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Ragsdale M, Dow B, Fernandes D, Han Y, Parikh A, Boyapati K, Landry CS, Kimbrough CW, Koshenkov VP, Preskitt JT, Berger AC, Davis CH. Sentinel lymph node positivity in melanoma: Which risk prediction tool is most accurate? Surgery 2024:S0039-6060(24)00366-0. [PMID: 38997863 DOI: 10.1016/j.surg.2024.05.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 05/01/2024] [Accepted: 05/21/2024] [Indexed: 07/14/2024]
Abstract
BACKGROUND Sentinel lymph node biopsy for melanoma determines treatment and prognostic factors and improves disease-specific survival. To risk-stratify patients for sentinel lymph node biopsy consideration, Memorial Sloan Kettering Cancer Center and Melanoma Institute Australia developed nomograms to predict sentinel lymph node positivity. We aimed to compare the accuracy of these 2 nomograms. METHODS A multi-institutional study of patients with melanoma receiving sentinel lymph node biopsy between September 2018 and December 2022 was performed. The accuracy of the 2 risk prediction tools in determining a positive sentinel lymph node biopsy was analyzed using receiver operating characteristic curves and area under the curve. RESULTS In total, 532 patients underwent sentinel lymph node biopsy for melanoma; 98 (18.4%) had positive sentinel lymph node. Increasing age was inversely related to sentinel lymph node positivity (P < .01); 35.7% of patients ≤30 years had positive sentinel lymph node compared with 9.7% of patients ≥75 years. When we analyzed the entire study population, accuracy of the 2 risk prediction tools was equal (area under the curveMemorial Sloan Kettering Cancer Center: 0.693; area under the curveMIA: 0.699). However, Memorial Sloan Kettering Cancer Center tool was a better predictor in patients aged ≥75 years (area under the curveMemorial Sloan Kettering Cancer Center: 0.801; area under the curveMelanoma Institute Australia: 0.712, P < .01) but Melanoma Institute Australia tool performed better in patients with a higher mitotic index (mitoses/mm2 ≥2; area under the curveMemorial Sloan Kettering Cancer Center: 0.659; area under the curveMelanoma Institute Australia: 0.717, P = .027). Both models were poor predictors of sentinel lymph node positivity in young patients (age ≤30 years; area under the curveMemorial Sloan Kettering Cancer Center: 0.456; area under the curveMelanoma Institute Australia: 0.589, P = .283). CONCLUSION The current study suggests that the 2 risk stratification tools differ in their abilities to predict sentinel lymph node positivity in specific populations: Memorial Sloan Kettering Cancer Center tool is a better predictor for older patients, whereas Melanoma Institute Australia tool is more accurate in patients with a higher mitotic index. Both nomograms performed poorly in predicting sentinel lymph node positivity in young patients.
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Affiliation(s)
| | - Bobby Dow
- Texas A&M University School of Medicine, Dallas, TX
| | | | - Yuri Han
- Robert Wood Johnson Medical School, New Brunswick, NJ
| | | | | | - Christine S Landry
- Texas A&M University School of Medicine, Dallas, TX; Division of Surgical Oncology, Baylor University Medical Center, Dallas, TX
| | - Charles W Kimbrough
- Texas A&M University School of Medicine, Dallas, TX; Division of Surgical Oncology, Baylor University Medical Center, Dallas, TX
| | - Vadim P Koshenkov
- Robert Wood Johnson Medical School, New Brunswick, NJ; Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ
| | - John T Preskitt
- Texas A&M University School of Medicine, Dallas, TX; Division of Surgical Oncology, Baylor University Medical Center, Dallas, TX
| | - Adam C Berger
- Robert Wood Johnson Medical School, New Brunswick, NJ; Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ
| | - Catherine H Davis
- Texas A&M University School of Medicine, Dallas, TX; Division of Surgical Oncology, Baylor University Medical Center, Dallas, TX.
