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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 why multiple studies of the same marker lead to differing conclusions. A variety of methodological 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 provide helpful suggestions on how to present 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.boxed-text

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References

  1. Hayes DF et al. (1996) Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers. J Natl Cancer Inst 88: 1456–1466

    Article  CAS  Google Scholar 

  2. Bast RC Jr et al. for the American Society of Clinical Oncology Tumor Markers Expert Panel. (2001) 2000 update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol 19: 1865–1878

    Article  Google Scholar 

  3. Schilsky RL and Taube SE (2002) Introduction: tumor markers as clinical cancer tests—are we there yet? Semin Oncol 29: 211–212

    Article  Google Scholar 

  4. McGuire WL (1991) Breast cancer prognostic factors: evaluation guidelines. J Natl Cancer Inst 83: 154–155

    Article  CAS  Google Scholar 

  5. Fielding LP et al. (1992) The future of prognostic factors in outcome prediction for patients with cancer. Cancer 70: 2367–2377

    Article  CAS  Google Scholar 

  6. Burke HB and Henson DE (1993) Criteria for prognostic factors and for an enhanced prognostic system. Cancer 72: 3131–3135

    Article  CAS  Google Scholar 

  7. Concato J et al. (1993) The risk of determining risk with multivariable models. Ann Intern Med 118: 201–210

    Article  CAS  Google Scholar 

  8. Gasparini G et al. (1993) Evaluating the potential usefulness of new prognostic and predictive indicators in node-negative breast cancer patients. J Natl Cancer Inst 85: 1206–1219

    Article  CAS  Google Scholar 

  9. Simon R and Altman DG (1994) Statistical aspects of prognostic factor studies in oncology. Br J Cancer 69: 979–985

    Article  CAS  Google Scholar 

  10. Gasparini G (1998) Prognostic variables in node-negative and node-positive breast cancer. Breast Cancer Res Treat 52: 321–331

    Article  CAS  Google Scholar 

  11. Hall PA and Going JJ (1999) Predicting the future: a critical appraisal of cancer prognosis studies. Histopathology 35: 489–494

    Article  CAS  Google Scholar 

  12. Hoppin JA et al. (2002) Potential for selection bias with tumor tissue retrieval in molecular epidemiology studies. Ann Epidemiol 12: 1–6

    Article  Google Scholar 

  13. Thor AD et al. (1999) Comparison of mitotic index, in vitro bromodeoxyuridine labeling, and MIB-1 assays to quantitate proliferation in breast cancer. J Clin Oncol 17: 470–477

    Article  CAS  Google Scholar 

  14. Gancberg D et al. (2000) Sensitivity of HER-2/neu antibodies in archival tissue samples of invasive breast carcinomas. Correlation with oncogene amplification in 160 cases. Am J Clin Pathol 113: 675–682

    Article  CAS  Google Scholar 

  15. McShane LM et al. and the National Cancer Institute Bladder Tumor Marker Network (2000) Reproducibility of p53 immunohistochemistry in bladder tumors. Clin Cancer Res 6: 1854–1864

    CAS  PubMed  Google Scholar 

  16. Paik S et al. (2002) Real-world performance of HER2 testing—National Surgical Adjuvant Breast and Bowel Project Experience. J Natl Cancer Inst 94: 852–854

    Article  Google Scholar 

  17. Roche PC et al. (2002) Concordance between local and central laboratory HER2 testing in the breast intergroup trial N9831. J Natl Cancer Inst 94: 855–857

    Article  Google Scholar 

  18. Altman DG et al. (1995) Review of survival analyses published in cancer journals. Br J Cancer 72: 511–518

    Article  CAS  Google Scholar 

  19. Brundage MD et al. (2002) Prognostic factors in non-small cell lung cancer: a decade of progress. Chest 122: 1037–1057

    Article  Google Scholar 

  20. Mirza AN et al. (2002) Prognostic factors in node-negative breast cancer: a review of studies with sample size more than 200 and follow-up more than 5 years. Ann Surg 235: 10–26

    Article  Google Scholar 

  21. Riley RD et al. (2003) Reporting of prognostic markers: current problems and development of guidelines for evidence-based practice in the future. Br J Cancer 88: 1191–1198

    Article  CAS  Google Scholar 

  22. Riley RD et al. (2003) A systematic review of molecular and biological markers in tumours of the Ewing's sarcoma family. Eur J Cancer 39: 19–30

