The Benefits and Risks of Iron interventionS in Children (BRISC) trial: Statistical analysis plan

Aims

The primary objective of this study is to determine whether 3 months of iron supplementation or home fortification with MNPs is superior to placebo on cognitive development in 8-month old children at the end of the intervention. The secondary objectives are to evaluate the impact of iron supplementation and home fortification with MNPs, compared with placebo, on developmental indices, prevalence of anaemia and iron deficiency, growth, and infection risks at the end of the intervention and 9 months post-intervention.

Design

BRISC is a three-arm, blinded, double-dummy, parallel group, placebo-controlled, individually-randomised, superiority trial. Starting at 8 months of age, children were randomised to either Arm 1: iron syrup (12.5 mg elemental iron) + placebo MNPs (powder sachet); Arm 2: MNPs (including 12.5 mg elemental iron) + placebo syrup; or Arm 3: placebo syrup and placebo powder/sachet (control), for 3 months (Figure 1). Children were then followed up for an additional 9 months post-intervention. The study received ethics approval from the Ethical Review Committee of the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) and the Melbourne Health Human Research Ethics Committee (Melbourne, Australia). It was prospectively registered at the Australian New Zealand Clinical Trials Registry (ACTRN1261700066038) and the World Health Organization (WHO) International Clinical Trials Registry Platform (U1111-1196-1125).

Figure 1. Study design.

Setting

The trial is conducted in Rupganj, a rural subdistrict/upazila of Narayanganj district about 50 km from Dhaka, in Bangladesh. Three unions (Bhulta, Golakandail, Rupganj) within the subdistrict are included, with each union covered by a dedicated field team.

Participants

Children eligible for enrolment were children who were 8 months of age ±14 days, were not expected to leave the study site for more than 1 week over the next 3 months or for more than one month over the next 12 months and had a legally acceptable representative capable of providing consent. Children were excluded if they had severe anaemia (haemoglobin <80 g/L), if their drinking (ground) water iron content was >1 mg/L, if their mid upper arm circumference <11.5 cm, if they had been previously diagnosed with inherited red cell disorders, or if they had a current infective illness with fever.

Randomisation and allocation

Children were randomly allocated to one of the three arms with 1:1:1 allocation using a computer-generated schedule of randomly permuted blocks of fixed size stratified by union and sex to achieve balance between the arms within each stratum. The randomisation list was computer-generated by an independent statistician. Blinding of the team visiting the site, the caregiver(s) and study participants was achieved through the use of identical packaging of sachets and syrup. Researchers, caregivers, persons involved with data collection (i.e., field team) or analysis will be blinded to the allocation code until the database has been cleaned and is ready for analysis.

Outcome variables

All efficacy and laboratory outcomes were measured at baseline, 3 months post-intervention and after a further 9 months follow-up. Data related to infectious morbidity and hospitalisation were collected weekly during the intervention period and monthly during the follow-up period. Serious adverse events were measured at any time. The primary time-point of interest for all outcome variables is at the end of the intervention.

The primary outcome of the study is cognitive development, as measured using the cognitive composite score of the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley III)⁷. Bayley-III is a validated index of child development and the preferred field assessment tool. It is a standard series of measurements primarily to assess cognitive, motor (fine and gross) and language (receptive and expressive) development of infants and toddlers aged 0–3 ½ yrs. The total number of credited items is converted into scaled scores based on child’s age, which are then converted to composite scores of each subscale.

