Clinical Reference / Dermatology Practical & Conceptual / July 2012 | Volume 2, No. 3 / Accuracy of the first step of the dermatoscopic 2-step algorithm for pigmented skin lesions

Accuracy of the first step of the dermatoscopic 2-step algorithm for pigmented skin lesions

July 2012 | Volume 2, No. 3

Philipp Tschandl, M.D.1, Cliff Rosendahl, MBBS2, Harald Kittler, M.D.1

1Department of Dermatology, Division of General Dermatology, Medical University of Vienna, Austria 2School of Medicine, University of Queensland, Brisbane, Australia

Citation: Tschandl P, Rosendahl C, Kittler H. Accuracy of the first step of the dermatoscopic 2-step algorithm for pigmented skin lesions. Dermatol Pract Conc. 2012;2(3):8.

History: Received: January 23, 2012. Accepted: May 31, 2012. Published: July 31, 2012.

Copyright: ©2012 Tschandl et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: None.

Competing interests: The authors have no conflicts of interest to disclose.

Corresponding Author: Harald Kittler, M.D., Department of Dermatology, Division of General Dermatology, Medical University of Vienna, WÄhringer GÜrtel 18-20, 1090 Vienna, Austria. M.D. Tel. +43.1.40400.7700. Email:


Objectives: To evaluate the frequency of misclassifications of equivocal pigmented lesions according to the first step of the dermatoscopic 2-step algorithm.

Patients and Methods: 707 consecutive cases from 553 patients of central Europe and Australia were included in the study. Dermatoscopic images were evaluated in a blinded fashion for the presence of features described in the 2-step algorithm to determine their melanocytic or non-melanocytic origin. Mucosal, genital and non-pigmented lesions were excluded.

Results: The sensitivity of the first step was 97.1% for patients from Australia and 96.8% for patients from central Europe. The specificity was 33.6% for Australian patients and 67.9% for European patients. The most common reasons for misclassification were the presence of a pigmented network in a non-melanocytic lesion (n=68, 25.2%) and the absence of dermatoscopic features of melanocytic and non-melanocytic lesions in 69 (25.6%) non-melanocytic lesions.

Conclusion: The first step of the dermatoscopic 2-step algorithm, if applied consistently, has high sensitivity but low specificity. Many non-melanocytic lesions, especially solar lentigines and seborrheic keratoses, are wrongly classified as melanocytic. The worse performance of the first step algorithm in Australian patients is probably due to a higher rate of solar lentigines in patients with severely sun-damaged skin.


Dermatoscopy improves diagnostic accuracy for melanocytic [1, 2] and non-melanocytic [3] skin lesions. Several diagnostic algorithms have been created [4-8] and tested [4-10]. Nearly all of them have been designed to distinguish between benign and malignant melanocytic lesions and are based on the 2-step method [9,10]. The 2-step method requires differentiation between melanocytic and non-melanocytic lesions in a first step. The 2-step algorithm was reviewed and confirmed by leading experts in the field [9] and is widely accepted in teaching dermatoscopy. Nevertheless, the first step especially runs the major risk of misclassification and can therefore lead to wrong diagnoses eventually, regardless of how good the algorithm of the second step is.

A few publications have reported single dermatoscopic features of the first step to be prone to misclassification [11,12], but the overall rate and reasons for wrong classifications have not been reported yet and this is the aim of this study.

Patients and methods

The cases originated from a tertiary referral center at a university hospital in Europe (Department of Dermatology, Medical University of Vienna) and from the Primary Skin Cancer Clinic in Brisbane, Australia. All documented cases between December 28, 2006, and May 20, 2009, were collected. Mucosal and genital non-pigmented lesions and cases without histopathologic diagnosis were excluded.

Dermatoscopic images were evaluated in a blinded fashion by two of the authors (P.T., H.K.) for the presence of every melanocytic and non-melanocytic feature described in the 2-step algorithm [9]. A lesion was regarded of melanocytic origin if either at least one melanocytic feature was present or no dermatoscopic feature was present at all (“melanocytic by default”). If no melanocytic but at least one non-melanocytic feature was present a lesion was classified non-melanocytic. Lesions histologically proven to be a collision lesion of both origins were histologically classified as melanocytic.

Devices used for taking dermatoscopic images were a DermLite Foto® (polarized imaging) and a DermLite Fluid® (non-polarized imaging). Pictures were taken at standard magnification (10x) and magnification encompassing the whole lesion. Images used for evaluation were in a JPEG format, had a resolution of at least 300 dots per inch, and a size not smaller than 800 x 600 pixels.

Statistical analysis

Sensitivity was calculated by dividing the number of correctly identified melanocytic lesions (according to the first step) with the total number of melanocytic lesions. Specificity was calculated by dividing the number of correctly identified non-melanocytic lesions (according to the first step) by the total number of non-melanocytic lesions. Continuous data are given as mean and standard deviation unless otherwise specified. Sensitivity, specificity, positive and negative predictive values were calculated according to standard formula.


