TY - JOUR
T1 - A model for predicting low probability of nonsentinel lymph node positivity in melanoma patients with a single positive sentinel lymph node
AU - Bhutiani, Neal
AU - Egger, Michael E.
AU - Stromberg, Arnold J.
AU - Gershenwald, Jeffrey E.
AU - Ross, Merrick I.
AU - Philips, Prejesh
AU - Martin, Robert C.G.
AU - Scoggins, Charles R.
AU - McMasters, Kelly M.
N1 - Publisher Copyright:
© 2018 Wiley Periodicals, Inc.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Background: Identifying factors associated with nonsentinel lymph node (NSN) metastases in melanoma patients with a single positive sentinel lymph node (SLN) could aid decision making regarding adjuvant therapy. We describe a model for identifying patients with a single positive SLN at low risk for NSN metastasis. Methods: Factors associated with NSN metastasis in patients with a primary cutaneous melanoma and a single positive SLN who underwent completion lymph node dissection (CLND) were identified. These factors were used to construct a model for predicting the NSN status. The model was validated using a separate data set from another tertiary referral cancer center. Results: In the training data set, 111 patients had a single positive SLN. Of these, 27 had positive NSN. SLN tumor deposit diameter ≥0.75 mm (OR, 3.43; P = 0.047), age ≥40 (OR, 12.14; P = 0.024), and multifocal SLN tumor deposit location (OR, 4.16; P = 0.0096) were independently associated with NSN positivity. Patients with 0 to 1 of these risk factors had a low risk of NSN metastasis in both the training (7.5%) and validation (4.6%) data sets. Conclusions: A combination of patient and SLN tumor burden characteristics can help to identify patients with a single positive SLN who are at a low risk of NSN metastasis.
AB - Background: Identifying factors associated with nonsentinel lymph node (NSN) metastases in melanoma patients with a single positive sentinel lymph node (SLN) could aid decision making regarding adjuvant therapy. We describe a model for identifying patients with a single positive SLN at low risk for NSN metastasis. Methods: Factors associated with NSN metastasis in patients with a primary cutaneous melanoma and a single positive SLN who underwent completion lymph node dissection (CLND) were identified. These factors were used to construct a model for predicting the NSN status. The model was validated using a separate data set from another tertiary referral cancer center. Results: In the training data set, 111 patients had a single positive SLN. Of these, 27 had positive NSN. SLN tumor deposit diameter ≥0.75 mm (OR, 3.43; P = 0.047), age ≥40 (OR, 12.14; P = 0.024), and multifocal SLN tumor deposit location (OR, 4.16; P = 0.0096) were independently associated with NSN positivity. Patients with 0 to 1 of these risk factors had a low risk of NSN metastasis in both the training (7.5%) and validation (4.6%) data sets. Conclusions: A combination of patient and SLN tumor burden characteristics can help to identify patients with a single positive SLN who are at a low risk of NSN metastasis.
KW - cutaneous melanoma
KW - nonsentinel lymph nodes
KW - predictive model
KW - sentinel lymph node (SLN) positive melanoma
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U2 - 10.1002/jso.25193
DO - 10.1002/jso.25193
M3 - Article
C2 - 30259521
AN - SCOPUS:85053924110
SN - 0022-4790
VL - 118
SP - 922
EP - 927
JO - Journal of Surgical Oncology
JF - Journal of Surgical Oncology
IS - 6
ER -