Clinical Models to Define Response and Survival With Anti-PD-1 Antibodies Alone or Combined With Ipilimumab in Metastatic Melanoma.

PURPOSE: Currently, there are no robust biomarkers that predict immunotherapy outcomes in metastatic melanoma. We sought to build multivariable predictive models for response and survival to anti-programmed cell death protein 1 (anti-PD-1) monotherapy or in combination with anticytotoxic T-cell lymphocyte-4 (ipilimumab [IPI]; anti-PD-1 ± IPI) by including routine clinical data available at the point of treatment initiation. METHODS: One thousand six hundred forty-four patients with metastatic melanoma treated with anti-PD-1 ± IPI at 16 centers from Australia, the United States, and Europe were included. Demographics, disease characteristics, and baseline blood parameters were analyzed. The end points of this study were objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The final predictive models for ORR, PFS, and OS were determined through penalized regression methodology (least absolute shrinkage and selection operator method) to select the most significant predictors for all three outcomes (discovery cohort, N = 633). Each model was validated internally and externally in two independent cohorts (validation-1 [N = 419] and validation-2 [N = 592]) and nomograms were created. RESULTS: The final model for predicting ORR (area under the curve [AUC] = 0.71) in immunotherapy-treated patients included the following clinical parameters: Eastern Cooperative Oncology Group Performance Status, presence/absence of liver and lung metastases, serum lactate dehydrogenase, blood neutrophil-lymphocyte ratio, therapy (monotherapy/combination), and line of treatment. The final predictive models for PFS (AUC = 0.68) and OS (AUC = 0.77) included the same variables as those in the ORR model (except for presence/absence of lung metastases), and included presence/absence of brain metastases and blood hemoglobin. Nomogram calculators were developed from the clinical models to predict outcomes for patients with metastatic melanoma treated with anti-PD-1 ± IPI. CONCLUSION: Newly developed combinations of routinely collected baseline clinical factors predict the response and survival outcomes of patients with metastatic melanoma treated with immunotherapy and may serve as valuable tools for clinical decision making.

Spatialized Audio in a Custom-Built OpenGL-Based Ear Training Virtual Environment.

Interval recognition is an important part of ear training-the key aspect of music education. Once trained, the musician can identify pitches, melodies, chords, and rhythms by listening to music segments. In a conventional setting, the tutor would teach a trainee the intervals using a musical instrument, typically a piano. However, this is expensive, time consuming, and nonengaging for either party. With the emergence of new technologies, including virtual reality (VR) and areas such as edutainment, this and similar trainings can be transformed into more engaging, more accessible, customizable (virtual) environments, with the addition of new cues and bespoke progression settings. In this work, we designed and implemented a VR ear training system for interval recognition. The usability, user experience, and the effect of multimodal integration through the addition of a perceptual cue, spatial audio, was investigated in two experiments with 46 participants. The results show that the system is highly acceptable and provides a very good experience for users. Furthermore, we show that the added spatial auditory cues provided in the VR application give users significantly more information for judging the musical intervals, something that is not possible in a non-VR environment.

Eye movement evidence that readers maintain and act on uncertainty about past linguistic input.

In prevailing approaches to human sentence comprehension, the outcome of the word recognition process is assumed to be a categorical representation with no residual uncertainty. Yet perception is inevitably uncertain, and a system making optimal use of available information might retain this uncertainty and interactively recruit grammatical analysis and subsequent perceptual input to help resolve it. To test for the possibility of such an interaction, we tracked readers' eye movements as they read sentences constructed to vary in (i) whether an early word had near neighbors of a different grammatical category, and (ii) how strongly another word further downstream cohered grammatically with these potential near neighbors. Eye movements indicated that readers maintain uncertain beliefs about previously read word identities, revise these beliefs on the basis of relative grammatical consistency with subsequent input, and use these changing beliefs to guide saccadic behavior in ways consistent with principles of rational probabilistic inference.