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    Guide to ID at-risk patients

    First risk model for cutaneous squamous cell carcinoma metastasis

    A recent study put forth the first metastatic risk model for cutaneous squamous cell carcinoma (cSCC), a utility that could significantly help clinicians better identify which patients may be at risk for metastasis, enabling the initiation of timely aggressive management to improve outcomes. 

    Cutaneous squamous cell carcinoma is one of the most common cancers capable of metastasis. Invasive cSCC refers to cancer cells that have grown beyond the epidermis. Cutaneous squamous cell carcinoma is the second most common cancer diagnosed, and there has been an alarming increase in global incidence. The rate of metastasis is relatively rare. However, in cases where metastasis occurs, the disease course has significant morbidity. 

    For the majority of patients diagnosed with cSCC, the disease is largely curable using techniques such as Mohs surgery or wide local excision. However, in the high-risk subgroup, an increasing number of people are requiring very extensive and potentially disfiguring surgery, which could negatively impact quality of life. 

    “It would be ideal if we could identify these higher-risk patients earlier, recognize the potential for a given SCC to metastasize, and accordingly choose appropriate aggressive therapies to optimally treat these tumors in a timely fashion,” says Brandon T. Beal, M.D., a dermatologist in the department of dermatology at Cleveland Clinic. Dr. Beal is a co-author of the study which was published in the first issue of Skin: The journal of cutaneous medicine (July 2017).

    THE STUDY

    Due to its high incidence and lack of inclusion in national databases, Dr. Beal says it has been very challenging to identify high-risk factors for cSCC associated with metastasis. He and colleagues recently conducted a study to explore a variety of different statistical approaches for developing a model to predict cSCC metastasis accurately, and that reflects routine clinical practice. 

    The study analysis included all of the cSCCs (n=800) diagnosed and treated at Saint Louis University from January 2010 to March 2012. Dermatology diagnosed, managed, and/or treated 93.4% of the tumors. 

    Researchers identified six risk factors associated with metastatic cSCC, including poorly or moderately differentiated histology (OR: 5.88), anatomic location (OR: 4.11), size in context of location (OR: 4.01), rapidly growing (OR: 3.03), recurrent (OR: 2.71), and perineural invasion (OR: 2.03).

    “This is an affirmation of what is being done in centers that treat high-risk skin cancer. This metastatic risk model offers clinicians a novel approach to calculate the risk of metastatic disease in their patients with cSCC, and could assist them in identifying high-risk patients early,” Dr. Beal says. 

    The three statistical approaches that were studied included: Multivariable logistic regression (MLR), pattern classification (PC), and sum score method (SSM). 

    Two models using the SSM were created with a different number of factors used to merit assignment to the metastatic cohort: Two factors (S2) or greater than two factors (S2+). For each model, sensitivity (SN), specificity (SP), and positive predictive value (PPV) were calculated. 

    Results showed that the PC model was the most accurate predicting metastasis. The SN, SP, and PPV for each model were: MLR: SN 4.3%, SP 97.4%, PPV 16%; S2: SN 78.3%, SP 83.7%, PPV 12.5%; S2+: SN 60.9%, SP 96.5%, PPV 34.1%; PC: SN 73.9%, SP 95.9%, and PPV 34.7%, respectively.

    NEXT: Guidelines

     

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