Diagnosis of cutaneous T-cell lymphoma by insurance type before and after the Affordable Care Act: a national database study

The Affordable Care Act (ACT) was implemented to increase health care access and reduce the uninsured in the age group between pediatric and Medicare populations (18-64). The association of the ACA with insurance type upon diagnosis (uninsured, Medicaid, non-Medicaid) has been investigated for otolaryngologic, gynecologic, and the top five non-skin malignancies. Such studies for cutaneous malignancies are lacking. We conducted a retrospective analysis of the prospective National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) cancer database to assess the impact of the ACA on new diagnoses of cutaneous T-cell lymphoma (CTCL) by insurance type. Unlike prior studies of other malignancies, we did not observe significant differences between rate of diagnosis of CTCL by insurance type before and after full implementation of the ACA in all states, expansion states, and non-expansion states. Skin cancers do not have screening guidelines and CTCL is an uncommon malignancy, both of which may contribute to these findings. However, Medicaid-expansion states were much closer to reducing the percentage of newly diagnosed uninsured patients with CTCL than non-expansion states. As such, it may be prudent to investigate intrinsic socioeconomic barriers to care in Medicaid patients to improve their access to care to decrease the uninsured population and improve outcomes

Development of Sézary syndrome following the administration of dupilumab

Dupilumab is a monoclonal antibody that inhibits interleukin-4 and interleukin-13 signaling. It is the first biologic agent to demonstrate efficacy in treating moderate-to-severe refractory atopic dermatitis [1, 2]. Although dupilumab provides promise for the treatment of atopic and allergic conditions, clinicians should take into account its novelty and the potential for unexpected adverse events. We present a patient who developed Sézary syndrome following the initiation of dupilumab

Clinical Efficacy of Romidepsin in Tumor Stage and Folliculotropic Mycosis Fungoides

AbstractBackgroundTumor stage and folliculotropic mycosis fungoides are uncommon subtypes of cutaneous T-cell lymphoma (CTCL) with an aggressive disease course. Romidepsin is a histone deacetylase inhibitor approved by the US Food and Drug Administration for patients with CTCL who have received ≥ 1 previous systemic therapy. In the present study, we examined the efficacy and safety of romidepsin in patients from the pivotal, single-arm, open-label, phase II study of relapsed or refractory CTCL with cutaneous tumors and/or folliculotropic disease involvement.Materials and MethodsPatients with CTCL who had received ≥ 1 previous systemic therapy received romidepsin at 14 mg/m2 on days 1, 8, and 15 of 28-day cycles. Responses were determined by a composite endpoint (assessments of the skin, blood, and lymph nodes). Patients with cutaneous tumors and/or folliculotropic disease involvement were identified by review of diagnosis and histology reports.ResultsThe objective response rate to romidepsin was 45% in patients with cutaneous tumors (n = 20) and 60% in patients with folliculotropic disease involvement (n = 10).ConclusionRomidepsin is active in subtypes of CTCL with less favorable outcomes, such as tumor stage and folliculotropic mycosis fungoides

White-light oblique-incidence diffuse reflectance spectroscopy for classification of in-vivo pigmented skin lesions

A study of in-vivo classification of pigmented skin lesions using oblique-incidence diffuse reflectance spectroscopy is presented. Spatio-spectral data in the wavelength range from 455 to 765 nm are collected from 111 pigmented lesions including 10 histopathologically diagnosed as melanoma. The first 67 lesions are used for training the classifiers, and 44 lesions are used for testing. The first classifier separates (1) malignant melanoma and severe dysplastic nevi from (2) moderate and mild dysplastic nevi, common nevi, actinic and seborrheic keratoses. The second classifier next distinguishes between (a) moderate and mild dysplastic nevi, common nevi from (b) actinic and seborrheic keratoses. The third classifier further separates (I) moderate and mild dysplastic nevi from (II) common nevi. The first classifier performs with 100% sensitivity and 91% specificity with overall classification rates of 93% and 95 % for the training and testing sets, respectively. The second classifier has classification rates of 95% and 97 % for the training and testing sets, respectively, whereas the third classifier has classification rates of 98% and 94 % for the training and testing sets, respectively

Skin lesion classification using oblique-incidence diffuse reflectance spectroscopic imaging

We discuss the use of a noninvasive in vivo optical technique, diffuse reflectance spectroscopic imaging with oblique incidence, to distinguish between benign and cancer-prone skin lesions. Various image features were examined to classify the images from lesions into benign and cancerous categories. Two groups of lesions were processed separately: Group 1 includes keratoses, warts versus carcinomas; and group 2 includes common nevi versus dysplastic nevi. A region search algorithm was developed to extract both one- and two-dimensional spectral information. A bootstrap-based Bayes classifier was used for classification. A computer-assisted tool was then devised to act as an electronic second opinion to the dermatologist. Our approach generated only one false-positive misclassification out of 23 cases collected for group 1 and two misclassifications out of 34 cases collected for group 2 under the worst estimation condition

Skin cancer detection by spectroscopic oblique-incidence reflectometry: classification and physiological origins

Data obtained from 102 skin lesions in vivo by spectroscopic oblique-incidence reflectometry were analyzed. The participating physicians initially divided the skin lesions into two visually distinguishable groups based on the lesions’ melanocytic conditions. Group 1 consisted of the following two cancerous and benign subgroups: (1) basal cell carcinomas and squamous cell carcinomas and (2) benign actinic keratoses, seborrheic keratoses, and warts. Group 2 consisted of (1) dysplastic nevi and (2) benign common nevi. For each group, a bootstrap-based Bayes classifier was designed to separate the benign from the dysplastic or cancerous tissues. A genetic algorithm was then used to obtain the most effective combination of spatiospectral features for each classifier. The classifiers, tested with prospective blind studies, reached statistical accuracies of 100% and 95% for groups 1 and 2, respectively. Properties that related to cell-nuclear size, to the concentration of oxyhemoglobin, and to the concentration of deoxyhemoglobin as well as the derived concentration of total hemoglobin and oxygen saturation were defined to explain the origins of the classification outcomes

Oblique-incidence spatially resolved diffuse reflectance spectroscopic diagnosis of skin cancer

This paper presents the use of spatially resolved oblique-incidence diffuse reflectance spectroscopy for skin cancer diagnosis. Spatio-spectral data from 166 pigmented skin lesions were collected for the wavelength range from 455 to 765 nm. A set of neural network based classifiers separates the pigmented malignant melanomas from the benign and dysplastic subgroups. A total of 110 lesions were used as the training set and 56 lesions were used as the testing set. This classifier performs with an overall 100% sensitivity and 92% specificity for the training set and 100% sensitivity and 88% specificity for the testing set. The second classifier was designed to separate the benign from the dysplastic subgroups. For the second classifier a total of 100 lesions were used as the training set and 51 lesions were used as the testing set. The overall classification rates were 94% and 88% for the training and testing sets respectively

Epithelial cancer detection by oblique-incidence optical spectroscopy

This paper presents a study on non-invasive detection of two common epithelial cancers (skin and esophagus) based on oblique incidence diffuse reflectance spectroscopy (OIDRS). An OIDRS measurement system, which combines fiber optics and MEMS technologies, was developed. In our pilot studies, a total number of 137 cases have been measured in-vivo for skin cancer detection and a total number of 20 biopsy samples have been measured ex-vivo for esophageal cancer detection. To automatically differentiate the cancerous cases from benign ones, a statistical software classification program was also developed. An overall classification accuracy of 90% and 100% has been achieved for skin and esophageal cancer classification, respectively