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Kött J, Zimmermann N, Zell T, Rünger A, Heidrich I, Geidel G, Smit DJ, Hansen I, Abeck F, Schadendorf D, Eggermont A, Puig S, Hauschild A, Gebhardt C. Sentinel lymph node risk prognostication in primary cutaneous melanoma through tissue-based profiling, potentially redefining the need for sentinel lymph node biopsy. Eur J Cancer 2024; 202:113989. [PMID: 38518535 DOI: 10.1016/j.ejca.2024.113989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 03/04/2024] [Indexed: 03/24/2024]
Abstract
PURPOSE OF REVIEW The role of Sentinel Lymph Node Biopsy (SLNB) is pivotal in the contemporary staging of cutaneous melanoma. In this review, we examine advanced molecular testing platforms like gene expression profiling (GEP) and immunohistochemistry (IHC) as tools for predicting the prognosis of sentinel lymph nodes. We compare these innovative approaches with traditional staging assessments. Additionally, we delve into the shared genetic and protein markers between GEP and IHC tests and their relevance to melanoma biology, exploring their prognostic and predictive characteristics. Finally, we assess alternative methods to potentially obviate the need for SLNB altogether. RECENT FINDINGS Progress in adjuvant melanoma therapy has diminished the necessity of Sentinel Lymph Node Biopsy (SLNB) while underscoring the importance of accurately identifying high-risk stage I and II melanoma patients who may benefit from additional anti-tumor interventions. The clinical application of testing through gene expression profiling (GEP) or immunohistochemistry (IHC) is gaining traction, with platforms such as DecisionDx, Merlin Assay (CP-GEP), MelaGenix GEP, and Immunoprint coming into play. Currently, extensive validation studies are in progress to incorporate routine molecular testing into clinical practice. However, due to significant methodological limitations, widespread clinical adoption of tissue-based molecular testing remains elusive at present. SUMMARY While various tissue-based molecular testing platforms have the potential to stratify the risk of sentinel lymph node positivity (SLNP), most suffer from significant methodological deficiencies, including limited sample size, lack of prospective validation, and limited correlation with established clinicopathological variables. Furthermore, the genes and proteins identified by individual gene expression profiling (GEP) or immunohistochemistry (IHC) tests exhibit minimal overlap, even when considering the most well-established melanoma mutations. However, there is hope that the ongoing prospective trial for the Merlin Assay may safely reduce the necessity for SLNB procedures if successful. Additionally, the MelaGenix GEP and Immunoprint tests could prove valuable in identifying high-risk stage I-II melanoma patients and potentially guiding their selection for adjuvant therapy, thus potentially reducing the need for SLNB. Due to the diverse study designs employed, effective comparisons between GEP or IHC tests are challenging, and to date, there is no study directly comparing the clinical utility of these respective GEP or IHC tests.
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Affiliation(s)
- Julian Kött
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Noah Zimmermann
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Tim Zell
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Alessandra Rünger
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Isabel Heidrich
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Institute of Tumor Biology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Glenn Geidel
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Daniel J Smit
- Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Institute of Tumor Biology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Inga Hansen
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Finn Abeck
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Dirk Schadendorf
- Department of Dermatology & Westdeutsches Tumorzentrum Essen (WTZ), University Hospital Essen, Essen, Germany; German Cancer Consortium, Partner Site Essen, Essen, Germany; National Center for Tumor Diseases (NCT-West), Campus Essen, Germany; Research Alliance Ruhr, Research Center One Health, University Duisburg-Essen, Essen, Germany
| | - Alexander Eggermont
- Princess Máxima Center and University Medical Center Utrecht, 3584 CS Utrecht, the Netherlands; Comprehensive Cancer Center Munich, Technical University Munich & Ludwig Maximilian University, Munich, Germany
| | - Susana Puig
- Department of Dermatology, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Center on Rare Diseases (CIBERER), ISCIII, Barcelona, Spain
| | - Axel Hauschild
- Department of Dermatology, University Hospital Schleswig-Holstein (UKSH) Campus Kiel, Kiel, Germany
| | - Christoffer Gebhardt
- University Skin Cancer Center Hamburg, Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Fleur Hiege Center for Skin Cancer Research, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
