BACKGROUND. Fanconi anemia (FA) is an autosomal recessive disease associatedwith an abnormal response to DNA damage. Although FA is well known for the association of aplastic anemia and characteristic birth defects, leukemia and solid tumors also occur at a high rate in this group of patients. A review of all reported cases is informative with regard to the specific types of cancer, the ages at which they occur, and the cumulative probability of their development. METHODS.Medline and bibliographies of publications were searched for articles containing "Fanconi's anemia" or "aplastic anemia" and all cases of FA from 1927 through 2001 were included in the database. Cancer cases were identified within these reports. Descriptive statistical analyses were performed using Stata7 software. RESULTS.One thousand three hundred cases of FA were identified. Nine percent had leukemia (primarily acute myeloid leukemia), 7% had myelodysplastic syndrome, 5% had solid tumors, and 3% had liver tumors. Patients with cancer were older than the cancer-free patients at the time of diagnosis of FA. The median age for cancer (including leukemia) was 16, compared with 68 in the general population. The most frequent solid tumors were aerodigestive and gynecological carcinomas. In approximately 25% of patients with cancer, the malignancy preceded the diagnosis of FA. CONCLUSIONS.If the competing risks of aplastic anemia and leukemia could be removed, the estimated cumulative probability of development of a solid tumor in

SummaryThe hand-foot-syndrome (HFS, palmoplantar erythrodysesthesia, chemotherapyassociated acral erythema) is characterized by painful predominantly palmoplantar lesions. The association with different chemotherapeutic agents has been known for over 20 years. More recently, HFS has been reported in association with regimens using targeted agents, in particular the multikinase inhibitors (MKI) sorafenib and sunitinib. The HFS associated with MKI has a different distribution and clinical appearance than the traditional disorder. In this review, similarities and differences between chemotherapy-and MKI-associated HFS are discussed and current recommendations for their prophylaxis and management are summarized.

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Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. However, the combination of classifiers frequently yields superior results, both in machine learning and among humans. In this study, we investigated the potential benefit of combining human and artificial intelligence for skin cancer classification. Methods: Using 11,444 dermoscopic images, which were divided into five diagnostic categories, novel deep learning techniques were used to train a single CNN. Then, both 112 dermatologists of 13 German university hospitals and the trained CNN independently classified a set of 300