A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.

The relatively high classification accuracy and AUC demonstrates the usefulness of this approach for objective monitoring of PD patients. The positive evaluation of computer's explanations suggests the potential use of this methodology in a decision support setting.

No abstract

Background Treatment of early-stage non-small cell lung cancer (NSCLC) is rapidly evolving. When introducing novelties, real-life data on effectiveness of currently used treatment strategies are needed. The present study evaluated outcomes of stage I–IIIA NSCLC patients treated with upfront radical surgery in everyday clinical practice, between 2010–2017. Patients and methods Data of 539 consecutive patients were retrieved from a prospective hospital-based registry. All diagnostic, treatment and follow-up procedures were performed at the same thoracic oncology centre according to the valid guidelines. The primary outcome was overall survival (OS) analysed by clinical(c) and pathological(p) TNM (tumour, node, metastases) stage. The impact of clinicopathological characteristics on OS was evaluated using univariable (UVA) and multivariable regression analysis (MVA). Results With a median follow-up of 53.9 months, median OS and 5-year OS rate in the overall population were 90.4 months and 64.4%. Five-year OS rates by pTNM stage I, II and IIIA were 70.2%, 60.21%, and 49.9%, respectively. Both cTNM and pTNM stages were associated with OS; but only pTNM retained its independent prognostic value (p = 0.003) in MVA. Agreement between cTNM and pTNM was 69.0%. Next to pTNM, age (p = 0.001) and gender (p = 0.004) retained their independent prognostic value for OS. Conclusions The study showed favourable outcomes of resectable stage I–IIIA NSCLC treated with upfront surgery in real-life. Relatively low agreement between cTNM and pTNM stages and independent prognostic value of only pTNM, observed in real-life data, suggest that surgery remains the most accurate provider of the anatomical stage of disease and important upfront therapy.