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Maddineni S, Dizon MP, Muralidharan V, Young LA, Sunwoo JB, Baik FM, Swetter SM. Validation of the Melanoma Institute of Australia's Sentinel Lymph Node Biopsy Risk Prediction Tool for Cutaneous Melanoma. Ann Surg Oncol 2024; 31:2737-2746. [PMID: 38216800 DOI: 10.1245/s10434-023-14862-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 12/17/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND For patients with cutaneous melanoma, sentinel lymph node biopsy (SLNB) is used to stage regional lymph nodes pathologically and inform prognosis, treatment, and surveillance. To reduce unnecessary surgeries, predictive tools aim to identify those at lowest risk for node-positive disease. The Melanoma Institute of Australia (MIA)'s Prediction Tool for Sentinel Node Metastasis Risk estimates risk of a positive SLNB using patient age and primary melanoma Breslow depth, histologic subtype, ulceration, mitotic rate, and lymphovascular invasion. METHODS A single-institution validation was performed of the MIA Calculator with 982 cutaneous melanoma patients that included all relevant clinicopathologic factors and SLNB pathology outcomes. The study evaluated discrimination via receiver operating characteristic (ROC) curves, calibration via calibration plots, and clinical utility via decision curve analysis of the MIA model in various subgroups. The data were fit to MIA model parameters via a generalized linear model to assess the odds ratio of parameters in our dataset. RESULTS The Calculator demonstrated limited discrimination based on ROC curves (C-statistic, 0.709) and consistently underestimated risk of SLN positivity. It did not provide a net benefit over SLNB performed on all patients or reduce unnecessary procedures in the risk domain of 0% to 16%. Compared with the original development and validation cohorts, the current study cohort had thinner tumors and a larger proportion of acral melanomas. CONCLUSIONS The Calculator generally underestimated SLN positivity risk, including assessment in patients who would be counseled to forego SLNB based on a predicted risk lower than 5%. Recognition of the tool's current limitations emphasizes the need to refine it further for use in medical decision-making.
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Affiliation(s)
- Sainiteesh Maddineni
- Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Matthew P Dizon
- Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Menlo Park, CA, USA
- Department of Health Policy, Stanford University School of Medicine, Stanford, CA, USA
- Dermatology Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Vijaytha Muralidharan
- Department of Dermatology/Pigmented Lesion and Melanoma Program, Stanford University Medical Center and Cancer Institute, Stanford, CA, USA
| | - Lexi A Young
- Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | - John B Sunwoo
- Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Fred M Baik
- Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Susan M Swetter
- Dermatology Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Dermatology/Pigmented Lesion and Melanoma Program, Stanford University Medical Center and Cancer Institute, Stanford, CA, USA.
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Maher NG, Vergara IA, Long GV, Scolyer RA. Prognostic and predictive biomarkers in melanoma. Pathology 2024; 56:259-273. [PMID: 38245478 DOI: 10.1016/j.pathol.2023.11.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 11/20/2023] [Indexed: 01/22/2024]
Abstract
Biomarkers help to inform the clinical management of patients with melanoma. For patients with clinically localised primary melanoma, biomarkers can help to predict post-surgical outcome (including via the use of risk prediction tools), better select patients for sentinel lymph node biopsy, and tailor catch-all follow-up protocols to the individual. Systemic drug treatments, including immune checkpoint inhibitor (ICI) therapies and BRAF-targeted therapies, have radically improved the prognosis of metastatic (stage III and IV) cutaneous melanoma patients, and also shown benefit in the earlier setting of stage IIB/C primary melanoma. Unfortunately, a response is far from guaranteed. Here, we review clinically relevant, established, and emerging, prognostic, and predictive pathological biomarkers that refine clinical decision-making in primary and metastatic melanoma patients. Gene expression profile assays and nomograms are emerging tools for prognostication and sentinel lymph node risk prediction in primary melanoma patients. Biomarkers incorporated into clinical practice guidelines include BRAF V600 mutations for the use of targeted therapies in metastatic cutaneous melanoma, and the HLA-A∗02:01 allele for the use of a bispecific fusion protein in metastatic uveal melanoma. Several predictive biomarkers have been proposed for ICI therapies but have not been incorporated into Australian clinical practice guidelines. Further research, validation, and assessment of clinical utility is required before more prognostic and predictive biomarkers are fluidly integrated into routine care.
