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The Decipher genomic classifier (GC) has shown to independently prognosticate outcomes in prostate cancer. The objective of this study was to validate the GC in a randomized phase III trial of dose-escalated salvage radiotherapy (SRT) after radical prostatectomy.A clinical-grade whole-transcriptome assay was carried out on radical prostatectomy samples obtained from patients enrolled in Swiss Group for Clinical Cancer Research (SAKK) 09/10, a phase III trial of 350 men with biochemical recurrence after radical prostatectomy randomized to 64 Gy versus 70 Gy without concurrent hormonal therapy or pelvic nodal RT. A prespecified statistical plan was developed to assess the impact of the GC on clinical outcomes. The primary endpoint was biochemical progression; secondary endpoints were clinical progression and time to hormone therapy. Multivariable analyses adjusted for age, T-category, Gleason score, postradical prostatectomy persistent prostate-specific antigen (PSA), PSA at randomization, and randomization arm were conducted, accounting for competing risks.The analytic cohort of 226 patients was representative of the overall trial, with a median follow-up of 6.3 years (interquartile range 6.1-7.2 years). The GC (high versus low-intermediate) was independently associated with biochemical progression [subdistribution hazard ratio (sHR) 2.26, 95% confidence interval (CI) 1.42-3.60; P0.001], clinical progression (HR 2.29, 95% CI 1.32-3.98; P = 0.003), and use of hormone therapy (sHR 2.99, 95% CI 1.55-5.76; P = 0.001). GC high patients had a 5-year freedom from biochemical progression of 45% versus 71% for GC low-intermediate. Dose escalation did not benefit the overall cohort, nor patients with lower versus higher GC scores.This study represents the first contemporary randomized controlled trial in patients treated with early SRT without concurrent hormone therapy or pelvic nodal RT that has validated the prognostic utility of the GC. Independent of standard clinicopathologic variables and RT dose, high-GC patients were more than twice as likely than lower-GC patients to experience biochemical and clinical progression and receive of salvage hormone therapy. These data confirm the clinical value of Decipher GC to personalize the use of concurrent systemic therapy in the postoperative salvage setting.

In regions with complex topography,incoming surface radiation is strongly influenced by terrain geometry:direct shortwave radiation is typically most affected and depends both on local surface inclination and neighbouring terrain (topographic shading). Diffuse shortwave and longwave radiation can be altered by partial sky obstruction and the reflectance or emission of radiation by surrounding slopes. Changes in the surface radiation balance impacts(near-)surface variables like (air) temperature and snow cover, which in turn can influence atmospheric processes like the development of valley wind systems.In atmospheric and climate models, topographic effects on surface radiation are not explicitly represented in the one-dimensional radiation schemes. Thus, different parameterisations have been developed that are either based on pure geometrical consideration or derived from Monte Carlo ray tracing simulations. These parameterisations are applied on a grid or sub-grid scale and for a wide range of grid spacings (~100 m to 100 km). However, it is still relatively unknown how well these parameterisations perform overall and on different spatial scales. To assess this uncertainties, we perform regional simulations with the COSMO (Consortium for Small-scale Modeling) climate model for the European Alps with a geometrical-based and sub-grid parametrisation scheme. Besides quantifying the uncertainty of specific parts of the scheme, we also evaluate the overall impact on simulated climate., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The improvement of Quantitative Precipitation Forecast (QPF) in mountainous area was the central supporting objective of the MAP project P1 devoted to the study of orographic precipitation. This paper attempts to review the main MAP-related achievements towards QPF improvement and to highlight the MAP-impact for developing QPF research and operational strategies.

A high-resolution atmospheric ensemble forecasting system, based on 51 runs of the Local Model (LM), has been used to make probabilistic runoff forecasts for a 5 day forecasting period in the alpine tributaries of the Rhine basin. The investigated cases are the spring 1999 flood, when a combination of snowmelt and heavy precipitation caused severe floods in Central Europe and the November 2002 flash flood in the Alpine Rhine area. This study focuses on the feasibility of ensemble prediction system (EPS) for runoff forecasting. Runoff predictions from the deterministic forecast are compared with those obtained from probabilistic atmospheric forecasts. For both cases, the deterministic simulations yield large forecast failures, while the hydrometeorologic EPS provides appropriate forecast guidance with proper uncertainty intervals. The use of clustering techniques showed that the clustering methodology does not reduce ensemble spread.