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Reducing workload in malignant melanoma sentinel node examination: a national study of pathology reports from 507 melanoma patients

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Aims Even though extensive melanoma sentinel node (SN) pathology protocols increase metastasis detection, there is a need for balancing high detection rates with reasonable workload. A newly tested Danish protocol… Click to show full abstract

Aims Even though extensive melanoma sentinel node (SN) pathology protocols increase metastasis detection, there is a need for balancing high detection rates with reasonable workload. A newly tested Danish protocol recommended examining nodes at six levels 150 µm apart (six-level model) and using SOX10 and Melan-A immunohistochemistry (IHC). We explored if a protocol examining 3 levels 300 µm apart (three-level model) combined with IHC would compromise metastasis detection. The study aim was to optimise the protocol to reduce workload without compromising detection rate. Methods 8 months after protocol implementation, we reviewed the pathology reports of SNs from 507 melanoma patients nationwide, including 117 SN-positive patients. Each report was reviewed to determine histopathological features, including detection of metastasis, exact levels with metastasis, exact levels with metastasis >1 mm in diameter and IHC results. Results The six-level model detected metastases in 23% of patients, whereas the three-level model would have detected metastases in 22% of patients. The three-level model would have missed a few small metastases (n=4), measuring <0.1 mm, 0.1 mm, 0.4 mm and 0.1 mm, respectively. The six-level model detected metastases >1 mm in 7% of patients. One of these metastases (measuring 1.1 mm) would have been detected by the three-level model, but not as >1 mm. SOX10 and Melan-A had equal sensitivity. Conclusions Reducing the number of levels examined to three levels 300 µm apart combined with IHC does not have significant impact on metastasis detection rate, and we will therefore recommend that the future melanoma SN guideline takes this into consideration to reduce overall workload.

Keywords: level model; melanoma; pathology; detection; workload

Journal Title: Journal of Clinical Pathology
Year Published: 2023

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