Performance of models predicting residual lymph node disease in melanoma patients following sentinel lymph node biopsy |
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| Affiliation: | 1. BC Cancer-Sindi Ahluwalia Hawkins Centre, Dept. of Surgical Oncology, 399 Royal Ave, Kelowna, BC, V1Y 5L3, Canada;2. University of British Columbia Southern Medical Program, 2312 Pandosy Street, Kelowna, BC, V1Y 1T3, Canada;1. Department of Surgery, Oregon Health & Science University, Portland, OR, USA;2. Quality Management, Oregon Health & Science University, Portland, OR, USA;3. Division of Pediatric Surgery, Oregon Health & Science University, Portland, OR, USA;4. Perioperative Services, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR, USA;1. Department of Surgery, Madigan Army Medical Center, Tacoma, WA, USA;2. Department of Surgery, Scripps Mercy Hospital, San Diego, CA, USA;1. Department of Surgery, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA;2. School of Medicine, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA;3. Somali Health Board, 625 Strander Blvd Building B, Tukwila, Washington, 98188, USA;4. School of Social Work, University of Washington, Seattle, WA, USA;5. Harborview Injury Prevention and Research Center, University of Washington, Seattle, WA, USA;6. Department of Anesthesiology, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA;7. Seattle and King County Public Health, 401 5th Ave, Seattle, WA, 98104, USA;8. Department of Medicine, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA;9. Department of Global Health, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA;10. Department of Pediatrics, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA;1. Vancouver General Hospital, Department of Surgery, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada;2. Centre for Health Services and Policy Research, School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada;3. Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada;4. St. Paul’s Hospital, Department of Surgery, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada;1. University of Washington School of Medicine, Seattle, WA, 98195, USA;2. Institute for Disease Modeling, Bellevue, WA, 98005, USA;3. Seattle Children’s Hospital, Seattle, WA, 98105, USA;4. Seattle Children’s Research Institute, Seattle, WA, 98101, USA |
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| Abstract: | BackgroundAmong melanoma patients with a tumor-positive sentinel node biopsy (SNB), approximately 20% harbor disease in non-sentinel nodes (nSN), as determined by a completion lymph node dissection (CLND). CLND lacks a survival benefit and has high morbidity. This study assesses predictive factors for nSN metastasis and validates five models predicting nSN metastasis.MethodsPatients with invasive melanoma were identified from the BC Cancer Agency (2005–2015). Clinicopathological data were collected from 296 patients who underwent a CLND after a positive SNB. Multivariate analysis was completed to assess predictive variables in the study population. Five models were externally validated using overall model performance (Brier score [calibration and discrimination]) and discrimination (area under the ROC curve [AUC]).ResultsSeventy-three patients had nSN metastasis at the time of CLND. The variable most predictive of nSN involvement was lymphovascular invasion (odds ratio [OR] 3.99; 95% confidence interval [CI] 1.67–9.54; p = 0.002). The highest discrimination was Lee et al. (2004) (AUC 0.68 [95% CI 0.61–0.75]), Rossi et al. (2018) (AUC 0.68 [95% CI 0.57–0.77]), and Bertolli et al. (2019) (AUC 0.68 [95% CI 0.60–0.75]). Rossi et al. (2018) had the lowest overall model performance (Brier score 0.44). Rossi et al. (2018) and Bertolli et al. (2019) had the ability to stratify patients to a risk of nSN involvement up to 99% and 95%, respectively.ConclusionBertolli et al. (2019) had amongst the highest overall model performance, was the most clinically meaningful and is recommended as the preferred model for predicting nSN metastasis. |
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| Keywords: | Melanoma Sentinel lymph node biopsy Completion lymph node dissection Nomogram |
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