The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)
Abstract
Despite years of research and hundreds of reports on tumor markers in oncology, the number of markers that have emerged as clinically useful is pitifully small. Often, initially reported studies of a marker show great promise, but subsequent studies on the same or related markers yield inconsistent conclusions or stand in direct contradiction to the promising results. It is imperative that we attempt to understand the reasons that multiple studies of the same marker lead to differing conclusions. A variety of methodologic problems have been cited to explain these discrepancies. Unfortunately, many tumor marker studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalizability of study results. The development of guidelines for the reporting of tumor marker studies was a major recommendation of the National Cancer Institute-European Organisation for Research and Treatment of Cancer (NCI-EORTC) First International Meeting on Cancer Diagnostics in 2000. As for the successful CONSORT initiative for randomized trials and for the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, preplanned hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, the guidelines suggest helpful presentations of data and important elements to include in discussions. The goal of these guidelines is to encourage transparent and complete reporting so that the relevant information will be available to others to help them to judge the usefulness of the data and understand the context in which the conclusions apply.
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In the citing paper
“While making revisions, conscious efforts were made to harmonize our recommendations with other reporting guidelines, and where possible we chose the same or similar wording for items [37,39,41,45,46].”
From Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement (2015) · cites this paper as [37]
In the citing paper
“These items have been identified as important in several well-known guidelines for reporting of clinical research [4],[38]–[41].”
From Reporting and Methods in Clinical Prediction Research: A Systematic Review (2012) · cites this paper as [4]
In the citing paper
“Most guidelines, such as the STROBE guidelines for the reporting of observational studies or the REMARK guidelines for tumour marker prognostic studies, specifically advise investigators to report both unadjusted results (i.e., from univariable analysis, yielding the association of each candidate predictor with the outcome) and adjusted results (i.e., from a multivariable analysis) [4],[38],[63].”
From Reporting and Methods in Clinical Prediction Research: A Systematic Review (2012) · cites this paper as [4]
In the citing paper
“However, none of these guidelines are entirely appropriate for prediction model studies.”
From Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement (2015) · cites this paper as [37]
In the citing paper
“However, the focus of the REMARK checklist is primarily on prognostic factors and not prediction models, whereas the GRIPS statement is aimed at risk prediction using genetic risk factors and the specific methodological issues around handling large numbers of genetic variants.”
From Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement (2015) · cites this paper as [37]
Citations
Cites
Meta-analysis of Observational Studies in Epidemiology<SUBTITLE>A Proposal for Reporting</SUBTITLE>
Stroup, D. F. (2000) · JAMA · doi:10.1001/jama.283.15.2008 · Cited by 20,623
Moher, D., Schulz, K. F., & Altman, D. G. (2001) · The Lancet · doi:10.1016/s0140-6736(00)04337-3 · Cited by 5,373
Self-citationMoher, D., Cook, D. J., Eastwood, S., Olkin, I., Rennie, D., & Stroup, D. F. (1999) · The Lancet · doi:10.1016/s0140-6736(99)04149-5 · Cited by 4,826
The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration
Altman, D. G., Schulz, K. F., Moher, D., Egger, M., Davidoff, F., Elbourne, D., Gøtzsche, P. C., Lang, T., & for the CONSORT Group (2001) · Annals of Internal Medicine · doi:10.7326/0003-4819-134-8-200104170-00012 · Cited by 3,835
Self-citationTowards complete and accurate reporting of studies of diagnostic accuracy: The STARD Initiative.
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., de Vet, H. C. W., et al. (2003) · Annals of Internal Medicine · doi:10.7326/0003-4819-138-1-200301070-00010 · Cited by 3,219
Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · BMJ · doi:10.1136/bmj.326.7379.41 · Cited by 3,215
Moher, D. (2001) · JAMA · doi:10.1001/jama.285.15.1987 · Cited by 2,545
Systematic Reviews in Health Care : Meta-Analysis in Context
Egger, M., Smith, G. D., & Altman, D. G. (2000) · Cited by 2,312
Self-citationDangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors
Altman, D. G., Lausen, B., Sauerbrei, W., & Schumacher, M. (1994) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/86.11.829 · Cited by 1,143
Self-citationThe Risk of Determining Risk with Multivariable Models
Concato, J., Feinstein, A. R., & Holford, T. R. (1993) · Annals of Internal Medicine · doi:10.7326/0003-4819-118-3-199302010-00009 · Cited by 1,129
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Kim, H. Y., Lee, D. H., Lee, J., Cho, Y. Y., Cho, E. J., Yu, S. J., Kim, Y. J., & Yoon, J. (2018) · BMC Cancer · doi:10.1186/s12885-018-4211-2 · Cited by 31
The potential utility of geminin as a predictive biomarker in breast cancer.
Sundara Rajan, S., Hanby, A. M., Horgan, K., Thygesen, H. H., & Speirs, V. (2014) · Breast Cancer Research and Treatment · doi:10.1007/s10549-013-2786-5 · Cited by 21
Heublein, S., Mayr, D., Egger, M., Karsten, U., Goletz, S., Angele, M., Gallwas, J., Jeschke, U., & Ditsch, N. (2015) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-015-0152-7 · Cited by 18
Metadata
- Authors
- McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- McShane, Lisa M.
- Venue
- JNCI: Journal of the National Cancer Institute
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-08-17
- Volume
- 97
- Issue
- 16
- Pages
- 1180-1184
- ISSN
- 0027-8874 (ISSN-L)
- 1460-2105
- OpenAlex
- W2096910745
- Cited by
- 2,162
- References
- 46
- Citations by year
- 2026: 112 · 2025: 38 · 2024: 44 · 2023: 42 · 2022: 39 · 2021: 93 · 2020: 100 · 2019: 126 · 2018: 116 · 2017: 127 · 2016: 163 · 2015: 192 · 2014: 167 · 2013: 150 · 2012: 173
- FWCI
- 56.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JNCI Journal of the National Cancer Institute (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Yale University
- Yale Cancer Center
- Cancer Research UK
- Translational Cancer Research Network
- National Cancer Institute (MD 20892, 20892)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Oncology › Cancer Diagnosis and Treatment
- Keywords
- tumor markers, prognostic factors, reporting guidelines, remarks, reporting quality, methodological discrepancies, research design, assay method, statistical analysis methods, cancer diagnosis, research transparency
- MeSH terms
- Humans, Neoplasms, Research Design, Biomarkers, Tumor, Information Dissemination, Biomedical Research
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