Open Access

Probiotics for prevention of necrotizing enterocolitis in preterm infants: systematic review and meta-analysis

  • Arianna Aceti1Email author,
  • Davide Gori2,
  • Giovanni Barone3,
  • Maria Luisa Callegari4,
  • Antonio Di Mauro5,
  • Maria Pia Fantini2,
  • Flavia Indrio5,
  • Luca Maggio3,
  • Fabio Meneghin6,
  • Lorenzo Morelli4,
  • Gianvincenzo Zuccotti6,
  • Luigi Corvaglia1 and
  • on behalf of the Italian Society of Neonatology
Italian Journal of Pediatrics201541:89

https://doi.org/10.1186/s13052-015-0199-2

Received: 27 July 2015

Accepted: 8 November 2015

Published: 14 November 2015

Abstract

Necrotizing enterocolitis (NEC) affects predominantly preterm infants, who have specific risk factors leading to intestinal dysbiosis. Manipulations of gut microbiota through probiotics have the potential to prevent NEC.

The aim of this systematic review and meta-analysis was to evaluate the effect of probiotics for NEC prevention in preterm infants, with a focus on specific strains, microbiological strength of currently available studies, and high-risk populations.

PubMed and the Cochrane Library were searched for trials published within 4th February 2015. Randomized-controlled trials reporting on NEC and involving preterm infants who were given probiotics in the first month of life were included in the systematic review.

Twenty-six studies were suitable for inclusion in the meta-analysis.

Data about study design, population, intervention and outcome were extracted and summarized independently by two observers. Study quality and quality of evidence were also evaluated.

Fixed-effects models were used and random-effects models where significant heterogeneity was present. Subgroup analyses were performed to explore sources of heterogeneity among studies. Results were expresses as risk ratio (RR) with 95 % confidence interval (CI).

The main outcome was incidence of NEC stage ≥2 according to Bell’s criteria.

Probiotics prevented NEC in preterm infants (RR 0.47 [95 % CI 0.36–0.60], p < 0.00001). Strain-specific sub-meta-analyses showed a significant effect for Bifidobacteria (RR 0.24 [95 % CI 0.10–0.54], p = 0.0006) and for probiotic mixtures (RR 0.39 [95 % CI 0.27–0.56], p < 0.00001). Probiotics prevented NEC in very-low-birth-weight infants (RR 0.48 [95 % CI 0.37–0.62], p < 0.00001); there were insufficient data for extremely-low-birth-weight infants. The majority of studies presented severe or moderate microbiological flaws.

Probiotics had an overall preventive effect on NEC in preterm infants. However, there are still insufficient data on the specific probiotic strain to be used and on the effect of probiotics in high-risk populations such as extremely-low-birth-weight infants, before a widespread use of these products can be recommended.

Keywords

Probiotics Newborn Necrotizing enterocolitis Meta-analysis

Background

Necrotizing enterocolitis (NEC), which is one of the most devastating neonatal diseases, has become a priority for research [1]. Despite great advances in neonatal care, the morbidity, mortality and health-care costs directly related to the disease are substantial: during hospital stay, the economic burden of NEC in the United States has been estimated as high as several billions USD per year, which is approximately 20 % of the costs for Neonatal Intensive Care Units in the country; furthermore, this estimate is likely to be much higher when the costs of long-term care of survivors are taken into account [2].

NEC is a multifactorial disease: prematurity is a well-recognized risk factor, and approximately 90 % of the infants who develop NEC are born preterm [3]. This is probably due to specific comorbidities of prematurity, such as immunodeficiency, use of broad-spectrum antimicrobials, delayed enteral feeding and low availability of human milk.

Recently, research has focused on the role of gut microbiota and its manipulations, such as the use of probiotics, on disease and health status. Probiotics are live–microorganisms which, when ingested in adequate amounts, confer a health-benefit to the host through an interaction with gut microbiota [4]. The intestinal microbiota undergoes dynamic changes during childhood. Gut colonization in preterm infants occurs differently than in healthy term newborns [5], and preterm infants frequently have delayed and aberrant acquisition of the “normal” digestive flora. Recent studies performed in preterm foetuses and infants demonstrated that amniotic fluid and meconium are not sterile, suggesting an intrauterine origin of gut microbiota [6, 7]; after birth, the preterm infant’s immature intestine is exposed to an unique environment and to several iatrogenic manipulations, including the use of broad-spectrum antibiotics. The subsequent intestinal dysbiosis is recognized as a risk factor for NEC: actually, it has been shown that preterm infants with NEC have reduced bacterial gut diversity and different bacterial strains compared to healthy controls [8]. In this perspective, provision of probiotics to preterm infants has the potential to “normalize” the abnormal colonization pattern, thus preventing the occurrence of the disease [9].

The use of probiotics for the prevention of NEC in preterm infants has been extensively investigated in many randomized-controlled trials, whose results have been summarized in several systematic-reviews and meta-analyses [10, 11]. The authors of these meta-analyses, which show that probiotics reduce NEC and mortality in preterm infants, strongly encourage a change in practice, promoting a widespread use of probiotics in this population [11], and also claim that withholding probiotics from high-risk neonates would be almost unethical [10]. However, the position of the American Academy of Paediatrics is more cautious, highlighting the need for more studies to address unanswered questions on the amount and specificity of which probiotic or mixture of probiotics should be used [12]. In addition, a recent systematic review, which analyzed the level of evidence of randomized-controlled trials on probiotics in preterm infants, concluded that there is still insufficient evidence to recommend routine probiotics use, but also that present data are encouraging and justify further research on specific probiotic products [13].

Actually, the beneficial effects of probiotics appear to be strain-specific, and pooling data from studies using different strains can result in misleading conclusions [14]. Furthermore, currently available studies often lack specificity in reporting correct identification of probiotic strain [15], dosage regimen and duration, and gut colonization, which are all fundamental to assess the ability of a probiotic to confer a health benefit to the host [16].

