Categorisation of continuous covariates for stratified randomisation: How should we adjust?

To obtain valid inference following stratified randomisation, treatment effects should be estimated with adjustment for stratification variables. Stratification sometimes requires categorisation of a continuous prognostic variable (eg, age), which raises the question: should adjustment be based on randomisation categories or underlying continuous values? In practice, adjustment for randomisation categories is more common. We reviewed trials published in general medical journals and found none of the 32 trials that stratified randomisation based on a continuous variable adjusted for continuous values in the primary analysis. Using data simulation, this article evaluates the performance of different adjustment strategies for continuous and binary outcomes where the covariate‐outcome relationship (via the link function) was either linear or non‐linear. Given the utility of covariate adjustment for addressing missing data, we also considered settings with complete or missing outcome data. Analysis methods included linear or logistic regression with no adjustment for the stratification variable, adjustment for randomisation categories, or adjustment for continuous values assuming a linear covariate‐outcome relationship or allowing for non‐linearity using fractional polynomials or restricted cubic splines. Unadjusted analysis performed poorly throughout. Adjustment approaches that misspecified the underlying covariate‐outcome relationship were less powerful and, alarmingly, biased in settings where the stratification variable predicted missing outcome data. Adjustment for randomisation categories tends to involve the highest degree of misspecification, and so should be avoided in practice. To guard against misspecification, we recommend use of flexible approaches such as fractional polynomials and restricted cubic splines when adjusting for continuous stratification variables in randomised trials

Plasma oxylipins and unesterified precursor fatty acids are altered by DHA supplementation in pregnancy: Can they help predict risk of preterm birth?

Oxidized lipids derived from omega-6 (n-6) and omega-3 (n-3) polyunsaturated fatty acids, collectively known as oxylipins, are bioactive signaling molecules that play diverse roles in human health and disease. Supplementation with n-3 docosahexaenoic acid (DHA) during pregnancy has been reported to decrease the risk of preterm birth in singleton pregnancies, which may be due to effects of DHA supplementation on oxylipins or their precursor n-6 and n-3 fatty acids. There is only limited understanding of the levels and trajectory of changes in plasma oxylipins during pregnancy, effects of DHA supplementation on oxylipins and unesterified fatty acids, and whether and how oxylipins and their unesterified precursor fatty acids influence preterm birth. In the present study we used liquid chromatography-tandem mass spectrometry to profile oxylipins and their precursor fatty acids in the unesterified pool using plasma samples collected from a subset of pregnant Australian women who participated in the ORIP (Omega-3 fats to Reduce the Incidence of Prematurity) study. ORIP is a large randomized controlled trial testing whether daily supplementation with n-3 DHA can reduce the incidence of early preterm birth compared to control. Plasma was collected at study entry (≈pregnancy week 14) and again at ≈week 24, in a subgroup of 48 ORIP participants-12 cases with spontaneous preterm (<37 weeks) birth and 36 matched controls with spontaneous term (≥40 weeks) birth. In the combined preterm and term pregnancies, we observed that in the control group without DHA supplementation unesterified AA and AA-derived oxylipins 12-HETE, 15-HETE and TXB2 declined between weeks 14-24 of pregnancy. Compared to control, DHA supplementation increased unesterified DHA, EPA, and AA, DHA-derived 4-HDHA, 10-HDHA and 19,20-EpDPA, and AA-derived 12-HETE at 24 weeks. In exploratory analysis independent of DHA supplementation, participants with concentrations above the median for 5-lipoxygenase derivatives of AA (5-HETE, Odds Ratio (OR) 8.2; p = 0.014) or DHA (4-HDHA, OR 8.0; p = 0.015) at 14 weeks, or unesterified AA (OR 5.1; p = 0.038) at 24 weeks had higher risk of spontaneous preterm birth. The hypothesis that 5-lipoxygenase-derived oxylipins and unesterified AA could serve as mechanism-based biomarkers predicting spontaneous preterm birth should be evaluated in larger, adequately powered studies

Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes

Many trials use stratified randomisation, where participants are randomised within strata defined by one or more baseline covariates. While it is important to adjust for stratification variables in the analysis, the appropriate method of adjustment is unclear when stratification variables are affected by misclassification and hence some participants are randomised in the incorrect stratum. We conducted a simulation study to compare methods of adjusting for stratification variables affected by misclassification in the analysis of continuous outcomes when all or only some stratification errors are discovered, and when the treatment effect or treatment-by-covariate interaction effect is of interest. The data were analysed using linear regression with no adjustment, adjustment for the strata used to perform the randomisation (randomisation strata), adjustment for the strata if all errors are corrected (true strata), and adjustment for the strata after some errors are discovered and corrected (updated strata). The unadjusted model performed poorly in all settings. Adjusting for the true strata was optimal, while the relative performance of adjusting for the randomisation strata or the updated strata varied depending on the setting. As the true strata are unlikely to be known with certainty in practice, we recommend using the updated strata for adjustment and performing subgroup analyses, provided the discovery of errors is unlikely to depend on treatment group, as expected in blinded trials. Greater transparency is needed in the reporting of stratification errors and how they were addressed in the analysis

Analysis of Randomised Trials Including Multiple Births When Birth Size Is Informative.

BACKGROUND: Informative birth size occurs when the average outcome depends on the number of infants per birth. Although analysis methods have been proposed for handling informative birth size, their performance is not well understood. Our aim was to evaluate the performance of these methods and to provide recommendations for their application in randomised trials including infants from single and multiple births. METHODS: Three generalised estimating equation (GEE) approaches were considered for estimating the effect of treatment on a continuous or binary outcome: cluster weighted GEEs, which produce treatment effects with a mother-level interpretation when birth size is informative; standard GEEs with an independence working correlation structure, which produce treatment effects with an infant-level interpretation when birth size is informative; and standard GEEs with an exchangeable working correlation structure, which do not account for informative birth size. The methods were compared through simulation and analysis of an example dataset. RESULTS: Treatment effect estimates were affected by informative birth size in the simulation study when the effect of treatment in singletons differed from that in multiples (i.e. in the presence of a treatment group by multiple birth interaction). The strength of evidence supporting the effectiveness of treatment varied between methods in the example dataset. CONCLUSIONS: Informative birth size is always a possibility in randomised trials including infants from both single and multiple births, and analysis methods should be pre-specified with this in mind. We recommend estimating treatment effects using standard GEEs with an independence working correlation structure to give an infant-level interpretation.Australian National Health and Medical Research Council. Grant Number: #ID 1052388 United Kingdom Medical Research Council. Grant Number: ID U1052 6055

Antenatal lifestyle advice for women who are overweight or obese: LIMIT randomised trial

for the LIMIT Randomised Trial GroupOBJECTIVE To determine the effect of antenatal dietary and lifestyle interventions on health outcomes in overweight and obese pregnant women. DESIGN Multicentre randomised trial. We utilised a central telephone randomisation server, with computer generated schedule, balanced variable blocks, and stratification for parity, body mass index (BMI) category, and hospital. SETTING Three public maternity hospitals across South Australia. PARTICIPANTS 2212 women with a singleton pregnancy, between 10+0 and 20+0 weeks’ gestation, and BMI ≥25. INTERVENTIONS 1108 women were randomised to a comprehensive dietary and lifestyle intervention delivered by research staff; 1104 were randomised to standard care and received pregnancy care according to local guidelines, which did not include such information. MAIN OUTCOME MEASURES Incidence of infants born large for gestational age (birth weight ≥90th centile for gestation and sex). Prespecified secondary outcomes included birth weight >4000 g, hypertension, pre-eclampsia, and gestational diabetes. Analyses used intention to treat principles. RESULTS 2152 women and 2142 liveborn infants were included in the analyses. The risk of the infant being large for gestational age was not significantly different in the two groups (lifestyle advice 203/1075 (19%) v standard care 224/1067 (21%); adjusted relative risk 0.90, 95% confidence interval 0.77 to 1.07; P=0.24). Infants born to women after lifestyle advice were significantly less likely to have birth weight above 4000 g (lifestyle advice 164/1075 (15%) v standard care 201/1067 (19%); 0.82, 0.68 to 0.99; number needed to treat (NNT) 28, 15 to 263; P=0.04). There were no differences in maternal pregnancy and birth outcomes between the two treatment groups. CONCLUSIONS For women who were overweight or obese, the antenatal lifestyle advice used in this study did not reduce the risk delivering a baby weighing above the 90th centile for gestational age and sex or improve maternal pregnancy and birth outcomes. TRIAL REGISTRATION Australian and New Zealand Clinical Trials Registry (ACTRN12607000161426).Jodie M Dodd, Deborah Turnbull, Andrew J McPhee, Andrea R Deussen, Rosalie M Grivell, Lisa N Yelland, Caroline A Crowther, Gary Wittert, Julie A Owens, and Jeffrey S Robinso