    Article  CAS  Google Scholar 

  23. Burton A and Altman DG (2004) Missing covariate data within cancer prognostic studies: a review of current reporting and proposed guidelines. Br J Cancer 91: 4–8

    Article  CAS  Google Scholar 

  24. Popat S et al. (2004) Thymidylate synthase expression and prognosis in colorectal cancer: a systematic review and meta-analysis. J Clin Oncol 22: 529–536

    Article  CAS  Google Scholar 

  25. Riley RD et al. (2004) A systematic review of molecular and biological tumor markers in neuroblastoma. Clin Cancer Res 10: 4–12

    Article  CAS  Google Scholar 

  26. Altman DG and Lyman GH (1998) Methodological challenges in the evaluation of prognostic factors in breast cancer. Breast Cancer Res Treat 52: 289–303

    Article  CAS  Google Scholar 

  27. Gion M et al. (1999) A guide for reviewing submitted manuscripts (and indications for the design of translational research studies on biomarkers). Int J Biol Markers 14: 123–133

    Article  CAS  Google Scholar 

  28. Altman DG (2001) Systematic reviews of evaluations of prognostic variables. In Systematic reviews in health care. Metaanalysis in context, edn 2, 228–247 (Eds Egger M et al.) London: BMJ Books

    Chapter  Google Scholar 

  29. Altman DG (2001) Systematic reviews of evaluations of prognostic variables. BMJ 323: 224–228

    Article  CAS  Google Scholar 

  30. McShane LM and Simon R (2001) Statistical methods for the analysis of prognostic factor studies. In Prognostic factors in cancer, edn 2, 37–48 (Eds Gospodarowicz MK et al.) New York: Wiley-Liss

    Google Scholar 

  31. Simon R (2001) Evaluating prognostic factor studies. In Prognostic factors in cancer, edn 2, 49–56 (Eds Gospodarowicz MK et al.) New York: Wiley-Liss

    Google Scholar 

  32. Biganzoli E et al. (2003) Biostatistics and tumor marker studies in breast cancer: design, analysis and interpretation issues. Int J Biol Markers 18: 40–48

    Article  CAS  Google Scholar 

  33. Schumacher M et al.: Prognostic factor studies. In: Handbook of Statistics in Clinical Oncology (Ed Crowley J) New York: CRC Press, in press

  34. Moher D et al. for the CONSORT Group (2001) The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. JAMA 285: 1987–1991

    Article  CAS  Google Scholar 

  35. Bossuyt PM et al. (2003) Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Standards for Reporting of Diagnostic Accuracy. Clin Chem 49: 1–6

    Article  CAS  Google Scholar 

  36. Altman DG et al. (1994) Dangers of using “optimal” cutpoints in the evaluation of prognostic factors. J Natl Cancer Inst 86: 829–835

    Article  CAS  Google Scholar 

  37. Hilsenbeck SG et al. (1992) Why do so many prognostic factors fail to pan out? Breast Cancer Res Treat 22: 197–206

    Article  CAS  Google Scholar 

  38. Moher D et al. for the QUOROM Group (1999) Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Lancet 354: 1896–1900

    Article  CAS  Google Scholar 

  39. Stroup DF et al. (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 283: 2008–2012

    Article  CAS  Google Scholar 

  40. Hammond ME and Taube SE (2002) Issues and barriers to development of clinically useful tumor markers: a development pathway proposal. Seminars in Oncology 29: 213–221

    Article  Google Scholar 

  41. Altman DG et al. for the CONSORT Group (2001) The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med 134: 663–694

    Article  CAS  Google Scholar 

  42. Bossuyt PM et al. (2003) Standards for Reporting of Diagnostic Accuracy. The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clin Chem 49: 7–18

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful to the US National Cancer Institute and the European Organisation for Research and Treatment of Cancer for their support of the NCI–EORTC International Meetings on Cancer Diagnostics from which the idea for these guidelines originated. We thank the UK National Translational Cancer Research Network for financial support provided to DG Altman.

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Correspondence to Lisa M McShane.

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The author declare no competing financial interests.

Glossary

CONSORT

Consolidated Standards of Reporting Trials

STARD

Standards for Reporting of Diagnostic Accuracy

QUOROM

Quality of Reporting of Meta-analyses

MOOSE

Meta-analysis Of Observational Studies in Epidemiology

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for the Statistics Subcommittee of the NCI—EORTC Working Group on Cancer Diagnostics. REporting recommendations for tumor MARKer prognostic studies (REMARK). Nat Rev Clin Oncol 2, 416–422 (2005). https://doi.org/10.1038/ncponc0252

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