The aim of this meta-analysis is thus to evaluate in detail the effect of probiotics for the prevention of NEC in preterm infants, with a focus on specific strains, on microbiological strength of currently available studies, and on high-risk populations.

Methods

Literature search

The study protocol was designed jointly by the members of the Task Force on Probiotics of the Italian Society of Neonatology.

A systematic review of published studies reporting the use of probiotics for the prevention of NEC in preterm infants was performed, following PRISMA guidelines [17].

Criteria for inclusion in the meta-analysis were the following: randomized and quasi-randomized controlled trials involving preterm infants (gestational age <37 weeks) and reporting on NEC (any stage, according to modified Bell staging criteria [18, 19]); enteral administration of any probiotic starting within one month of age, compared to placebo or no treatment. Being the search strategy focused specifically on NEC, data on different outcomes, such as sepsis or mortality, which were reported in the studies retrieved by the literature search, were not evaluated by meta-analysis.

A search was conducted in PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) for studies published before 4th February 2015, using the search string reported in Fig. 1. This string was built up combining all the terms related to NEC and probiotics, using PubMed MeSH terms and free-text words and their combinations through the most proper Boolean operators, in order to be as comprehensive as possible. Similar criteria were used for searching the Cochrane Library. The review was limited to studies written in English and involving human subjects.
Fig. 1

Flow chart showing the search strategy and search results. The relevant number of papers at each point is given

The search was conducted by AA and LC: relevant studies were identified from the abstract, and reference lists of papers retrieved were searched for additional studies. “Snowballing” technique was also used [20].

Data extraction and meta-analysis

Study details, including study population, characteristics of the intervention, use of placebo, and outcome, were assessed independently by AA and LC, and checked by DG. Study quality was evaluated independently using the risk of bias tool as proposed by the Cochrane collaboration (Chapter 8 of the Cochrane Handbook of Systematic Reviews) [21]. In addition, an assessment of the body of evidence using the GRADE working group approach was used in order to grade the quality of evidence. The evaluation was carried out following the Chapter 12 of the Cochrane Handbook [21] and classifying the evidence as high, moderate, low and very low (as suggested by the GRADE Working Group) [22].

The association between probiotic use and NEC was evaluated by meta-analyses, conducted by AA and DG, using the RevMan software (version 5.3.5; downloaded from the Cochrane website: http://tech.cochrane.org/revman/download). Risk ratio (RR) was calculated using the Mantel-Haenszel method, and reported with 95 % confidence interval (CI).

The following sub-meta-analyses were also performed, in order to evaluate the effect of probiotics:
  • in specific subgroups of patients (very-low-birth-weight [VLBW] infants);

  • in surgical NEC;

  • according to NEC incidence in different populations: the incidence of NEC stage ≥2 in the control population was used as a reference, because only a minority of studies reported NEC incidence in the general population. Studies were arbitrarily divided into three groups defined as “low-risk” (NEC incidence <5 %), “medium-risk” (incidence 5–10 %), and “high-risk” (incidence >10 %);

  • according to probiotic strain: studies were divided according to the specific probiotic strain used, and were considered as suitable for inclusion in the sub-meta-analyses when the same probiotic strain was used in at least two studies. Studies which used a probiotic mixture were considered together.

Microbiological quality of all the studies was evaluated by MLC and LM. Studies were defined as having severe, moderate or minor microbiological flaws according to the evaluation of proper strain identification and microbiological assessment. Specifically, the lack of proper strain identification was considered as a severe flaw; the lack of microbiological assessment regarding the probiotic persistence in stools was considered as a moderate flaw, whereas a low flaw was defined when the presence of the probiotic in stools was evaluated by indirect approaches such as the quantification of its species belonging.

A fixed-effect model was used for the analyses. Heterogeneity was measured using the I2 test. If significant heterogeneity was present (p < 0.05 from the χ 2 test), a random-effects model was used [23]. The random-effects model was also used when heterogeneity was not significant but the number of studies was ≤ 5, because the test for heterogeneity is known to have low power when the number of studies is small [24].

Forest plots were used to illustrate results from meta-analyses, and funnel plots to investigate bias.

The online version of GraphPad Quickcalcs software was used to calculate number needed to treat (NNT).

Results

Literature search

Three-hundred-sixty-eight papers were identified through the literature search (310 through PubMed and 58 through the Cochrane Library). Thirty-eight studies met the inclusion criteria: 22 were identified through the PubMed search [2548] and 16 through the Cochrane Library search [25, 26, 2832, 3437, 4043, 45]. Ten additional papers were identified from the reference lists of included studies [4958]. Of these 47 studies, 16 were excluded, as they were duplicates retrieved both by PubMed and Cochrane Library search. Six additional studies were excluded after examining the full-texts: one study reported maternal probiotic supplementation during pregnancy [29], one cohort was reported twice [31], one study included both term and preterm infants [36], two studies did not report NEC data [55, 56], and in one study randomization was not declared [54].

Twenty-six studies were suitable for inclusion in the meta-analysis [10, 2528, 30, 3235, 3742, 44, 46, 4853, 58]. A description of included studies is provided in Table 1; excluded studies are described in Table 2.
Table 1

Studies included in the systematic review and meta-analysis

Author, year

Study details

Study population

Intervention

Type of milk

Placebo

- Strain

- Dose (D)

- Start of treatment (S)

- End of treatment (E)

Al-Hosni, 2012 [33]

P

Preterm infants with BW 501–1000 g, appropriate for gestational age, and ≤ 14 days of age at time of feeding initiation

Lactobacillus rhamnosus GG LGG

Non specified

Extra milk

DB

Bifidobacterium infantis

R

D: 0.5 × 109 CFU each probiotic, OD

C

S: first enteral feeding

Multic.

