Skin regeneration,repair, and reconstruction: present and future

European Surgery - Large skin defects caused by trauma (e.g., burns) or due to other reasons (e.g., tumor-related skin resections) require sufficient skin replacement. The constant improvement of...     

Praxis der perioperativen Prävention von Phantomschmerz: eine deutschlandweite Umfrage

Die Anaesthesiologie - Phantomschmerzen haben eine hohe Prävalenz nach Majoramputationen und sind mit einer zusätzlichen Einschränkung der Lebensqualität verbunden....     

Standardisierte Kontrastmittelsonographie (CEUS) in der klinischen Akut- und Notfallmedizin sowie Intensivmedizin (CEUS-Akut)

Die Anaesthesiologie -     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

The clinical dilemma of JAK inhibitor failure in myelofibrosis: Predictive characteristics and outcomes

Two Janus-associated kinase inhibitors (JAKi) (initially ruxolitinib and, more recently, fedratinib) have been approved as treatment options for patients who have intermediate-risk and high-risk myelofibrosis (MF), with pivotal trials demonstrating improvements in spleen volume, disease symptoms, and quality of life. At the same time, however, clinical trial experiences with JAKi agents in MF have demonstrated a high frequency of discontinuations because of adverse events or progressive disease. In addition, overall survival benefits and clinical and molecular predictors of response have not been established in this population, for which the disease burden is high and treatment options are limited. Consistently poor outcomes have been documented after JAKi discontinuation, with survival durations after ruxolitinib ranging from 11 to 16 months across several studies. To address such a high unmet therapeutic need, various non-JAKi agents are being actively explored (in combination with ruxolitinib in first-line or salvage settings and/or as monotherapy in JAKi-pretreated patients) in phase 3 clinical trials, including pelabresib (a bromodomain and extraterminal domain inhibitor), navitoclax (a B-cell lymphoma 2/B-cell lymphoma 2-xL inhibitor), parsaclisib (a phosphoinositide 3-kinase inhibitor), navtemadlin (formerly KRT-232; a murine double-minute chromosome 2 inhibitor), and imetelstat (a telomerase inhibitor). The breadth of data expected from these trials will provide insight into the ability of non-JAKi treatments to modify the natural history of MF.