Population-Based Validation of the MIA and MSKCC Tools for Predicting Sentinel Lymph Node Status.


Journal

JAMA surgery
ISSN: 2168-6262
Titre abrégé: JAMA Surg
Pays: United States
ID NLM: 101589553

Informations de publication

Date de publication:
10 Jan 2024
Historique:
medline: 10 1 2024
pubmed: 10 1 2024
entrez: 10 1 2024
Statut: aheadofprint

Résumé

Patients with melanoma are selected for sentinel lymph node biopsy (SLNB) based on their risk of a positive SLN. To improve selection, the Memorial Sloan Kettering Cancer Center (MSKCC) and Melanoma Institute Australia (MIA) developed predictive models, but the utility of these models remains to be tested. To determine the clinical utility of the MIA and MSKCC models. This was a population-based comparative effectiveness research study including 10 089 consecutive patients with cutaneous melanoma undergoing SLNB from the Swedish Melanoma Registry from January 2007 to December 2021. Data were analyzed from May to August 2023. The predicted probability of SLN positivity was calculated using the MSKCC model and a limited MIA model (using mitotic rate as absent/present instead of count/mm2 and excluding the optional variable lymphovascular invasion) for each patient. The operating characteristics of the models were assessed and compared. The clinical utility of each model was assessed using decision curve analysis and compared with a strategy of performing SLNB on all patients. Among 10 089 included patients, the median (IQR) age was 64.0 (52.0-73.0) years, and 5340 (52.9%) were male. The median Breslow thickness was 1.8 mm, and 1802 patients (17.9%) had a positive SLN. Both models were well calibrated across the full range of predicted probabilities and had similar external area under the receiver operating characteristic curves (AUC; MSKCC: 70.8%; 95% CI, 69.5-72.1 and limited MIA: 69.7%; 95% CI, 68.4-71.1). At a risk threshold of 5%, decision curve analysis indicated no added net benefit for either model compared to performing SLNB for all patients. At risk thresholds of 10% or higher, both models added net benefit compared to SLNB for all patients. The greatest benefit was observed in patients with T2 melanomas using a threshold of 10%; in that setting, the use of the nomograms led to a net reduction of 8 avoidable SLNBs per 100 patients for the MSKCC nomogram and 7 per 100 patients for the limited MIA nomogram compared to a strategy of SLNB for all. This study confirmed the statistical performance of both the MSKCC and limited MIA models in a large, nationally representative data set. However, decision curve analysis demonstrated that using the models only improved selection for SLNB compared to biopsy in all patients when a risk threshold of at least 7% was used, with the greatest benefit seen for T2 melanomas at a threshold of 10%. Care should be taken when using these nomograms to guide selection for SLNB at the lowest thresholds.

Identifiants

pubmed: 38198163
pii: 2813699
doi: 10.1001/jamasurg.2023.6904
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Roger Olofsson Bagge (RO)

Sahlgrenska Center for Cancer Research, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
Department of Surgery, Sahlgrenska University Hospital, Gothenburg, Sweden.

Rasmus Mikiver (R)

Regional Cancer Center Southeast Sweden and Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.

Michael A Marchetti (MA)

Dermatology, Skagit Regional Health, Mt Vernon, Washington.

Serigne N Lo (SN)

Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.

Alexander C J van Akkooi (ACJ)

Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.

Daniel G Coit (DG)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.

Christian Ingvar (C)

Department of Clinical Sciences, Surgery, Lund University, Lund, Sweden.

Karolin Isaksson (K)

Department of Clinical Sciences, Surgery, Lund University, Lund, Sweden.
Department of Surgery, Kristianstad Hospital, Kristianstad, Sweden.

Richard A Scolyer (RA)

Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, New South Wales, Australia.
Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.

John F Thompson (JF)

Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.

Alexander H R Varey (AHR)

Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Department of Plastic Surgery, Westmead Hospital, Sydney, New South Wales, Australia.

Sandra L Wong (SL)

Department of Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.

Johan Lyth (J)

Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.

Edmund K Bartlett (EK)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.

Classifications MeSH