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Model comprehension and effective use and reuse of complex subsystems are problems currently encountered in the automotive industry. To address these problems we present a technique for extracting, presenting, and making use of signatures for Simulink subsystems. The signature of a subsystem is defined to be a generalization of its interface, including the subsystem's explicit ports, locally defined and inherited data stores, as well as scoped gotos/froms. We argue that the use of signatures has significant benefits for model comprehension and subsystem testing, and show how the incorporation of signatures into existing Simulink models is practical and useful by discussing various usage scenarios. Furthermore, outside of the model setting, signatures have proven to be an asset when exported and included in software documentation.

9540 Background: In BRAF mutated metastatic melanoma, potential outcome differences for different choices of 1st line treatments including immunotherapy or BRAF-/MEK inhibition are not completely understood. We therefore analyzed the treatment patterns and outcome of systemic therapies for patients BRAF mutated metastatic melanoma. Methods: From the EUMelaReg treatment registry, patients fulfilling the following inclusion criteria were consecutively included until a number of 1,000 evaluable cases was reached. 1) Patients with metastatic melanoma and BRAF V600 mutation 2) First line treatment with either combined BRAF-/MEK or immune checkpoint inhibition (ICI) with PD-1 single agent or combined PD-1/CTLA-4 antibodies. Multivariable cox regression analysis as well as propensity score based weighting were used to control for bias from baseline imbalances. Primary outcomes of interest were overall survival (OS) and 2nd line PFS (PFS-2), stratified for upfront treatment decision of ICI versus targeted therapy. PFS-2 was defined as the interval from start of first line treatment to a progression after a 2nd line treatment or death of any cause. Further endpoints were evaluated including time on treatment (ToT), time to next treatment and 2nd line treatments. Results: In total 529 (52.9 %) patients received BRAF/MEK-i, and 471 (47.1%) ICI. For various co-variates there were significant imbalances between strata, including number of metastatic sites, AJCC substage, serum LDH, and ECOG performance status, with more favorable prognostic variables for patients receiving immunotherapy. The ORR for BRAF/MEK-i was significantly higher than for ICI (53.3% vs. 42.0%; p=0.0004), but for OS and PFS2 the adjusted hazard ratios were significantly in favor for ICI (HR 0.62 and 0.66, respectively; p <0.0001). In 2nd line, patients switching from ICI to BRAF/MEK-i had again markedly higher ORR than patients switching vice versa (57.7% vs. 19.9%; P<0.0001), and also significantly longer unadjusted PFS (8.1 vs. 3.1 months; p <0.0001) and OS (15.7 vs. 10.6 mths; p=0.01) after start of 2nd line treatment. Conclusions: The two cohorts had imbalances on key prognosis variables. After adjustment for these imbalances, upfront ICI still resulted in significantly longer OS as compared to BRAF/MEK-i. Due to the nature of real-world observational data causing inherent imbalances in the treatments cohorts and being unable to account for potential unknown confounders, outcome may still be biased despite adjustment efforts.[Table: see text]

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