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Affiliation(s)
- Nigel G Maher
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Ismael A Vergara
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
| | - Georgina V Long
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Royal North Shore and Mater Hospitals, Sydney, NSW, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.
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5
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Drebin HM, Hosein S, Kurtansky NR, Nadelmann E, Moy AP, Ariyan CE, Bello DM, Brady MS, Coit DG, Marchetti MA, Bartlett EK. Clinical Utility of Melanoma Sentinel Lymph Node Biopsy Nomograms. J Am Coll Surg 2024; 238:23-31. [PMID: 37870230 DOI: 10.1097/xcs.0000000000000886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]
Abstract
BACKGROUND For patients with melanoma, the decision to perform sentinel lymph node biopsy (SLNB) is based on the estimated risk of lymph node metastasis. We assessed 3 melanoma SLNB risk-prediction models' statistical performance and their ability to improve clinical decision making (clinical utility) on a cohort of melanoma SLNB cases. STUDY DESIGN Melanoma patients undergoing SLNB at a single center from 2003 to 2021 were identified. The predicted probabilities of sentinel lymph node positivity using the Melanoma Institute of Australia, Memorial Sloan Kettering Cancer Center (MSK), and Friedman nomograms were calculated. Receiver operating characteristic and calibration curves were generated. Clinical utility was assessed via decision curve analysis, calculating the net SLNBs that could have been avoided had a given model guided selection at different risk thresholds. RESULTS Of 2,464 melanoma cases that underwent SLNB, 567 (23.0%) had a positive sentinel lymph node. The areas under the receiver operating characteristic curves for the Melanoma Institute of Australia, MSK, and Friedman models were 0.726 (95% CI, 0.702 to 0.750), 0.720 (95% CI, 0.697 to 0.744), and 0.721 (95% CI, 0.699 to 0.744), respectively. For all models, calibration was best at predicted positivity rates below 30%. The MSK model underpredicted risk. At a 10% risk threshold, only the Friedman model would correctly avoid a net of 6.2 SLNBs per 100 patients. The other models did not reduce net avoidable SLNBs at risk thresholds of ≤10%. CONCLUSIONS The tested nomograms had comparable performance in our cohort. The only model that achieved clinical utility at risk thresholds of ≤10% was the Friedman model.
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Affiliation(s)
- Harrison M Drebin
- From the Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY (Drebin, Ariyan, Bello, Brady, Coit, Bartlett)
| | - Sharif Hosein
- the Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY (Hosein, Kurtansky, Nadelmann, Marchetti)
| | - Nicholas R Kurtansky
- the Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY (Hosein, Kurtansky, Nadelmann, Marchetti)
| | - Emily Nadelmann
- the Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY (Hosein, Kurtansky, Nadelmann, Marchetti)
| | - Andrea P Moy
- the Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY (Moy)
| | - Charlotte E Ariyan
- From the Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY (Drebin, Ariyan, Bello, Brady, Coit, Bartlett)
| | - Danielle M Bello
- From the Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY (Drebin, Ariyan, Bello, Brady, Coit, Bartlett)
| | - Mary S Brady
- From the Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY (Drebin, Ariyan, Bello, Brady, Coit, Bartlett)
| | - Daniel G Coit
- From the Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY (Drebin, Ariyan, Bello, Brady, Coit, Bartlett)
| | - Michael A Marchetti
- the Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY (Hosein, Kurtansky, Nadelmann, Marchetti)
- Skagit Regional Health, Mt Vernon, WA (Marchetti)
| | - Edmund K Bartlett
- From the Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY (Drebin, Ariyan, Bello, Brady, Coit, Bartlett)
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Cheng TW, Hartsough E, Giubellino A. Sentinel lymph node assessment in melanoma: current state and future directions. Histopathology 2023; 83:669-684. [PMID: 37526026 DOI: 10.1111/his.15011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 07/03/2023] [Accepted: 07/05/2023] [Indexed: 08/02/2023]
Abstract
Assessment of sentinel lymph node status is an important step in the evaluation of patients with melanoma for both prognosis and therapeutic management. Pathologists have an important role in this evaluation. The methodologies have varied over time, from the evaluation of dimensions of metastatic burden to determination of the location of the tumour deposits within the lymph node to precise cell counting. However, no single method of sentinel lymph node tumour burden measurement can currently be used as a sole independent predictor of prognosis. The management approach to sentinel lymph node-positive patients has also evolved over time, with a more conservative approach recently recognised for selected cases. This review gives an overview of past and current status in the field with a glimpse into future directions based on prior experiences and clinical trials.
