# The Impact of Next‐Generation Sequencing on Interobserver Agreement and Diagnostic Accuracy of Deep Penetrating Melanocytic Neoplasms

**Authors:** Julia Edwin Jeyakumar, Afua Konadu Addo, Haya Mary Beydoun, Shantel Olivares, Armita Bahrami, Thiagarajah Balamurugan, Raymond L. Barnhill, Willeke A. M. Blokx, Klaus J. Busam, Lorenzo Cerroni, Martin Cook, Arnaud de La Fouchardière, Lyn M. Duncan, David E. Elder, Peter Ferguson, Gerardo Ferrara, Iva Johansson, Jennifer S. Ko, Ji Eun Kwon, Gilles Landman, Cecilia Lezcano, Lori Lowe, Daniela Massi, Jane Messina, Daniela Mihic‐Probst, Douglas C. Parker, Margaret Redpath, Michael R. Sargen, Richard A. Scolyer, Christopher R. Shea, Michael Tetzlaff, Carlos Torres‐Cabala, Victor Tron, Xiaowei Xu, Iwei Yeh, Sook Jung Yun, Artur Zembowicz, Pedram Gerami

PMC · DOI: 10.1111/cup.70049 · Journal of Cutaneous Pathology · 2025-12-23

## TL;DR

Next-generation sequencing improves agreement and accuracy in diagnosing deep melanocytic tumors, though it occasionally leads to misdiagnoses.

## Contribution

Demonstrates how NGS impacts diagnostic accuracy and interobserver agreement in challenging melanocytic neoplasm cases.

## Key findings

- Interobserver agreement improved from 0.41 to 0.51 with NGS data.
- Diagnostic accuracy increased, especially for DPN-M, with a 16% improvement.
- 218 diagnostic changes occurred, with 132 moving toward correct diagnoses and 86 toward incorrect ones.

## Abstract

Next‐generation sequencing (NGS) is becoming more commonly used for diagnosis in dermatopathology. It's critical to appraise its efficacy and limitations. Distinguishing benign deep penetrating nevi (DPN) from deep penetrating like‐melanoma (DPN‐M) is a challenging diagnostic scenario even for experienced dermatopathologists.

We sent a two‐phase survey (pre‐and postgenomics) to 32 experienced dermatopathologists to evaluate 39 diagnostically challenging cases from the DPN/WNT‐activated family of melanocytic neoplasms.

With NGS data, interobserver agreement improved from 0.41 to 0.51 (p < 0.0001) in distinguishing DPN‐M from nonmelanoma cases. Overall diagnostic accuracy improved, mostly driven by a 16% increase in accurate diagnosis of DPN‐M. However, in two cases, the inclusion of genomics shifted the majority vote from a correct to an incorrect diagnosis. A total of 218 diagnostic changes occurred between Survey 1 and 2. Among the changes, 132 votes moved toward the correct diagnosis while 86 moved toward an incorrect diagnosis. The shift in voting which resulted in improved diagnostic accuracy was statistically significant (p = 0.0001).

NGS has the potential to improve interobserver agreement and diagnostic accuracy. We provide guidance on the utilization of bioinformatic data to maximize its benefits and improve diagnostic accuracy and interobserver agreement.

## Linked entities

- **Diseases:** melanoma (MONDO:0005105)

## Full-text entities

- **Diseases:** DPN-M (MESH:D008545), DPN (MESH:D009506), Melanocytic Neoplasms (MESH:D009369)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12867587/full.md

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12867587/full.md

## References

16 references — full list in the complete paper: https://tomesphere.com/paper/PMC12867587/full.md

---
Source: https://tomesphere.com/paper/PMC12867587