Comparison of different protein concentrations of human milk fortifier for promoting growth and neurological development in preterm infants

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To compare the effects of different protein concentrations in human milk fortifier, fed to preterm infants, on growth and neurodevelopment.

Background

Description of the condition

Human milk is the optimal nutrition for preterm infants because of its immunological properties, ease of digestion and absorption, and more favourable neurodevelopmental outcomes when compared with formula milk (AAP 2012). However, human milk alone provides inadequate amounts of protein, energy and minerals to meet the high needs for preterm infant growth (Arslanoglu 2019). Infants with insufficient nutrient intake are at increased risk of postnatal growth faltering and impaired neurodevelopment, which is particularly a problem for extremely low birth weight infants (Kumar 2017). To address the preterm infants' nutritional needs, it has become a common clinical practice to fortify breast milk with additional nutrients using commercially available human milk fortifier (Arslanoglu 2019).

Description of the intervention

Protein is one of the main ingredients in human milk fortifiers. Preterm infants require higher level of protein intake as they grow rapidly (in line with fetal growth trajectories in the last trimester) and have higher nitrogen excretion in urine and faeces and via the skin than term infants (Hay 2010). However, protein needs cannot be considered in isolation since adequate energy must be supplied in order for the protein to be used for anabolic growth. Protein intake and protein energy ratio (the amount of protein in grams per 100 kcal) are the main determinants of growth in preterm infants (Koletzko 2014). Despite the routine use of commercial fortifiers, there is evidence that preterm infants do not meet their needs for protein intake and accrue substantial protein deficits during their hospital admission (Hay 2016; Moro 2015; Radmacher 2017). For this reason, clinical guidelines have changed over time to recommend an increased protein intake that is based on weight and gestation ranging between 3.5 g/kg/day and 4.5 g/kg/day (ESPGHAN 2010; Koletzko 2014; Ziegler 2011), particularly in extremely preterm (less than 28 weeks' gestation) or extremely low birth weight (less than 1000 g) infants (4 g/kg/day to 4.5 g/kg/day) (ESPGHAN 2010).

The protein in fortifiers is usually derived from bovine milk, predominantly whey protein, with some fortifiers using hydrolysed protein. The use of hydrolysed protein in formula may increase gastric emptying (Mihatsch 2002), and calcium absorption rate (Picaud 2001), without inducing the risk of feeding intolerance or necrotising enterocolitis (Ng 2019). However, it is not known if these effects also apply to hydrolysed protein fortifier. More recently, fortifiers derived from human milk have become available which allows for a diet that is exclusively human milk based. Bovine protein is thought to induce inflammation (Abdelhamid 2013), increase gut permeability (Taylor 2009), and may even cause death of intestinal cells (Penn 2012).

Regardless of the source and type of proteins used in fortifiers, there is considerable clinical practice variation in how and when fortifiers are administered. The usual regimen of a standard amount of fortifier added to human milk fails to account for individual and temporal variations in the protein concentration in maternal milk, and the differing requirements of preterm infants of different gestational ages and weight (ESPGHAN 2010). Individualised regimens are now recommended by some groups (Arslanoglu 2019; ESPGHAN 2010), where either the amount of fortifier is titrated against blood urea nitrogen concentration or adjusted according to the level in mother's milk. In addition, several trials have evaluated the timing of fortification, with evidence that starting fortification early rather than delaying is well tolerated but does not improve short‐term growth of infants (Godden 2019). These different fortification strategies (Fabrizio 2019), and timing of commencement of fortification (Thanigainathan 2019), are the focus of other Cochrane Reviews and are, therefore, not addressed in this review.

How the intervention might work

Protein is an essential component of all cells in the body. Protein provides the amino acids required for adequate growth, particularly lean tissue and maturation of multiple organ systems. Growth failure is commonly reported in very low birth weight infants and this is thought to be related to inadequate protein intake (Arslanoglu 2019; Kumar 2017). Related Cochrane Reviews have shown that, when compared with unsupplemented human milk, both protein (Amissah 2018) and multi‐nutrient fortifier (Brown 2016) resulted in short term weight gain (protein: mean difference (MD) 3.82 g/kg/day, 95% confidence interval (CI) 2.94 to 4.70; multi‐nutrient fortifier: 1.81 g/kg/day, 95% CI 1.23 to 2.40).