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Affiliation(s)
- Tiffany W Cheng
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Emily Hartsough
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Alessio Giubellino
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
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Freeman SC, Paz Munoz E, Latour E, Lim JY, Yu W. External validation of the Melanoma Institute Australia Sentinel Node Metastasis Risk Prediction Tool using the National Cancer Database. J Am Acad Dermatol 2023; 89:967-973. [PMID: 37454700 DOI: 10.1016/j.jaad.2023.07.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 06/27/2023] [Accepted: 07/04/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND To improve patient selection for sentinel node (SN) biopsy, the Melanoma Institute of Australia (MIA) created a predictive model based on readily available clinicopathologic factors. OBJECTIVES Validation of the MIA nomogram using the National Cancer Database (NCDB), a nationwide oncology outcomes database for >1500 Commission-accredited cancer programs in the United States. METHODS A total of 60,165 patients were included in the validation. The probability of SN positivity was calculated for each patient. Using calculated probabilities, a receiver operating characteristic curve was generated to assess the model's discrimination ability. RESULTS At baseline, the NCDB cohort had different clinicopathologic characteristics compared with the original MIA data set. Despite these differences, the MIA nomogram retained high-predictive accuracy within the NCDB dataset (C-statistic, 0.733 [95% CI, 0.726-0.739]), although calibration weakened for the highest risk decile. LIMITATIONS The NCDB collects data from hospital registries accredited by the Commission on Cancer. CONCLUSIONS In conclusion, this study validated the use of the MIA nomogram in a nationwide oncology outcomes database collected from >1500 Commission-accredited cancer programs in the United States, demonstrating the potential for this nomogram to predict SN positivity and reduce the number of negative SN biopsies.
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Affiliation(s)
- Steven Caleb Freeman
- Department of Dermatology, Oregon Health & Science University, Portland, Oregon.
