Search

Abstract Background Pediatric low-grade glioma (pLGG) is essentially a single pathway disease, with most tumors driven by genomic alterations affecting the mitogen-activated protein kinase/ERK (MAPK) pathway, predominantly KIAA1549::BRAF fusions and BRAF V600E mutations. This makes pLGG an ideal candidate for MAPK pathway-targeted treatments. The type I BRAF inhibitor, dabrafenib, in combination with the MEK inhibitor, trametinib, has been approved by the United States Food and Drug Administration for the systemic treatment of BRAF V600E-mutated pLGG. However, this combination is not approved for the treatment of patients with tumors harboring BRAF fusions as type I RAF inhibitors are ineffective in this setting and may paradoxically enhance tumor growth. The type II RAF inhibitor, tovorafenib (formerly DAY101, TAK-580, MLN2480), has shown promising activity and good tolerability in patients with BRAF-altered pLGG in the phase 2 FIREFLY-1 study, with an objective response rate (ORR) per Response Assessment in Neuro-Oncology high-grade glioma (RANO-HGG) criteria of 67%. Tumor response was independent of histologic subtype, BRAF alteration type (fusion vs. mutation), number of prior lines of therapy, and prior MAPK-pathway inhibitor use. Methods LOGGIC/FIREFLY-2 is a two-arm, randomized, open-label, multicenter, global, phase 3 trial to evaluate the efficacy, safety, and tolerability of tovorafenib monotherapy vs. current standard of care (SoC) chemotherapy in patients

Abstract Introduction Neurosurgery is considered the mainstay of treatment for pediatric low‐grade glioma (LGG); the extent of resection determines subsequent stratification in current treatment protocols. Yet, surgical radicality must be balanced against the risks of complications that may affect long‐term quality of life. We investigated whether this consideration impacted surgical resection patterns over time for patients of the German LGG studies. Patients and Methods Four thousand two hundred and seventy pediatric patients from three successive LGG studies (median age at diagnosis 7.6 years, neurofibromatosis (NF1) 14.7%) were grouped into 5 consecutive time intervals (TI1‐5) for date of diagnosis and analyzed for timing and extent of first surgery with respect to tumor site, histology, NF1‐status, sex, and age. Results The fraction of radiological LGG diagnoses increased over time (TI1 12.6%; TI5 21.7%), while the extent of the first neurosurgical intervention (3440/4270) showed a reduced fraction of complete/subtotal and an increase of partial resections from TI1 to TI5. Binary logistic regression analysis for the first intervention within the first year following diagnosis confirmed the temporal trends (p

The one-sample log-rank test is the preferred method for analysing the outcome of single-arm survival trials. It compares the survival distribution of patients with a prefixed reference survival curve that usually represents the expected outcome under standard of care. However, classical one-sample log-rank tests assume that the reference curve is known, ignoring that it is frequently estimated from historical data and therefore susceptible to sampling error. Neglecting the variability of the reference curve can lead to an inflated type I error rate, as shown in a previous paper. Here, we propose a new survival test that allows to account for the sampling error of the reference curve without knowledge of the full underlying historical survival time data. Our new test allows to perform a valid historical comparison of patient survival times when only a historical survival curve rather than the full historic data is available. It thus applies in settings where the two-sample log-rank test is not applicable as method of choice due to non-availability of historic individual patient survival time data. We develop sample size calculation formulas, give an example application and study the performance of the new test in a simulation study.

The required energy savings can be achieved in all automotive domains through weight savings and the merging of manufacturing processes in production. This fact is taken into account through functional integration in lightweight materials and manufacturing in a process close to large-scale production. In previous work, separate steps of a process chain for manufacturing a center console cover utilizing a sensoric hybrid laminate have been developed and evaluated. This includes the process steps of joining, forming and inline polarization as well as connecting to an embedded system. This work continues the research process by evaluating impact localization methods to use the center console as a haptic input device. For this purpose, different deep learning methods are derived from the state of the art and analyzed for their applicability in two consecutive studies. The results show that MLPs, LSTMs, GRUs and CNNs are suitable to localize impacts on the novel laminate with high localization rates of up to 99%, and thus the usability of the developed laminate as a haptic input device has been proven.