BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings

Background: Deciding whether a skin lesion requires biopsy to exclude skin cancer is often challenging for primary care clinicians in Australia. There are several published algorithms designed to assist with the diagnosis of skin cancer but apart from the clinical ABCD rule, these algorithms only evaluate the dermatoscopic features of a lesion. Objectives: The BLINCK algorithm explores the effect of combining clinical history and examination with fundamental dermatoscopic assessment in primary care skin cancer practice. Patients/Methods: Clinical and dermatoscopic images of 50 skin lesions were collected and shown to four primary care practitioners. The cases were assessed by each participant and lesions requiring biopsy were determined on separate occasions using the 3-Point Checklist, the Menzies method, clinical assessment alone and the BLINCK algorithm. Results: The BLINCK algorithm had the highest sensitivity and found more melanomas than any of the other methods. However, BLINCK required more biopsies than the other methods. When comparing diagnostic accuracy, there was no difference between BLINCK, Menzies method and clinical assessment but all were better than the 3-Point checklist. Conclusions: These results suggest that the BLINK algorithm may be a useful skin cancer screening tool for Australian primary care practice.


Introduction
Most GP skin cancer training courses in Australia encourage beginners to use dermatoscopy algorithms when deciding if a lesion requires biopsy to exclude skin cancer. Indeed, the ability to recognise dermatoscopic criteria correctly and apply a dermatoscopic algorithm is often seen as the sine qua non of excellence in primary care skin cancer practice.
The benefits of using a scored "dermatoscopy-only" algorithm are well documented [1,2]. However, this approach does not score often useful clinical information such as history of lesion change, the "ugly duckling" sign [3,4] and even the patient's own instinct regarding the lesion. The authors feel that a more "holistic" diagnostic approach, where these clinical aspects are also scored, may reduce the chances of the student missing less obvious skin cancers.

Methods
We performed a retrospective analytical trial to see if a new algorithm, incorporating clinical as well as dermatoscopic criteria, was any different to the three methods commonly used in Australia primary care practice to diagnose skin cancer.
The new algorithm, BLINCK, was developed and compared to two "dermatoscopy-only" algorithms, (the 3-Point Checklist and the Menzies method), and clinical assessment alone.
The BLINCK algorithm was designed as an assessment tool for primary care skin cancer clinicians and does not require the user to be an "expert" in dermatoscopy. In contrast to most existing algorithms, the distinction between melanocytic and non-melanocytic [5] lesions is not necessary and both pigmented and non-pigmented lesions may be assessed.
The acronym, BLINCK, refers to six questions that should be asked when assessing a skin lesion and includes both clinical and dermatoscopic features. B -Benign: Is the lesion immediately recognisable as a common benign tumour, on clinical and dermatoscopic examination, with other similar lesions being present on that part of the body, e.g., typical solar lentigo, seborrheic keratosis, haemangioma or dermatofibroma? If 'yes', no further action is required.
If 'no', then proceed to the following four questions. L -Lonely: Is this lesion, clinically and dermatoscopically, the only one of its type on that region of the body, i.e., an "outlier" or "ugly duckling"? 'Yes' scores 1. I -Irregular: For pigmented lesions, is the lesion dermatoscopically irregular, that is, does it have an asymmetrical pigmentation pattern and more than one colour? For non-pigmented lesions, is there an irregular vascular pattern? 'Yes' scores 1. N -Nervous: Is the patient nervous or concerned that this particular lesion may be a skin cancer? (This excludes the "generally anxious" patient or patients with hypochondriasis). C -Change: Does the patient, or another observer, feel that the lesion is changing? (Note that only a total score of 1 can be given if either or both of these last two questions are answered 'yes'.) K -Known clues: Does the lesion definitely have any one of the following dermatoscopic "clues" to malignancy?
A total score of 2 or more out of 4 requires biopsy.
To compare BLINCK with the other diagnostic methods a pilot trial was conducted using images of skin lesions typically seen in Australian primary care skin cancer practice. From documented, as well as whether the lesion was thought to be an "ugly duckling" by the original examiner. As common lesions such as the dermatofibroma, seborrhoeic keratosis and congenital naevus sometimes pose a diagnostic challenge for inexperienced clinicians, an example of each, seen during the collection period, was included in the set of 50. These three cases were assessed as being obviously benign by A.C. and not biopsied. As well, a flat naevus that was unchanged on sequential digital monitoring was included in the set without biopsy. Histopathological examination of the other 46 lesions revealed 19 to be skin cancers with nine being melanomas (eight in situ and one invasive). Figures 1 and 2 show an example of a melanoma case from the trial.   4. BLINCK-Dermatoscopic and clinical images were supplied as well as information regarding reported lesion change, "ugly duckling" sign or patient concern as recorded by original examiner.
The clinicians received prior instruction on the use of the three algorithms, and Excel answer sheets for each method listed the various criteria used in that algorithm. The clinicians were asked to decide if these criteria were present or not and the spreadsheet was used to calculate the results. The clinician's response for each case was compared to the correct diagnosis and graded as true positive, false negative, false positive or true negative. The number of cancers and melanomas correctly detected and the number of biopsies indicated for each clinician and each method were also recorded ( Table 1).
Four clinicians using four methods resulted in 16 contingency tables for sensitivity and specificity. As two of the methods related only to pigmented lesions, (3-Point and Menzies), the five non-pigmented specimens in the set of 50 were excluded from the contingency tables for these methods. Specificity, sensitivity and diagnostic accuracy were calculated according to standard formula. Analysis of variance (ANOVA) was used with the LSD test, (least significant difference test), to detect differences between clinicians and methods. A P-value of <0.05 indicated statistical significance.
The means for specificity, sensitivity and diagnostic accuracy are shown with their 95% Confidence Interval, (95% CI). We used the Statistica software package for statistical analysis.

Results
There were no differences between the clinicians regarding sensitivity, specificity, diagnostic accuracy, number of can-  Table 3.
Four clinically benign lesions were included in the set without a histological diagnosis, (dermatofibroma, seborrhoeic keratosis, congenital naevus and monitored flat naevus), and the remainder were subjected to histological examination (Table 4).

Discussion
Australia has the highest rate of melanoma in the world [6].
It is the third most common cancer in Australia in both men and in women [7]. Approximately two out of every three Australians will be diagnosed with skin cancer before the age of 70 [8] and roughly a million GP visits are made annually for skin cancer. This makes skin cancer the most expen-sive of all cancers for the Australian health system [9,10].
More skin cancers are diagnosed and treated in Australia by primary care doctors than by medical specialists [11]. These generalists require a simple yet accurate screening tool that will allow the detection of melanoma and other skin cancers at an early stage when complete cure is possible. Currently, most introductory skin cancer courses in Australia endorse dermatoscopic evaluation of suspicious skin lesions as the preferred screening method, commonly using the 3-Point checklist or the Menzies method [12,13].
Other clinical features that may assist with the diagnosis of skin cancer have been previously studied. The "ugly duck-  ling" sign has been shown to be of possible use in melanoma screening [4]. Importantly, the ability to assess whether a lesion is "different" from surrounding lesions does not appear to require advanced training. Hence, it would seem sensible that primary care clinicians seek out "ugly duckling" lesions when performing a skin examination, ("Lonely" in the BLINCK algorithm). Lesion change is also known to be associated with malignancy, particularly in patients over 50 years of age [14], and consideration of this clinical feature would also seem prudent. A disproportionate amount of concern for a lesion by the patient, ("Nervous"), may have