| | - Elena Paz Munoz
- Department of Dermatology, Oregon Health & Science University, Portland, Oregon
| | - Emile Latour
- Biostatistics Shared Resource, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon
| | - Jeong Youn Lim
- Biostatistics Shared Resource, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon
| | - Wesley Yu
- Department of Dermatology, Oregon Health & Science University, Portland, Oregon
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Dixon A, Steinman HK, Kyrgidis A, Smith H, Sladden M, Zouboulis C, Argenziano G, Apalla Z, Lallas A, Longo C, Nirenberg A, Popescu C, Tzellos T, Cleaver L, Zachary C, Anderson S, Thomas JM. Online prediction tools for melanoma survival: A comparison. J Eur Acad Dermatol Venereol 2023; 37:1999-2003. [PMID: 37210649 DOI: 10.1111/jdv.19219] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 04/26/2023] [Indexed: 05/22/2023]
Abstract
BACKGROUND Breslow thickness, patient age and ulceration are the three most valuable clinical and pathological predictors of melanoma survival. A readily available reliable online tool that accurately considers these and other predictors could be valuable for clinicians managing melanoma patients. OBJECTIVE To compare online melanoma survival prediction tools that request user input on clinical and pathological features. METHODS Search engines were used to identify available predictive nomograms. For each, clinical and pathological predictors were compared. RESULTS Three tools were identified. The American Joint Committee on Cancer tool inappropriately rated thin tumours as higher risk than intermediate tumours. The University of Louisville tool was found to have six shortcomings: a requirement for sentinel node biopsy, unavailable input of thin melanoma or patients over 70 years of age and less reliable hazard ratio calculations for age, ulceration and tumour thickness. The LifeMath.net tool was found to appropriately consider tumour thickness, ulceration, age, sex, site and tumour subtype in predicting survival. LIMITATIONS The authors did not have access to the base data used to compile various prediction tools. CONCLUSION The LifeMath.net prediction tool is the most reliable for clinicians in counselling patients with newly diagnosed primary cutaneous melanoma regarding their survival prospects.
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Affiliation(s)
- A Dixon
- Australasian College of Cutaneous Oncology, Victoria, Melbourne, Australia
| | - H K Steinman
- Campbell University, Buies Creek, North Carolina, USA
| | - A Kyrgidis
- Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - H Smith
- Oxford Dermatology, Western Australia, Perth, Australia
| | - M Sladden
- University of Tasmania, Tasmania, Launceston, Australia
| | - C Zouboulis
- Staedtisches Klinikum Dessau, Brandenburg Medical School, Dessau, Germany
| | - G Argenziano
- Dermatology, University of Campania, Naples, Italy
| | - Z Apalla
- Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - A Lallas
- Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - C Longo
- University of Modena and Reggio Emilia, Modena, Italy
- Azienda Unita Sanitaria Locale, IRCCS di Reggio Emilia, Skin Cancer Center, Regio Emilia, Italy
| | - A Nirenberg
- Australasian College of Cutaneous Oncology, Victoria, Melbourne, Australia
| | - C Popescu
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - T Tzellos
- Arctic University of Norway, Tromsø, Norway
| | - L Cleaver
- AT Still University, Missouri, Kirksville, USA
| | - C Zachary
- University of California Irvine, California, Irvine, USA
| | - S Anderson
- Australasian College of Cutaneous Oncology, Victoria, Melbourne, Australia
| | - J M Thomas
- Formerly of Royal Marsden Hospital, Chelsea, London, UK
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9
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Tripathi R, Larson K, Fowler G, Han D, Vetto JT, Bordeaux JS, Yu WY. A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma. Ann Surg Oncol 2023; 30:4321-4328. [PMID: 36840860 PMCID: PMC9961302 DOI: 10.1245/s10434-023-13220-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/24/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Although sentinel lymph node biopsy (SLNB) status is a strong prognostic indicator for cutaneous melanoma, unnecessary SLNBs have substantial cost and morbidity burden. OBJECTIVE This study was designed to develop, validate, and present a personalized, clinical, decision-making tool using nationally representative data with clinically actionable probability thresholds (Expected Lymphatic Metastasis Outcome [ELMO]). METHODS Data from the Surveillance, Epidemiology, and End Results (SEER) Registry from 2000 to 2017 and the National Cancer Database (NCDB) from 2004 to 2015 were used to develop and internally validate a logistic ridge regression predictive model for SLNB positivity. External validation was done with 1568 patients at a large tertiary referral center. RESULTS The development cohort included 134,809 patients, and the internal validation cohort included 38,518 patients. ELMO (AUC 0.85) resulted in a 29.54% SLNB reduction rate and greater sensitivity in predicting SLNB status for T1b, T2a, and T2b tumors than previous models. In external validation, ELMO had an accuracy of 0.7586 and AUC of 0.7218. Limitations of this study are potential miscoding, unaccounted confounders, and effect modification. CONCLUSIONS ELMO ( https://melanoma-sentinel.herokuapp.com/ ) has been developed and validated (internally and externally) by using the largest publicly available dataset of melanoma patients and was found to have high accuracy compared with other published models and gene expression tests. Individualized risk estimates for SLNB positivity are critical in facilitating thorough decision-making for healthcare providers and patients with melanoma.
