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[Kongreßabstract] Opus®-Magnum, ein neues Analysensystem für Immunoassays. Ein Methodenvergleich
(1995)
[Poster-Abstract] Formel zur Beurteilung der Blut-Liquor-Schrankenfunktion bei älteren Patienten
(1998)
Purpose: Classification and treatment of WHO grade II/III gliomas have dramatically changed. Implementing molecular markers into the WHO classification raised discussions about the significance of grading and clinical trials showed overall survival (OS) benefits for combined radiochemotherapy. As molecularly stratified treatment data outside clinical trials are scarce, we conducted this retrospective study.
Methods: We identified 343 patients (1995–2015) with newly diagnosed WHO grade II/III gliomas and analyzed molecular markers, patient characteristics, symptoms, histology, treatment, time to treatment failure (TTF) and OS.
Results: IDH-status was available for all patients (259 mutant, 84 IDH1-R132H-non-mutant). Molecular subclassification was possible in 173 tumors, resulting in diagnosis of 80 astrocytomas and 93 oligodendrogliomas. WHO grading remained significant for OS in astrocytomas/IDH1-R132H-non-mutant gliomas (p < 0.01) but not for oligodendroglioma (p = 0.27). Chemotherapy (and temozolomide in particular) showed inferior OS compared to radiotherapy in astrocytomas (median 6.1/12.1 years; p = 0.03) and oligodendrogliomas (median 13.2/not reached (n.r.) years; p = 0.03). While radiochemotherapy improved TTF in oligodendroglioma (median radiochemotherapy n.r./chemotherapy 3.8/radiotherapy 7.3 years; p < 0.001/ = 0.06; OS data immature) the effect, mainly in combination with temozolomide, was weaker in astrocytomas (median radiochemotherapy 6.7/chemotherapy 2.3/radiotherapy 2.0 years; p < 0.001/ = 0.11) and did not translate to improved OS (median 8.4 years).
Conclusion: This is one of the largest retrospective, real-life datasets reporting treatment and outcome in low-grade gliomas incorporating molecular markers. Current histologic grading features remain prognostic in astrocytomas while being insignificant in oligodendroglioma with interfering treatment effects. Chemotherapy (temozolomide) was less effective than radiotherapy in both astrocytomas and oligodendrogliomas while radiochemotherapy showed the highest TTF in oligodendrogliomas.
Knowledge discovery in biomedical data using supervised methods assumes that the data contain structure relevant to the class structure if a classifier can be trained to assign a case to the correct class better than by guessing. In this setting, acceptance or rejection of a scientific hypothesis may depend critically on the ability to classify cases better than randomly, without high classification performance being the primary goal. Random forests are often chosen for knowledge-discovery tasks because they are considered a powerful classifier that does not require sophisticated data transformation or hyperparameter tuning and can be regarded as a reference classifier for tabular numerical data. Here, we report a case where the failure of random forests using the default hyperparameter settings in the standard implementations of R and Python would have led to the rejection of the hypothesis that the data contained structure relevant to the class structure. After tuning the hyperparameters, classification performance increased from 56% to 65% balanced accuracy in R, and from 55% to 67% balanced accuracy in Python. More importantly, the 95% confidence intervals in the tuned versions were to the right of the value of 50% that characterizes guessing-level classification. Thus, tuning provided the desired evidence that the data structure supported the class structure of the data set. In this case, the tuning made more than a quantitative difference in the form of slightly better classification accuracy, but significantly changed the interpretation of the data set. This is especially true when classification performance is low and a small improvement increases the balanced accuracy to over 50% when guessing.
Vaccination represents one of the fundamentals in the fight against SARS-CoV-2. Myocarditis has been reported as a rare but possible adverse consequence of different vaccines, and its clinical presentation can range from mild symptoms to acute heart failure. We report a case of a 29-year-old man who presented with fever and retrosternal pain after receiving SARS-CoV-2 vaccine. Cardiac magnetic resonance imaging and laboratory data revealed typical findings of acute myocarditis.