Trial reportScientific reports2021
Carbon nanoparticle suspension could help get a more accurate nodal staging for patient with rectal cancer.
Trial report in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- The Role of Carbon Nanoparticles as Lymph Node Tracers in Colorectal Cancer: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2023Pooled it
- Preserving or peeling the inferior mesenteric arterial sheath during laparoscopic rectal cancer surgery: a prospective study of surgical outcomes.BMC surgery · 2023Trial
- 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 · 2026Article
- Histopathological evaluation of the efficacy of carbon nanoparticle staining in detecting lymph node metastasis in colorectal cancer surgery.Scientific reports · 2025Article
- Improved lymph node detection in minimally invasive radical surgery for colorectal cancer using nanocarbon tracer.Discover oncology · 2024Article
- The effect of carbon nanoparticles staining on lymph node tracking in colorectal cancer: A propensity score matching analysis.Frontiers in surgery · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to evaluate whether carbon nanoparticles could improve the accuracy of nodal staging in colorectal cancer (CRC). We performed a randomized controlled trial with CRC at the department of general surgery, the affiliated hospital of Nanjing University Medical School. A total of 160 patients were recruited in this research and 132 patients were included in the safety analyses. Among these patients, 72 cases were classified into control group and 60 cases into study group. The mean number of lymph nodes harvested from patients in study group was 19.3 ± 6.7 (range from 4 to 38), which was higher than that in control group (15.1 ± 5.7 (range from 3 to 29)) (p < 0.001). The mean number of positive lymph nodes got from patients in study group was 1.7 ± 3.5 (range from 0 to 22), which was also higher than that in control group (0.7 ± 1.4 (range from 0 to 7)) (p = 0.045). In study group, there were 30 patients (50%) proved to be N0, and remaining 30 patients (50%) were N1 or N2. However, 50 patients (69.4%) were N0 and 22 patients (30.6%) were N1 or N2 in control group. The rate of N0 in control group was significantly higher than that in study group (p = 0.023). Injecting carbon nanoparticle suspension could get a more accurate nodal staging to receive enough chemoradiotherapy, improving prognosis. Besides, injecting carbon nanoparticles suspension at four points 5 cm, 10 cm, 15 cm and 20 cm away from the anus by "sandwich" method was a new try.Trial registration: This study was registered with ClinicalTrials.gov, number ChiCTR1900025127 on 12/8/2019.
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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.