Novel Algorithm May Help to Identify Aggressive Basal Cell Carcinoma

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A novel algorithm may help physicians to identify which patients have a highly aggressive subtype of facial basal cell carcinoma, according to a recent study published by Ceder et al in Dermatology Practical & Conceptual.  


Basal cell carcinoma—the most common type of skin cancer—grows slowly and almost never metastasizes to other parts of the body. Although most basal cell carcinomas may be cured, without treatment, highly aggressive subtypes can progress and cause significant morbidity.

Mohs micrographic surgery allows for complete examination of all tissue margins, ensuring complete removal of basal cell carcinoma tumors and sparing as much healthy tissue as possible. While the patient is under local anesthesia, pathologists analyze the tissue samples to be certain the tumor has been completely removed prior to closing the surgical wound.

“Mohs micrographic surgery gives us full control of the margins while preserving healthy tissue. We have shown in a previous study that in patients with highly aggressive [basal cell carcinoma] of the nose, traditional surgery fails to remove the entire tumor in over half of the cases,” stressed lead study author Hannah Ceder, MD, a PhD student at the University of Gothenburg and a specialist physician in the Department of Dermatology and Venereology at Sahlgrenska University Hospital.

With other surgeries, there is a risk the procedure may need to be repeated, because the pathologist may find residual tumor cells in the tumor margins. However, the wait times for Mohs micrographic surgery may be long.  

Study Methods and Results

In the recent study, researchers used clinical and dermoscopic images from Sahlgrenska University Hospital to identify nearly 300 patients with confirmed facial basal cell carcinoma tumors. The images and findings were then reviewed and interpreted by six independent experienced dermatologists—which were used as the basis for the development of a novel clinical algorithm designed to discriminate between less and more aggressive subtypes of basal cell carcinoma.

The researchers discovered that basal cell carcinoma tumors with a bumpy surface, poorly defined borders, and a presence of a lighter area (called the white porcelain area) were associated with high-risk subtypes of the disease. Further, small blood vessels in the ulceration were also found to be characteristic of the more aggressive subtype of basal cell carcinoma, which was not previously known. They emphasized that the clinical algorithm identified most cases of high-risk basal cell carcinoma and demonstrated a high positive predictive value.


The researchers suggested that if more basal cell carcinomas are correctly identified as high risk, patients can receive the most effective treatments. They plan to revalidate the novel clinical algorithm in a prospective study to investigate its usefulness in a real-world clinical setting.

“It is desirable to develop simple preoperative methods that help [physicians] in identifying these high-risk tumors. Therefore, our clinical algorithm is relevant and important,” underscored Dr. Ceder. “This would make it easier to determine which tumors can be easily removed with traditional surgery without a prior biopsy and which ones require further investigation to screen out the cases that require Mohs micrographic surgery,” she concluded.

Disclosure: For full disclosures of the study authors, visit

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