However, increasing protein intake has potential adverse effects. These include metabolic acidosis and high serum levels of protein metabolites, such as urea and ammonia (Goldman 1969; Senterre 1983), high levels of some amino acids (Avery 1967), and increased risk of sepsis (Moltu 2013). However, results from these earlier studies may be due to poor quality of protein (Hay 2010), and research has shown that adverse effect may be due to other nutritional components (e.g. minerals) (Rochow 2011). Amissah's Cochrane Review showed increased blood urea levels in the protein supplements groups (MD 0.95 mmol/L, 95% CI 0.81 to 1.00) (Amissah 2018). However, these remained within the normal range and may reflect adequate rather than excess protein intake. Nevertheless, there may be risks of feeding intolerance and necrotising enterocolitis associated with increased protein intake (Amissah 2018), therefore, the benefits of increased protein intake must be balanced with any potential adverse effects.

Why it is important to do this review

There remains considerable debate regarding the optimum protein concentration of fortifiers (Bertino 2017). When human milk fortifier was first introduced, the common practice was to add less than 1 g of protein per 100 mL of human milk for safety and tolerance concern. Since then, there has been some evidence of more favourable developmental outcomes with higher protein (with adequate energy intakes) (Coviello 2018; Stephens 2009). The concentration of protein added into human milk has gradually increased over time in many neonatal units, from around 1 g per 100 mL of human milk, to greater than 1.4 g per 100 mL of human milk. However, the upper limit of protein intake, where no further benefit is conferred or an adverse effect may occur (or both), has not been determined. There has been no systematic review assessing the effect of different levels of protein fortification of human milk on growth and safety in preterm infants. Although there is another review comparing human milk‐derived versus bovine milk‐derived human milk fortifier for mortality prevention and subsequent growth and neurodevelopment of preterm infants (Premkumar 2019), we will undertake subgroup analyses specifically comparing the effect of proteins derived from these different sources.

Objectives

To compare the effects of different protein concentrations in human milk fortifier, fed to preterm infants, on growth and neurodevelopment.

Methods

Criteria for considering studies for this review

Types of studies

All published and unpublished randomised trials, quasi‐randomised trials and cluster‐randomised trials comparing two levels of protein content of human milk fortifier.

Types of participants

Preterm infants (less than 37 weeks' gestation) who receive any human milk with added human milk fortifier. Infants may also be on parenteral nutrition when beginning fortification. Participants may be exclusively fed human milk or be supplemented with formula.

Types of interventions

The intervention must compare two or more different levels of protein concentration in human milk fortifier. We will classify the protein concentrations examined in each study as follows.

1. Low: less than 1 g protein/100 mL breast milk.

2. Moderate: 1 g to less than 1.4 g protein/100 mL breast milk.

3. High: 1.4 g protein/100 mL breast milk or greater.

Studies where the two levels of protein concentrations compared fall into the same category will not be included.

Types of outcome measures

Primary outcomes

1. Growth as assessed at birth (or as defined by author) to discharge from hospital, at 12 months or 18 months (or both) or beyond corrected age expressed in absolute terms or relative to intrauterine growth standard for the following:

   1. weight gain (g/kg/day or g/day);

   2. length gain (cm/week);

   3. head circumference gain (cm/week);

   4. measures of body composition (lean/fat mass);

   5. proportion of infants who are small for gestational age (less than 10th percentile of intrauterine growth standards or post‐term growth charts as defined by the author).

2. Neurodevelopmental outcomes

   1. Neurodevelopmental disability at 18 months' postnatal age or greater defined as a neurological abnormality including any one of the following:

      1. cerebral palsy on clinical examination;

      2. developmental delay more than two standard deviations below population mean on a standardised test of development;

      3. blindness (visual acuity less than 6/60);

      4. deafness (any hearing impairment requiring amplification) at any time after term corrected.

3. Mortality

Secondary outcomes

1. Safety measures, as reported by the authors, including:

   1. blood urea nitrogen (mmol/L);

   2. plasma amino acid levels (µmol/L);

   3. plasma pH levels;

   4. incidence of necrotising enterocolitis (Bell's Stage II or greater);

   5. sepsis (as confirmed by blood culture).

