MolDX: Molecular Biomarker Testing for Risk Stratification of Cutaneous Squamous Cell Carcinoma

Title XVIII of the Social Security Act, §1862(a)(1)(A) allows coverage and payment for only those services that are considered to be reasonable and necessary.

42 CFR §410.32(a) Diagnostic x-ray tests, diagnostic laboratory tests, and other diagnostic tests: Conditions

CMS Internet-Only Manual, Pub. 100-02, Medicare Policy Manual, Chapter 15, §80 Requirements for Diagnostic X-Ray, Diagnostic Laboratory, and Other Diagnostic Tests, §80.1.1 Certification Changes

Current molecular biomarker tests that risk stratify individuals with cutaneous squamous cell carcinoma (cSCC) are non-covered by this contractor.

Clinical Background

Cutaneous squamous cell carcinoma (cSCC) is an epidermal keratinocyte-derived malignancy that is the second most common skin cancer.^1,2 Incidence is increasing and varies with latitude in the United States, with higher incidence in areas of greater sun exposure.³ Each year, over 700,000 new cases are diagnosed, 5600 to 12,600 patients develop nodal metastasis, and there are 4000-8800 deaths.^2,4-7 Incidence is highest in non-Hispanic white populations, greater in males compared to females, and increases with age for a mean age at diagnosis of approximately 71 years.³ Ultraviolet (UV) radiation due to cumulative and chronic sun exposure is the most important environmental risk factor, occurring more frequently in those with less pigmented skin types.^8-10 In individuals with highly pigmented skin, cSCC is more frequently found on non-sun exposed areas and is often associated with chronic inflammation, chronic wounds, or scarring.^4-7 cSCC of this etiology is more difficult to treat and exhibits a higher recurrence risk.^11-13

The overall prognosis is favorable with a 5-year survival of approximately 98%.^2,8,14 While most tumors are easily cured with surgical excision, a subset result in recurrence, metastasis, and disease-specific death.^14,15 The risk of nodal metastasis ranges from 1.2-5.8% in cohort and tumor registry studies and risk of death is approximately 2%.^14,16,17 In a cohort of patients treated with Mohs micrographic surgery (MMS), the rate of local recurrence was 2.5%, metastatic disease 1.9% and of disease-specific death 0.57%,¹⁸ underscoring the importance of adequate surgical treatment.

Approaches to Risk-Stratification and Staging

Significant effort has been placed on identifying tumors likely to result in poor outcomes (high-risk cSCC) through development of risk stratification or staging systems that lead to a more individualized, risk-based treatment approach and follow-up schedule.^19-25 However, this has not been defined consistently and currently available approaches have limited positive predictive value (PPV).^14,16,26 The most utilized staging systems and guidelines include the National Comprehensive Cancer Network (NCCN) Guidelines, the American Joint Committee on Cancer 8th Edition (AJCC 8) staging system for Head and Neck Tumors, and the Brigham and Women’s Hospital staging system (BWH).^16,27 Each will be discussed in brief.

As of 2021, the NCCN guidelines risk stratify cutaneous squamous cell cancer into low, high and very high-risk groups based on outcomes.⁸ The high-risk group is at increased risk of local recurrence and the very high-risk group is at increased risk of both local recurrence and metastasis.⁸ This stratification was validated by a large retrospective dual-center cohort, comparing outcomes of each group in patients treated with MMS or wide local excision (WLE). The cohort included 12,684 primary tumors from 8727 patients, which were subsequently stratified by NCCN guidelines into low, high, and very high-risk groups.²⁸

Patients with NCCN very high-risk cSCC tumors experienced worse outcomes compared to patients with high-risk and low risk tumors in terms of local recurrence (LR) (11.2% vs 2.0% and 0.7%, p< 0.001), nodal metastasis (NM) (8.9% vs 0.7% and 0.1%, p< 0.001), in transit metastasis (ITM) (4.1% vs 0.3% and 0.0%, p< 0.001), distant metastasis (DM) (5.4% vs 0.3% and 0.0%, p< 0.001), disease specific death (DSD) (10.2% vs 0.7% and 0.3%, p< 0.001), and any poor outcome (17.7% vs 1.8% and 0.3%, P< 0.001).²⁸ The study also demonstrated that MMS results in better local recurrence and distant metastasis outcomes compared to WLE after adjusting for NCCN risk groups, age and sex.²⁸

The AJCC 8 came into clinical use in January 2018 with an updated four T stage (T1-T4) cSCC tumor classification for cases located on the head and neck; it was validated by multiple studies.^16,26,29,30 Tumors are considered high-risk when staged as T3 or T4, and most high-risk tumors are staged as T3 due to relative rarity of T4 cases.³¹ More recently, in order to further reduce the prognostic heterogeneity of AJCC 8, the Salamanca refinement of the T3 classification was proposed, with significant difference in outcomes across three groups within T3.³² The BWH staging system was developed in 2013 to provide superior prognostic value compared to an earlier version of AJCC Staging (AJCC 7).^26,32,33 In AJCC7, higher tumor classes (T3 and T4) required the rare finding of bone invasion, and thus most poor outcomes occurred in stage T2.^26,34 BWH staging consists of four T stages (T1, T2a, T2b, and T3) and categorizes tumors by number of observed high-risk features.^26,35

AJCC 8 and BWH classification systems have been validated in studies conducted at single-center academic institutions^26,30,33 and in population-based studies.^16,29 In 2002, the American Joint Committee on Cancer defined the objectives of cancer staging systems such that they should aim to classify patients into groups that differ according to outcome (distinctiveness), have similar outcome within each group (homogeneity), and worsening outcome with increasing stage (monotonousness).^1,19,29,36 Harrell’s concordance index (c-index or c-statistic) is often calculated and represents the probability that a patient who will develop metastasis will be assigned a higher risk score of this event by the model/staging system compared with a patient who will remain event free. The c-index is equal to the area under the receiver operating characteristic curve for binary outcomes in logistic regression models.^1,29 Additionally, the sensitivity and specificity of high tumor classes (such as AJCC 8 T3/T4 and BWH T2b/T3) to predict poor outcomes, as well as PPV and negative predictive value (NPV) are of importance in assessing the prognostic value of each staging system.²⁶

Ruiz et al²⁶ compared the performance of AJCC 8 and BWH tumor classification systems with respect to distinctiveness, homogeneity, monotonicity, and c-statistic in a single-center academic cohort. The two classification systems showed similar homogeneity (proportion of poor outcomes occurring in low tumor classes) and monotonicity (proportion of poor outcomes occurring in high tumor classes). High tumor classes AJCC8 T3/T4 and BWH T2b/T3 accounted for 18% and 9% of total cSCC cases, respectively, as well as 71% and 70% metastases, and 85% and 92% of deaths. AJCC8 T2 and T3 represented 23% of total cases, with statistically indistinguishable outcomes.²⁶ Sensitivity, Specificity, PPV, and NPV of AJCC8 and BHW higher stages to detect NM/DSD were as follows: Sensitivity: 0.73 vs 0.78, Specificity: 0.93 vs 0.85, PPV: 0.30 vs 0.17, NPV: 0.99 vs 0.99.²⁶ C-statistic for LR demonstrated similar discriminative ability by BWH and AJCC8 for LR with a BWH c-statistic of 0.86 (95% CI, 0.79-0.92) and an AJCC8 c-statistic of 0.81 (95% CI, 0.73-0.88) (p = .09). BWH showed superior discriminative ability for NM and DSD with a BWH c-statistic for NM of 0.91 (95% confidence interval (CI), 0.85-0.96) vs an AJCC8 c-statistic of 0.84 (95% CI, 0.76-0.91) (p = .01). For DSD, the BWH c-statistic was 0.97 (95% CI, 0.94-0.99) and the AJCC8 c-statistic was 0.91; (95% CI, 0.88-0.94) (p= .005).²⁶

