Ten-year retrospective study to assess burden of illness in patients with probable Dravet syndrome (DS) identified from German healthcare data.
Methods: In the absence of an International Classification of Diseases code, patients with probable DS were identified using a selection algorithm considering diagnoses and drug prescriptions. Primary analyses were prevalence and demographics; secondary analyses included healthcare costs, annual hospitalization rate (AHR) and length of stay (LOS), medication use, and mortality.
Results: In the final study year, 64 patients with probable DS (mean [range] age: 33.2 [3–82] years; male: 48%) were identified. Prevalence: 4.7 per 100,000 people. During the study, 160 patients with probable DS were identified and followed up for 1,261 patient-years. Mean cost of healthcare was €11,048 per patient-year (PPY), mostly attributable to inpatient care (47%), medication (26%), and services and devices (19%). Annual healthcare costs were significantly greater for those with prescribed rescue medication (15% of patient-years) vs. without (€16,123 vs. €10,125 PPY, p < 0.001). Mean (standard deviation [SD]) AHR and LOS were 1.1 (1.7) and 17.5 (33.5) days PPY. AHR was significantly greater in patients with prescribed rescue medication vs. without (1.6 [2.0] vs. 1.0 [1.6] PPY, p < 0.001). Mean (SD) number of antiseizure medications prescribed was 2.6 (1.2) PPY and 5.0 (2.5) over the entire observable time for each patient. Mortality rate was significantly higher for probable DS vs. matched controls (11.88% [19 events] vs. 1.19% [172 events], p < 0.001).
Conclusion: Probable DS is associated with substantial healthcare costs in Germany.
Sulfuric acid is an important gas influencing atmospheric new particle formation (NPF). Both the binary (H2SO4-H2O) system, and the ternary system involving ammonia (H2SO4-H2O-NH3) may be important in the free troposphere. An essential step in the nucleation of aerosol particles from gas-phase precursors is the formation of a dimer, so an understanding of the thermodynamics of dimer formation over a wide range of atmospheric conditions is essential to describe NPF. We have used the CLOUD chamber to conduct nucleation experiments for these systems at temperatures from 208 to 248 K. Neutral monomer and dimer concentrations of sulfuric acid were measured using a Chemical Ionization Mass Spectrometer (CIMS). From these measurements dimer evaporation rates in the binary system were derived for temperatures of 208 and 223 K. We compare these results to literature data from a previous study that was conducted at higher temperatures but is in good agreement with the present study. For the ternary system the formation of H2SO4·NH3 is very likely an essential step in the formation of sulfuric acid dimers, which were measured at 210, 223, and 248K. We estimate the thermodynamic properties (dH and dS) of the H2SO4·NH3 cluster using a simple heuristic model and the measured data. Furthermore, we report the first measurements of large neutral sulfuric acid clusters containing as many as 10 sulfuric acid molecules for the binary system using Chemical Ionization-Atmospheric Pressure interface-Time Of Flight (CI-APi-TOF) mass spectrometry.
Sulfuric acid is an important gas influencing atmospheric new particle formation (NPF). Both the binary (H2SO4–H2O) system and the ternary system involving ammonia (H2SO4–H2O–NH3) may be important in the free troposphere. An essential step in the nucleation of aerosol particles from gas-phase precursors is the formation of a dimer, so an understanding of the thermodynamics of dimer formation over a wide range of atmospheric conditions is essential to describe NPF. We have used the CLOUD chamber to conduct nucleation experiments for these systems at temperatures from 208 to 248 K. Neutral monomer and dimer concentrations of sulfuric acid were measured using a chemical ionization mass spectrometer (CIMS). From these measurements, dimer evaporation rates in the binary system were derived for temperatures of 208 and 223 K. We compare these results to literature data from a previous study that was conducted at higher temperatures but is in good agreement with the present study. For the ternary system the formation of H2SO4·NH3 is very likely an essential step in the formation of sulfuric acid dimers, which were measured at 210, 223, and 248 K. We estimate the thermodynamic properties (dH and dS) of the H2SO4·NH3 cluster using a simple heuristic model and the measured data. Furthermore, we report the first measurements of large neutral sulfuric acid clusters containing as many as 10 sulfuric acid molecules for the binary system using chemical ionization–atmospheric pressure interface time-of-flight (CI-APi-TOF) mass spectrometry.
Highlights
• Artificial intelligence systems for mechanically ventilated patients are increasing.
• The clinical and financial impact of these models are often unexamined.
• We developed a generic health-economic model for artificial intelligence systems.
• This model assesses the cost-effectiveness for many different scenarios.
• The developed framework is easily adjustable to other (clinical) situations.
Abstract
Purpose: The health and economic consequences of artificial intelligence (AI) systems for mechanically ventilated intensive care unit patients often remain unstudied. Early health technology assessments (HTA) can examine the potential impact of AI systems by using available data and simulations. Therefore, we developed a generic health-economic model suitable for early HTA of AI systems for mechanically ventilated patients.
Materials and methods: Our generic health-economic model simulates mechanically ventilated patients from their hospitalisation until their death. The model simulates two scenarios, care as usual and care with the AI system, and compares these scenarios to estimate their cost-effectiveness.
Results: The generic health-economic model we developed is suitable for estimating the cost-effectiveness of various AI systems. By varying input parameters and assumptions, the model can examine the cost-effectiveness of AI systems across a wide range of different clinical settings.
Conclusions: Using the proposed generic health-economic model, investors and innovators can easily assess whether implementing a certain AI system is likely to be cost-effective before an exact clinical impact is determined. The results of the early HTA can aid investors and innovators in deployment of AI systems by supporting development decisions, informing value-based pricing, clinical trial design, and selection of target patient groups.