Evidence map›Paper›PMID 30822331›Full record

SynthesisPloS one2019

Detoxification therapy of traditional Chinese medicine for genital tract high-risk human papillomavirus infection: A systematic review and meta-analysis.

Mei Luo, JiaJie Yu, ShuYi Zhu, Li Huang, Yu Chen, ShaoBin Wei

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Functions of Traditional Chinese Medicine Combined with Recombinant Human InterferonEvidence-based complementary and alternative medicine : eCAM · 2021
    Article
  8. Zhidai Decoction Inhibits Cervical Cancer through Regulation of Vaginal Microbiota.Evidence-based complementary and alternative medicine : eCAM · 2020
    Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Mei LuoChengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, P.R. China.
JiaJie YuChinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, P.R. China.
ShuYi ZhuChengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, P.R. China.
Li HuangChengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, P.R. China.
Yu ChenChengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, P.R. China.
ShaoBin WeiHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, P.R. China.ORCID 0000-0002-8326-7397
Chengdu University of Traditional Chinese Medicine · CNFirst People's Hospital of Chongqing · CNSichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPersistence of high-risk human papillomavirus (hr-HPV) infections is the most critical risk factor for cervical intraepithelial neoplasia (CIN) and cervical cancer (CC). Treatment of persistent oncogenic HPV-positive women after 12-24 months follow-up is still controversy. Detoxification therapy of Chinese medicine (DTCM) has been conducted recently. However, the conclusions are still unclear. We planned to conduct a systematic review and meta-analysis to explore DTCM in the treatment of persistent hr-HPV infections.

methodsNine electronic databases were systematically searched from their inception to 30 September 2018. Randomized controlled trials comparing DTCM with follow-up or placebo were included. Risk of bias was assessed by the Cochrane 'Risk of Bias' tool. Review Manager 5.3 was used for statistical analyses. Relative ratios (RR) and 95% confidence intervals were used for dichotomous data, and the mean difference (MD) was used for continuous data. We assessed the quality of trials by the GRADE.

resultsSeventeen RCTs from 2011 to 2018 with 1906 participants were included. The evidence showed that DTCM had a pooled efficacy difference in favor of increasing the HPV clearance rate compared to placebo groups (RR = 2.62, 95% CI 1.28 to 5.33, very low quality) and follow-up groups (RR = 1.88, 95% CI 1.60 to 2.22, low quality). The median HPV persistence tended to decline from 50% within six months to 41.5% at 12 months, and 31.5% at 24 months. A significantly increased regression rate of CIN was found in the DTCM compared with placebo groups (RR = 3.61, 95% CI 1.21 to 10.83, very low quality) and follow-up groups (RR = 1.79, 95% CI 1.31 to 2.45, very low quality). Additionally, we found DTCM have an impact on TNF-α (MD = 2.99, 95% CI 1.90 to 4.07; very low quality), IFN-α (MD = 3.47, 95% CI 2.42 to 4.52; very low quality), CD4+/CD8+ cells (MD = 0.21, 95% CI 0.05 to 0.37; very low quality) compared with follow up groups in some trials with small sample sizes. The major adverse events were genital mucosal irritation symptoms (10%, 5/50).

conclusionsDTCM have favorable outcomes on improving the HPV clearance rate, increasing the regression rate of CIN, and impacting the proportion of some immune cells and cytokine levels. However, most of the evidence was of low quality. Any future high-quality trials and a more extended follow-up period of 24 months or more should be performed.

Indexed as

Drugs, Chinese HerbalFemaleHumansMedicine, Chinese TraditionalPapillomavirus InfectionsRandomized Controlled Trials as TopicReproductive Tract InfectionsDrugs, Chinese Herbal

Identifiers

PMID30822331
PMCPMC6396931
OpenAlexW2919206358

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.