General data

We included 702 consecutive cases from 548 patients (mean age 54.6 ±18.0 years, 59.9% males), of whom 331 (60%) were from Australia and 217 (40%) from Central Europe. Two hundred and seventy (39%) of the cases were non-melanocytic, 432 (61%) melanocytic, and the frequencies of histologic diagnoses are shown in Table 1. The lesions were located on head or neck in 18.4%, on the trunk in 45.7%, on the upper extremities in 11.8%, on the lower extremities in 19.4% and on acral sites in 2.7% (Figure 1).

Table 1. Frequencies of diagnosis according to study center

Figure 1. Distribution of lesions regarding body site and geographic origin. Given frequencies are calculated within each geographic group. [Copyright: ©2012 Tschandl et al.]

Accuracy of the first step

The sensitivity of the first step was 97.1% for patients from Australia and 96.8% for patients form Central Europe. The specificity was 33.6% for Australian patients and 67.9% for European patients. The positive and negative predictive values for melanocytic lesions were 0.62 and 0.91 for Australian and 0.91 and 0.85 for European patients, respectively.


The most common reasons for misclassification were a pigmented network in 69 (25.6%) non-melanocytic lesions (Figure 2) and an absence of any given non-melanocytic features (“melanocytic by default”) in 74 (27.4%) non-melanocytic lesions (Figure 3). A list of dermatoscopic features leading to misclassifications can be found in Table 2. Seven percent (n=13) of misdiagnosed lesions were melanocytic but misclassified as non-melanocytic and 161 (92.5%) non-melanocytic were misclassified as melanocytic. Seborrheic keratoses and solar lentigines were most commonly misclassified. The frequencies of misclassification by feature are given in Table 3. Table 4 shows the positive predictive value by feature.

Figure 2. Pigmented network leading to a wrong classification. (A) Seborrheic keratosis. (B) Solar lentigo. (C) Seborrheic keratosis. (D) Solar lentigo. [Copyright: ©2012 Tschandl et al.]

Figure 3. An absence of any specific melanocytic or non-melanocytic (“melanocytic by default”) features, leading to a wrong classification. (A & B) Pigmented Bowen’s disease. (C & D) Seborrheic keratosis. [Copyright: ©2012 Tschandl et al.]

Table 2. Conflicting criteria in misclassified non-melanocytic lesions.

Table 3. Conflicting criteria in misclassified melanocytic lesions.

Table 4. Positive predictive values for melanocytic lesion according to feature.


In this study we show that the accuracy of the first step of dermatoscopy is only moderate. It is very sensitive for melanocytic lesions but has low specificity. In other words, if the first step for dermatoscopy is used in the way it has been suggested many non-melanocytic lesions would be incorrectly classified as melanocytic lesions. The main reason for this is that criteria like the “pigment network” or “aggregated brown globules” are not specific to melanocytic lesions. Of 380 lesions with a pigment network, 69 (18.2%) were non-melanocytic. Of 96 lesions with “aggregated brown globules,” 19 (19.8%) were non-melanocytic. Many seborrheic keratoses and most solar lentigines have a pigment network when viewed by dermatoscopy. This comes as no surprise because the reticular lines of the pigment network are due to hyperpigmentation of basal keratinocytes, which is common in seborrheic keratoses and a hallmark of solar lentigo. The high number of misclassified lesions with aggregated globules is more surprising. Most of them were seborrheic keratoses (n=8) and basal cell carcinomas (n=6) and one reason for their misclassifications might be the ambiguous distinction in the definition of terms of “aggregated globules” and “multiple blue-gray globules.”

Another common reason for misclassification was the absence of either melanocytic or non-melanocytic criteria. According to the rules of the first step, these lesions should be classified as melanocytic by default. However, 68.5% of pigmented lesions without any specific criteria were not melanocytic and would be classified incorrectly. The misclassification of non-melanocytic as melanocytic lesions was more common than the other way round. Only 13 melanocytic lesions (7.5%) were incorrectly classified as non-melanocytic because of the absence of a pigment network or brown globules and the presence of criteria for non-melanocytic lesions such as red-bluish to reddish-black homogenous areas (n=4) or milia-like cysts (n=2).

