Pain is very common and its management with a huge burden for patients and the healthcare system,[1,2] and opioids are always prescribed to patients suffered from pain in clinical practice.[2,3] Recently, opioid-induced adverse effects, especially, constipation, have led to great concern for their using because of inadequately counsel. Therefore, studies related opioid-induced constipation are increasingly, correspondingly, many pharmacological and non-pharmacological interventions including naloxone, alvimopan, methylnaltrexone, subcutaneous, and herb medicine, acupuncture and massage, single or combination used to treat opioid-induced constipation. Although some studies[5–7] have discussed the question, their relative efficacy and safety are always no unclear. For example, Luthra et al found naloxone and naldemedine are the most effective treatments, naloxone was the safest agent, but they did not include traditional Chinese medicine and studies written with Chinese.
However, comprehensive and detailed search for all the available eligible studies is the cornerstone of the systematic review, and the issue has been discussed a long time, the only 1 effective method may be cooperating with non-native speaking groups to overcome language obstacle.[8,9]
Therefore, we designed a network meta-analysis to compare all pharmacological and non-pharmacological treatments for opioid-induced constipation and fill the gap. And we hope the results of the study will provide a reference for clinicians and improve patient's quality of life.
2.1 Eligibility criteria
2.1.1 Type of study
Randomized controlled trials that investigated the effect of pharmacological or non-pharmacological treatments for the treatment of opioid-induced constipation will be included in the network meta-analysis.
2.1.2 Type of patients
Adults (aged 18 years or older) with opioid-induced constipation, they were diagnosed based on the history of constipation associated with opioid analgesic use. There are no limitations in age, gender, race, or nationality.
2.1.3 Type of interventions
One or combination of pharmacological (eg, methylnaltrexone, oxycodone, and Chinese herb medicine, etc, including placebo) or non-pharmacological (eg, acupuncture, massage, and enemata, etc) treatments to compare others therapies. There are no limitations in form, dose, and duration, and so on.
2.1.4 Type of outcomes
The primary outcome is efficacy, including the disappearance or significant improvement in opioid-induced constipation. The secondary outcome is an overall adverse event, including diarrhea, nausea and abdominal pain, and so on. Randomized controlled trials reporting on at least one above situation will be included. And efficacy or adverse effect must be assessed with binary data.
2.2 Data source
We will search 7 electronic databases from their inceptions to November 2018, including PubMed, EMBASE, Cochrane library, CNKI, VIP, Wan Fang, and CBM. The search strategy of PubMed was as follows:
- #1 “Constipation”[Mesh] OR “Gastrointestinal Transit”[Mesh] OR constipation [Title/Abstract] OR “gastrointestinal transit”[Title/Abstract] OR “slow transit”[Title/Abstract]
- #2 “Opiate Alkaloids”[Mesh] OR “Analgesics”[Mesh] OR “Analgesics, Opioid”[Mesh] OR opiate [Title/Abstract] OR opiates [Title/Abstract] OR analgesics [Title/Abstract] OR opioid [Title/Abstract] OR opioids [Title/Abstract]
- #3 “Randomized Controlled Trial” [Publication Type] OR “Controlled Clinical Trial” [Publication Type] OR random*[Title/Abstract]
- #4 #1 AND #2 AND #3
2.3 Study selection
All records will be loaded from electronic databases and inputted into EndNote X9 software to remove duplicate and check their eligibility. The screening process including 2 stages, first, 2 authors will independently check the title and abstract of all citations according to our eligibility criteria, second, potentially relevant studies also will be loaded for further assessment to ensure all available studies are included. And any discrepancy will ask the third reviewer to make the final decision. The Microsoft Excel 2016 will be used to design a data-abstract form, 5 eligibility studies will be used to test its property, then will revise it and collect relevant information. The abstracted information, including first author, publication year, sample size, intervention details, and relevant outcomes.
2.4 Risk of bias of individual studies
Two authors will independently evaluate the risk of bias for all included studies using the risk of bias's tool, including 6 domains: random sequence generation, allocation concealment, blind, incomplete outcome data, selective reporting, and other bias. And any discrepancy will through discussion or asking the third author to reach the agreement.
2.5 Statistical analysis
2.5.1 Pairwise meta-analyses
The pairwise meta-analyses will be performed using STATA 13.0 software. The relative risk (RR) with 95% confidence interval (95% CI) will be used to measure outcomes. And random effects model will be used to pool effect estimate. The potential heterogeneity across all eligibility studies will be tested using I2. If the P value < .1 and I2 > 50%, we will explore sources of heterogeneity by subgroup analysis. Publication bias will be tested using Egger test through STATA 13.0 software when at least included 10 studies for 1 outcome.