2. Tolerance as assessed by:

   1. episodes of interruption of feeds;

   2. days to reach full enteral feeds (enteral intake 150 mL/kg/day or greater) or as defined by author.

3. Length of hospital stay (days)

Search methods for identification of studies

We will use the criteria and standard methods of Cochrane and Cochrane Neonatal (see the Cochrane Neonatal search strategy for specialised register; neonatal.cochrane.org/resources‐review‐authors). We will search for errata or retractions for included studies published in full text on PubMed (www.ncbi.nlm.nih.gov/pubmed).

Electronic searches

We will conduct a comprehensive search including: Cochrane Central Register of Controlled Trials (CENTRAL; 2019, Issue 8) in the Cochrane Library; Ovid MEDLINE Epub Ahead of Print, In‐Process & Other Non‐Indexed Citations, Ovid MEDLINE(R) Daily and Ovid MEDLINE(R) (1946 to present); MEDLINE via PubMed (1 August 2018 to present) for the previous year; and CINAHL (1981 to present). We include the search strategies for each database in Appendix 1. We will apply no language restrictions.

We will search clinical trial registries for ongoing or recently completed trials, including the World Health Organization's International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp/search/en/) and the U.S. National Library of Medicine's ClinicalTrials.gov (clinicaltrials.gov) via Cochrane CENTRAL. Additionally, we will search the ISRCTN Registry for any unique trials not found through the Cochrane CENTRAL search (www.isrctn.com/).

Searching other resources

We will also search the reference lists of any articles selected for inclusion in this review in order to identify additional relevant articles.

Data collection and analysis

We will use standard methods of Cochrane Neonatal and Cochrane to collect study information (Higgins 2019).

Selection of studies

We will include all randomised, quasi‐randomised, and cluster‐randomised controlled trials fulfilling our inclusion criteria. At least two review authors will independently review the results of the search and select studies for inclusion. We will resolve any disagreements by discussion or when necessary with a third author.

We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table (Moher 2009).

Where studies have multiple publications, we will collate the reports of the same study so that each study, rather than each report, is the unit of interest for the review, and such studies have a single identifier with multiple references

Data extraction and management

At least two review authors will independently extract data using a data extraction form integrated with a modified version of the Cochrane Effective Practice and Organisation of Care Group data collection checklist (Cochrane EPOC 2017). We will pilot the form within the review team using a sample of included studies.

We will extract the following characteristics from each included study.

1. Administrative details: study author(s); published or unpublished; year of publication; year in which study was conducted; presence of vested interest; details of other relevant papers cited.

2. Study: study design; type, duration and completeness of follow‐up (e.g. greater than 80%); country and location of study; informed consent; ethics approval.

3. Participants: sex, birth weight, gestational age, number of participants.

4. Interventions: initiation, dose and duration of administration.

5. Outcomes as mentioned above under Types of outcome measures.

We will resolve disagreements by discussion. We will describe ongoing studies identified by our search, when available, detailing the primary author, research question(s), methods and outcome measures, together with an estimate of the reporting date and report them in the 'Characteristics of ongoing studies' table.

Should any queries arise, or in cases for which additional data are required, we will contact study investigators/authors for clarification. At least two review authors will use Cochrane statistical software for data entry (Review Manager 2014). We will replace any standard error of the mean by the corresponding standard deviation.

Assessment of risk of bias in included studies

At least two review authors will independently assess the risk of bias (low, high or unclear) of all included trials using the Cochrane 'Risk of bias' tool (Higgins 2019) for the following domains.

1. Sequence generation (selection bias).

2. Allocation concealment (selection bias).

3. Blinding of participants and personnel (performance bias).

4. Blinding of outcome assessment (detection bias).

5. Incomplete outcome data (attrition bias).

6. Selective reporting (reporting bias).

7. Any other bias.

We will resolve any disagreements by discussion or with a third review author. See Appendix 2 for a more detailed description of risk of bias for each domain. 

Measures of treatment effect

We will perform the statistical analyses using Review Manager 5 software (Review Manager 2014). We will analyse categorical data using risk ratio (RR) and risk difference (RD). For statistically significant outcomes, we will calculate the number needed to treat for an additional beneficial outcome (NNTB) or number needed to treat for an additional harmful outcome (NNTH). We will calculate mean differences (MDs) between treatment groups where outcomes are measured in the same way for continuous data. Where outcomes are measured differently, we will report data as standardised mean differences (SMD). We will report 95% confidence intervals (CIs) for all outcomes.

