Rapid complete response of metastatic melanoma in a patient undergoing ipilimumab immunotherapy in the setting of active ulcerative colitis.

While blockade of the cytotoxic T-lymphocyte antigen-4 (CTLA-4) T cell regulatory receptor has become a commonly utilized strategy in the management of advanced melanoma, many questions remain regarding the use of this agent in patient populations with autoimmune disease. We present a case involving the treatment of a patient with stage IV melanoma and ulcerative colitis (UC) with anti-CTLA-4 antibody immunotherapy. Upon initial treatment, the patient developed grade III colitis requiring tumor necrosis factor-alpha (TNF-α) blocking antibody therapy, however re-treatment with anti-CTLA-4 antibody following a total colectomy resulted in a rapid complete response accompanied by the development of a tracheobronchitis, a previously described extra-intestinal manifestation of UC. This case contributes to the evolving literature on the use of checkpoint inhibitors in patients also suffering from autoimmune disease, supports future clinical trials investigating the use of these agents in patients with autoimmune diseases, and suggests that an understanding of the specific molecular pathways involved in a patient's autoimmune pathology may provide insight into the development of more effective novel combinatorial immunotherapeutic strategies.

SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

We propose a novel unsupervised approach for linking records across arbitrarily many files, while simultaneously detecting duplicate records within files. Our key innovation is to represent the pattern of links between records as a {\em bipartite} graph, in which records are directly linked to latent true individuals, and only indirectly linked to other records. This flexible new representation of the linkage structure naturally allows us to estimate the attributes of the unique observable people in the population, calculate $k$-way posterior probabilities of matches across records, and propagate the uncertainty of record linkage into later analyses. Our linkage structure lends itself to an efficient, linear-time, hybrid Markov chain Monte Carlo algorithm, which overcomes many obstacles encountered by previously proposed methods of record linkage, despite the high dimensional parameter space. We assess our results on real and simulated data.