E: discharge or until 34 w postmenstrual age

Bin-Nun, 2005 [40]

P

Preterm infants with BW < 1500 g, who began enteral feeding on a weekday

Bifidobacterium infantis

OMM, PFM

HM or FM

B

Streptococcus thermophilus

R

Bifidobacterium bifidus

C

D: 0.35 × 109 CFU each probiotic, OD

S: start of enteral feeding

E: 36 w postconceptual age

Braga, 2011 [35]

P

Inborn infants with BW 750–1499 g

Lactobacillus casei

HM

Extra HM

DB

Bifidobacterium breve

R

D: 3.5 × 107 CFU to 3.5 × 109 CFU OD

C

S: day 2

E: day 30, NEC diagnosis, discharge, death, whichever occurred first

Costalos, 2003 [49]

P

GA 28–32 w

Saccharomyces boulardii

PFM

MDX

R

No major GI problem

D: 1 × 109 CFU BD

C

Not receiving antibiotics

S: non-specified

Not receiving breast milk

Median duration of probiotic supplementation: 30 days

Dani, 2002 [42]

P

Infants with GA < 33 w or BW < 1500 g

Lactobacillus rhamnosus GG

OMM, DM or FM

MDX

DB

D: 6 × 109 CFU OD

R

S: first feed

C

E: discharge

Multic.

Demirel, 2013 [28]

P

Preterm infants with GA ≤ 32 w and BW ≤ 1500 g, who survived to feed enterally

Saccharomyces boulardii

HM, FM

None

B

D: 5 × 109 CFU OD

R

S: first feed

C

E: discharge

Dilli, 2015 [44]

P

Preterm infants with GA <32 weeks and BW <1500 g, born at or transferred to the NICU within the first week of life and fed enterally before inclusion

Bifidobacterium

HM, FM

MDX powder

DB

Lactis

R

D: 5 × 109 CFU

C

S: beyond d7 after birth

Multic.

E: death or discharge (max 8 weeks)

Fernández-Carrocera, 2013 [32]

P

Preterm infants with BW < 1500 g

Lactobacillus acidophilus 1 CFU/g

OMM, PFM

None

DB

Infants with NEC IA and IB were excluded

Lactobacillus rhamnosus 4.4 × 108 CFU/g

R

Lactobacillus casei 1 × 109 CFU/g

C

Lactobacillus plantarum 1.76 × 108 CFU/g

Bifidobacterium infantis 2.76 × 107 CFU/g

Streptococcus thermophilus 6.6 × 105 CFU/g

Total D: 1 g powder OD

S: start of enteral feeding

E: non-specified

Jacobs, 2013 [26]

P

Preterm infants with GA <32 w and BW < 1500 g

Bifidobacterium infantis BB-02 300 CFU × 106

HM, FM

MDX powder

DB

Streptococcus thermophilus Th-4 350 CFU × 106

R

Bifidobacterium lactis BB-12 350 CFU × 106

C

Total D: 1 × 109 CFU × 1.5 g maltodextrin powder OD

Multic.

S: enteral feed ≥ 1 ml every 4 h

E: discharge or term corrected age

Kitajima, 1997 [52]

P

Preterm infants with BW < 1500 g

Bifidobacterium breve YIT4010

OMM, FM after full enteral feeding had been reached

Distilled water

R

D: 0.5 × 109 CFU OD

C

S: within 24 h of life

Duration of probiotic supplementation: 28 days

Lin, 2005

P

Infants with BW < 1500 g, who started to feed enterally and survived beyond day 7

Lactobacillus acidophilus

OMM, DM

None

M

Bifidobacterium infantis

R

D: ≥ 106 CFU each probiotic (=125 mg/kg), BD

C

S: start of enteral feeding

E: discharge

Lin, 2008

P

Preterm infants with GA < 34 w and BW ≤ 1500 g, who survived to feed enterally

Lactobacillus acidophilus NCDO 1746

HM, FM

None

B

Bifidobacterium bifidum NCDO 1453

R

D: 1 × 109 CFU each probiotic (=125 mg/kg) BD

C

S: day 2 of age

Multic.

Duration: 6 weeks

Manzoni, 2006 [37]

P

Infants with BW < 1500 g, ≥ 3 days of life, who started enteral feeding with HM

Lactobacillus rhamnosus LGG

OMM, DM

None

DB

D: 6 × 109 CFU/day

R

S: day 3 of life

C

E: end of the 6th week or discharge

Mihatsch, 2010 [43]

P

Preterm infants with GA < 30 w and BW ≤ 1500 g

Bifidobacterium lactis BB12

HM, PFM

Indistinguishable powder

R

D: 2 × 109 CFU/kg 6 times a day

C

S: start of enteral feeding

E: non-specified

Mohan, 2006 [53]

P

Preterm infants (GA < 37 w)

Bifidobacterium lactis BB12

FM

Not stated

DB

D: 1.6 × 109 CFU on day 1 to 3, and 4.8 × 109 CFU from day 4 onwards

R

S: first day of life

C

Duration: 21 days

Oncel, 2013 [25]

P

Preterm infants with GA ≤ 32 w and BW ≤ 1500 g, who survived to feed enterally

Lactobacillus reuteri DSM 17938

HM, FM

Oil base

DB

D: 1 × 108 CFU OD

R

S: first feed

C

E: death or discharge

Patole, 2014 [45]

P

Preterm infants with GA < 33 w and BW < 1500 g

Bifidobacterium breve M16-V

HM, FM

Dextrin

DB

D: 3 × 109 CFU OD (1.5 × 109 CFU OD for newborns ≤ 27 w until they reached 50 ml/kg/day enteral feeds)

R

S: start of enteral feed

C

E: corrected age of 37 w

Rojas, 2012 [30]

P

Preterm infants with BW ≤ 2000 g, hemodynamically stable, ≤ 48 h of age (regardless start of enteral feeding)

Lactobacillus reuteri DSM 17938

HM, FM

Oil base

DB

D: 1 × 108 CFU OD

R

S: age ≤ 48 h

C

E: death or discharge

Multic.

Rougé, 2009 [50]

P

Preterm infants with GA < 32 w and BW < 1500 g, ≤ 2 w of age, without any disease other than those linked to prematurity, who started enteral feeding before inclusion

Bifidobacterium longum BB536

OMM, DM or PFM

MDX

DB

Lactobacillus rhamnosus GG BB536-LGG

R

Total D: 1 × 108 CFU/day

C

S: start of enteral feeding

Bic.

