Evidence map›Paper›PMID 31680943›Full record

ArticleFrontiers in pharmacology2019

Diagnostic Accuracy of Magnetometer-Guided Sentinel Lymphadenectomy After Intraprostatic Injection of Superparamagnetic Iron Oxide Nanoparticles in Intermediate- and High-Risk Prostate Cancer Using the Magnetic Activity of Sentinel Nodes.

Wiebke Geißen, Svenja Engels, Paula Aust, Jonas Schiffmann, Holger Gerullis, Friedhelm Wawroschek, Alexander Winter

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.5field-weighted citation impact, top 29% 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

10 citing papers in PubMed, 11 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Wiebke GeißenUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Svenja EngelsUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Paula AustUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Jonas SchiffmannUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Holger GerullisUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Friedhelm WawroschekUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Alexander WinterUniversity Hospital for Urology, Klinikum Oldenburg, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Klinikum Oldenburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the high morbidity of extended lymph node dissection (eLND) and the low detection rate of limited lymph node dissection (LND), targeted sentinel lymph node dissection (sLND) was implemented in prostate cancer (PCa). Subsequently, nonradioactive sentinel lymph node (SLN) detection using magnetic resonance imaging (MRI) and a magnetometer after intraprostatic injection of superparamagnetic iron oxide nanoparticles (SPIONs) was successfully applied in PCa. To validate the reliability of this approach, considering the magnetic activity of SLNs or whether it is sufficient to dissect only the most active SLNs as shown in other tumor entities for radio-guided sLND, we analyzed magnetometer-guided sLND results in 218 high- and intermediate-risk PCa patients undergoing eLND as a reference standard. Using a sentinel nomogram to predict lymph node invasion (LNI), a risk range was determined up to which LND could be dispensed with or sLND only would be adequate. In total, 3,711 LNs were dissected, and 1,779 SLNs (median, 8) were identified. Among 78 LN-positive patients, there were 264 LN metastases (median, 2). sLND had a 96.79% diagnostic rate, 88.16% sensitivity, 98.59% specificity, 97.1% positive predictive value (PPV), 93.96% negative predictive value (NPV), 4.13% false-negative rate, and 0.92% additional diagnostic value (LN metastases only outside the eLND template). For intermediate-risk patients only, the sensitivity, specificity, PPV, and NPV were 100%. Magnetic activities of SLNs were heterogeneous regardless of metastasis. The accuracy of predicting the presence of metastases for each LN from the proportion of activity was only 57.3% in high- and 65% in intermediate-risk patients. Patients with LNI risk of less than 5% could have been spared LND, as no positive LNs were found in this group. For patients with an LNI risk between 5% and 20%, sLND-only would have been sufficient to detect almost all LN metastases; thus, eLND could be dispensed with in 36% of patients. In conclusion, SPION-guided sLND is a reliable alternative to eLND in intermediate-/high-risk PCa. No conclusions can be drawn from magnetic SLN activity regarding the presence of metastases. LND could be dispensed with according to a nomogram of predicted probability for LNI of 5% without losing any LN-positive patient. Patients with LNI risk between 5% and 20% could be spared eLND by performing sLND.

Indexed as

lymphadenectomylymph node metastasesmagnetometernomogramprostate cancersentinel nodesuperparamagnetic iron oxide nanoparticle

Identifiers

PMID31680943
PMCPMC6797623
OpenAlexW2970761882

What OpenQuestion holds

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Registered trials

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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.