02574nas a2200217 4500000000100000008004100001100001500042700001600057700001500073700001600088700001700104700001400121700001500135700001300150245016200163250001500325300001200340490000600352520197100358020002702329 2015 d1 aMoseley G.1 aHenschke N.1 aMcAuley J.1 aWilliams C.1 aHübscher M.1 aKamper S.1 aTraeger A.1 aMaher C.00aDevelopment and validation of a screening tool to predict the risk of chronic low back pain in patients presenting with acute low back pain: a study protocol a2015/07/17 ae0079160 v53 a

INTRODUCTION: Around 40% of people presenting to primary care with an episode of acute low back pain develop chronic low back pain. In order to reduce the risk of developing chronic low back pain, effective secondary prevention strategies are needed. Early identification of at-risk patients allows clinicians to make informed decisions based on prognostic profile, and researchers to select appropriate participants for secondary prevention trials. The aim of this study is to develop and validate a prognostic screening tool that identifies patients with acute low back pain in primary care who are at risk of developing chronic low back pain. This paper describes the methods and analysis plan for the development and validation of the tool. METHODS/ANALYSIS: The prognostic screening tool will be developed using methods recommended by the Prognosis Research Strategy (PROGRESS) Group and reported using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. In the development stage, we will use data from 1248 patients recruited for a prospective cohort study of acute low back pain in primary care. We will construct 3 logistic regression models to predict chronic low back pain according to 3 definitions: any pain, high pain and disability at 3 months. In the validation stage, we will use data from a separate sample of 1643 patients with acute low back pain to assess the performance of each prognostic model. We will produce validation plots showing Nagelkerke R(2) and Brier score (overall performance), area under the curve statistic (discrimination) and the calibration slope and intercept (calibration). ETHICS AND DISSEMINATION: Ethical approval from the University of Sydney Ethics Committee was obtained for both of the original studies that we plan to analyse using the methods outlined in this protocol (Henschke et al, ref 11-2002/3/3144; Williams et al, ref 11638).

 a2044-6055 (Electronic)