E: discharge

Roy, 2014 [58]

P

Preterm infants (GA < 37w) and BW < 2500 g, with stable enteral feeding within 72 h of birth

Lactobacillus acidophilus 1.25 × 109 CFU × 1 g

HM

Sterile water

DB

B. longum 0.125 × 109 CFU × 1 g

R

B. bifidum 0.125 × 109 CFU × 1 g

C

B. lactis 1 × 109 CFU × 1 g

D: half a 1 g sachet

S: from 72 h of life

E: after 6 w or at discharge

Saengtawesin, 2014 [48]

P

Preterm infants with GA ≤ 34 w and BW ≤ 1500 g

Lactobacillus acidophilus 1 × 109 CFU

HM, PFM

None

R

Bifidobacterium

C

bifidum 1 × 109 CFU

D: 125 mg/kg BD

S: start of feeding

E: 6 w of age or discharge.

Samanta, 2009

P

Preterm infants with GA < 32 w and BW < 1500 g, who started enteral feeding and survived beyond 48 h of age

Bifidobacterium infantis

HM

None

DB

Bifidobacterium bifidum

R

Bifidobacterium longum

C

Lactobacillus acidophilus

D: 2.5 × 109 CFU each probiotic, BD

S: start of enteral feeding

E: discharge

Sari, 2011 [34]

P

Preterm infants with GA < 32 w or BW < 1500 g, who survived to feed enterally

Lactobacillus sporogenes

HM, FM

None

B

D: 0.35 × 109 CFU OD

R

S: first feed

C

E: discharge

Serce, 2013 [27]

P

Preterm infants with GA ≤ 32 w and BW ≤ 1500 g, who survived to feed enterally

Saccharomyces boulardii

HM, FM

Distilled water

M

D: 0.5 × 109 CFU/kg BD

R

S: non-specified

C

E: non-specified

Stratiki, 2007 [39]

P

Preterm infants with GA 27–32 w, formula-fed, without major congenital anomalies

Bifidobacterium lactis

FM

None

B

D: 2 × 107 CFU/g of milk powder

R

S: start of enteral feeding

C

E: non-specified

Totsu, 2014 [46]

P

Infants with BW < 1500 g

Bifidobacterium bifidum

HM, FM

Dextrin

DB

 

D: 2.5 × 109 CFU, divided in two doses

CLR

 

S: within 48 h after birth

C

 

E: body weight 2000 g

Multic.

P prospective, DB double-blinded, R randomized, C controlled, Multic multicentric, B blinded, M masked, Bic bicentric, BW birth weight, GA gestational age, NEC necrotizing enterocolitis, HM human milk, CFU colony forming unit, OD once daily, BD twice daily, OMM own mother’s milk, PFM preterm formula, DM donor milk, FM formula, MDX maltodextrin

Table 2

Studies excluded from the systematic review and meta-analysis

Author, year

Study summary

Reason for exclusion

Awad, 2010

Living vs. killed Lactobacillus acidophilus vs. placebo given to neonates admitted to the study NICU

Term and preterm infants included

Benor, 2014

Lactobacillus acidophilus and Bifidobacteria lactis vs. placebo given to mothers of VLBW infants

Maternal probiotic supplementation

Li, 2004

Bifidobacterium breve given to LBW infants

Randomization not declared

Millar, 1993

Lactobacillus GG given to preterm infants with GA < 33 w

No NEC data

Reuman, 1986

Formula containing lactobacilli vs. placebo given to preterm infants

No NEC data

Sari, 2012

Lactobacillus sporogenes given to preterm infants with GA < 32 w or BW < 1500 g, who survived to feed enterally

Duplicate population (Sari, 2011 [34])

NICU neonatal intensive care unit, VLBW very low birth weight, LBW low birth weight, GA gestational age, NEC necrotizing enterocolitis, BW birth weight

All the studies reported NEC data in a form suitable for meta-analysis, except one [53], for which data included in a previous Cochrane review were used [59]. For each study, NEC rate in the probiotic and in the placebo/control group is reported in Table 3. For the purpose of the meta-analysis, data on NEC stage ≥2 were used.
Table 3

Incidence of necrotizing enterocolitis in infants treated with probiotics and in controls

Author, year

Previous NEC rate

Number of subjects

NEC in probiotic group

NEC in control group

Al-Hosni, 2012 [33]

Not stated

50 probiotic

3/50 any stage

4/51 any stage

51 control

1/50 stage 1

2/51 stage 1

0/50 stage 2

0/51 stage 2

2/50 stage 3

2/51 stage 3

Bin-Nun, 2005 [40]

15 %

72 probiotic

3/72 any stage

12/73 any stage

73 control

1/72 stage ≥2

10/73 stage ≥2

1/72 stage 2

7/73 stage 2

0/72 stage 3

3/73 stage 3

Braga, 2011 [35]

10 %

119 probiotic

0/119 stage ≥2

4/112 stage ≥2

112 placebo

Costalos, 2003 [49]

Not stated

51 probiotic

5/51 any stage

6/36 any stage

36 placebo

Dani, 2002 [42]

Not stated

295 probiotic

4/295 stage ≥2

8/290 stage ≥2

290 placebo

Demirel, 2013 [28]

32 %

135 probiotic

6/135 stage ≥2

7/136 stage ≥2

136 control

Dilli, 2015 [44]

Not stated

100 probiotic

2/100 stage ≥2

18/100 stage ≥2

100 placebo

Fernández-Carrocera, 2013 [32]

20 %

75 probiotic

6/75 stage ≥2

12/75 stage ≥2

75 placebo

Jacobs, 2013 [26]

Not stated

548 probiotic

11/548 stage ≥2

24/551 stage ≥2

551 placebo

Kitajima, 1997 [52]

Not stated

45 probiotic

0/45 any stage

0/46 any stage

46 placebo

Lin, 2005 [41]

Approx. 23 % (NEC or death)

180 probiotic

2/180 stage ≥2

10/187 stage ≥2

187 control

2/180 stage 2

4/187 stage 2

0/180 stage 3

6/187 stage 3

Lin, 2008 [37]

Approx.