AJCC8 and BWH stratification performance was recently evaluated in a population-based nested case control study examining 887 metastatic cSCC cases and 887 non-metastatic controls, factoring in the Salamanca T3 sub-classification.²⁹ The highest specificity was demonstrated for BWH, being 92.8% (95% (CI 90.8–94.3%), with a PPV of 13.2 (95% CI 10.6–16.2), NPV of 99.0 (95% CI 98.9–99.1) and c-index of 0.84 (95% CI 0.82–0.86). AJCC8 specificity was 80.5 (95% CI 77.7–83.1), PPV was 6.8 (95% CI 6.0–7.7), NPV was 99.2 (95% CI 99.2-99.3) and c-index was 0.78 (95% CI 0.76–0.80). The AJCC8 T3 Salamanca refinement did not show any improvement in AJCC8 T3 cSCC staging, although the number of T3 tumors was small with 37 eligible cases and 37 controls.²⁹ Of note, the odds ratio (OR) for metastasis for ACJJ8 T2 was 3.9 (95% CI 2.6-5.8) and for T3, the OR was 11.6 (95% CI 8.3-16.0). The odds ratio for metastasis of BWH T2a was 6.8 (95% CI 4.6-10.1) and for T2b it was 33.3 (95% CI 20.8-53.2), demonstrating significantly higher odds of metastasis with increased stage.²⁹ These data also suggest that AJCC8 tends to upstage low-risk disease, whereas BWH is superior in identification of low risk patients.³⁷

Surveillance and Treatment Intensity are Influenced by Risk-Stratification Group

The American Academy of Dermatology currently recommends tumor stratification of localized cSCC using NCCN guidelines to provide practical clinical guidance for management and follow up and demonstrates preference for BWH in terms of the most accurate prognostication tool in localized cSCC.³⁸ Current NCCN management guidelines for local cSCC recommend MMS or other forms of peripheral and deep en face margin assessment (PDEMA) for very high-risk tumors, with consideration of adjuvant radiation therapy (RT) in cases with poor prognostic features. Suggested follow up frequency and intensity vary according to risk group. Patients with very high-risk cSCC that are recurrent or have multiple risk factors that place them in the very high-risk group warrant consideration of sentinel lymph node biopsy (SLNB) prior to PDEMA. At this time, studies assessing the role of SLNB in cSCC have been heterogeneous and small and while there may be prognostic value^8,39-49 it is not evident that SLNB with subsequent completion lymph node dissection or adjuvant radiation therapy result in improved patient outcomes.^8,40,42,44

A recent survey of 156 physicians aimed to assess how physicians across fields of dermatology and other cancer specialists from head and neck surgery/surgical oncology, radiation oncology, and medical oncology define high-risk cSCC and approach patient management.²⁷ Results revealed that most dermatologists (89%) and other cancer specialists (93%) apply staging criteria to cSCC, with dermatologists more often staging only high-risk tumors and other cancer specialists preferring to stage all tumors. 71% of the surveyed dermatologists used the BWH staging system along or in conjunction with AJCC8, whereas 71% of other cancer specialists used only AJCC8. A contributing factor to this preference is that BWH staging has been developed by dermatologists, published in dermatology journals, and discussed at dermatology conferences. There was consensus that AJCC T3 and BWH T2b or higher constitute a high enough risk threshold to merit increased management intensity, including radiologic imaging, SLNB, adjuvant radiation therapy, and increased follow up; as such, they would also fall into the ‘very high-risk’ NCCN category. This is aligned with Clinical Practice Guidelines from the American Society for Radiation Oncology that provide a strong recommendation for postoperative radiation therapy (PORT) in patients with T3 and T4 tumors and for patients with desmoplastic or infiltrative tumors in the setting of chronic immunosuppression.⁵⁰ Of note, this survey did not query participating physicians regarding use of NCCN guidelines for clinical management, although it did assess risk perception of various clinicopathologic factors. The recently added “very high- risk” category in NCCN guidelines represents an effort at unification of management across staging systems and clinicopathologic risk factors.²⁷

Predictive Biomarkers and Gene Expression Profiling

Tumor biomarkers have been used to improve risk prognostication and clinical decision-making in other cancer types⁵¹ and several are in development to improve risk stratification of cSCC with the goal of bolstering the information provided by the various staging systems. The AJCC8 and BWH staging systems both stand to benefit from a stronger c-index and from improved PPV, as lower PPV may lead to over-treatment and unduly intense follow up.⁵¹ Oh et al¹⁵ constructed a nomogram using protein markers, Axin2 and p53, and clinical variables such as tumor size, organ transplantation history, poor differentiation, and invasion into subcutaneous fat to estimate individualized risk for recurrence in a retrospective study with 145 cSCC patients, to reveal a c-index of 0.809. Additional investigational biomarkers demonstrating association with poor outcomes in patients with cSCC include PD-L1,^52-55 inositol polyphosphate 5-phosphatase (INPP5a),^56,57 p300,⁵⁸ telomerase reverse transcriptase (TERT) promoter mutations,⁵⁹ CD133,⁶⁰ long non-coding RNAs,⁶¹ and epidermal growth factor receptor (EGFR) overexpression.^62,63 Further studies are required to determine clinical validity and utility.

DecisionDx-SCC (40-GEP)

Castle Biosciences devised the DecisionDx-SCC (40-GEP) test which harnesses changes in gene expression of 34 metastasis-associated genes and 6 control genes to identify patients with high-risk of metastasis.^35,64-66 The 40-GEP is intended to be used in patients with localized, invasive and the presence of one or more risk factors (i.e., high-risk) to guide treatment plans within established management pathways. Risk factors that confer eligibility for testing include: Tumors ≥ 2cm anywhere on the body, tumors located on head, neck, hands, feet, pretibial, genitalia, tumors with poorly defined borders, rapidly growing tumors, neurological symptoms in tumor region, tumor at site of prior radiation therapy or chronic inflammation, immunosuppression, perineural invasion of large or small caliber nerves, poorly differentiated histology, deep invasion and aggressive histologic subtypes, aligning with NCCN high-risk and very high-risk categories. The test is not intended to be used in patients with localized low-risk cSCC, cSCC with the presence of lymphovascular invasion; OR bone invasion; OR all four of the following risk factors: diameter of at least 2 cm, AND poorly differentiated, AND perineural invasion of at least 0.1 mm, AND invasion beyond the subcutaneous fat, cSCC that has evidence of regional or distant metastasis, or on locally recurrent cSCC. As a result, these criteria exclude patients who are in the NCCN low risk category and many tumors that are staged as AJCC8 T1 and BWH T1. The exclusion criteria also exclude tumors staged as BWH T3 and AJCC8 T4 (and possibly some AJCC8 T3 tumors with minor bone invasion). However, it is important to note that some patients (for example patients who are immunosuppressed) may be classified as “high-risk” according to NCCN criteria (making them eligible for 40-GEP testing) though they have a stage T1 tumor by AJCC8 or BWH. In all, patients whose risk is either too low or too high to benefit from the 40-GEP are excluded from testing. Thereby, the intended use is focused on improving risk stratification within BWH T2a/2b and AJCC8 stages T2/T3, allowing for testing of some T1 patients who have other ‘high-risk’ factors.

