Public Release: 

Annals of Internal Medicine tip sheet for Jan. 6, 2015

American College of Physicians

1. Several common treatments for knee osteoarthritis effective for pain

A variety of oral and injectable treatments for knee osteoarthritis (OA) are more effective than placebo, but head-to-head comparisons are limited, according to a systematic evidence review being published in Annals of Internal Medicine. Knee OA is progressive joint disease affecting nearly 40 percent of the U.S. population over the age of 45. Many oral nonsteroidal anti-inflammatory drugs (NSAIDs) and injectable therapies are available to treat knee OA; however, it is difficult to know which treatments work best because few head-to-head comparison studies are available. Researchers reviewed published research to compare the relative efficacy of commonly used treatments. They selected randomized trials that compared two or more of the following: acetaminophen, diclofenac, ibuprofen, naproxen, celecoxib, corticosteroid injections, hyaluronic acid injections, oral placebo, and placebo injections. At three months, all interventions were significantly better than oral placebo for improving OA pain. Acetaminophen, the most commonly used over-the-counter treatment for knee OA, was shown to be the least effective option for pain. Except for celecoxib, all treatments were significantly better than acetaminophen. Injections proved to be the most effective treatment for knee OA pain. Even placebo injections were better than oral NSAIDs, suggesting a placebo effect of the delivery method.

Note: The article is accompanied by an editorial. The URLs will be live when embargo lifts. For a PDF, please contact Megan Hanks. To interview the lead author, please contact Jeremy Lechan at 617-636-0104 or jlechan@tuftsmedicalcenter.org,

2. New reporting guideline expected to change the landscape of clinical research reporting and improve decision-making

Transparency is a central theme of new TRIPOD recommendations

A consortium of international investigators, health care professionals, and journal editors is releasing a new set of reporting guidelines explicitly developed to improve the quality of reporting of published prediction model studies. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis, or TRIPOD Statement, is being published in Annals of Internal Medicine and 10 other prominent medical journals.

Many reviews have shown that the quality of reporting in published articles describing the development or validation of multivariable prediction models in medicine is poor, making it difficult for the scientific and health care community to objectively judge the strengths and weaknesses of a prediction model study. This is an issue because prediction models are intended to aid health care providers in estimating the probability or risk that a specific disease or condition is present or that a specific event will occur in the future.

The TRIPOD guideline is expected to address this issue by improving the transparency of the reporting of a prediction model study regardless of the study methods used. The guideline consists of a checklist of 22 items to be used in conjunction with the TRIPOD explanation and an elaboration document (http://www.annals.org/article.aspx?doi=10.7326/M14-0698) to support authors in writing reports describing the development, validation or updating of prediction models, aid editors and peer reviewers in reviewing manuscripts submitted for publication, and help readers in critically approaching published reports.

To encourage dissemination of the TRIPOD Statement, the article is also published in the BJOG, British Journal of Cancer, British Journal of Surgery, BMC Medicine, British Medical Journal, Circulation, Diabetic Medicine, European Journal of Clinical Investigation, European Urology, and Journal of Clinical Epidemiology. Up-to-date news on TRIPOD can be accessed at http://www.tripod-statement.org.

Note: The article is accompanied by an editorial. URLs will be live when the embargo lifts. For a PDF, contact Megan Hanks. To speak with the lead author, contact Jo Silva at jo.silva@ndorms.ox.ac.uk or 01865 737 649.

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