Evidence map›Paper›PMID 38315961›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2024

Predicting Recurrence-Free and Overall Survival for Patients With Stage II Melanoma: The MIA Calculator.

Alexander H R Varey, Isabel Li, Mary-Ann El Sharouni, Julie Simon, Aikaterini Dedeilia, Sydney Ch'ng, Robyn P M Saw, Andrew J Spillane, Kerwin F Shannon, Thomas E Pennington and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. 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

22 authors.

Alexander H R VareyMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-7665-8015
Isabel LiMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0009-0002-0039-7274
Mary-Ann El SharouniDepartments of Dermatology and Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.ORCID 0000-0003-4935-4670
Julie SimonDepartment of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Aikaterini DedeiliaMassachusetts General Hospital, Boston, MA.
Sydney Ch'ngMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-4011-1253
Robyn P M SawMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-3354-806X
Andrew J SpillaneMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-8354-434X
Kerwin F ShannonMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Thomas E PenningtonMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-0210-057X
Michael RtshiladzeMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
Jonathan R StretchMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-2556-2005
Omgo E NiewegMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0003-2997-6413
Alexander van AkkooiMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-3262-6935
Ryan J SullivanMassachusetts General Hospital, Boston, MA.ORCID 0000-0001-5344-6645
Genevieve M BolandMassachusetts General Hospital, Boston, MA.ORCID 0000-0002-7522-6173
Jeffrey E GershenwaldDepartment of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0003-4519-5369
Paul J van DiestDepartments of Dermatology and Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.ORCID 0000-0003-0658-2745
Richard A ScolyerMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-8991-0013
Georgina V LongMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0001-8894-3545
John F ThompsonMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-2816-2496
Serigne N LoMelanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.ORCID 0000-0001-5092-5544

Funding

The University of Texas MD Anderson Cancer Center SPORE in MelanomaP50CA221703 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DAVIES, MICHAEL · 2019 to 2023
$10.3M
NCI NIH HHS P50 CA221703
6 · The paper itself

Abstract

purposeImprovements in recurrence-free survival (RFS) were demonstrated in two recent randomized trials for patients with sentinel node (SN)-negative stage IIB or IIC melanoma receiving adjuvant systemic therapy (pembrolizumab/nivolumab). However, adverse events also occurred. Accurate individualized prognostic estimates of RFS and overall survival (OS) would allow patients to more accurately weigh the risks and benefits of adjuvant therapy. Since the current American Joint Committee on Cancer eighth edition (AJCC-8) melanoma staging system focuses on melanoma-specific survival, we developed a multivariable risk prediction calculator that provides estimates of 5- and 10-year RFS and OS for these patients.

methodsData were extracted from the Melanoma Institute Australia (MIA) database for patients diagnosed with stage II (clinical or pathological) melanoma (n = 3,220). Survival prediction models were developed using multivariable Cox regression analyses (MIA models) and externally validated twice using data sets from the United States and the Netherlands. Each model's performance was assessed using C-statistics and calibration plots and compared with Cox models on the basis of AJCC-8 staging (stage models).

resultsThe 5-year and 10-year RFS C-statistics were 0.70 and 0.73 (MIA-model) versus 0.61 and 0.60 (stage-model), respectively. For OS, the 5-year and 10-year C-statistics were 0.71 and 0.75 (MIA-model) compared with 0.62 and 0.61 (stage-model), respectively. The MIA models were well calibrated and externally validated.

conclusionThe MIA models offer accurate and personalized estimates of both RFS and OS in patients with stage II melanoma even in the absence of pathological staging with SN biopsy. These models were robust on external validations and may be used in everyday practice both with (ideally) and without performing SN biopsy to identify high-risk patients for further management strategies. An online tool will be available at the MIA website (Risk Prediction Tools).

Indexed as

MelanomaSkin NeoplasmsHumansNeoplasm StagingPrognosisProportional Hazards ModelsUnited States

Identifiers

PMID38315961
PMCPMC11003510

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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.