The 40-GEP stratifies patients with one or more risk factors into a low metastatic risk (Class 1), moderate metastatic risk (Class 2A) or high metastatic risk (Class 2B) groups. The test was developed using a discovery and development cohort consisting of 202 archival cSCC cases for gene selection and further validated using archival tissue from a separate cohort of 321 high-risk primary cSCC patients with known 3-year outcomes and an overall metastatic rate of 16.2%.³⁵ cSCC tissue and clinical data were obtained from 23 independent centers and enrollment targeted patients with at least one high-risk feature as defined by NCCN guidelines, or AJCC or BWH stage greater than T1, either at the patient or tumor level.³⁵ The 40-GEP signature demonstrated statistically significant capability of stratifying metastatic risk with different 3-year metastatic rates observed for patients with Class 1 (n=203; 8.9%), Class 2A (n=93; 20.4%) and Class 2B (n=25; 60.0%) results.³⁵ The 40-GEP signature maintained predictive value when analyzed in bivariable models with AJCC and BWH staging. Of note, AJCC and BWH also maintained statistical significance in their respective bivariable models with the 40-GEP. A multivariate Cox regression analysis was conducted for 295 patients with clinical features captured prior to definitive surgery including male sex, tumor diameter assessed as a continuous variable per unit increase, immune deficient status, location on head and neck and GEP Class 2A or 2B, to reveal statistical significance for tumor diameter, head, and neck location, as well as 40-GEP Class 2A or 2B (p<0.05). In a separate multivariate Cox regression analysis with histopathological features captured after definitive surgery for 321 cases, statistical significance was achieved for tumor thickness >6mm, poor histological grade, invasion into fat, and a Class 2B result. Of note, a Class 2A result was not statistically significant in this model that included histopathological features only. Clarks Level IV/V and perineural invasion were not significant predictors of metastasis on univariate analysis and were not included in the multivariate model.³⁵

It is important to note that 168 cases were missing clinicopathologic data (mostly tumor thickness) and were staged with assumption of null values for missing data which may have resulted in under-staging by BWH and AJCC, inserting an element of bias.³⁵ Post hoc sensitivity analyses showed robustness of the primary bivariable analyses in spite of possible under-staging. All specimens underwent central pathology review and restaging according to contemporary staging criteria with medical records reviewed for additional high-risk features. However, cases excised via Mohs had no tissue available for review other than the shave biopsy, therefore there is possibility for underreporting of high-stage features and resultant under-staging.³⁵ This is reflected in the higher percentage of metastasis occurring in low T stages than previously reported in the literature and lower sensitivities of AJCC and BWH staging than reported for other cohorts (39% and 25% vs 78% and 73%, respectively).^26,35 Accuracy metrics for risk prediction are found in Table 1 below, adapted from Wysong et al.³⁵ The PPV of a Class 2B result was 60%, whereas the PPV of any Class 2 result was similar to AJCC8 and BWH high stage/low stage categories.

Table 1. Accuracy of risk prediction of the 40-GEP and risk assessment methods (n=321)

Ibrahim et al subsequently reported on data from expansion of the previous cohort to 420 patients with high-risk factors, 63 of whom developed regional and/or distant metastases.⁶⁵ The median time to metastasis was 0.9 years.⁶⁵ Of the 420 cases, 212 were classified as Class 1 with a metastatic rate of 6.6%, 185 were classified as Class 2A with a metastatic rate of 20.0%, and 23 were classified as Class 2B with a metastatic risk of 52.2%. When stratified by NCCN high-risk vs very high-risk criteria, Class 1 was associated with a 4.1% metastatic rate in the high-risk cohort vs 11.9% in the very high-risk cohort; Class 2 was associated with a 15.7% metastatic rate in the high-risk vs 25.3% in the very high-risk cohort, and Class 2B was associated with a 37.5% metastatic rate in the high-risk vs 60% in the very high-risk cohort. The overall metastatic rate in the NCCN high-risk cohort was 9.8% vs 23.0% for the very high-risk cohort.⁶⁵ In multivariate Cox regression analysis with clinicopathologic risk factors that included 40-GEP results along with poor differentiation, perineural invasion, deep invasion, and tumor diameter, the 40-GEP was statistically significant along with poor differentiation and deep invasion. 40-GEP results were also significant in bivariable analysis along with either NCCN risk group, BWH, and AJCC 8 stage, which also remained significant contributors to each respective bivariable model. Sensitivity of the 40-GEP 2B vs 1/2A result was 19%, specificity 96.9%, PPV was 52.2% and NPV was 87.2%, all of which are similar to that reported in Wysong et al.^35,65

Arron et al⁶⁴ evaluated a subset (n=278, 66%) of this cohort from patients with cSCC of the head and neck with an overall metastatic rate of 19.4%. 126 of these patients had Class 1 results (metastatic rate: 8.7%), 134 had Class 2A results (metastatic rate: 24.6%), and 18 had Class 2B results (metastatic rate: 55.6%). In this subset of patients, the PPV of a 40-GEP Class 2B result was 55.6% compared to 37.0% for high stage AJCC8 and 40.0% for high stage BWH, and the difference between the three was not statistically significant. As in the larger cohort, the 40-GEP remained significant in bivariable analyses with AJCC8 and BWH criteria, which were also significant contributors to each respective model. In multivariate analysis with clinicopathologic risk factors, the HR of Class 2A result was 2.28 (95% CI 1.08-4.81) and the HR of a Class 2B result was 4.05 (95% CI 1.34-12.26). Clinicopathologic factors significant along with 40-GEP results in a multivariate Cox regression analysis included tumor diameter, poor differentiation, deep invasion, and male sex.⁶⁴ Sensitivity, specificity, PPV, and NPV of a 2B vs 1/2A result were similar to that reported in Wysong et al and Ibrahim et al.^35,65

The potential clinical utility of the 40-GEP lies in its incorporation into existing risk-assessment frameworks in order to improve prognostic value and facilitate individualized risk assessment, treatment, and follow up. Farberg et al aimed to refine risk-directed patient management using the 40-GEP along with NCCN guidelines and T stage criteria by examining 300 patients who met NCCN high-risk criteria from the validation cohort presented in Wysong et al.⁶⁷ Of note, this work was performed prior to introduction of the NCCN very high-risk category in 2021, and thereby only includes the former categorization of “high-risk.” As a result, this is not reflective of the most up-to-date classification.

The proposed algorithm, which is not currently part of clinical guidelines, starts with NCCN high-risk cSCC patients who subsequently undergo 40-GEP testing and staging by BWH/AJCC8 with the following proposed management strategy⁶⁷:

Table 2: Proposed Risk-Aligned Management Plans within the NCCN Guidelines Framework

(adapted from ⁶⁷):

Current NCCN Guidelines have not incorporated use of the 40-GEP and recommend follow up for high-risk patients to occur every 3-6 months for two years, then 6-12 months for 3 years, then annually for life. This includes complete skin and regional lymph node exam and imaging can be considered if clinical exam is insufficient for following the disease. Adjuvant radiation and systemic therapy would not be recommended, unless the patient has positive post-surgical margins and further surgery is not feasible.⁸ NCCN recommendations for very high-risk patients include follow up every 3-6 months for 2 years, then every 6 months for 3 years, then every 6-12 months for life, along with imaging if clinical exam is insufficient for following disease. SNLB is recommended for very high-risk patients who have multiple risk factors placing them in the very high-risk group with a normal exam of the draining nodal basin. Systemic therapy with or without radiation therapy is recommended in cases of positive margins after MMS or other PDEMA, residual disease after definitive therapy, and for non-surgical candidates. Adjuvant radiation therapy is recommended for cases with positive-post surgical margins if further surgery is not feasible and with negative margins in the setting of extensive perineural, large, or named nerve involvement or other poor prognostic features.⁸

Arron et al⁶⁸ convened an expert panel of Mohs surgeons, surgical oncologists, and radiation oncologists from academic medical centers and community practices and discussed rationales and scenarios where the 40-GEP test result may have clinical utility. The panel stated that the 40-GEP should not be used as surrogate for standard of care treatment but as an additional data point when determining individualized management plans for high-risk patients.⁶⁸ Possible uses of the GEP are explored in relation to nodal evaluation, adjuvant radiation therapy, and follow-up frequency as presented in Table 3 (adapted from ⁶⁸).