2.5.2 Network meta-analyses
The STATA 13.0 software and WinBUGS 1.4.3 software will be used to perform a Bayesian network meta-analysis. The outcomes will be reported as RR with 95% CI. The node splitting method will be used to test inconsistency between direct and indirect comparisons. Surface under the cumulative ranking area  will be used to rank the different therapeutic regimen. Network geometry will use nodes torepresent different treatments and edges to represent the head-to-head treatments. And the size of node represents sample sizes of treatments, thickness of edge represents numbers of included studies.
2.6 Quality of evidence
The quality of evidence of outcomes will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation,[16,17] and it including 5 degrade factors for randomized controlled trials, including risk of bias, inaccuracy, inconsistency, indirectness, publication bias, and results of assessment will be graded 4 levels: high level, moderate, low, and very low.
To the best of our knowledge, this is the first network meta-analysis to assess pharmacological and non-pharmacological treatments for opioid-induced constipation. Although there are similar studies have discussed the question, they did not include Traditional Chinese medicine, also did not include papers written with Chinese. Therefore, the results of this study will fill the gap for the field and will provide the reference for clinical practice. Eventually, we will report the network meta-analysis according to the PRISMA extension statement for network meta-analyses.
Conceptualization: Lanfang Mao, Longde Wang.
Data curation: Jing Zhang, Xiaojuan Du, Qiankun Liang, Hongli Wu.
Funding acquisition: Longde Wang.
Methodology: Jing Zhang, Lanfang Mao, Cuncun Lu.
Resources: Longde Wang.
Software: Cuncun Lu, Xiaojuan Du, Qiankun Liang.
Supervision: Bo Yang, Hongli Wu.
Validation: Cuncun Lu, Bo Yang, Hongli Wu.
Visualization: Qiankun Liang.
Writing – original draft: Jing Zhang.
Writing – review and editing: Jing Zhang, Lanfang Mao.
. Naldemedine (Symproic) for opioid-induced constipation
. Med Lett Drugs Ther 2017;59:196–8.
. Crockett SD, Greer KB, Heidelbaugh JJ, et al. American gastroenterological association institute guideline on the medical management of opioid-induced constipation
. Gastroenterology 2019;156:218–26.
. Pannemans J, Vanuytsel T, Tack J. New developments in the treatment of opioid-induced gastrointestinal symptoms. United European Gastroenterol J 2018;6:1126–35.
. Andresen V, Banerji V, Hall G, et al. The patient burden of opioid-induced constipation
: new insights from a large, multinational survey in five European countries. United European Gastroenterol J 2018;6:1254–66.
. Nusrat S, Syed T, Saleem R, et al. Pharmacological treatment
of opioid-induced constipation
is effective but choice of endpoints affects the therapeutic gain. Dig Dis Sci 2019;64:39–49.
. Luthra P, Burr NE, Brenner DM, et al. Efficacy of pharmacological therapies for the treatment of opioid-induced constipation
: systematic review
and network meta-analysis
. Gut 2018;May 5. pii: gutjnl-2018-316001. doi: 10.1136/gutjnl-2018-316001.
. Qi S, Lai H, Zhang Y, et al. Chinese herbal medicine for opioid induced constipation in cancer patients: protocol for a systematic review
. Medicine 2018;97:e12594.
. Murad MH, Montori VM, Ioannidis JPA, et al. How to read a systematic review
and meta-analysis and apply the results to patient care. JAMA 2014;312:171–9.
. Cohen JF, Korevaar DA, Wang J, et al. Should we search Chinese biomedical databases when performing systematic reviews? Syst Rev 2015;4:23.
. Higgins JPT, Altman DG, Gotzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ 2011;343:d5928–15928.
. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629–34.
. Harbord RM, Harris RJ, Sterne JAC. Updated tests for small-study effects in meta-analyses. Stata J 2009;9:197–210.
. Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 2004;23:3105–24.
. Salanti G, Ades AE, Ioannidis JP. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol 2011;64:163–71.
. Long G, Jin-Hui T, Lun L, et al. Mesh fixation methods in open inguinal hernia repair: a protocol for network meta-analysis
and trial sequential analysis of randomised controlled trials. BMJ Open 2015;5:e009369.
. Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 2008;336:924–6.
. Brignardello-Petersen R, Bonner A, Alexander PE, et al. Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis
. J Clin Epidemiol 2018;93:36–44.
. Hutton B, Salanti G, Caldwell DM, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med 2015;162:777–84.