Evidence map›Paper›PMID 38802717›Full record

ArticleAnnals of surgical oncology2024

Impact of an Online Risk Calculator for Sentinel Node Positivity on Management of Patients with T1 and T2 Melanomas.

Alec A Winder, Zoe Boyer, Sydney Ch'ng, Jonathan R Stretch, Robyn P M Saw, Kerwin F Shannon, Thomas E Pennington, Omgo E Nieweg, Alexander H R Varey, Richard A Scolyer and 5 more

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Article in Annals of surgical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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.

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

1 citing paper in PubMed.

  1. 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.

Alec A WinderMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia. alecwinder81@gmail.com.
Zoe BoyerFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia.
Sydney Ch'ngMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Jonathan R StretchMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Robyn P M SawMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Kerwin F ShannonMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Thomas E PenningtonMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Omgo E NiewegMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Alexander H R VareyMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Richard A ScolyerMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
John F ThompsonMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Anne E CustMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Serigne N LoMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Andrew J Spillane *Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Andrea L Smith *Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.

Funding

Melanoma Centre of Research Excellence 1135285National Health and Medical Research Council 1093017National Health and Medical Research Council 2008454National Health and Medical Research Council 2018514
6 · The paper itself

Abstract

backgroundPredicting which patients with American Joint Committee on Cancer (AJCC) T1-T2 melanomas will have a positive sentinel lymph node (SLN) is challenging. Melanoma Institute Australia (MIA) developed an internationally validated SLN metastatic risk calculator. This study evaluated the nomogram's impact on T1-T2 melanoma patient management at MIA.

methodsSLN biopsy (SLNB) rates were compared for the pre- and post-nomogram periods of 1 July 2018-30 June 2019 and 1 August 2020-31 July 2021, respectively.

resultsOverall, 850 patients were identified (pre-nomogram, 383; post-nomogram, 467). SLNB was performed in 29.0% of patients in the pre-nomogram group and 34.5% in the post-nomogram group (p = 0.091). The overall positivity rate was 16.2% in the pre-nomogram group and 14.9% in the post-nomogram group (p = 0.223). SLNB was performed less frequently in T1a melanoma patients in the pre-nomogram group (1.1%, n = 2/177) than in the post-nomogram group (8.6%, n = 17/198) [p ≤ 0.001]. This increase was particularly for melanomas with a risk score ≥ 5%, with an SLN positivity rate of 11.8% in the post-nomogram group (p = 0.004) compared with zero. For T1b melanomas with a risk score of > 10%, the SLNB rate was 40.0% (8/20) pre-nomogram and 75.0% (12/16) post-nomogram (p = 0.049).

conclusionsIn this specialized center, the SLN risk calculator appears to influence practice for melanomas previously considered low risk for metastasis, with increased use of SLNB for T1a and higher-risk T1b melanomas. Further evaluation is required across broader practice settings. Melanoma management guidelines could be updated to incorporate the availability of nomograms to better select patients for SLNB than previous criteria.

Indexed as

MelanomaNomogramsSentinel Lymph NodeSentinel Lymph Node BiopsySkin NeoplasmsAdultAgedAged, 80 and overFemaleFollow-Up StudiesHumansLymphatic MetastasisMaleMiddle AgedNeoplasm StagingPrognosis

Identifiers

PMID38802717
PMCPMC11236927

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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.