Table 3. GEP Test Results That May Impact Decisions on Follow-up and Surveillance Intensity During the First Two Years after Diagnosis (Adapted from Arron et al⁶⁸).

To further illustrate potential clinical utility, Au et al⁶⁹ described two retrospective analyses of NCCN very high-risk cases, one with a Class 1 result and the other with Class 2B result. Case 1 was a 65-year-old male with history of renal and liver transplantation and a 1.3 cm poorly differentiated cSCC on his left temple (BWH T2a and AJCC8 T1, NCCN very high-risk). He underwent MMS with possible residual disease. The patient declined further treatment and was disease free at 4 years. He was retrospectively found to have a 40-GEP Class 1 result. Patient 2 was a 69-year-old male with history of liver transplant and 1.5 cm poorly differentiated cSCC on his left temple (BWH T2a, AJCC8 T1, NCCN very high-risk) with subsequent clearing following MMS. The patient developed metastatic cSCC within three months of MMS and was retrospectively found to have a 40-GEP Class 2B result. Au et al⁶⁹ state that Case 1 highlighted a biologically less aggressive tumor that did not recur despite incomplete surgical clearance whereas Case 2 highlighted a more aggressive tumor in spite of clear surgical margins with MMS. The authors state that adjuvant treatment may have been appropriate for Case 2 earlier in the disease course.⁶⁹

The potential clinical impact of the 40-GEP has been assessed through presentation of clinical vignettes and clinician surveys at conferences showing that clinicians would alter their decisions to perform a SLNB and recommendations for adjuvant radiation therapy and chemotherapy/immunotherapy given 40-GEP results.^70,71 However, outcomes data from prospective studies with documented specific changes in management are lacking at this time.

Saleeby et al⁷² report on preliminary results from the prospective Clinical Utility and Health Outcomes Study (UTILISE), which aimed to demonstrate patterns of test utilization, distribution of results across clinicopathologic variables, and impact on clinician recommendations for management in Medicare-eligible high-risk patients. The study was conducted at 5 clinical sites and involved 11 unique clinicians (8 dermatologists and 3 dermatology-based physician assistants). The study consisted of two sequential phases, the Lead-in Phase and Clinical Utility Phase. During the Lead-in Phase, clinicians recorded a treatment plan assessment before receiving 40-GEP results for at least five patients. After completion of treatment plan assessment for five patients, clinicians were able to enroll new patients into the clinical utility phase. The Lead-in Phase included a second (post-test) treatment assessment completed after 40-GEP results receipt.⁷²

At time of publication, the Lead-in Phase consisted of 31 patients, with 81% having two or more risk factors. 68% (n=21) received a Class 1 result, 25% (n=~8) received a Class 2A result, and 6% (n=1-2) received a Class 2B result, with a median follow up of 41.7 weeks. At time of analysis, one patient with a Class 2A result experienced regional metastasis. The Clinical Utility Cohort included 59 patients, 60.3% of whom had more than one risk factor. This cohort was comprised of 88% Class 1 (n=52) results, and 12% Class 2A results. There were no Class 2B results and no cases of metastasis with a median follow up of 22.5 weeks. The impact on clinician perception of metastatic risk is depicted in Table 4 adapted from Saleeby et al and the impact of the 40-GEP on intensity of management is depicted in Table 5.⁷² The majority of queried clinicians reported reassurance in the management plan they developed prior to use of the 40-GEP and 24% stated that they made changes based on GEP results. The precise changes to management outside of the broad categories “low, moderate, high intensity” management were not published. Clinical patient outcomes are not available at time of publication, with the exception of the one Class 2A patient who developed metastasis. Therefore, it is not possible to ascertain the effect of the 40-GEP informed change in patient management on patient outcomes at this time.

Table 4. 40-GEP Impact on Clinician Perception of Metastatic Risk

Table 5. 40-GEP Impact on Intensity of Management

Hooper et al⁷³ reviewed 2455 samples submitted during the first year of clinical testing (August 31, 202-August 31, 2021) and found that 68.8% (n=1687) had a Class 1 result, 28.3% (n=696) had a Class 2A result, and 2.9% (n=72) had a Class 2B result. The majority of Class 1 results were identified in samples with 1–2 risk factors, confirmative of a low-risk of metastasis. Class 2A and 2B results were more likely to be found in samples from patients with a greater number of risk factors when compared with Class 1, demonstrating consistency with the increased risk associated with Class 2A and 2B results.⁷³

While the 40-GEP is capable of metastatic risk stratification, it is unclear how GEP-results can be consistently or accurately interpreted in the context of baseline clinicopathologic risk as part of a comprehensive risk assessment to change patient management. Along these lines, the literature presented to date suggests, but does not adopt, a consistent and recommended patient management strategy with regard to follow-up frequency, nodal assessment, and adjuvant therapy for Class 1, 2A, and 2B tumors according to which outcomes could be measured. Most patients receive a Class 1 or 2A result while Class 2B results are rare; therefore, it is important to clearly define the difference in management of patients with a Class 1 vs 2A result and the net benefit. To-date, this has not been done. It is also important to examine the impact of changes in patient management as a result on the 40-GEP on clinical outcomes from larger real-world trials (rather than anecdotal case reports), as misclassification can cause patient harm. Finally, test performance has not convincingly demonstrated superiority to currently available staging tools and clinicopathologic factors in the intended use population. The main concerns are further outlined below.

The Class 2B result is rare and occurs more often (though not exclusively) in patients with two or more risk factors, who would already likely be classified as higher risk by existing tools. The relative rarity of the Class 2B result is depicted in the Ibrahim et al⁶⁵ validation cohort of 420 patients wherein only 23 patients received a Class 2B result (12 metastatic), 18 of whom had 2 or more risk factors. Interestingly, when cSCC cases are stratified by NCCN criteria into high-risk and very high-risk populations, the metastatic rate associated with a Class 2B result was 37.5% in the NCCN high-risk cohort vs 60.0% in the very high-risk cohort,⁶⁵ perhaps reflective of the overall difference in prevalence of metastasis in both cohorts and underscoring the importance of additional clinicopathologic risk factors. In Hooper et al’s examination of 2455 clinical samples from a year of clinical testing with the 40-GEP, only 2.9% received a Class 2B result.⁷³ The majority of Class 1 results were identified in samples with 1–2 risk factors, confirmative of a low-risk of metastasis. Class 2A and 2B results were more likely to be found in samples from patients with a greater number of risk factors when compared with Class 1.⁷³

In the most recent prospective Clinical Utility and Health Outcomes Study (UTILISE) conducted in 90 Medicare-eligible patients evaluated prospectively, 73 received a Class 1 result and 17 received a Class 2 result (Class 2A +2B) (of which 1-2 were class 2B), demonstrating that a class 2B result is indeed very rare in the community setting.⁷² 11 clinicians (8 board certified dermatologists and 3 physician assistants) who participated in the study were queried about their perception of risk, demonstrating mostly reassurance in their current treatment plan with a Class 1 result and some increase in perceived risk with a class 2A result.⁷² 24% of these 11 clinicians reported that they made management changes based on 40-GEP results. It would be prudent to examine in greater detail the patients for whom the 40-GEP led to a change in management, the specific change in management, and the subsequent impact on outcomes when compared to the currently recommended approach provided by Society Guidelines (such as NCCN).