217 placebo

4/217 any stage

14/217 any stage

217 control

2/217 stage 2

9/217 stage 2

2/217 stage 3

5/217 stage 3

Manzoni, 2006 [37]

Not stated

39 probiotic

1/39 any stage

3/41 any stage

41 control

1/39 stage 2

2/41 stage 2

0/39 stage 3

1/41 stage 3

Mihatsch, 2010 [43]

Not stated

84 probiotic

2/84 stage ≥2

4/82 stage ≥2

82 placebo

Mohan, 2006 [53]

Not stated

21 probiotic

2/37 stage ≥2

1/32 stage ≥2

17 placebo

Unpublished data, taken from Alfaleh 2011 [58]

Unpublished data, taken from Alfaleh 2011 [58]

Oncel, 2013 [25]

15 %

200 probiotic

8/200 stage ≥2

10/200 stage ≥2

200 placebo

Patole, 2014 [45]

Not stated

74 probiotic

0/74 stage ≥2

1/66 stage ≥2

66 placebo

Rojas, 2012 [30]

Not stated

372 probiotic

NEC stage ≥2

NEC stage ≥2

378 placebo

≤1500 g

≤1500 g

6/176 probiotic

10/184 placebo

>1500 g

>1500 g

3/196 probiotic

5/194 placebo

Rougé, 2009 [50]

Not stated

45 probiotic

2/45 any stage

1/49 any stage

49 placebo

Roy, 2014 [58]

Not stated

56 probiotic

2/56 any stage

2/56 any stage

56 placebo

Saengtawesin, 2014 [48]

Not stated

31 probiotic

1/31 stage ≥2

1/29 stage ≥2

29 placebo

Samanta, 2009

Not stated

91 probiotic

5/91 stage ≥2

15/95 stage ≥2

95 control

Sari, 2011 [34]

Approx. 32 % (death or NEC)

110 probiotic

6/110 stage ≥2

10/111 stage ≥2

111 control

4/110 stage 2

7/111 stage 2

2/110 stage 3

3/111 stage 3

Serce, 2013 [27]

17 %

104 probiotic

7/104 stage ≥2

7/104 stage ≥2

104 placebo

Stratiki, 2007 [39]

Not stated

41 probiotic

0/41 stage ≥2

3/34 stage ≥2

34 control

Totsu, 2014 [46]

Not stated

153 probiotic

0/153 stage ≥1

0/130 stage ≥1

130 control

NEC necrotizing enterocolitis

Probiotics and NEC stage ≥2

Data from 6605 infants (3324 in the probiotic group and 3281 in the control group) were analyzed. Fewer infants in the probiotic group developed NEC stage ≥2 compared to infants in the control group (88 [2.65 %] vs. 188 [5.73 %], respectively). The RR was significantly lower in infants treated with probiotics (0.47 [95 % CI 0.36–0.60], p < 0.00001; fixed-effect analysis). NNT was 33 (95 % CI 24.7–47.2), which means that 33 infants needed to be treated with probiotics in order to prevent one more case of NEC stage ≥2. Heterogeneity among trials was absent (I2 = 0 %, p = 0.63; Fig. 2a). The funnel plot did not show any clear asymmetry (Fig. 2b).
Fig. 2

Forest plot (2a) and funnel plot (2b) of the included studies. The forest plot shows the association between the use of probiotics and necrotizing enterocolitis in the overall population of preterm infants. The funnel plot does not show any clear visual asymmetry. M-H: Mantel-Haenszel method

VLBW infants

Twenty-two studies [2528, 30, 3235, 37, 38, 4042, 4446, 48, 5052] reported data from 5912 VLBW infants, 2959 in the probiotic and 2953 in the control group. NEC stage ≥2 occurred less frequently in the probiotic group than in controls (82 [2.77 %] infants vs. 174 [5.89 %], respectively), with a RR of 0.48 ([95 % CI 0.37–0.62], p < 0.00001; fixed-effect analysis; I2 = 0 %, p = 0.56). NNT was 33 (95 % CI 24.1–47.9).

Surgical NEC

Only 6 studies [33, 34, 37, 40, 41, 51] reported separate data for surgical NEC (NEC stage 3), which occurred in 6/668 (0.90 %) infants in the probiotic group and in 20/680 (2.94 %) infants in the control group. The RR for NEC stage 3 was significantly lower in the probiotic group (0.35 [95 % CI 0.16–0.81], p = 0.01; fixed-effect analysis; I2 = 0 %, p = 0.69). NNT was 49 (95 % CI 28.6–170.8).

NEC incidence

NEC incidence in controls was <5 % in 13 studies (Fig. 3a) [26, 30, 33, 35, 42, 43, 45, 46, 48, 50, 52, 53, 58], between 5 and 10 % in 8 studies (Fig. 3b) [25, 27, 28, 34, 37, 39, 41, 51], and >10 % in 5 studies (Fig. 3c) [32, 38, 40, 44, 49].
Fig. 3

Forest plot showing the association between the use of probiotics and necrotizing enterocolitis (NEC), according to NEC incidence: (3a). NEC incidence < 5 %; (3b). NEC incidence 5–10 %; (3c). NEC incidence >10 %. M-H: Mantel-Haenszel method

The RR for NEC stage ≥2 was significantly lower in the probiotic group compared to the control group in all the three populations (RR 0.52 [95 % CI 0.35–0.78], p = 0.001; RR 0.54 [95 % CI 0.36–0.80], p = 0.002; RR 0.33 [95 % CI 0.17–0.62], p = 0.0006, respectively). Heterogeneity was non-significant in all the three sub-analyses.

