| Literature DB >> 33922897 |
Louise Pitsillides1, Gianluca Pellino2,3, Paris Tekkis1,4,5, Christos Kontovounisios1,4,5.
Abstract
The perioperative care of colorectal cancer (CRC) patients includes antibiotics. Although antibiotics do provide a certain protection against infections, they do not eliminate them completely, and they do carry risks of microbial resistance and disruption of the microbiome. Probiotics can maintain the microbiome's balance postoperatively by maintaining intestinal mucosal integrity and reducing bacterial translocation (BT). This review aims to assess the role of probiotics in the perioperative management of CRC patients. The outcomes were categorised into: postoperative infectious and non-infectious complications, BT rate analysis, and intestinal permeability assessment. Fifteen randomised controlled trials (RCTs) were included. There was a trend towards lower rates of postoperative infectious and non-infectious complications with probiotics versus placebo. Probiotics reduced BT, maintained intestinal mucosal permeability, and provided a better balance of beneficial to pathogenic microorganisms. Heterogeneity among RCTs was high. Factors that influence the effect of probiotics include the species used, using a combination vs. single species, the duration of administration, and the location of the bowel resection. Although this review provided evidence for how probiotics possibly operate and reported notable evidence that probiotics can lower rates of infections, heterogeneity was observed. In order to corroborate the findings, future RCTs should keep the aforementioned factors constant.Entities:
Keywords: colonic resection; colorectal cancer; colorectal surgery; perioperative care; probiotics
Mesh:
Year: 2021 PMID: 33922897 PMCID: PMC8146873 DOI: 10.3390/nu13051451
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Keywords and MeSH terms used to search Embase, Medline, and Cochrane through the dates 2–10 February 2020.
| Key Words | MESH Terms |
|---|---|
| Probiotic(s), | Probiotics, |
Figure 1Flowchart of the search strategy.
Postoperative infectious complications incidence.
|
|
|
|
|
|
| Aisu (2015) [ | 156 (75 + 81) | 6.7 | 19.7 | 0.016 * |
| Kotzampassi (2015) [ | 164 (84 + 80) | 6.0 | 16.0 | 0.040 * |
| Bajramagic (2019) [ | 78 (39 + 39) | 28.2 | 35.9 | 0.682 |
| Kakaei (2019) [ | 99 (50 + 49) | 6.0 | 10.0 | 0.460 |
| Tan (2016) [ | 40 (20 + 20) | 5.0 | 10.0 | 0.548 |
| Liu (2011) [ | 100 (50 + 50) | 7.0 | 11.0 | >0.05 |
| Zhang (2012) [ | 60 (30 + 30) | 3.3 | 13.3 | 0.353 |
| Mangell (2012) [ | 72 (36 + 36) | 3.0 | 3.0 | N/A |
| Sadahiro (2014) [ | 310 (100 + 95) (third group taking antibiotics: 99) | 18.9 | 17.9 | 1.00 |
|
|
|
|
|
|
| Aisu (2015) [ | 156 (75 + 81) | 2.7 | 4.9 | 0.016 * |
| Sadahiro (2014) [ | 310 (100 + 95) (third group taking antibiotics: 99) | 4 | 5.3 | 0.93 |
|
|
|
|
|
|
| Bajramagic (2019) [ | 78 (39 + 39) | 12.8 | 17.9 | 0.530 |
| Consoli (2016) [ | 33 (15 + 18) | 0 | 4.0 | >0.10 |
| Mangell (2012) [ | 72 (36 + 36) | 0 | 3.0 | N/A |
| Zhang (2012) [ | 60 (30 + 30) | 6.7 | 3.3 | 1.00 |
|
|
|
|
|
|
| Kotzampassi (2015) [ | 164 (84 + 80) | 1.2 | 8.8 | 0.031 * |
| Sadahiro (2014) [ | 310 (100 + 95) (third group taking antibiotics, 99) | 7.4 | 12.0 | 0.560 |
| Yang (2016) [ | 60 (30 + 30) | 3.3 | 6.7 | 1.00 |
| Mizuta (2016) [ | 60 (31 + 29) | 9.7 | 17.2 | >0.05 |
| Tan (2016) [ | 40 (20 + 20) | 5.0 | 10.0 | 0.548 |
| Zhang (2012) [ | 60 (30 + 30) | 0 | 3.3 | 0.492 |
| Mangell (2012) [ | 72 (36 + 36) | 0 | 3.0 | N/A |
|
|
|
|
|
|
| Liu (2011) [ | 100 (50 + 50) | 6.0 ±1.9 | 7.2 ± 2.1 | <0.05 * |
| Liu (2013) [ | 138 (70 + 68) | 5.82 ± 1.98 | 6.68 ± 2.29 | 0.015 * |
| Yang (2016) [ | 60 (30 + 30) | 1.80 ± 2.34 | 4.77 ± 1.79 | 0.951 |
* = p-value is less than <0.05.
