Noninvasive Diagnosis of Melanoma for Today’s Dermatologist

Melanoma incidence and mortality has continually risen over the past 50 years despite countless advances in health care and technology. In fact, melanoma is now considered the 19th most-common malignancy worldwide¹ and among the top cancers in average years of life lost per death.² The primary determinant of patient survival is stage at diagnosis, with 5-year mortality rates remarkably dropping from 97% at stage IA to just 15% to 20% at stage IV.³ Considering its prevalence and prognostic implications, early detection of melanoma should be among the top priorities for all dermatologists and health care providers.

For decades, melanoma diagnosis has followed an algorithmic approach of visual inspection and subsequent biopsy. In this model, dermatologists assess lesional morphology and subjectively determine the need for biopsy, serial follow-up, among others. As one can imagine, the efficacy of such screening is quite variable. In fact, the number of benign lesions needed to be excised (NNE) in order to diagnose a single melanoma can range from four to 40, depending on lesion characteristics and clinician expertise.⁴

As with visual screening, the second half of the classic algorithm, tissue biopsy and histology, comes with its own set of drawbacks, primarily invasiveness and diagnostic reliability. Studies have shown that pigmented lesion specimens are best obtained via excisional biopsy, as to maximize validity of histologic assessment. However, this also correlates to maximum invasiveness, with the largest resultant scar and potential interference to subsequent sentinel lymph node studies.⁵ Alternatively, specimens from less invasive incisional or scouting biopsies can miss critical features found elsewhere in the lesion, which may lead to erroneous diagnosis or staging. Finally, in regard to histologic reliability, a recent study by US pathologists found that surgical biopsy and histopathology carried a false negative rate of 35% in the diagnosis of in situ/stage IA melanoma.⁶ 

In recent years, several tools and techniques have been developed with the intent to improve detection of cutaneous melanoma. Dermoscopy, for example, has become a well-accepted practice to enhance the screening process and reduce key parameters such as numbers needed to biopsy (NNB) and NNE. While this improves the diagnostic algorithm, it does not replace the need for biopsy and histopathologic interpretation. Conversely, the ideal diagnostic model would be noninvasive with consistent, inclusive detection and limited reliance on subjective analysis, both clinical and histological. There are at least two approved techniques at this time that have demonstrated the potential to fulfill such criteria: reflectance confocal microscopy (RCM) and noninvasive genomic analysis (Pigmented Lesion Assay; PLA).

The purpose of this article is to review the published data on these products with an emphasis on practical utility measures, including clinical performance, availability, cost, and limitations. 

Techniques
Here we will briefly review the key principles of each method. As mentioned, the primary focus of this paper is clinical utility; please refer to external sources for further information on the development and basic science of these tools. 

RCM. In essence, RCM provides visualization via the refractive indices of cellular and subcellular components of the skin. Illumination is provided by a nondestructive 830-nm laser source that can penetrate to a depth of nearly the upper papillary dermis (200 µm). Microscopic tissue elements reflect light with their unique refractive indices back through a pinhole aperture, which filters out surrounding light to allow only that from the point of interest to be detected. In this way, both the point of interest and the pinhole aperture align to create a coincidence of two focal planes (hence ‘confocal’) and resultant high-resolution, grayscale imaging (<1 µm horizontal and <5 µm vertical) of 0.5 mm x 0.5 mm to 8 mm x 8 mm areas. The end result is that of real-time imaging at cellular resolution, akin to an optical biopsy. 

Though RCM resolution approaches that of histology, it should be noted that images are acquired in the horizontal plane, parallel to the skin surface, as opposed to the vertical assessment of classic histopathology.^7,8 

PLA. Rather than morphology, PLA utilizes genomic information for a unique molecular approach to melanoma detection. In essence, lesions are analyzed for molecular changes associated with malignant transformation. While genomic analysis has become a mainstay throughout modern oncology, historically, it has required invasive surgical biopsies. Contrarily, PLA makes use of proprietary adhesive patches that are applied over the lesion then removed. The lesional RNA sample obtained in the adhesive is then processed and subjected to reverse transcriptase polymerase chain reaction (PCR) to produce complementary DNA (cDNA). This cDNA is subsequently analyzed via quantitative real-time PCR to measure gene expression.⁹

Samples are assessed for specific genetic targets that tend to become overexpressed within melanoma. Specifically, the PLA detects the expression of two such genes, LINC00518 and PRAME. Though their individual roles in the progression of melanoma are not completely understood, both have been shown to positively correlate with the presence of high-risk driver mutations in the BRAF, NRAS, and TERT promoter genes⁸. 

Limitations of this approach include the inability to obtain sufficient RNA samples from palms, soles, or mucous membranes.⁹

Clinical Impact
This section reviews pertinent findings in the literature and relies on data provided by recent meta-analyses. 

RCM. There are over 800 publications in the literature on RCM, though notably, the vast majority are of international sources. Among this plethora of data, meta-analyses suggest impressive diagnostic capabilities, with sensitivity and specificity of 92.7% and 78.3%, respectively, for melanoma. Furthermore, analyses for all cutaneous malignancies (including nonmelanoma subtypes) have shown to be even more impressive, with a 93.6% sensitivity and 83.7% specificity.⁸  

Practically speaking, the utility of RCM may be best visualized as a rule-out study. In such context, there is a negative predictive value (NPV) of 99%, positive predictive value (PPV) of 87%, and NNB of 6.3. For comparison, those of dermoscopy alone is 95%, 40%, and 19.4, respectively.⁸ 

Commercially available in vivo RCMs (VivaScope System) are Class II, 510(k)-cleared devices.