Dichotomous data

For dichotomous data, we will present results using RRs and RDs with 95% CIs. We will calculate the NNTB or NNTH with 95% CIs if there is a statistically significant reduction (or increase) in RD.

Continuous data

For continuous data, we will use the MD when outcomes were measured in the same way between trials. We will use the SMD to combine trials that measured the same outcome but used different methods. Where trials reported continuous data as median and interquartile range (IQR) and data passed the test of skewness, we will convert the mean to median and estimate the standard deviation as IQR/1.35.

Unit of analysis issues

The unit of analysis will be the participating infant in individually randomised trials, and an infant will be considered only once in the analysis. The participating neonatal unit or section of a neonatal unit or hospital will be the unit of analysis in cluster‐randomised trials. We will analyse them using an estimate of the intracluster correlation coefficient (ICC) derived from the trial (if possible), or from a similar trial or from a study with a similar population as described in Section 16.3.6 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2019). If we use ICCs from a similar trial or from a study with a similar population, we will report this and conduct a sensitivity analysis to investigate the effect of variation in the ICC.

If we identify both cluster‐randomised trials and individually randomised trials, we will only combine the results from both if there is little heterogeneity between the study designs, and the interaction between the effect of the intervention and the choice of randomisation unit is considered to be unlikely.

We will acknowledge any possible heterogeneity in the randomisation unit and perform a sensitivity analysis to investigate possible effects of the randomisation unit.

Dealing with missing data

Where data are missing, and cannot be derived as described, we will approach the analysis as follows.

1. We will contact the original study investigators to request the missing data.

2. Where possible, we will impute missing standard deviations using the coefficient of variation or calculate from other available statistics including standard errors, CIs, t values and P values.

3. If the data are assumed to be missing at random, we will analyse the data without imputing any missing values.

4. If this cannot be assumed then we will impute the missing outcomes with replacement values assuming all to have a poor outcome and conduct sensitivity analyses to assess any changes in the direction or magnitude of effect resulting from data imputation.

Assessment of heterogeneity

We will estimate the treatment effects of individual trials and examine heterogeneity among trials by inspecting the forest plots and quantifying the impact of heterogeneity using the I² statistic. We will grade the degree of heterogeneity as: less than 25%: no heterogeneity; 25% to 49%: low heterogeneity; 50% to 75%: moderate heterogeneity; more than 75%: substantial heterogeneity. If we note statistical heterogeneity (I² greater than 50%), we will explore the possible causes (e.g. differences in study quality, participants, intervention regimens or outcome assessments).

Assessment of reporting biases

We will assess reporting bias by comparing the stated primary outcomes and secondary outcomes and reported outcomes. Where study protocols are available, we will compare these to the full publications to determine the likelihood of reporting bias. We will document studies using the interventions in a potentially eligible infant population but not reporting on any of the primary and secondary outcomes in the 'Characteristics of included studies' tables. We will use funnel plots to screen for publication bias where there are sufficient number of studies (more than 10) reporting the same outcome. If publication bias is suggested by a significant asymmetry of the funnel plot on visual assessment, we will incorporate this in our assessment of certainty of the evidence.

Data synthesis

If we identify multiple studies that we consider to be sufficiently similar, we will perform meta‐analysis using Review Manager 5 (Review Manager 2014). For categorical outcomes, we will calculate the typical estimates of RR and RD, each with its 95% CI; for continuous outcomes, we will calculate the MD or the SMD, each with its 95% CI. We will use a fixed‐effect model to combine data where it is reasonable to assume that studies were estimating the same underlying treatment effect. If we judge meta‐analysis to be inappropriate, we will analyse and interpret individual trials separately. If there is evidence of clinical heterogeneity, we will try to explain this based on the different study characteristics and subgroup analyses.

Certainty of the evidence

We will use the GRADE approach using GRADEpro GDT (GRADEpro GDT), as outlined in the Handbook for Grading the Quality of Evidence and the Strength of Recommendations Using the GRADE Approach (Schünemann 2013), to assess the certainty of evidence of the primary outcomes.