Low-dose thiamine supplementation of lactating Cambodian mothers improves human milk thiamine concentrations: a randomized controlled trial.

BACKGROUND: Infantile beriberi-related mortality is still common in South and Southeast Asia. Interventions to increase maternal thiamine intakes, and thus human milk thiamine, are warranted; however, the required dose remains unknown. OBJECTIVES: We sought to estimate the dose at which additional maternal intake of oral thiamine no longer meaningfully increased milk thiamine concentrations in infants at 24 wk postpartum, and to investigate the impact of 4 thiamine supplementation doses on milk and blood thiamine status biomarkers. METHODS: In this double-blind, 4-parallel arm randomized controlled dose-response trial, healthy mothers were recruited in Kampong Thom, Cambodia. At 2 wk postpartum, women were randomly assigned to consume 1 capsule, containing 0, 1.2 (estimated average requirement), 2.4, or 10 mg of thiamine daily from 2 through 24 weeks postpartum. Human milk total thiamine concentrations were measured using HPLC. An Emax curve was plotted, which was estimated using a nonlinear least squares model in an intention-to-treat analysis. Linear mixed-effects models were used to test for differences between treatment groups. Maternal and infant blood thiamine biomarkers were also assessed. RESULTS: In total, each of 335 women was randomly assigned to1 of the following thiamine-dose groups: placebo (n = 83), 1.2 mg (n = 86), 2.4 mg (n = 81), and 10 mg (n = 85). The estimated dose required to reach 90% of the maximum average total thiamine concentration in human milk (191 µg/L) is 2.35 (95% CI: 0.58, 7.01) mg/d. The mean ± SD milk thiamine concentrations were significantly higher in all intervention groups (183 ± 91, 190 ± 105, and 206 ± 89 µg/L for 1.2, 2.4, and 10 mg, respectively) compared with the placebo group (153 ± 85 µg/L; P < 0.0001) and did not significantly differ from each other. CONCLUSIONS: A supplemental thiamine dose of 2.35 mg/d was required to achieve a milk total thiamine concentration of 191 µg/L. However, 1.2 mg/d for 22 wk was sufficient to increase milk thiamine concentrations to similar levels achieved by higher supplementation doses (2.4 and 10 mg/d), and comparable to those of healthy mothers in regions without beriberi. This trial was registered at clinicaltrials.gov as NCT03616288

DHA supplementation during pregnancy does not reduce BMI or body fat mass in children: follow-up of the DHA to Optimize Mother Infant Outcome randomized controlled trial

