Evidence map›Paper›PMID 36074703›Full record

Trial reportThe British journal of surgery2022

Ultrasound-assisted carbon nanoparticle suspension mapping versus dual tracer-guided sentinel lymph node biopsy in patients with early breast cancer (ultraCars): phase III randomized clinical trial.

Liulu Zhang, Minyi Cheng, Yingyi Lin, Junsheng Zhang, Bo Shen, Yuanqi Chen, Ciqiu Yang, Mei Yang, Teng Zhu, Hongfei Gao and 3 more

2 registry-linked trialsAbstract readRandomized Controlled TrialClinical Trial, Phase IIIEquivalence Trial
In one paragraph

Trial report in The British journal of surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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.

NCT04951245 phase3completednot on this map

Ultrasound-assisted Carbon Nanoparticle Suspensions Mapping Versus Dual-tracer-guided Sentinel Lymph Node Biopsy in Patients With Early Breast Cancer (UltraCars): a Prospective, Randomized Controlled Phase 3 Trial

TypeinterventionalSponsorGuangdong Provincial People's HospitalRan2019 to 2021Enrolled330ConditionsBreast CancerArmsUC group: ultrasound-assisted CNSs guided, GC group: CNSs plus ICG dual-tracer-guided
NCT07391514 completednot on this mapstarted 2024, after this paper: background citation

Deep Learning-Based Intraoperative Dual-tracer Video Analysis of Sentinel Lymph Node Mapping for Metastasis Prediction in cN0 Papillary Thyroid Carcinoma: A Prospective Cohort Study

Typeobservational_patient_registrySponsorFirst Affiliated Hospital of Chongqing Medical UniversityRan2024 to 2024Enrolled131ConditionsPapillary Thyroid CarcinomaArmsIndocyanine green (ICG) sentinel lymph node mapping, Carbon nanoparticle (CNs) sentinel lymph node mapping, Dual-tracer (ICG combined with CNs) sentinel lymph node mapping
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Trial
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  4. Article
  5. Article
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  8. Axillary lymph node management strategies in cN + breast cancer patients after neoadjuvant chemotherapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Review
  9. Review
  10. Review
  11. Article
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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

13 authors.

Liulu ZhangDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Minyi ChengDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Yingyi LinDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Junsheng ZhangDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Bo ShenDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Yuanqi ChenDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Ciqiu YangDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Mei YangDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Teng ZhuDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Hongfei GaoDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Fei JiDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jieqing LiDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Kun WangDepartment of Breast Cancer, Cancer Centre, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.

Funding

Beijing Medical Award Foundation YXJL-2020-0941-0758CSCO-Hengrui Cancer Research Fund Y-HR2016-067High-level Hospital Construction Project DFJH202109National Natural Science Foundation of China 82171898Science and Technology Planning Project of Guangzhou City 202002030236
6 · The paper itself

Abstract

backgroundAppropriate tracing methods for sentinel lymph node biopsy (SLNB) play a key role in accurate axillary staging. This prospective, non-inferiority, phase III RCT compared the feasibility and diagnostic performance of ultrasound-assisted carbon nanoparticle suspension (CNS) mapping with dual tracer-guided SLNB in patients with early breast cancer.

methodsEligible patients had primary breast cancer without nodal involvement (cN0), or had clinically positive lymph nodes (cN1) that were downstaged to cN0 after neoadjuvant chemotherapy. Patients were randomly assigned (1 : 1) to undergo either ultrasound-assisted CNS sentinel lymph node (SLN) mapping (UC group) or dual tracer-guided mapping with CNS plus indocyanine green (ICG) (GC group). The primary endpoint was the SLN identification rate.

resultsBetween 1 December 2019 and 30 April 2021, 330 patients were assigned randomly to the UC (163 patients) or GC (167 patients) group. The SLN identification rate was 94.5 (95 per cent c.i. 90.9 to 98.0) per cent in the UC group and 95.8 (92.7 to 98.9) per cent in the GC group. The observed difference of -1.3 (-5.9 to 3.3) per cent was lower than the prespecified non-inferiority margin of 6 per cent (Pnon-inferiority = 0.024). No significant difference was observed in metastatic node rate (30.5 versus 24.4 per cent; P = 0.222), median number of SLNs harvested (3 (range 1-7) versus 3 (1-8); P = 0.181), or duration of surgery (mean(s.d.) 7.53(2.77) versus 7.63(3.27) min; P = 0.316) between the groups. Among the subgroup of patients who had undergone neoadjuvant treatment, the SLN identification rate was 91.7 (82.2 to 100) per cent in the UC group and 90.7 (81.7 to 99.7) per cent in the GC group.

conclusionThe diagnostic performance of ultrasound-assisted CNS mapping was non-inferior to that of dual tracer-guided SLN mapping with CNS plus ICG in patients with early breast cancer. REGISTRATION NUMBER: NCT04951245 (http://www.clinicaltrials.gov).

Indexed as

Breast NeoplasmsNanoparticlesSentinel Lymph NodeCarbonFemaleHumansIndocyanine GreenLymph NodesProspective StudiesSentinel Lymph Node BiopsyCarbonIndocyanine Green

Identifiers

PMID36074703
PMCPMC10364740

What OpenQuestion holds

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LicenceCC BY
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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.