Key secondary outcomes include motor and language composite scores assessed by Bayley III, growth (length-for-age z-score, weight-for-age z-score), and laboratory indices (haemoglobin and ferritin concentrations). Secondary outcomes include other anthropometry measures (weight-for-length z-score, stunting, wasting, underweight, head circumference) and haematological and iron diagnoses (anaemia, iron deficiency, iron deficiency anaemia). Anthropometry outcomes (z-scores) will be derived using the child’s length and weight together with age and sex of the child according to age and sex specific WHO international reference growth standards⁸. Using the z-scores, stunting will be defined as length-for-age z-score <-2, underweight as weight-for-age z-score <-2, and wasting as weight-for-length z-score <-2. Using the child’s haemoglobin (g/L), ferritin (µg/L), and C-reactive protein (mg/L), anaemia will be defined as haemoglobin <110 g/L, iron deficient as ferritin <12 µg/L or ferritin <30 µg/L if C-reactive protein >5 mg/L, and iron deficient anaemia as iron deficient and anaemia.

Exploratory outcomes include child’s behaviour using items from the Wolke’s Behaviour rating scale⁹, consisting of nine behaviours each scored on a nine-point scale with higher scores indicating more favourable behaviour, and the temperament questionnaire¹⁰, consisting of 33 questions each scored on a four-point scale with higher scores indicating a better temperament which will be grouped by summing into seven temperament summary scores.

Safety outcomes include infectious morbidity (includes fever, diarrhoea, bloody stool, vomiting, cough/ difficulty breathing), (serious) adverse events, and C-reactive protein (an inflammatory biomarker) and inflammation defined as C-reactive protein >5 mg/L.

Additional data collected included household baseline characteristics (union, religion, number of household members, parity, number of children under five years of age living in the household, maternal and paternal education, maternal and paternal occupation, wealth index¹¹, maternal depression^12,13, household food insecurity¹⁴) and child baseline characteristics (sex, age, currently breastfed, home stimulation as measured using the family care indicator score¹⁵). Daily study medication intake was collected weekly during the 3-month intervention period and included reasons for non-adherence to the allocated treatment regimen.

Sample size

The sample size for the trial was to recruit 3300 children (1100 per treatment arm) in order to have 80% power to detect a two-point difference in Bayley III composite cognitive score between the iron supplementation and placebo arm and the MNPs and placebo arm (two-sided 2.5% level of significance per comparison), assuming a standard deviation of 15 and a 20% loss to follow up after 3 months of intervention. No interim analyses to stop the trial early were planned, and no interim analysis was conducted.

Statistical analysis plan

The analysis will be conducted by statisticians from the University of Melbourne. After all study data are available and clean, a blinded data review meeting to review protocol violations, overall compliance, and missing data will be held prior to database lock. The final statistical analysis plan will be signed off during this meeting. The analysis of the primary outcome will be checked by an independent statistician. Discrepancies will be discussed and resolved by consensus.

General principles

The intention-to-treat population will be used for the analysis of all primary, key secondary, secondary, and exploratory outcomes and will include all children who were randomised. In case of missing outcome data, we will follow the missing data handling strategy outlined below. The safety population will be used for the analysis of all safety outcomes and consists of all children who received at least one study treatment (including control). Children who have withdrawn informed consent for use of all their data will be excluded from all analyses. Children will be reported and analysed according to their randomised treatment allocation. Time-windows will be applied to all visit-wise data collected at baseline, month 3, and month 12, with assessments outside the predefined visit windows excluded from the analyses. Outcomes will be summarised using frequencies and percentages (based on the non-missing sample size) for categorical variables, mean and standard deviation for continuous variables, or median and quartiles (25th and 75th percentile) for non-symmetrical continuous variables. All analyses models will be adjusted for the stratification variables used during the randomisation (union and sex). All confidence intervals and P-Values will be two-sided.

Trial profile

The flow of children through the trial will be presented in a Consolidated Standards of Reporting Trials (CONSORT) diagram, reasons for exclusion will be reported (Figure 2).

Figure 2. The CONSORT flow chart.

MNPs denotes multiple micronutrient powders.

Baseline characteristics

Demographic and baseline variables of household and child characteristics will be summarised descriptively and presented by treatment group (Table 1). No formal comparisons between groups will be made.

