Replication is an essential part of the scientific method, yet replication of systematic reviews is too often overlooked, and done unnecessarily or poorly. Excessive replication (doing the same study repeatedly) is unethical and a cause of research wastage. This article provides consensus based guidance on when to replicate and not replicate systematic reviews.

N-of-1 trials are a useful tool for clinicians who want to determine the effectiveness of a treatment in a particular individual. The reporting of N-of-1 trials has been variable and incomplete, hindering their usefulness in clinical decision making and by future researchers. This document presents the CONSORT (Consolidated Standards of Reporting Trials) extension for N-of-1 trials (CENT 2015). CENT 2015 extends the CONSORT 2010 guidance to facilitate the preparation and appraisal of reports of an individual N-of-1 trial or a series of prospectively planned, multiple, crossover N-of-1 trials. CENT 2015 elaborates on 14 items of the CONSORT 2010 checklist, totalling 25 checklist items (44 sub-items), and recommends diagrams to help authors document the progress of one participant through a trial or more than one participant through a trial or series of trials, as applicable. Examples of good reporting and evidence based rationale for CENT 2015 checklist items are provided.

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Background: Addresses in some provincial health care registries are not systematically updated. If individuals are attributed to the wrong location, this can lead to errors in health care planning and research. Our purpose was to investigate the accuracy of socioeconomic classification based on addresses in Ontario's provincial health care registry. Methods: The study setting was Toronto's inner city, an area with a population of 799,595 in 1996. We ordered enumeration areas by 1996 mean household income and divided them into five roughly equal income groups by population. We then assigned an income quintile to each individual using both the address from Ontario's provincial heath care registry and that from hospital discharge abstracts. We compared these two sets of income quintiles and also used them to generate quintile-specific rates of medical hospital admissions in the year 2000. Results: Provincial registry and hospital-based addresses agreed on the exact enumeration area for 78.1% of individuals and for income quintile for 84.8% of individuals. Disagreement by more than one income quintile occurred for 7.4% of individuals. The two methods of assigning income quintiles yielded income-specific medical hospitalization rates and rate ratios that agreed within 1%. La traduction du résumé se trouve à la fin de l'article.

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