Preterm Formula, Fortified or Unfortified Human Milk for Very Preterm Infants, the PREMFOOD Study: A Parallel Randomised Feasibility Trial.

OBJECTIVE: Uncertainty exists regarding optimal supplemental diet for very preterm infants if the mother's own milk (MM) is insufficient. We evaluated feasibility for a randomised controlled trial (RCT) powered to detect important differences in health outcomes. METHODS: In this open, parallel, feasibility trial, we randomised infants 25+0-31+6 weeks of gestation by opt-out consent to one of three diets: unfortified human milk (UHM) (unfortified MM and/or unfortified pasteurised human donor milk (DM) supplement), fortified human milk (FHM) (fortified MM and/or fortified DM supplement), and unfortified MM and/or preterm formula (PTF) supplement from birth to 35+0 weeks post menstrual age. Feasibility outcomes included opt-outs, adherence rates, and slow growth safety criteria. We also obtained anthropometry, and magnetic resonance imaging body composition data at term and term plus 6 weeks (opt-in consent). RESULTS: Of 35 infants randomised to UHM, 34 to FHM, and 34 to PTF groups, 21, 19, and 24 infants completed imaging at term, respectively. Study entry opt-out rate was 38%; 6% of parents subsequently withdrew from feeding intervention. Two infants met predefined slow weight gain thresholds. There were no significant between-group differences in term total adipose tissue volume (mean [SD]: UHM: 0.870 L [0.35 L]; FHM: 0.889 L [0.31 L]; PTF: 0.809 L [0.25 L], p = 0.66), nor in any other body composition measure or anthropometry at either timepoint. CONCLUSIONS: Randomisation to UHM, FHM, and PTF diets by opt-out consent was acceptable to parents and clinical teams, associated with safe growth profiles and no significant differences in body composition. Our data provide justification to proceed to a larger RCT.

A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis.

BACKGROUND: Retroperitoneal sarcomas are tumours with a poor prognosis. Upfront characterisation of the tumour is difficult, and under-grading is common. Radiomics has the potential to non-invasively characterise the so-called radiological phenotype of tumours. We aimed to develop and independently validate a CT-based radiomics classification model for the prediction of histological type and grade in retroperitoneal leiomyosarcoma and liposarcoma. METHODS: A retrospective discovery cohort was collated at our centre (Royal Marsden Hospital, London, UK) and an independent validation cohort comprising patients recruited in the phase 3 STRASS study of neoadjuvant radiotherapy in retroperitoneal sarcoma. Patients aged older than 18 years with confirmed primary leiomyosarcoma or liposarcoma proceeding to surgical resection with available contrast-enhanced CT scans were included. Using the discovery dataset, a CT-based radiomics workflow was developed, including manual delineation, sub-segmentation, feature extraction, and predictive model building. Separate probabilistic classifiers for the prediction of histological type and low versus intermediate or high grade tumour types were built and tested. Independent validation was then performed. The primary objective of the study was to develop radiomic classification models for the prediction of retroperitoneal leiomyosarcoma and liposarcoma type and histological grade. FINDINGS: 170 patients recruited between Oct 30, 2016, and Dec 23, 2020, were eligible in the discovery cohort and 89 patients recruited between Jan 18, 2012, and April 10, 2017, were eligible in the validation cohort. In the discovery cohort, the median age was 63 years (range 27-89), with 83 (49%) female and 87 (51%) male patients. In the validation cohort, median age was 59 years (range 33-77), with 46 (52%) female and 43 (48%) male patients. The highest performing model for the prediction of histological type had an area under the receiver operator curve (AUROC) of 0·928 on validation, based on a feature set of radiomics and approximate radiomic volume fraction. The highest performing model for the prediction of histological grade had an AUROC of 0·882 on validation, based on a radiomics feature set. INTERPRETATION: Our validated radiomics model can predict the histological type and grade of retroperitoneal sarcomas with excellent performance. This could have important implications for improving diagnosis and risk stratification in retroperitoneal sarcomas. FUNDING: Wellcome Trust, European Organisation for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group, the National Institutes for Health, and the National Institute for Health and Care Research Biomedical Research Centre at The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research.

Clinical and molecular evidence of accelerated ageing following very preterm birth.

BACKGROUND: The mechanisms responsible for the associations between very preterm birth and a higher risk of poor cardiovascular and metabolic health in adult life are unknown. METHODS: Here, we compare the clinical and molecular phenotypes of healthy, normal-weight young adults (18-27 years), born very preterm (<33 weeks gestational age (GA)) and at full-term (37-42 weeks GA). Outcomes included whole-body MRI, hepatic and muscle 1H MRS, blood pressure measurements and telomere length. RESULTS: We recruited 156 volunteers, 69 preterm (45 women; 24 men) and 87 born at full-term (45 women; 42 men). Preterm individuals had a significantly altered blood pressure profile, including higher systolic blood pressure (SBP mmHg: preterm men 133.4 ± 10.1, term men 23.0 ± 6.9; preterm women 124.3 ± 7.1, term women 118.4 ± 8.0, p < 0.01 for all). Furthermore, preterm men had fewer long telomeres (145-48.5 kb: preterm men 14.1 ± 0.9%, term men 17.8 ± 1.1%, p < 0.05; 48.5-8.6 kb: preterm men 28.2 ± 2.6, term men 37.0 ± 2.4%, p < 0.001) and a higher proportion of shorter telomeres (4.2-1.3 kb: preterm men 40.4 ± 3.5%, term men 29.9 ± 3.2%, p < 0.01). CONCLUSION: Our data indicate that healthy young adults born very preterm manifest clinical and molecular evidence of accelerated ageing.

Development of Early Adiposity in Infants of Mothers With Gestational Diabetes Mellitus.

OBJECTIVE: Infants born to mothers with gestational diabetes mellitus (GDM) are at greater risk of later adverse metabolic health. We examined plausible candidate mediators, adipose tissue (AT) quantity and distribution and intrahepatocellular lipid (IHCL) content, comparing infants of mothers with GDM and without GDM (control group) over the first 3 postnatal months. RESEARCH DESIGN AND METHODS: We conducted a prospective longitudinal study using MRI and spectroscopy to quantify whole-body and regional AT volumes, and IHCL content, within 2 weeks and 8-12 weeks after birth. We adjusted for infant size and sex and maternal prepregnancy BMI. Values are reported as the mean difference (95% CI). RESULTS: We recruited 86 infants (GDM group 42 infants; control group 44 infants). Mothers with GDM had good pregnancy glycemic control. Infants were predominantly breast-fed up to the time of the second assessment (GDM group 71%; control group 74%). Total AT volumes were similar in the GDM group compared with the control group at a median age of 11 days (-28 cm(3) [95% CI -121, 65], P = 0.55), but were greater in the GDM group at a median age of 10 weeks (247 cm(3) [56, 439], P = 0.01). After adjustment for size, the GDM group had significantly greater total AT volume at 10 weeks than control group infants (16.0% [6.0, 27.1], P = 0.002). AT distribution and IHCL content were not significantly different at either time point. CONCLUSIONS: Adiposity in GDM infants is amplified in early infancy, despite good maternal glycemic control and predominant breast-feeding, suggesting a potential causal pathway to later adverse metabolic health. Reduction in postnatal adiposity may be a therapeutic target to reduce later health risks.