Distributed learning on 20 000+ lung cancer patients - The Personal Health Train

Background and purpose Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) provides a privacy-by-design infrastructure connecting FAIR (Findable, Accessible, Interoperable, Reusable) data sources and allows distributed data analysis and machine learning. Patient data never leaves a healthcare institute. Materials and methods Lung cancer patient-specific databases (tumor staging and post-treatment survival information) of oncology departments were translated according to a FAIR data model and stored locally in a graph database. Software was installed locally to enable deployment of distributed machine learning algorithms via a central server. Algorithms (MATLAB, code and documentation publicly available) are patient privacy-preserving as only summary statistics and regression coefficients are exchanged with the central server. A logistic regression model to predict post-treatment two-year survival was trained and evaluated by receiver operating characteristic curves (ROC), root mean square prediction error (RMSE) and calibration plots. Results In 4 months, we connected databases with 23 203 patient cases across 8 healthcare institutes in 5 countries (Amsterdam, Cardiff, Maastricht, Manchester, Nijmegen, Rome, Rotterdam, Shanghai) using the PHT. Summary statistics were computed across databases. A distributed logistic regression model predicting post-treatment two-year survival was trained on 14 810 patients treated between 1978 and 2011 and validated on 8 393 patients treated between 2012 and 2015. Conclusion The PHT infrastructure demonstrably overcomes patient privacy barriers to healthcare data sharing and enables fast data analyses across multiple institutes from different countries with different regulatory regimens. This infrastructure promotes global evidence-based medicine while prioritizing patient privacy

Hot and Cool Forms of Inhibitory Control and Externalizing Behavior in Children of Mothers who Smoked during Pregnancy: An Exploratory Study

This study examined whether children exposed to prenatal smoking show deficits in “hot” and/or “cool” executive functioning (EF). Hot EF is involved in regulation of affect and motivation, whereas cool EF is involved in handling abstract, decontextualized problems. Forty 7 to 9-year-old children (15 exposed to prenatal smoking, 25 non-exposed) performed two computerized tasks. The Sustained Attention Dots (SA-Dots) Task (as a measure of “cool” inhibitory control) requires 400 non-dominant hand and 200 dominant hand responses. Inhibitory control of the prepotent response is required for dominant hand responses. The Delay Frustration Task (DeFT) (as a measure of “hot” inhibitory control) consists of 55 simple maths exercises. On a number of trials delays are introduced before the next question appears on the screen. The extent of response-button pressing during delays indicates frustration-induced inhibitory control. Prenatally exposed children showed poorer inhibitory control in the DeFT than non-exposed children. A dose–response relationship was also observed. In addition, prenatally exposed children had significantly higher (dose-dependent) conduct problem- and hyperactivity-inattention scores. There were no significant group differences in inhibitory control scores from the SA-Dots. These results indicate that children exposed to prenatal smoking are at higher risk of hot but not cool executive function deficits

Prophylactic radiotherapy for the prevention of procedure-tract metastases after surgical and large-bore pleural procedures in malignant pleural mesothelioma (SMART): a multicentre, open-label, phase 3, randomised controlled trial.

The use of prophylactic radiotherapy to prevent procedure-tract metastases (PTMs) in malignant pleural mesothelioma remains controversial, and clinical practice varies worldwide. We aimed to compare prophylactic radiotherapy with deferred radiotherapy (given only when a PTM developed) in a suitably powered trial.This article is freely available via Open Access. Click on the 'Additional Link' above to access the full-text via the publisher's site.Published (Open Access

Disruptive behaviour disorders: a systematic review of environmental antenatal and early years risk factors

Disruptive behaviour disorders (DBDs), including attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD) and conduct disorder (CD) are chronic disorders with significant overlap in aetiology and presentation. An integrative examination of environmental risk factors is lacking. Six literature searches of web-based bibliographic databases were completed to identify literature on DBDs in general and five disorders in particular: CD, ODD, ADHD, deficits of attention, motor control and perception, and reactive attachment disorder. Searches were filtered to focus on studies including diagnostic assessment, focussing on environmental risk and protective factors in the first 4 years of life. The database searches generated 9806 papers of which 47 were reviewed after filters had been applied. The evidence suggests links between a number of early life risk factors and DBDs, including prenatal cigarette smoking and alcohol use, prenatal viral illness, maternal stress and anxiety, low birthweight, peri-partum and early neonatal complications, parental stress and parenting styles in infancy, early deprivation, adoption and separation. Despite the understanding that there is sharing of risk factors between the DBDs, there has been a disproportionate focus on the role of certain risk factors at the expense of others and the field is weakened by difficulties in controlling for all potential confounding variables