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Affiliation(s)
- Raghav Tripathi
- Department of Dermatology, Johns Hopkins Medicine, Baltimore, MD, USA.
| | | | - Graham Fowler
- Department of Surgery, Oregon Health and Science University, Portland, OR, USA
| | - Dale Han
- Department of Surgery, Oregon Health and Science University, Portland, OR, USA
| | - John T Vetto
- Department of Surgery, Oregon Health and Science University, Portland, OR, USA
| | - Jeremy S Bordeaux
- Department of Dermatology, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, OH, USA
| | - Wesley Y Yu
- Department of Dermatology, Oregon Health and Science University, Portland, OR, USA
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Hosein S, Drebin HM, Kurtansky NR, Bagge RO, Coit DG, Bartlett EK, Marchetti MA. Are the MIA and MSKCC nomograms useful in selecting patients with melanoma for sentinel lymph node biopsy? J Surg Oncol 2023; 127:1167-1173. [PMID: 36905337 PMCID: PMC10147582 DOI: 10.1002/jso.27231] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 02/26/2023] [Indexed: 03/12/2023]
Abstract
BACKGROUND AND METHODS The Melanoma Institute of Australia (MIA) and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms were developed to help guide sentinel lymph node biopsy (SLNB) decisions. Although statistically validated, whether these prediction models provide clinical benefit at National Comprehensive Cancer Network guideline-endorsed thresholds is unknown. We conducted a net benefit analysis to quantify the clinical utility of these nomograms at risk thresholds of 5%-10% compared to the alternative strategy of biopsying all patients. External validation data for MIA and MSKCC nomograms were extracted from respective published studies. RESULTS The MIA nomogram provided added net benefit at a risk threshold of 9% but net harm at 5%-8% and 10%. The MSKCC nomogram provided added net benefit at risk thresholds of 5% and 9%-10% but net harm at 6%-8%. When present, the magnitude of net benefit was small (1-3 net avoidable biopsies per 100 patients). CONCLUSION Neither model consistently provided added net benefit compared to performing SLNB for all patients. DISCUSSION Based on published data, use of the MIA or MSKCC nomograms as decision-making tools for SLNB at risk thresholds of 5%-10% does not clearly provide clinical benefit to patients.
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Affiliation(s)
- Sharif Hosein
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Harrison M. Drebin
- Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Nicholas R. Kurtansky
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Roger Olofsson Bagge
- Department of Surgery, Sahlgrenska University Hospital, Sweden
- Sahlgrenska Center for Cancer Research, Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Sweden
| | - Daniel G. Coit
- Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Edmund K. Bartlett
- Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Michael A. Marchetti
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
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Wang Z, Liu J, Han J, Yang Z, Wang Q. Analysis of prognostic factors of undifferentiated pleomorphic sarcoma and construction and validation of a prediction nomogram based on SEER database. Eur J Med Res 2022; 27:179. [PMID: 36109828 PMCID: PMC9479354 DOI: 10.1186/s40001-022-00810-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/06/2022] [Indexed: 11/10/2022] Open
Abstract
Background Undifferentiated pleomorphic sarcoma (UPS) is considered one of the most common types of soft tissue sarcoma (STS). Current studies have shown that the prognosis of UPS is related to some of its clinical characteristics, but no survival prediction model for the overall survival (OS) of UPS patients has been reported. The purpose of this study is to construct and validate a nomogram for predicting OS in UPS patients at 3, 5 years after the diagnosis. Methods According to the inclusion and exclusion criteria, 1079 patients with UPS were screened from the SEER database and randomly divided into the training cohort (n = 755) and the validation cohort (n = 324). Patient demographic and clinicopathological characteristics were first described, and the correlation between the two groups was compared, using the Kaplan–Meier method and Cox regression analysis to determine independent prognostic factors. Based on the identified independent prognostic factors, a nomogram for OS in UPS patients was established using R language. The nomogram’s performance was then validated using multiple indicators, including the area under the receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, and decision curve analysis (DCA). Results Both the C-index of the OS nomogram in the training cohort and the validation cohort were greater than 0 .75, and both the values of AUC were greater than 0.78. These four values were higher than their corresponding values in the TNM staging system, respectively. The calibration curves of the Nomogram prediction model and the TNM staging system were well fitted with the 45° line. Decision curve analysis showed that both the nomogram model and the TNM staging system had clinical net benefits over a wide range of threshold probabilities, and the nomogram had higher clinical net benefits than the TNM staging system as a whole. Conclusion With good discrimination, accuracy, and clinical practicability, the nomogram can individualize the prediction of 3-year and 5-year OS in patients with UPS, which can provide a reference for clinicians and patients to make better clinical decisions.