At least two review authors will independently assess the certainty of the evidence for each of the primary outcomes above. We will consider evidence from randomised controlled trials as high certainty but downgrade the evidence one level for serious (or two levels for very serious) limitations based upon the following: design (risk of bias), consistency across studies, directness of the evidence, precision of estimates and presence of publication bias. We will use the GRADEpro GDT Guideline Development Tool to create 'Summary of findings' tables to report the certainty of the evidence for the primary outcomes.

The GRADE approach results in an assessment of the certainty of a body of evidence as one of four grades.

1. High certainty: further research is very unlikely to change our confidence in the estimate of effect.

2. Moderate certainty: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.

3. Low certainty: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.

4. Very low certainty: we are very uncertain about the estimate.

Subgroup analysis and investigation of heterogeneity

We will explore high statistical heterogeneity in the outcomes by visually inspecting the forest plots and by removing the outlying studies in the sensitivity analysis (Higgins 2019). Where statistical heterogeneity is significant, we will interpret the results of the meta‐analyses accordingly; and we will downgrade the quality of evidence in the 'Summary of findings' tables, according to the GRADE recommendations.

We will consider the following groups for subgroup analysis where data are available:

1. less mature infants (defined as less than 1250 g or less than 28 weeks' gestation);

2. source of protein (bovine, human, other animal);

3. use of hydrolysed protein;

4. the energy content of the two human milk fortifier compared (isocaloric or non‐isocaloric).

We will restrict these analyses to the primary outcomes.

Sensitivity analysis

Where we identify substantial heterogeneity, we will conduct sensitivity analysis to determine if the findings are affected by inclusion of only those trials considered to have used adequate methodology with a low risk of bias (selection and performance bias). We will report results of sensitivity analyses for primary outcomes only.

What's new

Date	Event	Description
8 November 2019	Amended	Protocol update

Appendices

Appendix 1. Cochrane Neonatal standard search strategy

We created the randomised controlled trial filters using Cochrane's highly sensitive search strategies for identifying randomised trials (Higgins 2019). The Cochrane Neonatal Information Specialist created and tested neonatal filters.

Cochrane CENTRAL via CRS Web

Date searched: 15 August 2019
 Terms:
 1 MESH DESCRIPTOR Milk, Human EXPLODE ALL AND CENTRAL:TARGET
 2 MESH DESCRIPTOR Milk Ejection EXPLODE ALL AND CENTRAL:TARGET
 3 MESH DESCRIPTOR Breast Milk Expression EXPLODE ALL AND CENTRAL:TARGET
 4 ((human or breast* or mother* or expressed or maternal or donor*) and milk*) AND CENTRAL:TARGET
 5 breastmilk* AND CENTRAL:TARGET
 6 #1 OR #2 OR #3 OR #4 OR #5
 7 MESH DESCRIPTOR Dietary Proteins EXPLODE ALL AND CENTRAL:TARGET
 8 protein* AND CENTRAL:TARGET
 9 #8 OR #7
 10 MESH DESCRIPTOR Infant, Newborn EXPLODE ALL AND CENTRAL:TARGET
 11 infant or infants or infantile or infancy or newborn* or "new born" or "new borns" or "newly born" or neonat* or baby* or babies or premature or prematures or prematurity or preterm or preterms or "pre term" or premies or "low birth weight" or "low birthweight" or VLBW or LBW or ELBW or NICU AND CENTRAL:TARGET
 12 #11 OR #10 AND CENTRAL:TARGET
 13 #6 AND #9 AND #12

Ovid MEDLINE

Epub Ahead of Print, In‐Process & Other Non‐Indexed Citations, Ovid MEDLINE(R) Daily and Ovid MEDLINE(R).
 Date ranges: 1946 to 15 August 2019
 Terms:
 1. exp Milk, Human/
 2. exp Milk Ejection/
 3. exp Breast Milk Expression/
 4. ((human or breast* or mother* or expressed or maternal or donor*) and milk*).mp.
 5. breastmilk*.mp.
 6. 1 or 2 or 3 or 4 or 5
 7. exp Dietary Proteins/
 8. protein*.mp.
 9. 7 or 8
 10. exp infant, newborn/
 11. (newborn* or new born or new borns or newly born or baby* or babies or premature or prematurity or preterm or pre term or low birth weight or low birthweight or VLBW or LBW or infant or infants or infantile or infancy or neonat*).ti,ab.
 12. 10 or 11
 13. randomized controlled trial.pt.
 14. controlled clinical trial.pt.
 15. randomized.ab.
 16. placebo.ab.
 17. drug therapy.fs.
 18. randomly.ab.
 19. trial.ab.
 20. groups.ab.
 21. or/13‐20
 22. exp animals/ not humans.sh.
 23. 21 not 22
 24. 12 and 23
 25. 6 and 9 and 24

