Citations

OBJECTIVES— To systematically review the incidence of posttransplantation diabetes (PTD), risk factors for its development, prognostic implications, and optimal management.RESEARCH DESIGN AND METHODS— We searched databases (MEDLINE, EMBASE, the Cochrane Library, and others) from inception to September 2000, reviewed bibliographies in reports retrieved, contacted transplantation experts, and reviewed specialty journals. Two reviewers independently determined report inclusion (original studies, in all languages, of PTD in adults with no history of diabetes before transplantation), assessed study methods, and extracted data using a standardized form. Meta-regression was used to explain between-study differences in incidence.RESULTS— Nineteen studies with 3,611 patients were included. The 12-month cumulative incidence of PTD is lower (<10% in most studies) than it was 3 decades ago. The type of immunosuppression explained 74% of the variability in incidence (P = 0.0004). Risk factors were patient age, nonwhite ethnicity, glucocorticoid treatment for rejection, and immunosuppression with high-dose cyclosporine and tacrolimus. PTD was associated with decreased graft and patient survival in earlier studies; later studies showed improved outcomes. Randomized trials of treatment regimens have not been conducted.CONCLUSIONS— Physicians should consider modification of immunosuppressive regimens to decrease the risk of PTD in high-risk transplant recipients. Randomized trials are needed to evaluate the use of oral glucose-lowering agents in transplant recipients, paying particular attention to interactions with immunosuppressive drugs.

Purpose: Several Medline search strategies exist to retrieve complementary and alternative medicine (CAM) literature related to oncology. The objective of this study was to compare different search methods to ascertain the most optimal strategy. Methods: All clinical trials with CAM interventions in patients with cancer, published from 1965 to 2004, were abstracted using 4 different approaches. In the CAM filter search, the PubMed complementary medicine filter was used. The Ovid search was performed using a complex search strategy with the Ovid search engine. CAM keyword and not phytogenic searches involved the CAM filter search with the addition of the search terms “AND (complementary OR alternative)” and “NOT (antineoplastic agents, phytogenic), respectively. Articles were evaluated by 3 reviewers to ascertain whether they were clinical trials, the study intervention was related to CAM, and the condition prevented/treated was cancer related (inclusion criteria). Results: The CAM filter search retrieved 10 718 citations, Ovid retrieved 1190, CAM keyword retrieved 2895, and not phytogenic retrieved 1806. Compared to the CAM filter search, all other methods had significantly lower sensitivity (Ovid 48.3% ± 3.2%, CAM keyword 5.8% ± 1.5%, and not phytogenic 77.9% ± 2.7%, P < .001). The specificity of Ovid (38.4% ± 2.8%) and not phytogenic (40.8% ± 2.3%) searches was significantly higher ( P < .001) compared to CAM filter (8.8% ± 0.5%) and CAM keyword searches (1.9% ± 0.5%). Conclusion: The search strategy using PubMed’s complementary medicine filter, although comprehensive, lacks specificity; other methods, although more specific, lack sensitivity. Future indexing of all CAM clinical trials with a common medical subject heading term complementary medicine would enhance efficient retrieval of relevant citations.