Since a Class 2B result is rare, the clinical utility and PPV of a Class 2A (which is more likely) or Class 2 result should be examined. In the 40-GEP validation by Ibrahim et al,⁶⁵ the PPV of any Class 2 result (Class 2A + 2B) is 23.6%, compared with 33.9% of BWH T2b/T3 and 30.0% of AJCC8 (T3/T4). In a cohort restricted to the head and neck, the PPV of any Class 2 result is 28.3%, compared with 37.0% for AJCC8 and 40.0% of BWH T2b/T3.⁶⁴ Thus, the PPV of any Class 2 result is comparable to that of existing staging criteria. In bivariable models that include the 40-GEP along with either BWH or AJCC8 staging criteria, the HR of a Class 2A result is comparable to that of BWH T stage T2b/T3 or AJCC8 T3/T4.⁶⁵ The majority of patients tested with the 40-GEP receive a Class 1 or 2A result, which is comparable in terms of predictive value to existing staging criteria. It would be prudent to further explore the patients with Class 2B results who were not identified as very high-risk according to all available staging criteria and risk factor analysis, but for whom a Class 2B result would enable them to benefit from more intense management. This data is not available aside from a handful of clinical anecdotes.

While it has been shown that clinicians are willing to adopt the 40-GEP and to potentially act on the results,^69-71 it is not clear what the recommended management changes should be and there is no outcomes data to support changes in management. Also, some de-escalations of care may not be warranted based on the risk scores provided in patient clinical reports as the metastatic risk associated with a Class 1 and Class 2A result depends on other clinicopathological variables. For example, sample patient reports state that the metastatic rate for patients with 1 risk factor is Class 1 (6.6%), Class 2A (20.0%), Class 2B (52.2%) and for patients with 2 or more risk factors, the metastatic rate is: Class 1 (9.0%), Class 2A (25.0%), Class 2B (50.0%), based on data from Ibrahim et al.⁶⁵ Farberg et al,⁶⁷ showed that individuals with AJCC8 stage T3/T4 have a 16.7% rate of metastasis with a Class 1 result and BWH T2b/T3 Stage has 18.8% risk of metastasis with a Class 1 result. A Class 2A result carries a 34.8% metastatic rate in patients with ACJJ8 stage T3/T4 and 35.7% in those with BWH stage T2b/T3. This variability in metastatic rate with a Class 1 result as a function of other clinicopathologic factors underscores their importance and makes de-escalation of management intensity challenging based on 40-GEP results, highlighting the importance of the complete clinical picture beyond the absolute number of risk factors presented in patient reports. Farberg et al⁶⁷ attempted to integrate GEP results within the NCCN guidelines framework, along with BWH and/or AJCC8 staging, however this was not clearly defined nor consistently implemented in clinical practice, with a lack of outcomes data. Accordingly, it is concerning that in the UTILISE study presented by Saleeby et al,⁷² the majority of clinicians had a perception that a Class I result conferred <5% risk of metastasis (Table 4), which is not congruent with the above data, especially given that most of the patients in the UTILISE study had more than 1 risk factor. As a result, there is a risk that some patients may be under-treated as a result of the 40-GEP.

In addition, the currently available published literature does not describe test performance in a patient population with the exclusion criteria proposed by the test manufacturer - namely excluding patients with cSCC with the presence of lymphovascular invasion; OR bone invasion; OR all four of the following risk factors: diameter of at least 2 cm, AND poorly differentiated, AND perineural invasion of at least 0.1 mm, AND invasion beyond the subcutaneous fat, cSCC that has evidence of regional or distant metastasis, or on locally recurrent cSCC. While these features are rare, they are likely responsible for a portion of the very high-risk cases and PPV and NPV vary with prevalence of metastasis. Also, while the presented literature compares the 40-GEP to BWH and AJCC8 staging on sensitivity, specificity, positive and negative predictive value, it does not examine distinctiveness, homogeneity, and monotonicity, and c-index of the 40-GEP to better assess its overall performance.

There are several limitations of the multivariate analysis performed in Wysong et al and Ibrahim et al.^35,65 These include treatment of tumor diameter as a continuous variable when it may not show a linear relationship with outcome.⁷⁴ Tumor size greater than 2 cm but less than 4 cm is considered a high-risk feature according to NCCN criteria and upstages tumors from T1 to T2 in AJCC8, whereas tumors greater than 4 cm are considered very high-risk, and upstage AJCC8 stage from T2 to T3.^8,75 Also, perineural invasion was considered positive in the analysis regardless of nerve caliber, whereas nerves measuring 0.1 mm or more are an NCCN very high-risk feature as are tumor cells within the nerve sheath of a nerve lying deeper than the dermis.⁸ Additional risk factors that characterize a patient as high-risk and eligible for testing with the 40-GEP were not included in the model but may have clinical predictive value. These include tumor location on the head, neck, hands, feet, pretibial, and anogenital region, site of prior radiation therapy or chronic inflammatory process, rapidly growing tumors, presence of neurologic symptoms, and aggressive histologic features such as acantholytic/adenoid, adenosquamous, or metaplastic tumors as well as desmoplasia, which although rare, is associated with a 10-fold greater risk of local recurrence and a 6-fold increased risk of metastasis compared to tumors without this feature.⁷⁶ Additional considerations include the clinical utility of this test for patients with tumors with positive surgical margins after excision and in patients with multiple tumors.⁷⁷ Finally, there are differences in metastatic risk as a function of surgical approach, such that it would be prudent to explore the 40-GEP’s PPV for tumors treated with MMS vs WLE. A more complete analysis that includes all of the high-risk factors that confer test eligibility would provide greater clarity of the predictive capability of the 40-GEP along with possible additive value. The significance of other clinicopathologic factors along with 40-GEP in the multivariate model presented in Ibrahim et al⁶⁵ underscores their collective importance and perhaps the 40-GEP may have increased predictive value and offer a more personalized assessment of risk as a nomogram.

In addition, local recurrence contributes significantly to disease-specific death^78-80 and the 40-GEP proposes changes in management and follow-up frequency based on the risk of metastasis. It would be prudent to examine performance of the 40-GEP with disease specific death as an endpoint aside from metastasis-free survival to determine the overall impact on patient outcomes. Finally, the clinical utility and test performance of the 40-GEP has been reported in a population that is 73.3% male and 99.3% Caucasian,⁶⁵ which is representative of the majority of patients with cSCC. Nevertheless, this represents a potential evidence gap, as representation of test performance characteristics should be inclusive of and addressed in patients of color, who have been shown to have a higher metastatic rate compared to Caucasians.^81-84

The published literature to date does not outline a consistent and clear management strategy for patients with Class 1, Class 2A, and Class 2B results with respect to frequency of follow up, SNLB, and adjuvant therapy within the existing framework of clinical guidelines and staging. While management strategies have been proposed,^67,68 it is imperative to clearly define changes in patient management given 40-GEP results and to measure clinical outcomes based on those changes. Ideally, there should be evidence of improved risk stratification without detriment to patient outcomes. Patient misclassification and under-treatment as a result of a false negative result could cause significant harm and needs to be addressed.

In conclusion, although there is apparent need and clinical utility for molecular markers to improve risk stratification of patients with cSCC, the current evaluated tests at the time of drafting this policy have not yet demonstrated definitive value above the combination of available clinical, pathological, and staging criteria in accurate risk stratification. Therefore, clinical validity and clinical utility have not yet been established for molecular tests that offer risk stratification for cSCC. This contractor will continue to monitor the evidence and may modify coverage based on new information in the pertinent literature and society recommendations.

