CORRESPONDENCE

Re: Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)

Sanjay Popat, Richard S. Houlston

Affiliations of authors: Kent Oncology Centre, Maidstone Hospital, Kent, U.K. (SP); Section of Cancer Genetics, Institute of Cancer Research, Sutton, U.K. (RSH)

Correspondence to: Sanjay Popat, BSc, MB, MRCP, PhD, Kent Oncology Centre, Maidstone Hospital, Kent ME16 9QQ, U.K. (e-mail: sanjay.popat{at}icr.ac.uk).

We warmly welcome the National Cancer Institute-European Organisation for Research and Treatment of Cancer (NCI-EORTC) reporting guidelines for tumor marker prognostic studies (REMARK) recently reported in the Journal (1). We believe the authors are correct to point out the inadequacies in reporting results of many tumor marker-prognostic studies and the difficulty in interpreting and comparing data from such articles (2). However, we feel that the authors have missed a major opportunity by falling short of mandating public access to raw time-to-event data.

Although molecular markers that directly determine therapeutic efficacy play a major role in determining prognosis, other molecular determinants may only modulate patient outcome and are likely to have only a small to medium impact on overall patient survival. Most studies of prognostic molecular markers published to date have, however, been based on analyses of small sample sets that have inevitably been too underpowered to realistically determine the true relationship between a marker and patient prognosis. Pooling data from small studies by meta-analyses provides a means of generating more precise estimates of the true impact of markers without wasting considerable resources on clinical trials evaluating potentially nondiscriminating markers. We therefore applaud point 16 in the REMARK guidelines (mandatory citation of the multivariable effect ratio with appropriate confidence intervals), which will substantially aid meta-analysis of published literature by mandating suitable data points and will also help to avoid selection bias by reducing the number of excluded studies in which the marker effect could not be accurately reconstructed.

Meta-analysis of individual patient data is, however, the gold standard for pooling time-to-event data (3), and its clinical utility in assessing therapeutic interventions has been proven. Unfortunately, this method of meta-analysis has had little impact in the field of molecular prognostics because of major constraints that include time, cost, and a requirement for collaboration (and is therefore prone to selection bias because of the potential for excluding datasets from noncollaborating groups) (4). Although others in the molecular marker community have recognized the potential biases associated with analysis of molecular data and have striven for improved clarity by means of public access (5), we feel that the REMARK guidelines have fallen short in this area and have left open the possibility of wasting precious scientific and public effort in analysis of futile markers. Specifically, we do not fully concur with the authors' assertion that to do so would "serve to propagate bad science." This claim is contrary to the fundamental principles of meta-analysis, a technique that, when correctly applied, has the ability not only to accurately gauge the true pooled effect but also to assess and to correct the causes of inconsistency (6).

REFERENCES

(1) McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM, et al. Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK). J Natl Cancer Inst 2005;97:1180–4.[Abstract/Free Full Text]

(2) Simon R, Altman DG. Statistical aspects of prognostic factor studies in oncology. Br J Cancer 1994;69:979–85.[ISI][Medline]

(3) Stewart LA, Parmar MK. Meta-analysis of the literature or of individual patient data: is there a difference? Lancet 1993;341:418–22.[CrossRef][ISI][Medline]

(4) Piedbois P, Buyse M. Meta-analyses based on abstracted data: a step in the right direction, but only a first step. J Clin Oncol 2004;22:3839–41.[Free Full Text]

(5) Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 2001;29:365–71.[CrossRef][ISI][Medline]

(6) Egger M, Smith GD. Meta-analysis: potentials and promise. BMJ 1997;315:1371–4.[Free Full Text]



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