The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index.
Methodological challenges in the evaluation of prognostic factors in breast cancer.
Abstract
Many studies are carried out in an effort to find factors that help explain the large unexplained variation in prognosis of breast cancer patients. The principles of good study design and analysis are less well appreciated for prognostic factor studies than for therapeutic trials. The oncology literature is full of results from studies of varying quality, often with conflicting findings. As a consequence, despite the large number of studies, there is still uncertainty about the importance of most prognostic factors. Few recently proposed prognostic factors for breast cancer have become widely accepted. This paper reviews the important methodological issues underlying such research. These issues are illustrated with examples from published studies and recent reviews of papers published in cancer journals. Guidelines are proposed for conducting and evaluating prognostic factor studies which should improve the quality of research in this important area.
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“Poor reporting of sample size rationale has also been observed by others [3],[21],[68].”
From Reporting and Methods in Clinical Prediction Research: A Systematic Review (2012) · cites this paper as [3]
Citations
Cites
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Self-citationRegression Models and Life-Tables
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Self-citationSample Size Tables for Clinical Studies
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Dangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors
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Self-citationPublication bias: evidence of delayed publication in a cohort study of clinical research projects
Stern, J. M., & Simes, R. J. (1997) · BMJ · doi:10.1136/bmj.315.7109.640 · Cited by 818
Flagged first, then by citations
1 of the 63 references couldn’t be matched to a known paper.
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- Gardner MJ, Altman DG (eds) Statistics with Confidence. British Medical Journal, London, 1989
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Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)
McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/dji237 · Cited by 2,162
Self-citationMoons, K. G. M., de Groot, J. A. H., Bouwmeester, W., Vergouwe, Y., Mallett, S., Altman, D. G., Reitsma, J. B., & Collins, G. S. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001744 · Cited by 2,018
Self-citationCassidy, J. D., Carroll, L., Peloso, P. M. J., Borg, J., von Holst, H., Holm, L. W., Kraus, J. F., & Coronado, V. G. (2004) · Journal of Rehabilitation Medicine · doi:10.1080/16501960410023732 · Cited by 1,612
Evaluation of the Quality of Prognosis Studies in Systematic Reviews
Hayden, J. A., Côté, P., & Bombardier, C. (2006) · Annals of Internal Medicine · doi:10.7326/0003-4819-144-6-200603210-00010 · Cited by 1,452
REporting recommendations for tumour MARKer prognostic studies (REMARK).
for the Statistics Subcommittee of the NCI-EORTC Working Group on Cancer Diagnostics, McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · British Journal of Cancer · doi:10.1038/sj.bjc.6602678 · Cited by 1,394
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Metadata
- Authors
- Altman, D. G., & Lyman, G. H.
- Affiliations
- University of Oxford (GB)
- University of South Florida (US)
- Venue
- Breast Cancer Research and Treatment
- Published
- 1998-11
- Volume
- 52
- Issue
- 1-3
- Pages
- 289-303
- ISSN
- 0167-6806 (ISSN-L)
- 1573-7217
- OpenAlex
- W2092931112
- Cited by
- 271
- References
- 63
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 7 · 2023: 6 · 2022: 6 · 2021: 6 · 2020: 9 · 2019: 2 · 2018: 5 · 2017: 4 · 2016: 2 · 2015: 4 · 2014: 9 · 2013: 11 · 2012: 17
- FWCI
- 0.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Breast Cancer Research and Treatment (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- breast cancer, prognostic factors, research design, statistical analysis, research quality, methodological issues, research guidelines
- MeSH terms
- Breast Neoplasms, Female, Humans, Prognosis, Regression Analysis, Research Design, Meta-Analysis as Topic, Sample Size
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