Strengthening the reporting of genetic risk prediction studies: the GRIPS statement

Janssens et al. Genome Medicine 2011, 3:16 http://genomemedicine.com/content/3/3/16 CO R R E S P O N D E N C E Open Access Strengthening the reporting of genetic risk prediction studies: the GRIPS statement A Cecile JW Janssens1*, John PA Ioannidis2,3,4,5,6, Cornelia M van Duijn1, Julian Little7 and Muin J Khoury8; for the GRIPS Group Abstract The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but the quality and completeness of reporting varies. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of genetic risk prediction studies (the GRIPS statement), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct, or analysis. A detailed Explanation and Elaboration document is published at http://www.plosmedicine.org. Introduction The recent successes of genome-wide association studies and the promises of whole genome sequencing fuel interest in the translation of this new wave of basic genetic knowledge to health care practice. Knowledge about genetic risk factors may be used to target diagnostic, preventive, and therapeutic interventions for complex disorders based on a person’s genetic risk, or to complement existing risk models based on classical nongenetic factors, such as the Framingham risk score for cardiovascular disease. Implementation of genetic risk prediction in health care requires a series of studies that encompass all phases of translational research [1,2], *Correspondence: A Cecile JW Janssens. Email: 1 Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, Rotterdam 3000 CA, The Netherlands Full list of author information is available at the end of the article starting with a comprehensive evaluation of genetic risk prediction. With increasing numbers of discovered genetic markers that can be used in future genetic risk prediction studies, it is crucial to enhance the quality of the reporting of these studies, since valid interpretation could be compromised by the lack of reporting of key information. Information that is often missing includes details in the description of how the study was designed and conducted (for example, how genetic variants were selected and coded, how risk models or genetic risk scores were constructed, and how risk categories were chosen), or how the results should be interpreted. An appropriate assessment of the study’s strengths and weaknesses is not possible without this information. There is ample evidence that prediction research often suffers from poor design and bias, and these may also have an impact on the results of the studies and on models of disease outcomes based on these studies [3-5]. Although most prognostic studies published to date claim significant results [6,7], very few translate to clinically useful applications. Just as for observational epidemiological studies [8], poor reporting complicates the use of the specific study for research, clinical, or public health purposes and hampers the synthesis of evidence across studies. Reporting guidelines have been published for various research designs [9], and these contain many items that are also relevant to genetic risk prediction studies. In particular, the guidelines for genetic association studies (STrenghtening the REporting of Genetic Association studies - STREGA) have relevant items on the assessment of genetic variants, and the guidelines for observational studies (Strengthening the Reporting of OBservational studies in Epidemiology - STROBE) have relevant items about the reporting of study design. The guidelines for diagnostic studies (STAndards for Reporting Diagnostic accuracy - STARD) and those for tumor marker prognostic studies (Reporting of tumor MARKer studies REMARK) include relevant items about test evaluation; © 2011 Janssens et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Janssens et al. Genome Medicine 2011, 3:16 http://genomemedicine.com/content/3/3/16 the REMARK guidelines also have relevant items about risk prediction [10-13]. However, none of these guidelines are fully suited to genetic risk prediction studies, an emerging field of investigation with specific methodo logical issues that need to be addressed, such as the handling of large numbers of genetic variants (from tens to tens of thousands) and flexibility in handling such large numbers in analyses. We organized a two-day workshop with an international group of risk prediction researchers, epidemiologists, geneticists, methodologists, statisticians, and journal editors to develop recom mendations for the reporting of genetic risk prediction studies - the GRIPS statement. Genetic risk prediction studies Genetic risk prediction studies typically develop or validate models that predict the risk of disease, but they are also being investigated for use in predicting prognostic outcome, treatment response, or treatment-related harms. Risk prediction models are statistical algorithms, which may be simple genetic risk scores (for example, risk allele counts), may be based on regression analyses (for example, weighted risk scores or predicted risks), or may be based on more complex analytic approaches, such as support vector machine learning or classification trees. The risk models may be based on genetic variants only, or include both genetic and non-genetic risk factors [14]. Aims and use of the GRIPS statement The 25 items of the GRIPS statement are intended to maximize the transparency, quality, and completeness of reporting on research methodology and findings in a particular study. It is important to emphasize that these recommendations are guidelines only for how to report research and do not prescribe how to perform genetic risk prediction studies. The guidelines do not support or oppose the choice of any particular study design or method; for example, the guidelines recommend that the study population should be described, but do not specify which population is preferred in a particular study. The intended audience for the reporting guidelines is broad and includes epidemiologists, geneticists, statis ticians, clinician scientists, and laboratory-based investi gators who undertake genetic risk prediction studies, as well as journal editors and reviewers who have to appraise the design, conduct and analysis of such studies. In addition (...truncated)