First published March 30, 2016The omega-3 (n-3) long-chain polyunsaturated fatty acid (LCPUFA) docosahexaenoic acid (DHA) has proven effective at reducing fat storage in animal studies. However, a systematic review of human trials showed a lack of quality data to support or refute this hypothesis.We sought to determine whether maternal DHA supplementation during the second half of pregnancy results in a lower body mass index (BMI) and percentage of body fat in children.We conducted a follow-up at 3 and 5 y of age of children who were born to mothers enrolled in the DOMInO (DHA to Optimize Mother Infant Outcome) double-blind, randomized controlled trial, in which women with a singleton pregnancy were provided with DHA-rich fish-oil capsules (800 mg DHA/d) or vegetable-oil capsules (control group) in the second half of pregnancy. Primary outcomes were the BMIzscore and percentage of body fat at 3 and 5 y of age. Potential interactions between prenatal DHA and the peroxisome proliferator-activated receptor-γ (PPARγ) genotype as a measure of the genetic predisposition to obesity were investigated.A total of 1614 children were eligible for the follow-up. Parent or caregiver consent was obtained for 1531 children (95%), and these children were included in the analysis. BMIzscores and percentages of body fat of children in the DHA group did not differ from those of children in the control group at either 3 y of age [BMIzscore adjusted mean difference: 0.03 (95% CI: -0.07, 0.13;P= 0.61); percentage of body fat adjusted mean difference: -0.26 (95% CI: -0.99, 0.46;P= 0.47)] or 5 y of age [BMIzscore adjusted mean difference: 0.02 (95% CI: -0.08, 0.12;P= 0.66); percentage of body fat adjusted mean difference: 0.11 (95% CI: -0.60, 0.82;P= 0.75)]. No treatment effects were modified by thePPARγgenotype of the child.Independent of a genetic predisposition to obesity, maternal intake of DHA-rich fish oil during the second half of pregnancy does not affect the growth or body composition of children at 3 or 5 y of age. This trial was registered atwww.anzctr.org.auas ACTRN1260500056906 and ACTRN12611001127998.Beverly S Muhlhausler, Lisa N Yelland, Robyn McDermott, Linda Tapsell, Andrew McPhee, Robert A Gibson, and Maria Makride

The effects of antenatal dietary and lifestyle advice for women who are overweight or obese on maternal diet and physical activity: the LIMIT randomised trial

BACKGROUND Overweight and obesity is a significant health concern during pregnancy. Our aim was to investigate the effect of providing antenatal dietary and lifestyle advice to women who are overweight or obese on components of maternal diet and physical activity. METHODS We conducted a randomised controlled trial, in which pregnant women with a body mass index ?25 kg/m2, and singleton gestation between 10+0 to 20+0 weeks were recruited and randomised to Lifestyle Advice (involving a comprehensive dietary and lifestyle intervention over their pregnancy) or Standard Care. Within the intervention group, we conducted a nested randomised trial in which a subgroup of women were further randomised to receive access to supervised group walking sessions in addition to the standard information presented during the intervention contacts (the Walking group) or standard information only. The outcome measures were maternal dietary intake, (including food groups, macronutrient and micronutrient intake, diet quality (using the Healthy Eating Index; HEI), dietary glycaemic load, and glycaemic index) and maternal physical activity. Women completed the Harvard Semi-Structured Food Frequency Questionnaire, and the Short Questionnaire to Assess Health-enhancing Physical Activity (SQUASH), at trial entry, 28 and 36 weeks¿ gestational age, and 4 months postpartum. Analyses were performed on an intention-to-treat basis, using linear mixed effects models with adjustment for the stratification variables. RESULTS Women randomised to Lifestyle Advice demonstrated a statistically significant increase in the number of servings of fruit and vegetables consumed per day, as well as increased consumption of fibre, and reduced percentage energy intake from saturated fats (P?<?0.05 for all). Maternal HEI was significantly improved at both 28 (73.35?±?6.62 versus 71.86?±?7.01; adjusted difference in means 1.58; 95% CI 0.89 to 2.27; P?<?0.0001) and 36 (72.95?±?6.82 versus 71.17?±?7.69; adjusted difference in means 1.77; 95% CI 1.01 to 2.53; P?<?0.0001) weeks. There were no differences in dietary glycaemic index or glycaemic load. Women randomised to Lifestyle Advice also demonstrated greater total physical activity (adjusted difference in means 359.76 metabolic equivalent task units (MET) minutes/week; 95% CI 74.87 to 644.65; P?=?0.01) compared with women receiving Standard Care. The supervised walking group was poorly utilised. CONCLUSIONS For women who are overweight or obese, antenatal lifestyle advice improves maternal diet and physical activity during pregnancy. Please see related articles: http://www.biomedcentral.com/1741-7015/12/163 and http://www.biomedcentral.com/1741-7015/12/201. TRIAL REGISTRATION Australian and New Zealand Clinical Trials Registry (http://ACTRN12607000161426)Jodie M Dodd, Courtney Cramp, Zhixian Sui, Lisa N Yelland, Andrea R Deussen, Rosalie M Grivell, Lisa J Moran, Caroline A Crowther, Deborah Turnbull, Andrew J McPhee, Gary Wittert, Julie A Owens, Jeffrey S Robinso