Melanoma
Jason M. Aubrey, MD
Resident
Corewell Health - Michigan State University
Grand Rapids, Michigan, United States
Jason M. Aubrey, MD
Resident
Corewell Health - Michigan State University
Grand Rapids, Michigan, United States
Jason M. Aubrey, MD
Resident
Corewell Health - Michigan State University
Grand Rapids, Michigan, United States
Hannah R. Liefeld, MD
Resident
Corewell Health - Michigan State University, United States
Hordur M. Kolbeinsson, MD
Resident
Corewell Health - Michigan State University, United States
Allison Swider, B.S.
Medical Student
Michigan State University College of Human Medicine, United States
Cade A. Cantu, B.S.
Medical Student
Central Michigan College of Medicine, United States
Madi Mangione, B.S.
Medical Student
Michigan State University College of Human Medicine, United States
Gerald P. Wright, MD
Surgical Oncologist
Corewell Health - Michigan State University, United States
Nomograms predicting the risk of a SLNB are commonly used for shared decision making with patients. The Melanoma Institute of Australia (MIA) published a publicly available and validated risk calculator utilizing age, tumor thickness, melanoma subtype, mitotic index, ulceration and lymphovascular invasion. We aim to elucidate the adoption of this calculator in clinical practice on SLNB rates in thin melanomas.
Methods:
A single center, retrospective analysis of consecutive patients who underwent treatment of T1 melanomas from 2017-2023. Groups were divided based on before (pre-MIA) and after (post-MIA) adoption of the MIA risk calculator in preoperative shared decision making. The primary outcome measure was SLNB utilization rate. The MIA risk calculator was retrospectively applied to patients in the pre-MIA group for comparisons. High risk features were defined as age < 42, elevated mitotic index and lymphovascular invasion. Comparisons were also made between the MIA and MSKCC nomograms.
Results:
A total of 416 patients were included, 139 and 277 patients in the pre-MIA and post-MIA groups, respectively. There were no differences in age, T stage or mitotic index between groups. Overall SLNB was utilized in 179 (43%) patients and positive in 19 (10.6%). SLNB decreased in the post-MIA group (51.1% vs 39.0%, p = 0.019). Stratified by T stage, there was no difference in SLNB utilization rates in the pre-MIA and post-MIA groups (T1a: 22.7% vs 18.9%, p=0.490; T1b: 83.6% vs 73.5%, p=0.137). Stratified by MIA risk calculator estimates, there was a decrease in SLNB rate in the post-MIA group for risk < 5% (17.3% vs 5.3%, p=0.009), with no difference seen for risk of 5-9% (62.7% vs 62.0%, p=0.931) or risk ≥10% (89.3% vs 94.4%, p=0.446). Presence of any high-risk feature was associated with increased SLNB utilization in each group (Pre-MIA: 70.6% vs 39.8%, p< 0.001; Post-MIA: 79.0% vs 27.4%, p< 0.001). The median MIA risk was higher for patients who had SLNB performed (8% vs 3%, p < 0.001) and had a positive SLNB (10% vs 7%, p = 0.007). The MIA calculator gave a higher median risk than the MSKCC calculator (5% vs 4%, p < 0.001). The MIA risk calculator estimate strongly predicted having SLNB performed (AUC 0.883, 95% CI 0.850-0.916) and a significant but weaker prediction of SLNB positivity (AUC 0.688, 95% CI 0.574-0.801).
Conclusions:
Adoption of the MIA Sentinel Lymph Node Metastasis risk calculator into routine preoperative counseling resulted in decreased rates of SLNB being performed in T1 melanomas, predominantly in those with risk estimate < 5%.