Originally, the differentiation of melanocytic and non-melanocytic lesions (the first step) was not part of pattern analysis. The first step was introduced to simplify dermatoscopy and to exclude non-melanocytic lesions from further analysis by short algorithms like the ABCD rule, the 7-point checklist, Menzies rule, or the CASH algorithm. The reason for introducing the first step probably was that many non-melanocytic lesions, especially seborrheic keratoses, would have been wrongly classified as melanomas. Although a structured approach to the analysis of pigmented skin lesions by dermatoscopy is reasonable, it is simply a matter of convention and convenience how the diagnostic procedure is structured. Simplicity, reproducibility and accuracy are among the most important criteria to evaluate the usefulness of a diagnostic algorithm. Given the fair performance of the first step and the fact that its application is rather complex and not simple, the question is whether its usage is still justified. There is no easy answer to this question because its usage strongly depends on convenience and habit. However, in a person with chronically sun-damaged skin and many solar lentigines the 2-step approach cannot be recommended. We have shown that the risk of misclassification is especially high in individuals from Australia with chronically sun-damaged skin. Solar lentigines are very common in this population [13,14]. Solar lentigines with a pigment network contributed largely to the low positive predictive value of the first step in the Australian group.

The introduction of the 2-step algorithm was partly motivated by the relative importance of melanoma in comparison to non-melanoma skin cancer. However, we hold to the opinion that the differentiation between benign and malignant lesions is a better first step than deciding whether a lesion is melanocytic or non-melanocytic [3]. We prefer a system that differentiates between chaotic and symmetric lesions first. This system is not more accurate but conceptually simpler (Figure 4). Our study has a significant limitation. The authors are very critical with regard to the use of the first step and advocate another method instead [3]. We have tried to minimize any form of bias by blind assessment of the lesions and by selecting consecutive lesions form different parts of the world. We have used the criteria and the algorithm precisely in the way they are advocated. We acknowledge that many seborrheic keratosis or solar lentigines with a pigment network can be diagnosed correctly based on other criteria. We are convinced that experienced dermatoscopists are tacitly aware of the limitations of the first step, i.e., its low specificity in solar lentigines and seborrheic keratosis and that they use other criteria to diagnose these lesions with specificity. However, this is not what the first step tells us to do. According to the first-step algorithm, the presence of a “pigment network” trumps all other criteria and thus would lead to a wrong diagnosis if used in a pedantic fashion.

Figure 4. Difference between 2-step algorithm (A) versus “chaos and clues” algorithm (B). [Copyright: ©2012 Tschandl et al.]


The first step of the dermatoscopic 2-step algorithm, if applied consistently, has high sensitivity but low specificity especially in patients with severely sun-damaged skin.


1. Kittler H, Pehamberger H, Wolff K, Binder M. Diagnostic accuracy of dermoscopy. Lancet Oncol. 2002;3(3):159-65.

2. Vestergaard ME, Macaskill P, Holt PE, Menzies SW. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol. 2008;159(3):669-76.

3. Rosendahl C, Tschandl P, Cameron A, Kittler H. Diagnostic accuracy of dermatoscopy for melanocytic and nonmelanocytic pigmented lesions. J Am Acad Dermatol. 2011;64(6):1068-73.

4. Argenziano G, Fabbrocini G, Carli P, De Giorgi V, Sammarco E, Delfino M. Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis. Arch Dermatol. 1998;134(12):1563-70.

5. Henning JS, Dusza SW, Wang SQ, et al. The CASH (color, architecture, symmetry, and homogeneity) algorithm for dermoscopy. J Am Acad Dermatol. 2007;56(1):45-52.

6. Nachbar F, Stolz W, Merkle T, et al. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. J Am Acad Dermatol.1994;30(4):551-9.

7. Menzies SW, Ingvar C, Crotty KA, McCarthy WH. Frequency and morphologic characteristics of invasive melanomas lacking specific surface microscopic features. Arch Dermatol. 1996;132(10):1178-82.

8. Soyer HP, Argenziano G, Zalaudek I, et al. Three-point checklist of dermoscopy. A new screening method for early detection of melanoma. Dermatology. 2004;208(1):27-31.

9. Argenziano G, Soyer HP, et al. Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol. 2003;48(5):679-93.

10. Marghoob AA, Braun R. Proposal for a revised 2-step algorithm for the classification of lesions of the skin using dermoscopy. Arch Dermatol. 2010;146(4):426-8.

11. Argenziano G, Rossiello L, Scalvenzi M, et al. Melanoma simulating seborrheic keratosis: a major dermoscopy pitfall. Arch Dermatol. 2003;139(3):389-91.

12. Scope A, Benvenuto-Andrade C, Agero AL, Marghoob AA. Nonmelanocytic lesions defying the two-step dermoscopy algorithm. Dermatol Surg. 2006;32(11):1398-406.

13. Bastiaens M, Hoefnagel J, Westendorp R, Vermeer BJ, Bouwes Bavinck JN. Solar lentigines are strongly related to sun exposure in contrast to ephelides. Pigment Cell Res. 2004;17(3):225-9.

14. Holzle E. Pigmented lesions as a sign of photodamage. Br J Dermatol. 1992;127 Suppl 41:48-50.