BackgroundThe brain represents a frequent progression site in lung adenocarcinoma. This study was designed to analyse the association between the epidermal growth factor receptor (EGFR) mutation status and the frequency of brain metastases (BM) and survival in routine clinical practice.Patients and methodsWe retrospectively analysed the medical records of 629 patients with adenocarcinoma in Slovenia who were tested for EGFR mutations in order to analyse the cumulative incidence of BM, the time from the diagnosis to the development of BM (TDBM), the time from BM to death (TTD) and the median survival.ResultsOut of 629 patients, 168 (27%) had BM, 90 patients already at the time of diagnosis. Additional 78 patients developed BM after a median interval of 14.3 months; 25.8 months in EGFR positive and 11.8 months in EGFR negative patients, respectively (p = 0.002). EGFR mutations were present in 47 (28%) patients with BM. The curves for cumulative incidence of BM in EGFR positive and negative patients demonstrate a trend for a higher incidence of BM in EGFR mutant patients at diagnosis (19% vs. 13%, p = 0.078), but no difference later during the course of the disease. The patients with BM at diagnosis had a statistically longer TTD (7.3 months) than patients who developed BM later (3.1 months). The TTD in EGFR positive patients with BM at diagnosis was longer than in EGFR negative patients (12.6 vs. 6.8, p = 0.005), while there was no impact of EGFR status on the TTD of patients who developed BM later.ConclusionsExcept for a non-significant increase of frequency of BM at diagnosis in EGFR positive patients, EGFR status had no influence upon the cumulative incidence of BM. EGFR positive patients had a longer time to CNS progression. While EGFR positive patients with BM at diagnosis had a longer survival, EGFR status had no influence on TTD in patients who developed BM later during the course of disease.

Background. There are concerns about growing barriers to cancer research. We explored the characteristics of and barriers to global clinical cancer research. Methods. The American Society of Clinical Oncology International Affairs Committee invited 300 selected oncologists with research experience from 25 countries to complete a Web‐based survey. Fisher's exact test was used to compare answers between participants from high‐income countries (HICs) and low‐ and middle‐income countries (LMICs). Barriers to clinical cancer research were ranked from 1 (most important) to 8 (least important). Mann‐Whitney's nonparametric test was used to compare the ranks describing the importance of investigated obstacles. Results. Eighty oncologists responded, 41 from HICs and 39 from LMICs. Most responders were medical oncologists (62%) at academic hospitals (90%). Researchers from HICs were more involved with academic and industry‐driven research than were researchers from LMICs. Significantly higher proportions of those who considered their ability to conduct academic research and industry‐driven research over the past 5 years more difficult were from HICs (73% vs. 27% and 70% vs. 30%, respectively). Concerning academic clinical cancer research, a lack of funding was ranked the most important (score: 3.16) barrier, without significant differences observed between HICs and LMICs. Lack of time or competing priorities and procedures from competent authorities were the second most important barriers to conducting academic clinical research in HICs and LMICs, respectively. Conclusion. Lack of funding, lack of time and competing priorities, and procedures from competent authorities might be the main global barriers to academic clinical cancer research.

Staining intensity of STMN1, but not SYK, predicted outcome in our collective of ER- positive tamoxifen treated EBC patients.

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.

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