N/A

N/A

1. Lomas A, Leonardi-Bee J, Bath-Hextall F. A systematic review of wordwide incidence of nonmelanoma skin cancer. Br J Dermatol. 2012;166(5):1069-1080. doi: 10.1111/j.1365-2133.2012.10830.x
2. Schmults CD, Blitzblau R, Aasi SZ, et al. NCCN Guidelines^® insights: squamous cell skin cancer, version 1.2022. J Natl Compr Canc Netw. 2021;19(12):1382-1394. doi:10.6004/jnccn.2021.0059
3. Muzic JG, Schmitt AR, Wright AC, et al. Incidence and trends of basal cell carcinoma and cutaneous squamous cell carcinoma: a population-based study in Olmsted County, Minnesota, 2000 to 2010. Mayo Clin Proc. 2017;92(6):890-898. doi:10.1016/j.mayocp.2017.02.015
4. Karia PS, Han J, Schmults CD. Cutaneous squamous cell carcinoma: estimated incidence of disease, nodal metastasis, and deaths from disease in the United States, 2012. J Am Acad Dermatol. 2013;68(6):957-966. doi:10.1016/j.jaad.2012.11.037
5. Que SKT, Zwald FO, Schmults CD. Cutaneous squamous cell carcinoma: incidence, risk factors, diagnosis, and staging. J Am Acad Dermatol. 2018;78(2):237-247. doi:10.1016/j.jaad.2017.08.059
6. Waldman A, Schmults C. Cutaneous squamous cell carcinoma. Hematol Oncol Clin North Am. 2019;33(1):1-12. doi:10.1016/j.hoc.2018.08.001
7. Stang A, Khil L, Kajüter H, et al. Incidence and mortality for cutaneous squamous cell carcinoma: comparison across three continents. J Eur Acad Dermatol Venereol. 2019;33 Suppl 8(Suppl 8):6-10. doi:10.1111/jdv.15967
8. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Squamous Cell Skin Cancer. Version 1.2023. https://www.nccn.org/professionals/physician_gls/pdf/squamous.pdf. Accessed April 18, 2023.
9. Xiang F, Lucas R, Hales S, Neale R. Incidence of nonmelanoma skin cancer in relation to ambient UV radiation in white populations, 1978-2012: empirical relationships. JAMA Dermatol. 2014;150(10):1063-1071. doi:10.1001/jamadermatol.2014.762
10. Juzeniene A, Grigalavicius M, Baturaite Z, Moan J. Minimal and maximal incidence rates of skin cancer in Caucasians estimated by use of sigmoidal UV dose-incidence curves. Int J Hyg Environ Health. 2014;217(8):839-844. doi:10.1016/j.ijheh.2014.06.002
11. Rowe DE, Carroll RJ, Day CL Jr. Prognostic factors for local recurrence, metastasis, and survival rates in squamous cell carcinoma of the skin, ear, and lip. Implications for treatment modality selection. J Am Acad Dermatol. 1992;26(6):976-990. doi:10.1016/0190-9622(92)70144-5
12. Eroglu A, Berberoglu U, Berreroglu S. Risk factors related to locoregional recurrence in squamous cell carcinoma of the skin. J Surg Oncol. 1996;61(2):124-130. doi:10.1002/(SICI)1096-9098(199602)61:2<124::AID-JSO6>3.0.CO;2-E
13. Mullen JT, Feng L, Xing Y, et al. Invasive squamous cell carcinoma of the skin: defining a high-risk group. Ann Surg Oncol. 2006;13(7):902-909. doi:10.1245/ASO.2006.07.022
14. Schmults CD, Karia PS, Carter JB, Han J, Qureshi AA. Factors predictive of recurrence and death from cutaneous squamous cell carcinoma: a 10-year, single-institution cohort study. JAMA Dermatol. 2013;149(5):541-547. doi:10.1001/jamadermatol.2013.2139
15. Oh Y, Zheng Z, Kim KY, et al. A nomogram combining clinical factors and biomarkers for predicting the recurrence of high-risk cutaneous squamous cell carcinoma. BMC Cancer. 2022;22(1):1126.
16. Roscher I, Falk RS, Vos L, et al. Validating 4 staging systems for cutaneous squamous cell carcinoma using population-based data: a nested case-control study. JAMA Dermatol. 2018;154(4):428-434. doi:10.1001/jamadermatol.2017.6428
17. Nelson TG, Ashton RE. Low incidence of metastasis and recurrence from cutaneous squamous cell carcinoma found in a UK population: do we need to adjust our thinking on this rare but potentially fatal event?. J Surg Oncol. 2017;116(6):783-788. doi:10.1002/jso.24707
18. Matsumoto A, Li JN, Matsumoto M, Pineider J, Nijhawan RI, Srivastava D. Factors predicting outcomes of patients with high-risk squamous cell carcinoma treated with Mohs micrographic surgery. J Am Acad Dermatol. 2021;85(3):588-595. doi:10.1016/j.jaad.2021.01.063
19. Thompson AK, Kelley BF, Prokop LJ, Murad MH, Baum CL. Risk factors for cutaneous squamous cell carcinoma recurrence, metastasis, and disease-specific death: a systematic review and meta-analysis. JAMA Dermatol. 2016;152(4):419-428. doi:10.1001/jamadermatol.2015.4994
20. Baum CL, Wright AC, Martinez JC, et al. A new evidence-based risk stratification system for cutaneous squamous cell carcinoma into low, intermediate, and high risk groups with implications for management. J Am Acad Dermatol. 2018;78(1):141-147. doi:10.1016/j.jaad.2017.07.031
21. Farasat S, Yu SS, Neel VA, et al. A new American Joint Committee on Cancer staging system for cutaneous squamous cell carcinoma: creation and rationale for inclusion of tumor (T) characteristics. J Am Acad Dermatol. 2011;64(6):1051-1059. doi:10.1016/j.jaad.2010.08.033
22. Lydiatt WM, Patel SG, O'Sullivan B, et al. Head and neck cancers-major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin. 2017;67(2):122-137. doi:10.3322/caac.21389
23. Karia PS, Jambusaria-Pahlajani A, Harrington DP, Murphy GF, Qureshi AA, Schmults CD. Evaluation of American Joint Committee on Cancer, International Union Against Cancer, and Brigham and Women's Hospital tumor staging for cutaneous squamous cell carcinoma. J Clin Oncol. 2014;32(4):327-334. doi:10.1200/JCO.2012.48.5326
24. Stratigos AJ, Garbe C, Dessinioti C, et al. European interdisciplinary guideline on invasive squamous cell carcinoma of the skin: part 1. epidemiology, diagnostics and prevention. Eur J Cancer. 2020;128:60-82. doi:10.1016/j.ejca.2020.01.007
25. Brunner M, Ng BC, Veness MJ, Clark JR. Comparison of the AJCC N staging system in mucosal and cutaneous squamous head and neck cancer. Laryngoscope. 2014;124(7):1598-1602. doi:10.1002/lary.24549
26. Ruiz ES, Karia PS, Besaw R, Schmults CD. Performance of the American Joint Committee on Cancer Staging Manual, 8th Edition vs the Brigham and Women's Hospital Tumor Classification System for cutaneous squamous cell carcinoma. JAMA Dermatol. 2019;155(7):819-825. doi:10.1001/jamadermatol.2019.0032
27. Patel VA, McCullum C, Sparks AD, Schmults CD, Arron ST, Jambusaria-Pahlajani A. Cutaneous squamous cell carcinoma staging may influence management in users: a survey study. Cancer Med. 2022;11(1):94-103. doi:10.1002/cam4.4426
28. Stevens JS, Murad F, Smile TD, et al. CLO22-085: A dual-center retrospective cohort validation of the 2021 NCCN risk stratification for cutaneous squamous cell carcinoma. J Natl Compr Canc Netw. 2022;20(3.5):CLO22-085-CLO22-085. doi:10.6004/jnccn.2021.7281