Multiple testing adjustment

The two primary comparisons of interest for the primary and key secondary outcomes are iron versus placebo and MNPs versus placebo. We will use a Bonferroni adjustment combined with a gatekeeping procedure to ensure control of the Type I error rate for the primary outcome across all three pairwise comparisons. Using the Bonferroni correction, we will test each of the two primary null hypotheses of no difference between iron and placebo and MNPs and placebo for the primary outcome at the two-sided 2.5% level of significance. If at least one of the two primary null hypotheses can be rejected (multiplicity unadjusted P-Value < 0.025), a comparison of iron versus MNPs will take place at either the two-sided 2.5% (if either iron or MNPs is superior to placebo) or 5% level of significance (if both iron and MNPs are superior to placebo). Estimates and two-sided confidence intervals will be presented with the same level of significance as used for the testing of these null hypotheses, along with multiplicity unadjusted and adjusted P-Values. If neither iron nor MNPs is superior to placebo, we will report the estimate and two-sided 95% confidence interval but not the P-Value for the comparison of iron versus MNPs.

For the set of key secondary outcomes, we will use the Hochberg procedure for each of the three pairwise comparisons at the level of significance used for the primary outcome only if the corresponding null hypothesis is rejected for the primary outcome. No multiplicity adjustment is planned for secondary and exploratory outcomes, and no P-Values will be presented.

We will follow the above outlined multiple testing approach for the primary and key secondary outcomes both for the primary time-point at month 3 and the secondary time-point at month 12 separately. The primary objective of the trial will have been met if one of the two primary null hypotheses for the primary outcome at the primary time-point can be rejected at the predetermined significance level.

Efficacy (including selected laboratory) outcomes: analysis

A constrained longitudinal data analysis method proposed by Liang and Zeger¹⁶ will be used to examine the primary outcome (Bayley III cognitive composite score at baseline, 3 months and 12 months post-baseline). The model will incorporate study visit as a categorical variable, treatment and treatment by study visit interaction and adjust for the stratification randomisation factors (union and sex) as main effects. The model will assume a common baseline mean across the three treatment arms and an unstructured variance-covariance among the repeated measurements. In case of non-convergence, we will consider alternative structures (first-order autoregressive, Toeplitz, compound symmetry). The treatment effect will be estimated from this model as the difference between two treatments in mean change from baseline to 3 months post-intervention (Table 2).

Continuous key secondary, secondary, and exploratory outcomes will be analysed similarly as the primary outcome. Ferritin (µg/L) will be log_e transformed before analysis. Binary outcomes will be analysed using a generalised linear mixed model with a log-link function and binomial distribution, including child as a random intercept. In case of non-convergence, we will use a logit link function instead.

Safety outcomes: analysis

The total number of times at least one infection (fever, diarrhoea, bloody stool, vomiting, cough/ difficulty breathing) was reported will be summarised per infection type during the intervention period (weekly reports), extended follow-up period (monthly reports), and (total) study period. The incidence rate ratio will be estimated using a Poisson regression model, with a logarithm of the time at risk as offset (Table 3).

The number and percentage of children who died, had at least one (overnight) hospitalisation, reported at least one serious adverse event, and had at least one clinic visit (due to any infection, fever, diarrhoea, bloody stool, vomiting, cough/ difficulty breathing, other infection) during the intervention period, extended follow-up period, and study period will be reported and compared between treatments using a log-binomial regression model (Table 4).

C-reactive protein levels will be analysed using similar models as those described for the primary outcome and for inflammation similar models to those described for the binary key secondary and secondary outcomes.

We will present the multiplicity unadjusted P-Values for the safety outcomes, no multiple testing adjustment is planned.

Missing data handling

To describe the missing data, the frequency and percentage of children with missing data at baseline, month 3 and month 12 will be summarised for the child development, anthropometry, and laboratory outcomes. In addition, baseline and demographic characteristics will be summarized by those with and without missing data for the cognitive composite score (at baseline, month 3, and month 12) to explore the missing data assumption and identify any variables not included in the target analyses that are potentially associated with missingness (known as auxiliary variables).

