“Prediction without Pigment: a decision algorithm for non-pigmented skin malignancy” proposes a new algorithm for diagnosing non-pigmented skin malignancies. Non-pigmented skin malignancies are challenging for clinicians, as they lack the visual cues of pigmented lesions. The authors present an algorithm that incorporates clinical features such as patient age, gender, and lesion characteristics, as well as diagnostic tools such as dermoscopy and reflectance confocal microscopy, to aid in diagnosing non-pigmented skin malignancies.
The authors discuss the potential benefits of this algorithm in aiding in the early diagnosis and treatment of non-pigmented skin malignancies. They suggest this algorithm could lead to more accurate diagnoses and fewer unnecessary biopsies, reducing the burden on patients and the healthcare system. Additionally, the authors suggest that this algorithm could be used to improve clinician confidence in making diagnoses of non-pigmented skin malignancies. Overall, the paper highlights the importance of developing new diagnostic tools and algorithms for diagnosing non-pigmented skin malignancies and underscores the potential benefits of such tools in improving patient outcomes.
While there are several published comprehensive stepwise algorithmic methods for diagnosing pigmented skin malignancy, only limited material has been published for the stepwise assessment of non-pigmented lesions. We present a method based on pattern analysis, with a stepwise assessment, first, for ulceration, second, for white clues (defined as white lines, or in the case of a raised lesion, any of the keratin clues: dermatoscopic white circles, dermatoscopic white structureless areas or surface keratin), and third, if no ulceration or white clues are present, proceed to vessel pattern analysis.
This is a novel method, and apart from the assessment of white clues in raised lesions, it has not been formally tested. However, the priority of keratin clues in raised lesions over vessel pattern analysis has been verified.
It is conceded that this method is less specific than those with clues of pigmented structures. By accepting these limitations, Prediction without Pigment is a decision algorithm that guides the clinician in deciding whether to perform a biopsy rather than consistently leading to a specific diagnosis. Reaching a more specific diagnosis at the end of our flowchart can be achieved by weighing of clues both clinical and dermatoscopic. That ability can be expected to improve with both knowledge and experience, but no diagnostic method, including this one, can be 100% sensitive in diagnosing malignancy, in particular melanoma. Considering these limitations, any non-pigmented lesion, regardless of pattern analysis, which is raised and firm (nodular) and for which a confident, specific benign diagnosis cannot be made, should be excised to exclude the nodular variant of amelanotic melanoma.
This small series supports what is already known: that a significant proportion of NMs may be dermatoscopically symmetrical but known clues to melanoma are frequently present. Nodular lesions, pigmented or non-pigmented, should be excised to exclude NM if there is any clue to malignancy, regardless of symmetry, unless a confident specific benign diagnosis can be made.
Rosendahl C, Cameron A, Tschandl P, Bulinska A, Zalaudek I, Kittler H. Prediction without Pigment: a decision algorithm for non-pigmented skin malignancy. Dermatol Pract Concept. 2014 Jan 31;4(1):59-66. doi: 10.5826/dpc.0401a09. PMID: 24520516; PMCID: PMC3919842.