Evidence map›Paper›PMID 22798061›Full record

ArticlePathology oncology research : POR2013

Multi-institutional comparison of non-sentinel lymph node predictive tools in breast cancer patients with high predicted risk of further axillary metastasis.

Gábor Cserni, Rita Bori, Róbert Maráz, Marjut H K Leidenius, Tuomo J Meretoja, Paivi S Heikkila, Peter Regitnig, Gero Luschin-Ebengreuth, Janez Zgajnar, Andraz Perhavec and 5 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Pathology oncology research : POR, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 15 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

15 authors at 6 institutions in 5 countries.

Gábor CserniDepartment of Pathology, University of Szeged, Állomás u. 2., 6720 Szeged, Hungary. cserni@freemail.hu
Rita Bori
Róbert Maráz
Marjut H K Leidenius
Tuomo J Meretoja
Paivi S Heikkila
Peter Regitnig
Gero Luschin-Ebengreuth
Janez Zgajnar
Andraz Perhavec
Barbara Gazic
György Lázár
Tibor Takács
András Vörös
Riccardo A Audisio
Bács-Kiskun Megyei Kórház · HUHelsinki University Hospital · FIInstitute of Oncology Ljubljana · SIUniversity of Szeged · HUMedical University of Graz · ATSt Helens Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although axillary lymph node dissection (ALND) has been the standard intervention in breast cancer patients with sentinel lymph node (SLN) metastasis, only a small proportion of patients benefit from this operation, because most do not harbor additional metastases in the axilla. Several predictive tools have been constructed to identify patients with low risk of non-SLN metastasis who could be candidates for the omission of ALND. In the present work, predictive nomograms were used to predict a high (>50 %) risk of non-SLN metastasis in order to identify patients who would most probably benefit from further axillary treatment. Data of 1000 breast cancer patients with SLN metastasis and completion ALND from 5 institutions were tested in 4 nomograms. A subset of 313 patients with micrometastatic SLNs were also tested in 3 different nomograms devised for the micrometastatic population (the high risk cut-off being 20 %). Patients with a high predicted risk of non-SLN metastasis had higher rates of metastasis in the non-SLNs than patients with low predicted risk. The positive predictive values of the nomograms ranged from 44 % to 64 % with relevant inter-institutional variability. The nomograms for micrometastatic SLNs performed much better in identifying patients with low risk of non-SLN involvement than in high-risk-patients; for the latter, the positive predictive values ranged from 13 % to 20 %. The nomograms show inter-institutional differences in their predictive values and behave differently in different settings. They are worse in identifying high risk patients than low-risk ones, creating a need for new predictive models to identify high-risk patients.

Indexed as

BiopsyBreast NeoplasmsDatabases, FactualFemaleHumansLymphatic MetastasisLymph NodesNeoplasm MicrometastasisPredictive Value of TestsReproducibility of ResultsRisk

Identifiers

PMID22798061
OpenAlexW1980168674

What OpenQuestion holds

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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.