As the primary strategy to handle missing data, the analysis will use a likelihood-based approach. This approach relies on the underlying assumption that the probability of missing outcome data is not related to the missing data but to some of the observed measured data in the model (Missing At Random [MAR]).

As the secondary strategy (sensitivity analysis), missing data on the outcomes will be multiply imputed using chained equations. The imputation model will include union, sex, visit (categorical), the family care indicator total score (continuous), maternal education (continuous), all variables listed as specified for subgroup analyses, and it will be performed separately by treatment group. In addition, auxiliary variables identified during the blinded data review meeting may be included. The variables with missing data will be imputed using a linear regression model if continuous and logistic regression if binary, whereby ferritin will be log_e transformed prior to imputation as this outcome will be log_e transformed in the analysis of interest. The missing outcome data at baseline, 3-month and 12-month visits will be imputed using the “just another variable” approach (also known as imputing in wide format) which requires a separate imputation model for imputing the variable at each assessment time. The number of imputed data sets will be greater than or equal to the percentage of missing data in the available case analyses. The imputed data sets will be analysed using the models described. The estimates from the analyses of the imputed data sets will be combined to obtain a pooled common estimate and corresponding confidence interval using Rubin’s rules. For the above standard implementation of multiple imputation, we have assumed the outcome data are MAR.

Adherence

Overall compliance across the 3-month intervention period will be derived as the total number of days the child has reported taking both the syrup and the sachet divided by the child’s study participation duration, with ‘complier’ defined as those with overall compliance ≥70%. If no data on treatment intake is available, compliance will be assumed to be 0%.

Sensitivity analyses

In addition to the analyses specified for the primary, key secondary, and secondary outcomes, the following sensitivity analyses will be applied for these outcomes:

1. Analyses consisting of models adjusted for potential prognostic or predictive variables:

2. Analyses of the secondary strategy to handle missing data.

3. Analyses of the model adjusted for union and sex for the per-protocol population defined as randomised children who were compliant to treatment, and without protocol violations (no informed consent or withdrawn informed consent for use of all data, violation in/ exclusion criteria, or improper unblinding of the child’s allocated treatment).

4. Analyses using the Complier Average Causal Effect method to estimate the average effect of treatment among compliers¹⁷.

Subgroup analyses

Exploratory subgroup analyses will be performed for cognitive motor and language composite scores assessed by Bayley III at 3 and 12 months. Subgroup (main effect) and the subgroup-by-treatment-by-visit interaction (as well as subgroup-by-treatment and subgroup-by-visit interaction) terms will be added to the constrained longitudinal data analysis model to evaluate whether the treatment effect differs between subgroup categories. The following subgroups will be explored: sex (male/female), baseline anaemia status (yes/no), baseline iron deficient status (yes/no), baseline iron deficient anaemia status (yes/no), baseline stunting (yes/no), baseline home stimulation as measured by the family care indicator questionnaire (below/ above median family care indicator total score), baseline household food insecurity status (yes/no), baseline wealth status (below/ above median wealth index score), and union (Bhulta, Golakandail, Rupganj). No multiplicity adjustments are planned for the subgroup analyses due to their explorative nature, we will present the estimates and two-sided 95% confidence interval along with (multiplicity unadjusted) P-Values. Results of the subgroup analyses will be displayed using Forest plots.

Changes from the registry and published study protocol

This paper includes changes to the statistical analysis plan of the BRISC trial in the registry (registered May 2017) and protocol paper (accepted September 2017). These changes are:

This paper documents version 1 of the statistical analysis plan dated April 20, 2020. Any changes to this version between publishing and breaking of the code will be tracked and still considered as planned analyses. The statistical analysis plan will be approved during the blinded data review before breaking of the allocation code. Any changes after this signed version will be considered post-hoc.