Evidence-based assessment and application of prognostic markers: The long way from single studies to meta-analysis

The identification and assessment of prognostic markers constitutes one of the major tasks in clinical research. Despite huge research effort, the prognostic value of most traditional factors under discussion is uncertain and the usefulness of many specific markers, prognostic indices, and classification schemes is still unproven. Results from different studies are often contradictory, and a general assessment of the usefulness of a specific marker is very difficult. One reason is that systematic reviews of prognostic marker studies have received rather little attention in the literature. It is obvious that a clinically useful and sensible systematic review of a prognostic marker is only possible if the published studies reflect the true nature of the marker and if sufficient details are given in each report. An important goal of a systematic review is to produce a quantitative summary of an effect of interest by a meta-analysis, a statistical approach that combines the results of individual primary studies by a weighted average. For observational studies, an estimate from a univariate model is only of limited interest; a multivariable approach is absolutely essential to derive an estimate that is adjusted for other factors. However, even when adjusted estimates are presented, it is common for different studies to use different variables for adjustment, and specific adjustment variables may be measured in different ways or may be used with different scales. These difficulties are partly caused by the large variety of available statistical methods of analyzing prognostic marker studies. In three related papers published in a proceedings volume, Hollander and Sauerbrei (2006), Riley et al. (2006), and Altman et al. (2006) discuss statistical approaches for multivariable analysis, issues of reporting of primary studies, and the feasibility of obtaining individual patient data from multiple studies on prognosis. Hollander and Sauerbrei (2006) show that the specific statistical method can have a strong influence on the final multivariable model and on the interpretation of the effect of a specific factor. Possible approaches to help improve reporting standards are discussed in the paper by Riley et al. (2006), which also considers other important issues such as how to improve the design and clinical relevance of primary prognostic studies. For a sensible summary assessment, individual patient data (IPD) and a close collaboration between different study groups seem to be essential. However, Altman et al. (2006) discuss in their paper practical problems in using the IPD approach to evaluate evidence relating to a prognostic marker. Here the three papers are summarized with the aim of demonstrating difficulties and making some recommendations to improve future research in evidence-based assessment of prognostic markers. For many more details we refer to the original papers.