: The Strengthening Families Programme for youth aged 10-14 and parents/carers (SFP10-14) is a family-based prevention intervention with positive results in trials in the United States. We assessed the effectiveness of SFP10-14 for preventing substance misuse in Poland. : Cluster randomized controlled trial with 20 communities (511 families; 614 young people) were allocated to SFP10-14 or a control arms. Primary outcomes were alcohol, smoking and other drug use. Secondary outcomes included parenting practices, parent-child relations, and child problem behaviour. Interview-based questionnaires were administered at baseline and at 12- and 24-months post-baseline, with respective 70.4 and 54.4%, follow-up rates. : In Bayesian regression models with complete case data we found no effects of SFP10-14 for any of the primary or secondary outcomes at either follow-up. For example at 24-months, posterior odds ratios and 95% credible intervals for past year alcohol use, past month binge drinking, past year smoking, and past year other drug use, were 0.83 (0.44-1.56), 0.83 (0.27-2.65), 1.94 (0.76-5.38) and 0.74 (0.15-3.58), respectively. Although moderate to high attrition rates, together with some evidence of systematic attrition bias according to parent education and family disposable income, could have biased the results, the results were supported in further analyses with propensity score matched data and 40 multiple imputed datasets. : We found no evidence for the effectiveness of SFP10-14 on the prevention of alcohol or tobacco use, parenting behaviour, parent-child relations or child problem behaviour at 12- or 24-month follow-up in a large cluster randomized controlled trial in Poland.

Background: UK Biobank is a large prospective study that recruited 500,000 participants aged 40 to 69 years, between 2006-2010.The study has collected (and continues to collect) extensive phenotypic and genomic data about its participants. In order to enhance further the value of the UK Biobank resource, a wide range of biochemistry markers were measured in all participants with an available biological sample. Here, we describe the approaches UK Biobank has taken to minimise error related to sample collection, processing, retrieval and assay measurement. Methods: During routine quality control checks, the laboratory team observed that some assay results were lower than expected for samples acquired during certain time periods. Analyses were undertaken to identify and correct for the unexpected dilution identified during sample processing, and for expected error caused by laboratory drift of assay results. Results: The vast majority (92%) of biochemistry serum assay results were assessed to be not materially affected by dilution, with an estimated difference in concentration of less than 1% (i.e. either lower or higher) than that expected if the sample were unaffected; 8.3% were estimated to be diluted by up to 10%; very few samples appeared to be diluted more than this. Biomarkers measured in urine (creatinine, microalbumin, sodium, potassium) and red blood cells (HbA1c) were not affected. In order to correct for laboratory variation over the assay period, all assay results were adjusted for date of assay, with the exception of those that had a high biological coefficient of variation or evident seasonal variability: vitamin D, lipoprotein (a), gamma glutamyltransferase, C-reactive protein and rheumatoid factor. Conclusions: Rigorous approaches related to sample collection, processing, retrieval, assay measurement and data analysis have been taken to mitigate the impact of both systematic and random variation in epidemiological analyses that use the biochemistry assay data in UK Biobank.

Background: UK Biobank is a large prospective study that recruited 500,000 participants aged 40 to 69 years, between 2006-2010.The study has collected (and continues to collect) extensive phenotypic and genomic data about its participants. In order to enhance further the value of the UK Biobank resource, a wide range of biochemistry markers were measured in all participants with an available biological sample. Here, we describe the approaches UK Biobank has taken to minimise error related to sample collection, processing, retrieval and assay measurement. Methods: During routine quality control checks, the laboratory team observed that some assay results were lower than expected for samples acquired during certain time periods. Analyses were undertaken to identify and correct for the unexpected dilution identified during sample processing, and for expected error caused by laboratory drift of assay results. Results: The vast majority (92%) of biochemistry serum assay results were assessed to be not materially affected by dilution, with an estimated difference in concentration of less than 1% (i.e. either lower or higher) than that expected if the sample were unaffected; 8.3% were estimated to be diluted by up to 10%; very few samples appeared to be diluted more than this. Biomarkers measured in urine (creatinine, microalbumin, sodium, potassium) and red blood cells (HbA1c) were not affected. In order to correct for laboratory variation over the assay period, all assay results were adjusted for date of assay, with the exception of those that had a high biological coefficient of variation or evident seasonal variability: vitamin D, lipoprotein (a), gamma glutamyltransferase, C-reactive protein and rheumatoid factor. Conclusions: Rigorous approaches related to sample collection, processing, retrieval, assay measurement and data analysis have been taken to mitigate the impact of both systematic and random variation in epidemiological analyses that use the biochemistry assay data in UK Biobank.

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