29. Venables ZC, Tokez S, Hollestein LM, et al. Validation of four cutaneous squamous cell carcinoma staging systems using nationwide data. Br J Dermatol. 2022;186(5):835-842. doi:10.1111/bjd.20909
30. Cañueto J, Burguillo J, Moyano-Bueno D, et al. Comparing the eighth and the seventh editions of the American Joint Committee on Cancer staging system and the Brigham and Women's Hospital alternative staging system for cutaneous squamous cell carcinoma: implications for clinical practice. J Am Acad Dermatol. 2019;80(1):106-113.e2. doi:10.1016/j.jaad.2018.06.060
31. Puebla-Tornero L, Corchete-Sánchez LA, Conde-Ferreirós A, et al. Performance of Salamanca refinement of the T3-AJCC8 versus the Brigham and Women's Hospital and Tübingen alternative staging systems for high-risk cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2021;84(4):938-945. doi:10.1016/j.jaad.2020.12.020
32. Conde-Ferreirós A, Corchete LA, Puebla-Tornero L, et al. Definition of prognostic subgroups in the T3 stage of the eighth edition of the American Joint Committee on Cancer staging system for cutaneous squamous cell carcinoma: tentative T3 stage subclassification. J Am Acad Dermatol. 2021;85(5):1168-1177. doi:10.1016/j.jaad.2020.03.088
33. Jambusaria-Pahlajani A, Kanetsky PA, Karia PS, et al. Evaluation of AJCC tumor staging for cutaneous squamous cell carcinoma and a proposed alternative tumor staging system. JAMA Dermatol. 2013;149(4):402-410. doi:10.1001/jamadermatol.2013.2456
34. Karia PS, Morgan FC, Califano JA, Schmults CD. Comparison of tumor classifications for cutaneous squamous cell carcinoma of the head and neck in the 7th vs 8th edition of the AJCC cancer staging manual. JAMA Dermatol. 2018;154(2):175-181. doi:10.1001/jamadermatol.2017.3960
35. Wysong A, Newman JG, Covington KR, et al. Validation of a 40-gene expression profile test to predict metastatic risk in localized high-risk cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2021;84(2):361-369. doi:10.1016/j.jaad.2020.04.088
36. Amin MB, Edge S, Green F, et al., eds. AJCC Cancer Staging Manual. 8^th ed. Springer; 2018.
37. Burns C, Kubicki S, Nguyen QB, et al. Advances in cutaneous squamous cell carcinoma management. Cancers (Basel). 2022;14(15):3653.
38. Work Group; Invited Reviewers, Kim JYS, et al. Guidelines of care for the management of cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2018;78(3):560-578. doi:10.1016/j.jaad.2017.10.007
39. Schmitt AR, Brewer JD, Bordeaux JS, Baum CL. Staging for cutaneous squamous cell carcinoma as a predictor of sentinel lymph node biopsy results: meta-analysis of American Joint Committee on Cancer criteria and a proposed alternative system. JAMA Dermatol. 2014;150(1):19-24. doi:10.1001/jamadermatol.2013.6675
40. Ross AS, Schmults CD. Sentinel lymph node biopsy in cutaneous squamous cell carcinoma: a systematic review of the English literature. Dermatol Surg. 2006;32(11):1309-1321. doi:10.1111/j.1524-4725.2006.32300.x
41. Durham AB, Lowe L, Malloy KM, et al. Sentinel lymph node biopsy for cutaneous squamous cell carcinoma on the head and neck. JAMA Otolaryngol Head Neck Surg. 2016;142(12):1171-1176. doi:10.1001/jamaoto.2016.1927
42. Gore SM, Shaw D, Martin RC, et al. Prospective study of sentinel node biopsy for high-risk cutaneous squamous cell carcinoma of the head and neck. Head Neck. 2016;38 Suppl 1:E884-E889. doi:10.1002/hed.24120
43. Renzi C, Caggiati A, Mannooranparampil TJ, et al. Sentinel lymph node biopsy for high risk cutaneous squamous cell carcinoma: case series and review of the literature. Eur J Surg Oncol. 2007;33(3):364-369. doi:10.1016/j.ejso.2006.10.017
44. Kwon S, Dong ZM, Wu PC. Sentinel lymph node biopsy for high-risk cutaneous squamous cell carcinoma: clinical experience and review of literature. World J Surg Oncol. 2011;9:80. doi:10.1186/1477-7819-9-80
45. Ahmed MM, Moore BA, Schmalbach CE. Utility of head and neck cutaneous squamous cell carcinoma sentinel node biopsy: a systematic review. Otolaryngol Head Neck Surg. 2014;150(2):180-187. doi:10.1177/0194599813511949
46. Fukushima S, Masuguchi S, Igata T, et al. Evaluation of sentinel node biopsy for cutaneous squamous cell carcinoma. J Dermatol. 2014;41(6):539-541. doi:10.1111/1346-8138.12508
47. Takahashi A, Imafuku S, Nakayama J, Nakaura J, Ito K, Shibayama Y. Sentinel node biopsy for high-risk cutaneous squamous cell carcinoma. Eur J Surg Oncol. 2014;40(10):1256-1262. doi:10.1016/j.ejso.2014.05.009
48. Maruyama H, Tanaka R, Fujisawa Y, Nakamura Y, Ito S, Fujimoto M. Availability of sentinel lymph node biopsy for cutaneous squamous cell carcinoma. J Dermatol. 2017;44(4):431-437. doi:10.1111/1346-8138.13577
49. Tejera-Vaquerizo A, García-Doval I, Llombart B, et al. Systematic review of the prevalence of nodal metastases and the prognostic utility of sentinel lymph node biopsy in cutaneous squamous cell carcinoma. J Dermatol. 2018;45(7):781-790. doi:10.1111/1346-8138.14342
50. Likhacheva A, Awan M, Barker CA, et al. Definitive and postoperative radiation therapy for basal and squamous cell cancers of the skin: executive summary of an American Society for Radiation Oncology clinical practice guideline. Pract Radiat Oncol. 2020;10(1):8-20. doi:10.1016/j.prro.2019.10.014
51. Farberg AS, Fitzgerald AL, Ibrahim SF, et al. Current methods and caveats to risk factor assessment in cutaneous squamous cell carcinoma (cSCC): a narrative review. Dermatol Ther (Heidelb). 2022;12(2):267-284. doi:10.1007/s13555-021-00673-y
52. Kamiya S, Kato J, Kamiya T, et al. Association between PD-L1 expression and lymph node metastasis in cutaneous squamous cell carcinoma. Asia Pac J Clin Oncol. 2020;16(2):e108-e112. doi:10.1111/ajco.13102
53. García-Pedrero JM, Martínez-Camblor P, Diaz-Coto S, et al. Tumor programmed cell death ligand 1 expression correlates with nodal metastasis in patients with cutaneous squamous cell carcinoma of the head and neck. J Am Acad Dermatol. 2017;77(3):527-533. doi:10.1016/j.jaad.2017.05.047
54. Slater NA, Googe PB. PD-L1 expression in cutaneous squamous cell carcinoma correlates with risk of metastasis. J Cutan Pathol. 2016;43(8):663-670. doi:10.1111/cup.12728
55. Amoils M, Kim J, Lee C, et al. PD-L1 expression and tumor-infiltrating lymphocytes in high-risk and metastatic cutaneous squamous cell carcinoma. Otolaryngol Head Neck Surg. 2019;160(1):93-99. doi:10.1177/0194599818788057
56. Maly CJ, Cumsky HJL, Costello CM, et al. Prognostic value of inositol polyphosphate-5-phosphatase expression in recurrent and metastatic cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2020;82(4):846-853. doi:10.1016/j.jaad.2019.08.027
