Evidence map›Paper›PMID 36686792›Full record

ArticleFrontiers in oncology2022

The safety and efficacy of carbon nanoparticle suspension injection versus indocyanine green tracer-guided lymph node dissection during radical gastrectomy (FUTURE-01): A single-center randomized controlled trial protocol.

Yuan Tian, Yue Pang, Peigang Yang, Honghai Guo, Yang Liu, Ze Zhang, Pingan Ding, Tao Zheng, Yong Li, Liqiao Fan and 5 more

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05229874 (A Prospective Randomized Controlled Study of the Efficacy of Carbon Nanoparticles Versus Indocyanine Green in Robotic or Laparoscopic Gastrectomy), which is not on this map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT05229874 phase2unknown statusnot on this map

A Prospective Randomized Controlled Study of the Efficacy of Carbon Nanoparticles Versus Indocyanine Green in Robotic or Laparoscopic Gastrectomy

TypeinterventionalSponsorHebei Medical UniversityRan2022 to 2025Enrolled96ConditionsGastric CancerArmscarbon nanoparticles, Indocyanine green
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Efficacy of Nano-Carbon Tracing Versus Indocyanine Green in Lymph Node Detection for Minimally Invasive Colorectal Resection.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Article
  3. Article
  4. 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

15 authors.

Yuan TianThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Yue PangThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Peigang YangThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Honghai GuoThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Yang LiuThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Ze ZhangThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Pingan DingThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Tao ZhengThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Yong LiThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Liqiao FanThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Zhidong ZhangThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Xuefeng ZhaoThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Bibo TanThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Dong WangThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Qun ZhaoThird Surgery Department, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The use of lymph node (LN) tracers can help obtain a complete dissection of the lymph nodes and increase the detection rate of LNs and metastatic LNs. Carbon nanoparticle suspension injection (CNSI) and indocyanine green (ICG) have been widely used in radical gastrectomy in recent years. Nevertheless, the comparison of their clinical effects has not been studied. Method/design: The FUTURE-01 trial will be the first randomized, open-label, single-center trial to compare CNSI and ICG. The study started in 2021 and enrolled 96 patients according to a prior sample size calculation. The primary outcome is the number of LNs retrieved. The secondary outcomes are LN staining rate, LN metastasis rate, stained LN metastasis rate, perioperative recovery and survival. Conclusion: By comparing the safety and efficacy of CNSI and ICG tracer-guided LN dissection in patients with gastric cancer, we can determine the most appropriate LN tracer at present. With the help of LN tracers, the operation is simplified, and the prognosis of these patients is improved. Our study is a prospective exploration of the safety, efficacy, and prognosis of CNSI and ICG. Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT05229874?cond=NCT05229874&draw=2&rank=1, identifier NCT05229874.

Indexed as

carbon nanoparticle suspension injectionclinical trialdesigngastrectomygastric cancerindocyanine greenlymph nodeprotocol

Identifiers

PMID36686792
PMCPMC9852878

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Registered trials

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.