MEDLINE via PubMed

Date ranges: 1 August 2018 to 15 August 2019
 Terms: ((("Milk, Human"[Mesh] OR "Milk Ejection"[Mesh] OR "Breast Milk Expression"[Mesh] OR ((human OR breast* OR mother* OR expressed OR maternal OR donor*) AND milk*) OR breastmilk*))) AND ("Dietary Proteins"[Mesh] OR protein*)) AND (((infant, newborn[MeSH] OR newborn*[TIAB] OR "new born"[TIAB] OR "new borns"[TIAB] OR "newly born"[TIAB] OR baby*[TIAB] OR babies[TIAB] OR premature[TIAB] OR prematurity[TIAB] OR preterm[TIAB] OR "pre term"[TIAB] OR “low birth weight”[TIAB] OR "low birthweight"[TIAB] OR VLBW[TIAB] OR LBW[TIAB] OR infant[TIAB] OR infants[TIAB] OR infantile[TIAB] OR infancy[TIAB] OR neonat*[TIAB]) AND (randomized controlled trial[pt] OR controlled clinical trial[pt] OR randomized[tiab] OR placebo[tiab] OR drug therapy[sh] OR randomly[tiab] OR trial[tiab] OR groups[tiab]) NOT (animals[mh] NOT humans[mh]))) Filters activated: Publication date from 2018/08/01

CINAHL via EBSCOhost

Date ranges: 1981 to 15 August 2019
 Terms:
 (((human OR breast* OR mother* OR expressed OR maternal OR donor*) AND milk*) OR breastmilk* OR “milk ejection”)
 AND
 protein*
 AND
 (infant or infants or infantile or infancy or newborn* or "new born" or "new borns" or "newly born" or neonat* or baby* or babies or premature or prematures or prematurity or preterm or preterms or "pre term" or premies or "low birth weight" or "low birthweight" or VLBW or LBW)
 AND
 (randomized controlled trial OR controlled clinical trial OR randomized OR placebo OR clinical trials as topic OR randomly OR trial OR PT clinical trial)

ISRCTN.com

Search terms: milk AND Interventions: Protein* AND Participant age range: Neonate

Appendix 2. Risk of bias

1. Sequence generation (checking for possible selection bias). Was the allocation sequence adequately generated?

For each included study, we categorised the method used to generate the allocation sequence as:

1. low risk (any truly random process, e.g. random number table; computer random number generator);

2. high risk (any non‐random process, e.g. odd or even date of birth; hospital or clinic record number); or

3. unclear risk.

2. Allocation concealment (checking for possible selection bias). Was allocation adequately concealed?

For each included study, we categorised the method used to conceal the allocation sequence as:

1. low risk (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);

2. high risk (open random allocation; unsealed or non‐opaque envelopes, alternation; date of birth); or

3. unclear risk.

3. Blinding of participants and personnel (checking for possible performance bias). Was knowledge of the allocated intervention adequately prevented during the study?

For each included study, we categorised the methods used to blind study participants and personnel from knowledge of which intervention a participant received. Blinding was assessed separately for different outcomes or class of outcomes. We categorised the methods as:

1. low risk, high risk or unclear risk for participants; and

2. low risk, high risk or unclear risk for personnel.

4. Blinding of outcome assessment (checking for possible detection bias). Was knowledge of the allocated intervention adequately prevented at the time of outcome assessment?

For each included study, we categorised the methods used to blind outcome assessment. Blinding was assessed separately for different outcomes or class of outcomes. We categorised the methods as:

1. low risk for outcome assessors;

2. high risk for outcome assessors; or

3. unclear risk for outcome assessors.

5. Incomplete outcome data (checking for possible attrition bias through withdrawals, dropouts, protocol deviations). Were incomplete outcome data adequately addressed?