Probiotic strain

Lactobacillus GG was used in 2 studies [42, 51] and Lactobacillus reuteri in 2 other studies [25, 30]: the effect of these probiotics in reducing NEC was not significant, either for Lactobacillus GG and Lactobacillus reuteri (RR 0.50 [95 % CI 0.17–1.44], p = 0.20 [Fig. 4a], and RR 0.69 [95 % CI 0.38–1.26], p = 0.23 [Fig. 4b]). One study used Lactobacillus sporogenes [34].
Fig. 4

Forest plot showing the association between probiotics and necrotizing enterocolitis in the studies which used a single-strain product containing Lactobacilli ((4a). L. reuteri; (4b). L. GG; (4c). pooled analysis of all the studies using Lactobacilli). M-H: Mantel-Haenszel method

The results of all the studies including Lactobacilli were pooled, except for the study by Sari et al. [34]: Lactobacillus sporogenes is a species which has not an international recognition, shows characteristics of both genera Lactobacillus and Bacillus, and its strains should be better classified as Bacillus coagulans [60]. Thus, when the results of studies using Lactobacillus GG and reuteri were pooled, no significant reduction in the RR for NEC in the probiotic group was observed (0.62 [95 % CI 0.37–1.05], p = 0.07, Fig. 4c).

Four studies used Bifidobacterium lactis [39, 43, 44, 53], 2 studies Bifidobacterium breve [45, 52] and 1 study Bifidobacterium bifidum [46]. The use of Bifidobacterium lactis resulted in a significant reduction in the RR for NEC (0.23 [95 % CI 0.10–0.55], p = 0.0008, Fig. 5a). No effect of Bifidobacterium breve in reducing NEC was documented (RR 0.30 [95 % CI 0.01–7.19], p = 0.46, Fig. 5b); the only study reporting the use of Bifidobacterium bifidum did not report any case on NEC. When the results of studies using Bifidobacteria were pooled, a significant reduction in the RR for NEC in the probiotic group was observed (0.24 [95 % CI 0.10–0.54], p = 0.0006, Fig. 5c).
Fig. 5

Forest plot showing the association between probiotics and necrotizing enterocolitis in the studies which used a single-strain product containing Bifidobacteria ((5a). B. lactis; (4b). B. breve; (4c). pooled analysis of all the studies using Bifidobacteria). M-H: Mantel-Haenszel method

Saccharomyces boulardii was used in 3 studies [27, 28, 49]: no significant effect of this probiotic was documented (RR 0.81 [95 % CI 0.44–1.49], p = 0.50; random effects analysis).

The pooled analysis of the 11 studies [26, 32, 33, 35, 37, 38, 40, 41, 48, 50, 58] in which a probiotic mixture was used showed an overall and significant benefit of these products in reducing NEC (RR 0.39 [95 % CI 0.27–0.56], p < 0.00001, Fig. 6).
Fig. 6

Forest plot showing the association between probiotics and necrotizing enterocolitis in the studies which used a probiotic mix. M-H: Mantel-Haenszel method

Study quality

Evaluation of the quality of the studies included in the meta-analysis according to the risk of bias tool as proposed by the Cochrane Collaboration is showed in Table 4, which also shows the level of evidence evaluated following the recommendations of the GRADE Working Group.
Table 4

Evaluation of the quality of the studies included in the meta-analysis according to the risk of bias tool as proposed by the Cochrane collaboration and evaluation of the level of evidence according to the GRADE approach

Study

Random sequence generation

Allocation concealment

Blinding

Incomplete outcome data

Selective outome reporting

Other sources of bias

Levels of quality of evidence in the grade approach

Al-Hosni, 2012 [33]

UNCLEAR

UNCLEAR

LOW

UNCLEAR

UNCLEAR

UNCLEAR

LOW

Bin-Nun, 2005 [40]

UNCLEAR

UNCLEAR

HIGH

UNCLEAR

UNCLEAR

UNCLEAR

VERYLOW

Braga, 2011 [35]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Costalos, 2003 [49]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Dani, 2002 [42]

UNCLEAR

LOW

LOW

LOW

UNCLEAR

UNCLEAR

MODERATE

Demirel, 2013 [28]

LOW

LOW

LOW

UNCLEAR

UNCLEAR

UNCLEAR

MODERATE

Dilli, 2015 [44]

LOW

LOW

LOW

UNCLEAR

UNCLEAR

UNCLEAR

MODERATE

Fernández-Carrocera, 2013 [32]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Jacobs, 2013 [26]

LOW

UNCLEAR

LOW

UNCLEAR

UNCLEAR

UNCLEAR

LOW

Kitajima, 1997 [52]

LOW

UNCLEAR

LOW

UNCLEAR

UNCLEAR

LOW

MODERATE

Lin, 2005 [41]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Lin, 2008 [37]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Manzoni, 2006 [37]

LOW

LOW

LOW

UNCLEAR

UNCLEAR

LOW

MODERATE

Mihatsch, 2010 [43]

LOW

UNCLEAR

LOW

LOW

UNCLEAR

LOW

MODERATE

Mohan, 2006 [53]

UNCLEAR

LOW

LOW

UNCLEAR

UNCLEAR

UNCLEAR

LOW

Oncel, 2013 [25]

LOW

UNCLEAR

LOW

LOW

UNCLEAR

UNCLEAR

MODERATE

Patole, 2014 [45]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Rojas, 2012 [30]

LOW

LOW

LOW

LOW

UNCLEAR

LOW

HIGH

Rougé, 2009 [50]

LOW

UNCLEAR

UNCLEAR

UNCLEAR

UNCLEAR

HIGH

LOW

Roy, 2014 [58]

LOW

UNCLEAR

LOW

LOW

UNCLEAR

UNCLEAR

MODERATE

Saengtawesin, 2014 [48]

HIGH

HIGH

HIGH

UNCLEAR

UNCLEAR

UNCLEAR

LOW

Samanta, 2009

LOW

LOW

LOW

UNCLEAR

UNCLEAR

UNCLEAR

MODERATE

Sari, 2011 [34]

LOW

LOW

LOW

UNCLEAR

UNCLEAR

UNCLEAR

MODERATE

Serce, 2013 [27]

