The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use?
Open accessAbstract
A substantial number of studies have reported the development of gene expression-based prognostic signatures for lung cancer. The ultimate aim of such studies should be the development of well-validated clinically useful prognostic signatures that improve therapeutic decision making beyond current practice standards. We critically reviewed published studies reporting the development of gene expression-based prognostic signatures for non-small cell lung cancer to assess the progress made toward this objective. Studies published between January 1, 2002, and February 28, 2009, were identified through a PubMed search. Following hand-screening of abstracts of the identified articles, 16 were selected as relevant. Those publications were evaluated in detail for appropriateness of the study design, statistical validation of the prognostic signature on independent datasets, presentation of results in an unbiased manner, and demonstration of medical utility for the new signature beyond that obtained using existing treatment guidelines. Based on this review, we found little evidence that any of the reported gene expression signatures are ready for clinical application. We also found serious problems in the design and analysis of many of the studies. We suggest a set of guidelines to aid the design, analysis, and evaluation of prognostic signature studies. These guidelines emphasize the importance of focused study planning to address specific medically important questions and the use of unbiased analysis methods to evaluate whether the resulting signatures provide evidence of medical utility beyond standard of care-based prognostic factors.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1 retracted
A Genomic Strategy to Refine Prognosis in Early-Stage Non–Small-Cell Lung Cancer
Potti, A., Mukherjee, S., Petersen, R., Dressman, H. K., Bild, A., Koontz, J., Kratzke, R., Watson, M. A., Kelley, M., Ginsburg, G. S., et al. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa060467 · Cited by 576
RetractedJemal, A., Siegel, R., Ward, E., Hao, Y., Xu, J., Murray, T., & Thun, M. J. (2008) · CA: A Cancer Journal for Clinicians · doi:10.3322/ca.2007.0010 · Cited by 10,188
Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
Heagerty, P. J., Lumley, T., & Pepe, M. S. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00337.x · Cited by 2,854
Bhattacharjee, A., Richards, W. G., Staunton, J., Li, C., Monti, S., Vasa, P., Ladd, C., Beheshti, J., Bueno, R., Gillette, M., et al. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.191502998 · Cited by 2,576
Oncogenic pathway signatures in human cancers as a guide to targeted therapies
Bild, A. H., Yao, G., Chang, J. T., Wang, Q., Potti, A., Chasse, D., Joshi, M.-B., Harpole, D., Lancaster, J. M., Berchuck, A., et al. (2006) · Nature · doi:10.1038/nature04296 · Cited by 2,032
Gene-expression profiles predict survival of patients with lung adenocarcinoma
Beer, D. G., Kardia, S. L. R., Huang, C.-C., Giordano, T. J., Levin, A. M., Misek, D. E., Lin, L., Chen, G., Gharib, T. G., Thomas, D. G., et al. (2002) · Nature Medicine · doi:10.1038/nm733 · Cited by 2,025
Diversity of gene expression in adenocarcinoma of the lung
Garber, M. E., Troyanskaya, O. G., Schluens, K., Petersen, S., Thaesler, Z., Pacyna-Gengelbach, M., van de Rijn, M., Rosen, G. D., Perou, C. M., Whyte, R. I., et al. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.241500798 · Cited by 1,298
Pepe, M. S. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh101 · Cited by 1,276
Director's Challenge Consortium for the Molecular Classification of Lung Adenocarcinoma (2008) · Nature Medicine · doi:10.1038/nm.1790 · Cited by 1,190
Pitfalls in the Use of DNA Microarray Data for Diagnostic and Prognostic Classification
Simon, R., Radmacher, M. D., Dobbin, K., & McShane, L. M. (2003) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/95.1.14 · Cited by 1,006
Self-citation
Cited by
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
The prognostic landscape of genes and infiltrating immune cells across human cancers
Gentles, A. J., Newman, A. M., Liu, C. L., Bratman, S. V., Feng, W., Kim, D., Nair, V. S., Xu, Y., Khuong, A., Hoang, C. D., et al. (2015) · Nature Medicine · doi:10.1038/nm.3909 · Cited by 3,118
A catalogue of reporting guidelines for health research
Simera, I., Moher, D., Hoey, J., Schulz, K. F., & Altman, D. G. (2010) · European Journal of Clinical Investigation · doi:10.1111/j.1365-2362.2009.02234.x · Cited by 1,047
Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research
Riley, R. D., Hayden, J. A., Steyerberg, E. W., Moons, K. G. M., Abrams, K., Kyzas, P. A., Malats, N., Briggs, A., Schroter, S., Altman, D. G., et al. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001380 · Cited by 823
Aguirre-Gamboa, R., Gomez-Rueda, H., Martínez-Ledesma, E., Martínez-Torteya, A., Chacolla-Huaringa, R., Rodriguez-Barrientos, A., Tamez-Peña, J. G., & Treviño, V. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074250 · Cited by 686
Metadata
- Authors
- Subramanian, J., & Simon, R.
- Venue
- JNCI Journal of the National Cancer Institute
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-03-16
- Volume
- 102
- Issue
- 7
- Pages
- 464-474
- ISSN
- 0027-8874 (ISSN-L)
- 1460-2105
- OpenAlex
- W2107986563
- Cited by
- 351
- References
- 40
- FWCI
- 19.52
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use? https://app.cochat.ai/papers/10.1093/jnci/djq025
- The paper
- Subramanian, J., & Simon, R. (2010). Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use? JNCI Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djq025
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