PLA. Though comparatively less literature exists on the evaluation of PLA, results to date have been just as impressive of that of its RCM counterpart. However, the PLA assesses gene expression changes that may not yet have morphological correlates, with potential to further enhance early detection. As outlined above, the assay tests for detectable levels of PRAME and LINC00518 RNA, with the presence of either or both mutations yielding 91% to 97% sensitivity, 69% to 91% specificity, and >99% NPV for the diagnosis of melanoma.^9-11 

As with RCM, PLA’s noninvasiveness and high NPV may lend it best for ruling out lesions that are clinically equivocal. In fact, initial studies suggest proper usage of PLA could reduce surgical biopsies by approximately 90% while missing fewer melanomas.^10,12 These preliminary findings have been further validated by follow-up registry data. Earlier this year, Ferris et al¹³ reported that their nationwide database failed to demonstrate a single case where melanoma had developed following PLA negativity (12-month monitoring period, N=734). 

Table 1 shows a comparison of RCM and PLA against visual assessment and histopathology (VAH).

Cost
The purpose of this section is to review the financial implications for the patient, provider, and health care system as a whole.

RCM. In 2016, the Centers for Medicare and Medicaid Services (CMS) created six new Current Procedural Terminology (CPT) codes (96931-96936) for physician reimbursement of RCM for cellular and subcellular imaging of skin (Table 2). These codes cover image acquisition and/or interpretation, with relative value units (RVUs) comparable to the technical component and professional component (TC/PC) of 88305. The American Academy of Dermatology (AAD) voiced their support in the development of such codes and have since, along with the College of American Pathologists (CAP), gone on to publish position statements^14,15 in support of their usage. However, several Medicare providers and large private payors have either failed to institute written policy for RCM or have deemed the procedure “experimental/investigational,” utilizing such as terms for claim denials. Both the AAD and CAP have formed In Vivo Microscopy Working Groups to facilitate physician education for image interpretation and billing, and the American Confocal Group (https://americanconfocalgroup.com/) has developed a committee in dedication to working with physicians and payors to reverse negative payment policies. A manufacturer of a clinical RCM device, Caliber I.D., is also aiding physicians with the appeals process.

Evidence on the cost-effectiveness of RCM is particularly limited, with no economic analyses to date on the US health care system. While international studies appear promising, the vast differences between health care systems limit the utility of such data with regards to financial implications.^12,16

PLA. In contrast to RCM, providers are not able to bill for a PLA sampling procedure directly. Similar to routine bloodwork (eg, complete blood cell count), neither the collection nor interpretation of PLA is reimbursable, though there may be implications on degree of management complexity. In fact, this increased complexity may even elicit reclassification of an encounter, depending on the complexity of the decision making, thoroughness of the skin exam, and other visit factors including patient history. 

Similar to RCM, issues have been reported with regards to insurers and claim denials. The PLA service price ranges from $350 to $500, though DermTech has developed extensive programs (eg, prior authorization, financial assistance) to minimize the risk of patient financial burden.

In terms of health economics, PLA has demonstrated potential for cost reduction while improving patient care. In a US economic model, PLA was shown to reduce surveillance and stage-related treatment costs by $119 and $433, respectively, with a total cost savings of $447 (47%) per lesion at PLA price of $500.¹⁷  

Conclusion
For today’s dermatologist, both RCM and PLA can be utilized to assist in the diagnosis of melanoma. Based on clinical data, these techniques may reliably exclude malignancy and, in specific clinical setting, offer alternative to invasive biopsy procedures. Neither technique appears superior (Tables 3 and 4), and maybe even more important, the two do not appear to be mutually exclusive (the authors hypothesize that combination testing may have clinical benefits). The decision of which to use, however, appears less clear, and may ultimately come down to characteristics of both provider and patient.

Dr Creel is a PGY-3 dermatology resident at Louisiana State University Health Sciences Center (LSUHSC) in New Orleans, LA.
Mr Boudreaux is a fourth-year medical student at LSUHSC-Shreveport in Shreveport, LA. Ms Harrington is a third-year medical student at LSUHSC-Shreveport.

Disclosure: The authors report no relevant financial relationships.

References
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14. Position statement on reflectance confocal microscopy (RCM) [position statement]. Rosemont, IL: American Academy of Dermatology; July 27, 2019. https://server.aad.org/forms/policies/uploads/ps/ps-reflectance%20confocal%20microscopy.pdf?. Accessed January 29, 2020.

15. Shevchuck MM, Tearney G, Glassy EF, Myles JL. In vivo microscopy [position statement]. Northfield, IL; College of American Pathologists; August 12, 2013. https://webapps.cap.org/apps/docs/hints/why_ivm.pdf. Accessed February 3, 2020.

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17. Hornberger J, Siegel DM. Economic analysis of a noninvasive molecular pathologic assay for pigmented skin lesions. JAMA Dermatol. 2018;154(9):1025-1031. doi:10.1001/jamadermatol.2018.1764