57. Cumsky HJL, Costello CM, Zhang N, et al. The prognostic value of inositol polyphosphate 5-phosphatase in cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2019;80(3):626-632.e1. doi:10.1016/j.jaad.2018.10.018
58. Chen MK, Cai MY, Luo RZ, et al. Overexpression of p300 correlates with poor prognosis in patients with cutaneous squamous cell carcinoma. Br J Dermatol. 2015;172(1):111-119. doi:10.1111/bjd.13226
59. Campos MA, Macedo S, Fernandes M, et al. TERT promoter mutations are associated with poor prognosis in cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2019;80(3):660-669.e6. doi:10.1016/j.jaad.2018.08.032
60. Xu R, Cai MY, Luo RZ, Tian X, Han JD, Chen MK. The expression status and prognostic value of xancer stem cell biomarker CD133 in cutaneous squamous cell carcinoma. JAMA Dermatol. 2016;152(3):305-311. doi:10.1001/jamadermatol.2015.3781
61. Piipponen M, Nissinen L, Riihilä P, et al. p53-Regulated long noncoding RNA PRECSIT promotes progression of cutaneous squamous cell carcinoma via STAT3 signaling. Am J Pathol. 2020;190(2):503-517. doi:10.1016/j.ajpath.2019.10.019
62. Ch'ng S, Low I, Ng D, et al. Epidermal growth factor receptor: a novel biomarker for aggressive head and neck cutaneous squamous cell carcinoma. Hum Pathol. 2008;39(3):344-349. doi:10.1016/j.humpath.2007.07.004
63. Cañueto J, Cardeñoso E, García JL, et al. Epidermal growth factor receptor expression is associated with poor outcome in cutaneous squamous cell carcinoma. Br J Dermatol. 2017;176(5):1279-1287. doi:10.1111/bjd.14936
64. Arron ST, Wysong A, Hall MA, et al. Gene expression profiling for metastatic risk in head and neck cutaneous squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2022;7(1):135-144. doi:10.1002/lio2.724
65. Ibrahim SF, Kasprzak JM, Hall MA, et al. Enhanced metastatic risk assessment in cutaneous squamous cell carcinoma with the 40-gene expression profile test. Future Oncol. 2022;18(7):833-847. doi:10.2217/fon-2021-1277
66. Borman S, Wilkinson J, Meldi-Sholl L, et al. Analytical validity of DecisionDx-SCC, a gene expression profile test to identify risk of metastasis in cutaneous squamous cell carcinoma (SCC) patients. Diagn Pathol. 2022;17(1):32. doi:10.1186/s13000-022-01211-w
67. Farberg AS, Hall MA, Douglas L, et al. Integrating gene expression profiling into NCCN high-risk cutaneous squamous cell carcinoma management recommendations: impact on patient management. Curr Med Res Opin. 2020;36(8):1301-1307. doi:10.1080/03007995.2020.1763284
68. Arron ST, Blalock TW, Guenther JM, et al. Clinical considerations for integrating gene expression profiling into cutaneous squamous cell carcinoma management. J Drugs Dermatol. 2021;20(6):5s-s11. doi:10.36849/JDD.2021.6068
69. Au JH, Hooper PB, Fitzgerald AL, Somani AK. Clinical utility of the 40-gene expression profile (40-GEP) test for improved patient management decisions and disease-related outcomes when combined with current clinicopathological risk factors for cutaneous squamous cell carcinoma (cSCC): Case Series. Dermatol Ther (Heidelb). 2022;12(2):591-597. doi:10.1007/s13555-021-00665-y
70. Litchman GH, Fitzgerald AL, Kurley SJ, Cook RW, Rigel DS. Impact of a prognostic 40-gene expression profiling test on clinical management decisions for high-risk cutaneous squamous cell carcinoma. Curr Med Res Opin. 2020;36(8):1295-1300. doi:10.1080/03007995.2020.176328
71. Rebeca T, Giselle P, Litchman GH, Rigel DS. Impact of gene expression profile testing on the management of squamous cell carcinoma by dermatologists. J Drugs Dermatol. 2019;18(10):980-984.
72. Saleeby R, Bielinksi K, Fitzgerald A, Siegel J, Ibrahim S. A prospective, multi-center clinical utility study demonstrates that the 40-gene expression profile (40-GEP) test impacts clinical management for Medicare-eligible patients with high-risk cutaneous squamous cell carcinoma (cSCC). SKIN The Journal of Cutaneous Medicine. 2022;6(6):482-496.
73. Hooper PB, Farberg AS, Fitzgerald AL, et al. Real-world evidence shows clinicians appropriately use the prognostic 40-gene expression profile (40-GEP) test for high-risk cutaneous squamous cell carcinoma (cSCC) patients. Cancer Invest. 2022;40(10):911-922. doi:10.1080/07357907.2022.2116454
74. Tokez S, Venables ZC, Hollestein LM, et al. Risk factors for metastatic cutaneous squamous cell carcinoma: refinement and replication based on 2 nationwide nested case-control studies. J Am Acad Dermatol. 2022;87(1):64-71. doi:10.1016/j.jaad.2022.02.056
75. Part II head and neck. In: Amin MB, Edge S, Green F, et al., eds. AJCC Cancer Staging Manual. 8^th ed. Springer; 2018.
76. Levine DE, Karia PS, Schmults CD. Outcomes of patients with multiple cutaneous squamous cell carcinomas: a 10-year single-institution cohort study. JAMA Dermatol. 2015;151(11):1220-1225. doi:10.1001/jamadermatol.2015.1702
77. Eigentler TK, Leiter U, Häfner HM, Garbe C, Röcken M, Breuninger H. Survival of patients with cutaneous squamous cell carcinoma: results of a prospective cohort study. J Invest Dermatol. 2017;137(11):2309-2315. doi:10.1016/j.jid.2017.06.025
78. Brantsch KD, Meisner C, Schönfisch B, et al. Analysis of risk factors determining prognosis of cutaneous squamous-cell carcinoma: a prospective study. Lancet Oncol. 2008;9(8):713-720. doi:10.1016/S1470-2045(08)70178-5
79. Roozeboom MH, Lohman BG, Westers-Attema A, et al. Clinical and histological prognostic factors for local recurrence and metastasis of cutaneous squamous cell carcinoma: analysis of a defined population. Acta Derm Venereol. 2013;93(4):417-421. doi:10.2340/00015555-1501
80. Harb JN, Owens AL, Potter KM, Montuno M, De Jesus RO, Konda S. Resident rounds part III: case report: metastatic cutaneous squamous cell carcinoma in an African American female. J Drugs Dermatol. 2017;16(1):81-84.
81. Harb JN, Owens AL, Potter KM, Montuno M, De Jesus RO, Konda S. Resident rounds part III: case report: metastatic cutaneous squamous cell carcinoma in an African American female. J Drugs Dermatol. 2017;16(1):81-84.
82. Agbai ON, Buster K, Sanchez M, et al. Skin cancer and photoprotection in people of color: a review and recommendations for physicians and the public. J Am Acad Dermatol. 2014;70(4):748-762. doi:10.1016/j.jaad.2013.11.038
83. Bradford PT. Skin cancer in skin of color. Dermatol Nurs. 2009;21(4):170-178.
84. Battie C, Gohara M, Verschoore M, Roberts W. Skin cancer in skin of color: an update on current facts, trends, and misconceptions. J Drugs Dermatol. 2013;12(2):194-198.

• Provider Education/Guidance

• Cutaneous Squamous Cell Carcinoma