Budget impact analysis of a novel gene expression assay for the diagnosis of malignant melanoma

Real world validation of an adjunctive gene expression-profiling assay for melanoma diagnosis and correlation with clinical outcomes at an academic center

A commercially available diagnostic gene expression profiling (GEP) assay (MyPath™) reportedly has high sensitivity and specificity in distinguishing nevi from melanoma based on manufacturer-conducted studies. However, data regarding the performance of this GEP assay in routine clinical practice are lacking. The purpose of this study was to better assess the real-world performance of GEP in a large academic practice. Retrospective review of GEP scores were compared with final histomorphologic interpretation on a wide spectrum of melanocytic lesions demonstrating some degree of atypia. In a sample of 369 lesions, the sensitivity (76.1%) and specificity (83.9%) of the GEP test as compared with final dermatopathologist-rendered diagnosis in our dataset was appreciably lower than that reported in the prior manufacturer-conducted validation studies. Limitations of this study were that it was a single-center study, its retrospective nature, nonblinded nature of GEP test result, concordance of only two pathologists, and limited follow-up time.The sensitivity and specificity of a commercially available GEP diagnostic assay for melanoma may be lower in routine clinical practice, where melanocytic lesions typically exhibit some degree of histomorphologic atypia. Reported cost effectiveness of GEP testing is questionable if all ambiguous lesions that undergo such testing are re-excised in clinical practice.

Current Molecular Markers of Melanoma and Treatment Targets

Melanoma is a deadly skin cancer that becomes especially difficult to treat after it metastasizes. Timely identification of melanoma is critical for effective therapy, but histopathologic diagnosis can frequently pose a significant challenge to this goal. Therefore, auxiliary diagnostic tools are imperative to facilitating prompt recognition of malignant lesions. Melanoma develops as result of a number of genetic mutations, with UV radiation often acting as a mutagenic risk factor. Novel methods of genetic testing have improved detection of these molecular alterations, which subsequently revealed important information for diagnosis and prognosis. Rapid detection of genetic alterations is also significant for choosing appropriate treatment and developing targeted therapies for melanoma. This review will delve into the understanding of various mutations and the implications they may pose for clinical decision making.

Technological advances for the detection of melanoma: Advances in molecular techniques

The growth of molecular technologies analyzing skin cells and inherited genetic variations has the potential to address current gaps in both diagnostic accuracy and prognostication in patients with melanoma or in individuals who are at risk for developing melanoma. In the second article in this continuing medical education series, novel molecular technologies are reviewed. These have been developed as adjunct tools for melanoma management and include the Pigmented Lesion Assay, myPath Melanoma, and DecisionDx-Melanoma tests, and genetic testing in patients with a strong familial melanoma history. These tests are commercially available and marketed as ancillary tools for clinical decision-making, diagnosis, and prognosis. We review fundamental principles behind each test, discuss peer-reviewed literature assessing their performance, and highlight the utility and limitations of each assay. The goal of this article is to provide a comprehensive, evidence-based foundation for clinicians regarding the management of patients with difficult pigmented lesions.

A molecular multi-gene classifier for disease diagnostics

Despite its early promise as a diagnostic and prognostic tool, gene expression profiling remains cost-prohibitive and challenging to implement in a clinical setting. Here, we introduce a molecular computation strategy for analysing the information contained in complex gene expression signatures without the need for costly instrumentation. Our workflow begins by training a computational classifier on labelled gene expression data. This in silico classifier is then realized at the molecular level to enable expression analysis and classification of previously uncharacterized samples. Classification occurs through a series of molecular interactions between RNA inputs and engineered DNA probes designed to differentially weigh each input according to its importance. We validate our technology with two applications: a classifier for early cancer diagnostics and a classifier for differentiating viral and bacterial respiratory infections based on host gene expression. Together, our results demonstrate a general and modular framework for low-cost gene expression analysis.

The influence of a gene-expression signature on the treatment of diagnostically challenging melanocytic lesions

AIM

The effect of a gene-expression-based test on treatment of melanocytic neoplasms by dermatologists was evaluated.

PATIENTS & METHODS

Pathologists submitted diagnostically challenging melanocytic neoplasms to a clinical laboratory for testing accompanied by pretest surveys documenting the intended treatment recommendations. The actual treatment rendered by dermatologists was then documented after testing. Changes between the pretest recommendations and actual treatment were analyzed.

RESULTS

In 71.4% (55/77) of cases, there was a change from pretest recommendations to actual treatment. The majority of changes were consistent with the test result. There was an 80.5% (33/41) reduction in the number of biopsy site re-excisions performed for cases with a benign test result.

CONCLUSION

The actual treatment of diagnostically challenging melanocytic neoplasms is influenced by the test.

Underexpression of Specific Interferon Genes Is Associated with Poor Prognosis of Melanoma

Because the prognosis of melanoma is challenging and inaccurate when using current clinical approaches, clinicians are seeking more accurate molecular markers to improve risk models. Accordingly, we performed a survival analysis on 404 samples from The Cancer Genome Atlas (TCGA) cohort of skin cutaneous melanoma. Using our recently developed gene network model, we identified biological signatures that confidently predict the prognosis of melanoma (p-value < 10-5). Our model predicted 38 cases as low-risk and 54 cases as high-risk. The probability of surviving at least 5 years was 64% for low-risk and 14% for high-risk cases. In particular, we found that the overexpression of specific genes in the mitotic cell cycle pathway and the underexpression of specific genes in the interferon pathway are both associated with poor prognosis. We show that our predictive model assesses the risk more accurately than the traditional Clark staging method. Therefore, our model can help clinicians design treatment strategies more effectively. Furthermore, our findings shed light on the biology of melanoma and its prognosis. This is the first in vivo study that demonstrates the association between the interferon pathway and the prognosis of melanoma.

Cost and Budget Impact Analysis of an Accurate Intraoperative Sentinel Lymph Node Diagnosis for Breast Cancer Metastasis

BACKGROUND

Conventional intraoperative sentinel lymph node biopsy (SLNB) in breast cancer (BC) has limitations in establishing a definitive diagnosis of metastasis intraoperatively, leading to an unnecessary second operation. The one-step nucleic amplification assay (OSNA) provides accurate intraoperative diagnosis and avoids further testing. Only five articles have researched the cost and cost effectiveness of this diagnostic tool, although many hospitals have adopted it, and economic evaluation is needed for budget holders.

OBJECTIVE

We aimed to measure the budget impact in Japanese BC patients after the introduction of OSNA, and assess the certainty of the results.

METHODS

Budget impact analysis of OSNA on Japanese healthcare expenditure from 2015 to 2020. Local governments, society-managed health insurers, and Japan health insurance associations were the budget holders. In order to assess the cost gap between the gold standard (GS) and OSNA in intraoperative SLNB, a two-scenario comparative model that was structured using the clinical pathway of a BC patient group who received SLNB was applied. Clinical practice guidelines for BC were cited for cost estimation.

RESULTS

The total estimated cost of all BC patients diagnosed by GS was US$1,023,313,850. The budget impact of OSNA in total health expenditure was -US$24,413,153 (-US$346 per patient). Two-way sensitivity analysis between survival rate (SR) of the GS and OSNA was performed by illustrating a cost-saving threshold: y ≅ 1.14x - 0.16 in positive patients, and y ≅ 0.96x + 0.029 in negative patients (x = SR-GS, y = SR-OSNA). Base inputs of the variables in these formulas demonstrated a cost saving.

CONCLUSION

OSNA reduces healthcare costs, as confirmed by sensitivity analysis.