Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Ο ρόλος των προγραμμάτων απώλειας βάρους στην οστική κατάσταση γυναικών της άμεσης μετεμμηνοπαυσιακής ηλικίας

Η εμμηνόπαυση αποτελεί ορόσημο για την οστική πυκνότητα των γυναικών. Κατά τη διάρκεια της μετεμμηνοπαυσιακής περιόδου, τα επίπεδα οιστρογόνων στο σώμα, μειώνονται με ταχύτατους ρυθμούς. Η θετική συσχέτιση μεταξύ σωματικού βάρους ή ΔΜΣ και οστικής πυκνότητας είναι καλά τεκμηριωμένη. Η απώλεια του υπερβάλλοντος σωματικού βάρους στη μετεμμηνοπαυσιακή ηλικία καθίσταται σημαντική για τη μείωση της πιθανότητας εμφάνισης συνοδών νοσημάτων (Καρδιαγγειακά νοσήματα, Σακχαρώδης διαβήτης), αλλά μπορεί να δράσει επιβαρυντικά στην οστική μάζα και να ενισχύσει την ανάπτυξη οστεοπόρωσης διαμέσου διαφόρων μηχανισμών. Το ιστορικό της απώλειας βάρους στη μεσαία ηλικία μπορεί να αποτελεί παράγοντα κινδύνου κατάγματος του ισχίου σε μεταγενέστερο στάδιο της ζωής, υπό προϋποθέσεις. Κατά τη διάρκεια της απώλειας βάρους σε γυναίκες αμέσως μετά την εμμηνόπαυση, η συνηθισμένη πρόσληψη Ca (1g / ημέρα) είναι ανεπαρκής, και μπορεί να επηρεάσει τον άξονα Ca-PTH. Σε περιπτώσεις όπου η απώλεια βάρους η οποία προκαλείται από τη διατροφή συνδυάζεται με άσκηση με αντιστάσεις, η άσκηση μπορεί να προστατέψει την οστική πυκνότητα, καθώς η BMD σχετίζεται στενότερα με τη μυϊκή μάζα παρά με τον λιπώδη ιστό. Η δράση των πρωτεϊνικών διαιτών στα οστά είναι πολύπλοκη και τα αποτελέσματά τους εξαρτώνται και από άλλα τρόφιμα που καταναλώνονται μέσα στη διατροφή. Τέλος, για την καλύτερη υγεία των οστών στη μετεμμηνοπαυσιακή ηλικία, σημαντική είναι η παρακολούθηση ενός υγιεινού προτύπου διατροφής που θα καλύπτει τις ανάγκες σε θρεπτικά συστατικά και τις επιπλέον ανάγκες σε ασβέστιο.Menopause is an important milestone for the bone mineral density (BMD) of women. During postmenopausal period, levels of estrogen in the body reduce rapidly. The positive association between body weight or BMI and bone mineral density is well documented. Loss of excess weight at this age is important in order to reduce co-morbidities (Cardiovascular disease, Diabetes Mellitus), but it can also deteriorate bone mass and boost the development of osteoporosis through various mechanisms. Τhe history of weight loss at middle age may be an indicator of the risk of hip fracture at a later stage of life, under conditions. During weight loss in early postmenopausal women, the usual Ca intake (1g/day) is insufficient, as increase the Ca-PTH axis through the reduction of Ca absorption. In cases where weight loss induced by diet is combined with resistance exercise, it can possibly prevent bone loss, since BMD is more closely related to muscle mass rather than to adipose tissue. The role of protein diets on bone mass is complicated and their effect depends on the total food consumption on the diet. Finally, at menopause it is important to follow a healthy diet with adequate nutrients intake and additional Ca needs for the prevention and management of BMD

Clinical implementation of preemptive pharmacogenomics in psychiatryResearch in context

Summary: Background: Pharmacogenomics (PGx) holds promise to revolutionize modern healthcare. Although there are several prospective clinical studies in oncology and cardiology, demonstrating a beneficial effect of PGx-guided treatment in reducing adverse drug reactions, there are very few such studies in psychiatry, none of which spans across all main psychiatric indications, namely schizophrenia, major depressive disorder and bipolar disorder. In this study we aim to investigate the clinical effectiveness of PGx-guided treatment (occurrence of adverse drug reactions, hospitalisations and re-admissions, polypharmacy) and perform a cost analysis of the intervention. Methods: We report our findings from a multicenter, large-scale, prospective study of pre-emptive genome-guided treatment named as PREemptive Pharmacogenomic testing for preventing Adverse drug REactions (PREPARE) in a large cohort of psychiatric patients (n = 1076) suffering from schizophrenia, major depressive disorder and bipolar disorder. Findings: We show that patients with an actionable phenotype belonging to the PGx-guided arm (n = 25) present with 34.1% less adverse drug reactions compared to patients belonging to the control arm (n = 36), 41.2% less hospitalisations (n = 110 in the PGx-guided arm versus n = 187 in the control arm) and 40.5% less re-admissions (n = 19 in the PGx-guided arm versus n = 32 in the control arm), less duration of initial hospitalisations (n = 3305 total days of hospitalisation in the PGx-guided arm from 110 patients, versus n = 6517 in the control arm from 187 patients) and duration of hospitalisation upon readmission (n = 579 total days of hospitalisation upon readmission in the PGx-guided arm, derived from 19 patients, versus n = 928 in the control arm, from 32 patients respectively). It was also shown that in the vast majority of the cases, there was less drug dose administrated per drug in the PGx-guided arm compared to the control arm and less polypharmacy (n = 124 patients prescribed with at least 4 psychiatric drugs in the PGx-guided arm versus n = 143 in the control arm) and smaller average number of co-administered psychiatric drugs (2.19 in the PGx-guided arm versus 2.48 in the control arm. Furthermore, less deaths were reported in the PGx-guided arm (n = 1) compared with the control arm (n = 9). Most importantly, we observed a 48.5% reduction of treatment costs in the PGx-guided arm with a reciprocal slight increase of the quality of life of patients suffering from major depressive disorder (0.935 versus 0.925 QALYs in the PGx-guided and control arm, respectively). Interpretation: While only a small proportion (∼25%) of the entire study sample had an actionable genotype, PGx-guided treatment can have a beneficial effect in psychiatric patients with a reciprocal reduction of treatment costs. Although some of these findings did not remain significant when all patients were considered, our data indicate that genome-guided psychiatric treatment may be successfully integrated in mainstream healthcare. Funding: European Union Horizon 2020