LOW

LOW

LOW

UNCLEAR

UNCLEAR

LOW

MODERATE

Stratiki, 2007 [39]

UNCLEAR

UNCLEAR

LOW

UNCLEAR

UNCLEAR

LOW

LOW

Totsu, 2014 [46]

LOW

LOW

LOW

LOW

UNCLEAR

UNCLEAR

MODERATE

Microbiological quality

Microbiological quality of included studies is described in Table 5. Eight studies were evaluated as having severe microbiological flaws [27, 32, 34, 35, 38, 40, 41, 49], meaning that they did not report a proper probiotic strain identification. Thirteen studies [25, 26, 28, 30, 33, 37, 4244, 46, 48, 51, 58] were evaluated as having moderate microbiological flaws, because none of them evaluated the probiotic persistence in stools. There were only five studies [39, 45, 50, 52, 53] with minor microbiological flaws.
Table 5

Evaluation of the included studies according to their microbiological quality

Author, year

Probiotic strain

Strain identification

Microbiological assessment

Microbiological flaw

Al-Hosni, 2012 [33]

Lactobacillus rhamnosus LGG

LGG identified at the strain level

No assessment

Moderate

Bifidobacterium infantis

B. infantis identified via the web site of the producer: Bifantis (Bifidobacterium infantis 35624)

Bin-Nun, 2005 [40]

Bifidobacterium infantis

Strains not identified at the strain level

No assessment

Severe

Streptococcus thermophilus

Bifidobacterium bifidus

Braga, 2011 [35]

Lactobacillus casei

Strains non identified clearly

No assessment

Severe

Bifidobacterium breve

Costalos, 2003 [49]

Saccharomyces boulardii

Strain not identified at the strain level

S. boulardii not characterized in stools.

Severe

Gut flora assessed by plate count

Dani, 2002 [42]

Lactobacillus rhamnosus GG

Strain identified

No assessment

Moderate

Demirel, 2013 [28]

Saccharomyces boulardii

Strain identified

No assessment

Moderate

Dilli, 2015 [44]

B. lactis

Strain non identified at the strain level but probably Bb12

No assessment

Moderate

Fernández-Carrocera, 2013 [32]

Lactobacillus acidophilus

Strains not identified at the strain level

No assessment

Severe

Lactobacillus rhamnosus

Lactobacillus casei

Lactobacillus plantarum

Bifidobacterium infantis

Streptococcus thermophilus

Jacobs, 2013 [26]

Bifidobacterium infantis

Strains identified at the strain level

No assessment

Moderate

Streptococcus thermophilus Bifidobacterium lactis

Kitajima, 1997 [52]

Bifidobacterium breve

Strain identified

Assessment by a strain-specific monoclonal antibody conjugated with colloidal gold particle

Minor

Lin, 2005 [41]

Lactobacillus acidophilus

Strains not identified at the strain level

No assessment

Severe

Bifidobacterium infantis

Lin, 2008 [37]

Lactobacillus acidophilus

Strain identified

No assessment

Moderate

Bifidobacterium bifidum

Manzoni, 2006 [51]

Lactobacillus rhamnosus LGG

Strain identified

No assessment

Moderate

Mihatsch, 2010 [43]

Bifidobacterium lactis

Strain identified

No assessment

Moderate

Mohan, 2006 [53]

Bifidobacterium lactis

Strain identified

Species-specific (not strain-specific) assessment

Minor

Oncel, 2013 [25]

Lactobacillus reuteri

Strain identified

No assessment

Moderate

Patole, 2014 [45]

Bifidobacterium breve

Strain identified

Microbiological assessment by PCR

Minor

Rojas, 2012 [30]

Lactobacillus reuteri

Strain identified

No assessment

Moderate

Rougé, 2009 [50]

Bifidobacterium longum

Strain identified

Microbiological assessment by PCR

Minor

Lactobacillus rhamnosus GG

Roy, 2014 [58]

Lactobacillus acidophilus, B. longum, B. bifidum, and B. lactis

Strains not identified at the strain level/identification of the commercial product

No assessment

Moderate

Saengtawesin, 2014 [48]

Lactobacillus acidophilus and Bifidobacterium bifidum

Strains not identified at the strain level/identification of the commercial product

No assessment

Moderate

Samanta, 2009

Bifidobacterium infantis

Strains not identified at the strain level

No assessment

Severe

Bifidobacterium bifidum

Bifidobacterium longum

Lactobacillus acidophilus

Sari, 2011 [34]

Lactobacillus sporogenes

Strains not identified at the strain level

No assessment

Severe

Serce, 2013 [27]

Saccharomyces boulardii

Strains not identified at the strain level

No assessment

Severe

Stratiki, 2007 [39]

Bifidobacterium lactis

Strain identified

Assessment by plate count, no strain-specific assessment

Minor

Totsu, 2014 [46]

Bifidobacterium bifidum

Strain identified

No assessment

Moderate

Discussion

The results of this systematic review and meta-analysis show an overall benefit of probiotic supplementation for the prevention of NEC in preterm infants. These results are strengthened by the absence of significant statistical heterogeneity among studies and by the low-risk of publication bias documented by the funnel plot.

However, despite the overall benefit, it is remarkable that the 26 studies included in the meta-analysis were extremely heterogeneous in terms of probiotic strain, dosage, duration of intervention, and target population. Furthermore, only few studies documented an effective colonization of the infants’ gut with the probiotic strain. Thus, the proposal made by the authors of the recent Cochrane review of a “change in practice” in the use of probiotics in preterm infants [11] might require further investigation.