For each included study and for each outcome, we described the completeness of data including attrition and exclusions from the analysis. We noted whether attrition and exclusions were reported, the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information was reported or supplied by the trial authors, we reincluded missing data in the analyses. We categorised the methods as:

1. low risk (less than 20% missing data);

2. high risk (20% missing data or greater); or

3. unclear risk.

6. Selective reporting bias. Were reports of the study free of suggestion of selective outcome reporting?

For each included study, we described how we investigated the possibility of selective outcome reporting bias and what we found. For studies in which study protocols were published in advance, we compared prespecified outcomes versus outcomes eventually reported in the published results. If the study protocol was not published in advance, we contacted study authors to gain access to the study protocol. We assessed the methods as:

1. low risk (where it was clear that all of the study's prespecified outcomes and all expected outcomes of interest to the review were reported);

2. high risk (where not all the study's prespecified outcomes were reported; one or more reported primary outcomes were not prespecified outcomes of interest and were reported incompletely and so could not be used; study failed to include results of a key outcome that would have been expected to have been reported); or

3. unclear risk.

7. Other sources of bias. Was the study apparently free of other problems that could have put it at a high risk of bias?

For each included study, we described any important concerns we had about other possible sources of bias (e.g. whether there was a potential source of bias related to the specific study design or whether the trial was stopped early due to some data‐dependent process). We assessed whether each study was free of other problems that could have put it at risk of bias as:

1. low risk;

2. high risk; or

3. unclear risk.

If needed, we explored the impact of the level of bias through sensitivity analyses.

Contributions of authors

The methods section of this review is based on a standard template used by Cochrane Neonatal.

All review authors conceptualised the protocol.

JM wrote the initial protocol; other authors edited and approved the final version of the protocol.

Sources of support

Internal sources

• Carmel Collins is supported by a NHMRC Translating Research into Practice Fellowship (APP1132596), Australia.

• South Australian Health and Medical Research Institute, Australia.

• Chang Gao is supported by a PhD Scholarship from the University of Adelaide, Australia.

• Nutrition for Mother and Child Centre of Research Excellence, Australia.

External sources

• Vermont Oxford Network, USA.

  Cochrane Neonatal Reviews are produced with support from Vermont Oxford Network, a worldwide collaboration of health professionals dedicated to providing evidence‐based care of the highest quality for newborn infants and their families.

• The Gerber Foundation, USA.

  Editorial support for this review, as part of a suite of preterm nutrition reviews, has been provided by a grant from The Gerber Foundation. The Gerber Foundation is a separately endowed, private, 501(c)(3) foundation not related to Gerber Products Company in any way.

Declarations of interest

Core editorial and administrative support for this protocol was provided by a grant from The Gerber Foundation. The Gerber Foundation is a separately endowed, private foundation, distinct from the Gerber Products Company. The grantor has no input on the content of the review or the editorial process.

CG: none.

JM and CC declared the following conflicts of interest: Nestle Nutrition donated half of the human milk fortifier, and Nutricia donated Polyjoule and Protifar, used in a randomised controlled trial of increased protein content human milk fortifier (Reid J, Makrides M, McPhee AJ, Stark MJ, Miller J, Collins CT. The effect of increasing the protein content of human milk fortifier to 1.8 g/100 ml on growth in preterm infants: a randomised controlled trial. Nutrients 2018;10:1‐12. doi.org/10.3390/nu10050634). Study product for a separate randomised controlled trial of increased protein content human milk fortifier was manufactured and donated by Nestle Product Technology Centre, Konolfingen, Switzerland (Miller J, Makrides M, Gibson RA, McPhee AJ, Stanford TE, Morris S, et al. Effect of increasing the protein content of human milk fortifier on growth in preterm infants born less than 31 weeks' gestation: a randomized controlled trial. American Journal of Clinical Nutrition 2012;95:648‐55). The sponsors had no role (in either study) in the design of the study, in the collection, analyses or interpretation of data, in writing of the manuscript, or the decision to publish the results.

CC is supported by a National Health and Medical Research Council (NHMRC) Translating Research into Practice Fellowship (APP1132596). The views expressed in this article are solely the responsibility of the authors and do not reflect the views of the NHMRC.

AR: none.

Edited (no change to conclusions)