Incidence of postoperative non-infectious complications and outcomes.
|
|
|
|
|
| |
| Bajramagic (2019) [ | 78 (39 + 39) | 2.6 | 23.1 | 0.007 * | |
|
|
|
|
|
| |
| Aisu (2015) [ | 156 (75 + 81) | 2.0 ± 1.1 | 2.8 ± 2 | 0.001 * | |
| Yang (2016) [ | 60 (30 + 30) | 3.27 ± 0.58 | 3.63 ± 0.67 | 0.0274 * | |
| Mangell (2012) [ | 72 (36 + 36) | Median day to first flatus | Median day to first flatus | N/A | |
| 2 | 3 | ||||
|
|
|
|
|
| |
| Kotzampassi (2015) [ | 164 (84 + 80) | Lower a | Higher a | 0.001 * | |
| Yang (2016) [ | 60 (30 + 30) | 3.87 ± 1.17 | 4.53 ± 1.11 | 0.0268 * | |
| Mangell (2012) [ | 72 (36 + 36) | Median day to first stool | Median day to first stool | N/A | |
| 4 | 4 | ||||
|
|
|
|
|
| |
| Liu (2011) [ | 100 (50 + 50) | 21.0 | 36.0 | <0.05 * | |
| Yang (2016) [ | 60 (30 + 30) | 30.0 | 43.3 | <0.05 * | |
|
|
|
|
|
| |
| Liu (2011) [ | 60 (30 + 30) | 26.0 | 39.0 | <0.05 * | |
|
|
|
|
|
| |
| Liu (2011) [ | 100 (50 + 50) | 17.0 | 34.0 | <0.05 * | |
| Liu (2013) [ | 128 (70 + 68) | 14.7 | 29.3 | 0.03 * | |
| Yang (2016) [ | 60 (30 + 30) | 26.7 | 53.3 | 0.0352 * | |
|
|
|
|
|
| |
| Kotzampassi (2015) [ | 164 (75 + 81) | Median length of stay | Median length of stay | <0.0001 * | |
| 8 | 10 | ||||
| Consoli (2016) [ | 33 (15 + 18) | 10 | 11 | >0.10 | |
| Kakaei (2019) [ | 99 (50 + 49) | 5.96 ± 2.53 | 6.10 ± 2.44 | 0.30 | |
| Liu (2011) [ | 100 (50 + 50) | 12.3 ± 2.3 | 12.6 ± 3.3 | >0.05 | |
| Mizuta (2016) [ | 60 (31 + 29) | 21.4 ± 10.1 | 23.0 ± 13.8 | >0.05 | |
| Pellino (2013) [ | 18 (10 + 8) | 12.0 ± 8.3 | 13.5 ± 4.8 | >0.05 | |
| Stephens (2012) [ | 38 (20 + 18) | 5.60 ± 2.93 | 6.45 ± 7.50 | 0.564 | |
| Zhang (2012) [ | 60 (30 + 30) | 12.0 ± 3.0 | 14.0 ± 3.0 | 0.109 | |
| Yang (2016) [ | 60 (30 + 30) | 15.86 ± 4.92 | 15.0 ± 4.31 | 0.487 | |
a = Kotzampassi et al. [19] provided no raw values for mean day to first stool, but the cumulative logarithmic graph illustrated a lower value for the probiotics group overall than the placebo, and this was statistically significant (p = 0.001). * = p-value is less than <0.05.
Figure 2Bar chart exhibiting the number of times each probiotic species was used in the RCTs included in this study.
Probiotic composition and the number of probiotic strains used in each RCT included in this study.
| Study | Probiotic Strains | No. of Strains | Duration of Administration |
|---|---|---|---|
| Bajramagic | 8 | +3 to +30 | |
| Pellino | 8 | +0 to +28 | |
| Stephens | 8 | +0 to +28 | |
| Tan | 6 | −7 to +0 | |
| Kakaei | 5 | −7 to +23 | |
| Yang | 5 | −5 to +7 | |
| Kotzampassi | 4 | −1 to +14 | |
| Aisu | 3 | −15/−3 a | |
| Liu 2011 | 3 | −6 to +10 | |
| Liu 2013 | 3 | −6 to +10 | |
| Zhang | 3 | −5 to +3 | |
| Sadahiro |
| 1 | −8 to −2 and +5 to +15 |
| Consoli |
| 1 | −7 to +0 b |
| Mangell |
| 1 | −8 to +0 and +1 to +6 |
| Mizuta |
| 1 | −14/−7 to +14 |
a = restarted when the patient started drinking water (duration not stated), b = post-operative duration not stated.