Currently available literature does not provide any definite conclusion on which probiotic strain should be used, and which group of preterm infants would benefit most from a probiotic intervention. It is important to note that the effect of a live-microorganism used as a probiotic is strictly strain-specific [61]. In this paper we aimed to perform strain-specific sub-meta-analyses but our efforts were weakened by the fact that in very few studies the same probiotic strain was used. For this reason, we were unable to draw definite conclusions on which single-strain of probiotics would be more effective in reducing NEC. When studies using single strains were pooled according to the probiotic genus, no significant effect was documented for Lactobacilli and Saccharomyces. This is partially in contrast with the recent Cochrane review on probiotics and NEC [11], which showed a beneficial effect of Lactobacilli: this discrepancy appears to be due mainly to differences in the studies included in the two sub-meta-analyses. Actually, the present meta-analysis included the study by Oncel et al. [25], which was on-going when the Cochrane review was published, but excluded the study by Manzoni et al. [57], where probiotics were used in addition to lactoferrin, and the study by Sari et al. [34], which used a probiotic product which is not properly a Lactobacillus [60].

The analysis of studies using Bifidobacteria showed a significant effect of Bifidobacterium breve in reducing NEC. This is also in contrast with the results of the Cochrane review; however, the discrepancy is explained by the inclusion in the present meta-analysis of the recent study by Dilli et al. [44], which appears to drive the beneficial effect documented for Bifidobacteria. Similarly to the Cochrane review [11], the analysis of studies in which more than one strain was used documented a strong and significant effect of these products in the prevention of NEC. No definite conclusion can be drawn from these results, even if it could be suggested that further research should be focused on mixed rather than on single-strain products; a potential rationale for this approach could be that a mix of strains might be more effective in providing an ecological barrier than a single strain.

The evidence that probiotics are effective in reducing NEC in VLBW infants does not necessarily apply also to extremely LBW infants (ELBWs), who are the highest-risk population. Only three studies [26, 33, 58] reported the rate of NEC in ELBWs: in two of these studies [33, 58], the same number of ELBWs in the probiotic and control group developed NEC [33], while in the ProPrems trial NEC incidence was slightly lower in the probiotic group [26]. Given the relatively small number of ELBWs and the inconclusive results, no specific recommendation can be drawn from the analysis of these two studies. Similarly, no study reported separate data for intrauterine-growth-restricted (IUGR) infants, and thus no recommendation can be made either for this high-risk population.

In the analysis of trials evaluating a specific intervention, it is pivotal to understand whether the results of these trials are generalizable or applicable only in specific clinical settings. According to our data, the common belief that probiotics are more effective in populations with a high rate of NEC [62] can be called into question: actually, when studies were divided according to NEC incidence in the control population, NEC reduction was striking and significant also when NEC rate in controls was extremely low. NEC rate in controls can be considered as a proxy for the quality of neonatal care: in this perspective, it is interesting to note that, in contrast with previous data, probiotics appear to confer a preventive benefit also in high quality-of-care settings. NEC rate in control populations was used for the analysis, rather than the baseline NEC rate stated by the authors and used in several studies for sample size calculation: this approach was considered more appropriate, because baseline NEC rate was not provided in many studies and, when provided, there was often a discrepancy with NEC rate detected in controls.

The analysis of included studies according to their microbiological quality points out that clinical studies aiming at evaluate the preventive effect of probiotics on NEC often lack an adequate microbiological assessment and this represents a major limitation of these studies. Actually, it is well known that the correct identification of a probiotic at species level corresponds to evaluate its safety, whereas the identification at strain level is extremely relevant as probiotic beneficial properties are strain-specific. Furthermore, the evaluation of probiotic colonisation, even if temporary, is important to correlate the probiotic presence to the beneficial effects.

The development of gut microbiota in preterm infants is known to be influenced by several factors, including gestational age, mode of delivery, diet, and antibiotic exposure [63]. All these factors are likely to be significant confounders in the relationship between probiotics and NEC: actually, it is well documented that infants fed maternal or donor breast milk have a lower risk of NEC compared to formula-fed infants [64], and that caesarean delivery is associated with a disruption in gut microbiota [65]. Quite surprisingly, however, in published studies data are not analyzed taking these confounders into account [66]. Given the definite protective role of human milk feeding and the symbiotic properties of human milk, it would be fundamental to understand whether the use of probiotics should be encouraged also in human-milk fed infants, or if this intervention should be directed towards exclusively formula-fed infants.

The studies included in the meta-analysis did not report any short-term adverse effect of probiotic supplementation (i.e., bloodstream infection with the probiotic strain). Growing evidence suggests the influence of gut microbiota on long-term health and disease, including both type 1 and type 2 diabetes mellitus, atherosclerosis, asthma, colon cancer, and inflammatory bowel disease [67]. However, at present little is known on the long-term outcome possibly related to the alteration of gut flora in preterm infants, which is the result of the supplementation with exogenous strains.

The choice to investigate a single outcome might be viewed as a limitation of the study: however, this choice was deliberate, as the literature search strategy was focused exclusively on NEC. Any speculation on different outcomes such as sepsis or mortality would have been inevitably misleading, because it would have been impossible to be sure to have identified all the studies reporting on those outcomes.

Conclusions

Meta-analyses give a valuable contribution in guiding researchers to focus future clinical studies on specific unanswered questions. The results of the present meta-analysis confirm that research on probiotics and NEC is on the right track, but also suggest that there are several unanswered questions which should be addressed before radically changing clinical practice. Our data highlight the need for further, well-designed studies aimed at clarifying the specific effect of probiotics in high-risk populations (i.e., ELBWs, IUGRs) and at addressing the choice of the most effective probiotic product, at the proper dose and duration of supplementation. For this reason, we encourage, for future studies, the publication of study protocols detailing study population and characteristics of the intervention, in order to narrow probiotic research to the most promising strains or combination of strains and to the most vulnerable populations, thus allowing a confirmative individual patient data analysis.

Declarations

Funding

No funding was received from any of the authors for this paper.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Neonatal Intensive Care Unit, Department of Medical and Surgical Sciences (DIMEC), University of Bologna, S.Orsola-Malpighi Hospital
(2)
Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna
(3)
Neonatal Unit, Catholic University
(4)
Institute of Microbiology, UCSC
(5)
Department of Pediatrics, Aldo Moro University
(6)
Department of Pediatrics, University of Milan, Luigi Sacco Hospital

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