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  • Post-transplant lymphoproli...
    Kumarasinghe, Gayathri; Lavee, Orly; Parker, Andrew; Nivison-Smith, Ian; Milliken, Samuel; Dodds, Anthony; Joseph, Joanne; Fay, Keith; Ma, David D; Malouf, Monique; Plit, Marshall; Havryk, Adrian; Keogh, Ann M; Hayward, Christopher S; Kotlyar, Eugene; Jabbour, Andrew; Glanville, Allan R; Macdonald, Peter S; Moore, John J

    The Journal of heart and lung transplantation, 11/2015, Letnik: 34, Številka: 11
    Journal Article

    Heart and lung transplant recipients have among of the highest incidence rates of post-transplant lymphoproliferative disease (PTLD). Despite this, there is a paucity of data specific to this group. We collated data on heart, lung and heart-lung transplant recipients with PTLD to identify disease features and prognostic factors unique to this group of patients. Seventy cases of PTLD were identified from a single institution (41 heart, 22 lung, 6 heart-lung and 1 heart-kidney transplant) from 1984 to 2013. Demographics, immunosuppression, treatment, response, complications and survival data were analyzed. Uni- and multivariate Cox regression analyses were performed to identify prognostic factors. The incidence of PTLD was 7.59% in heart-lung, 5.37% in heart and 3.1% in lung transplant recipients. Extranodal disease (82%) with diffuse large B-cell lymphoma (72%) was the most common presentation. Bone marrow involvement (13%) and central nervous system disease (3%) were uncommon. Heart transplant recipients had later onset of PTLD (>1 year post-transplant), with less allograft involvement, compared with lung and heart-lung recipients. Poor prognostic markers were bone marrow involvement (HR 6.75, p < 0.001) and serum albumin <30 g/liter (HR 3.18, p = 0.006). Improved survival was seen with a complete response within 3 months of treatment (HR 0.08, p < 0.001). Five-year overall survival was 29%. This analysis is the largest to date on PTLD in heart and lung transplant recipients. It provides a detailed analysis of the disease in this group of patients and identifies unique prognostic features to aid risk stratification and guide treatment allocation.