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DOI 10.1002/jso.25193

Медицинская библиотека · Journal of surgical oncology · 2018

A model for predicting low probability of nonsentinel lymph node positivity in melanoma patients with a single positive sentinel lymph node.

Bhutiani Neal, Egger Michael E, Stromberg Arnold J, Gershenwald Jeffrey E, Ross Merrick I, Philips Prejesh, Martin Robert C G, Scoggins Charles R, McMasters Kelly M

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Аннотация

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.

Для цитирования: Bhutiani Neal, Egger Michael E, Stromberg Arnold J, Gershenwald Jeffrey E, Ross Merrick I, Philips Prejesh, Martin Robert C G, Scoggins Charles R, McMasters Kelly M. A model for predicting low probability of nonsentinel lymph node positivity in melanoma patients with a single positive sentinel lymph node.. Journal of surgical oncology. 2018. DOI: 10.1002/jso.25193.

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