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Purpose: Molecular diagnostics including next generation gene sequencing are increasingly used to determine options for individualized therapies in brain tumor patients. We aimed to evaluate the decision-making process of molecular targeted therapies and analyze data on tolerability as well as signals for efficacy.
Methods: Via retrospective analysis, we identified primary brain tumor patients who were treated off-label with a targeted therapy at the University Hospital Frankfurt, Goethe University. We analyzed which types of molecular alterations were utilized to guide molecular off-label therapies and the diagnostic procedures for their assessment during the period from 2008 to 2021. Data on tolerability and outcomes were collected.
Results: 413 off-label therapies were identified with an increasing annual number for the interval after 2016. 37 interventions (9%) were targeted therapies based on molecular markers. Glioma and meningioma were the most frequent entities treated with molecular matched targeted therapies. Rare entities comprised e.g. medulloblastoma and papillary craniopharyngeoma. Molecular targeted approaches included checkpoint inhibitors, inhibitors of mTOR, FGFR, ALK, MET, ROS1, PIK3CA, CDK4/6, BRAF/MEK and PARP. Responses in the first follow-up MRI were partial response (13.5%), stable disease (29.7%) and progressive disease (46.0%). There were no new safety signals. Adverse events with fatal outcome (CTCAE grade 5) were not observed. Only, two patients discontinued treatment due to side effects. Median progression-free and overall survival were 9.1/18 months in patients with at least stable disease, and 1.8/3.6 months in those with progressive disease at the first follow-up MRI.
Conclusion: A broad range of actionable alterations was targeted with available molecular therapeutics.
However, efficacy was largely observed in entities with paradigmatic oncogenic drivers, in particular with BRAF mutations. Further research on biomarker-informed molecular matched therapies is urgently necessary.
We set up and solve a rich life-cycle model of household decisions involving consumption of both perishable goods and housing services, stochastic and unspanned labor income, stochastic house prices, home renting and owning, stock investments, and portfolio constraints. The model features habit formation for housing consumption, which leads to optimal decisions closer in line with empirical observations. Our model can explain (i) that stock investments are low or zero for many young agents and then gradually increasing over life, (ii) that the housing expenditure share is age- and wealth-dependent, (iii) that perishable consumption is more sensitive to wealth and income shocks than housing consumption, and (iv) that non-housing consumption is hump-shaped over life.
Treatment‐related complications contribute substantially to morbidity and mortality in acute myeloid leukemia (AML) patients undergoing induction chemotherapy. Although AML patients are susceptible to fluid overload (FO) (e.g., in the context of chemotherapy protocols, during sepsis treatment or to prevent tumor lysis syndrome), little attention has been paid to its role in AML patients undergoing induction chemotherapy. AML patients receiving induction chemotherapy between 2014 and 2019 were included in this study. FO was defined as ≥5% weight gain on day 7 of induction chemotherapy compared to baseline weight determined on the day of admission. We found FO in 23 (12%) of 187 AML patients undergoing induction chemotherapy. Application of >100 ml crystalloid fluids/kg body weight until day 7 of induction chemotherapy was identified as an independent risk factor for FO. AML patients with FO suffered from a significantly increased 90-day mortality rate and FO was demonstrated as an independent risk factor for 90-day mortality. Our data suggests an individualized, weight-adjusted calculation of crystalloid fluids in order to prevent FO-related morbidity and mortality in AML patients during induction chemotherapy. Prospective trials are required to determine the adequate fluid management in this patient population.
We show that the optimal consumption of an individual over the life cycle can have the hump shape (inverted U-shape) observed empirically if the preferences of the individual exhibit internal habit formation. In the absence of habit formation, an impatient individual would prefer a decreasing consumption path over life. However, because of habit formation, a high initial consumption would lead to high required consumption in the future. To cover the future required consumption, wealth is set aside, but the necessary amount decreases with age which allows consumption to increase in the early part of life. At some age, the impatience outweighs the habit concerns so that consumption starts to decrease. We derive the optimal consumption strategy in closed form, deduce sufficient conditions for the presence of a consumption hump, and characterize the age at which the hump occurs. Numerical examples illustrate our findings. We show that our model calibrates well to U.S. consumption data from the Consumer Expenditure Survey.