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Predicting outcomes from sentinel node biopsy for melanoma in the UK: Is the MIA nomogram the answer? J Plast Reconstr Aesthet Surg 2022; 75:1497-1520. [DOI: 10.1016/j.bjps.2022.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 01/09/2022] [Indexed: 11/19/2022]
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Weitemeyer MB, Helvind NM, Brinck AM, Hölmich LR, Chakera AH. More sentinel lymph node biopsies for thin melanomas after transition to AJCC 8th edition do not increase positivity rate: A Danish population-based study of 7148 patients. J Surg Oncol 2021; 125:498-508. [PMID: 34672372 DOI: 10.1002/jso.26723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 10/11/2021] [Accepted: 10/15/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND We evaluated the outcome of sentinel lymph node biopsies (SLNB) in patients with thin melanoma before and after the implementation of AJCC 8th edition (AJCC8) and identified predictors of positive sentinel lymph nodes (+SLN). METHODS Patients diagnosed with T1 melanomas (Breslow thickness ≤1 mm) during 2016-2017 as per AJCC 7th edition (AJCC7) (n = 3414) and 2018-2019 as per AJCC8 (n = 3734) were identified in the Danish Melanoma Database. RESULTS More SLNBs were performed in the AJCC8 cohort compared to the AJCC7 (22.2% vs. 16.2%, p < 0.001), with no significant difference in +SLN rates (4.7% vs. 6.7%, p = 0.118). In the AJCC7 + SLN subgroup, no melanomas were ulcerated, 94.6% had mitotic rate (MR) ≥ 1, 67.6% were ≥0.8 mm and 32.4% would be T1a according to AJCC8. In the AJCC8 + SLN subgroup, 10.3% were ulcerated, 74.4% had MR≥ 1, 97.4% were ≥0.8 mm and 23.1% would be T1a according to AJCC7. On multivariable analysis younger age and MR ≥ 1 were significant predictors of +SLN. CONCLUSION More SLNBs were performed in T1 melanomas after transition to AJCC8 without an increase in +SLN rate. None of the AJCC8 T1b criteria were significant predictors of +SLN. We suggest that mitosis and younger age should be considered as indications for SLNB in thin melanoma.
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Affiliation(s)
- Marie B Weitemeyer
- Department of Plastic and Reconstructive Surgery, Herlev and Gentofte University Hospital, Herlev, Denmark
| | - Neel M Helvind
- Department of Plastic and Reconstructive Surgery, Herlev and Gentofte University Hospital, Herlev, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Anne M Brinck
- Department of Plastic and Reconstructive Surgery, Herlev and Gentofte University Hospital, Herlev, Denmark
| | - Lisbet R Hölmich
- Department of Plastic and Reconstructive Surgery, Herlev and Gentofte University Hospital, Herlev, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Annette H Chakera
- Department of Plastic and Reconstructive Surgery, Herlev and Gentofte University Hospital, Herlev, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
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