The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Sample Features Associated with Success Rates in Population-Based EGFR Mutation Testing
Open accessAbstract
Introduction Epidermal growth factor receptor (EGFR) mutation testing has become critical in the treatment of patients with advanced non-small-cell lung cancer. This study involves a large cohort and epidemiologically unselected series of EGFR mutation testing for patients with nonsquamous non-small-cell lung cancer in a North American population to determine sample-related factors that influence success in clinical EGFR testing.Methods Data from consecutive cases of Canadian province-wide testing at a centralized diagnostic laboratory for a 24-month period were reviewed. Samples were tested for exon-19 deletion and exon-21 L858R mutations using a validated polymerase chain reaction method with 1% to 5% detection sensitivity.Results From 2651 samples submitted, 2404 samples were tested with 2293 samples eligible for analysis (1780 histology and 513 cytology specimens). The overall test-failure rate was 5.4% with overall mutation rate of 20.6%. No significant differences in the failure rate, mutation rate, or mutation type were found between histology and cytology samples. Although tumor cellularity was significantly associated with test-success or mutation rates in histology and cytology specimens, respectively, mutations could be detected in all specimen types. Significant rates of EGFR mutation were detected in cases with thyroid transcription factor (TTF)-1-negative immunohistochemistry (6.7%) and mucinous component (9.0%).Conclusions EGFR mutation testing should be attempted in any specimen, whether histologic or cytologic. Samples should not be excluded from testing based on TTF-1 status or histologic features. Pathologists should report the amount of available tumor for testing. However, suboptimal samples with a negative EGFR mutation result should be considered for repeat testing with an alternate sample.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“molecular studies of biopsy and cytologic samples with adequate material have yielded similar failure rates.40,43,44”
In the citing paper
“large population-based testing experiences have reported that 70% to 85% of tested samples include core needle biopsy specimens, fine-needle aspiration samples, and fluid specimens.4,40”
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
Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
Multiple imputation using chained equations: Issues and guidance for practice
White, I. R., Royston, P., & Wood, A. M. (2011) · Statistics in Medicine · doi:10.1002/sim.4067 · Cited by 9,792
EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy
Paez, J. G., Jänne, P. A., Lee, J. C., Tracy, S., Greulich, H., Gabriel, S., Herman, P., Kaye, F. J., Lindeman, N., Boggon, T. J., et al. (2004) · Science · doi:10.1126/science.1099314 · Cited by 9,368
Travis, W. D., Brambilla, E. M., Noguchi, M., Nicholson, A. G., Geisinger, K. R., Yatabe, Y., Beer, D. G., Powell, C. A., Riely, G. J., Schil, P. E. V., et al. (2011) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e318206a221 · Cited by 4,834
Self-citationSchafer, J. L. (1999) · Statistical Methods in Medical Research · doi:10.1177/096228029900800102 · Cited by 3,949
New driver mutations in non-small-cell lung cancer
Pao, W. J., & Girard, N. (2011) · The Lancet Oncology · doi:10.1016/s1470-2045(10)70087-5 · Cited by 1,200
EGFR Mutations and Lung Cancer
Santos, G. D. C., Shepherd, F. A., & Tsao, M. (2011) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathol-011110-130206 · Cited by 964
Self-citationNew driver mutations in non-small-cell lung cancer
Tanoue, L. T. (2012) · Yearbook of Pulmonary Disease · doi:10.1016/j.ypdi.2012.01.036 · Cited by 833
_, _. (2008) · Journal of the National Comprehensive Cancer Network · doi:10.6004/jnccn.2008.0021 · Cited by 737
Ettinger, D. S., Akerley, W., Bepler, G., Blum, M. G., Chang, A. C., Cheney, R. T., Chirieac, L. R., D’Amico, T. A., Demmy, T. L., Ganti, A. K., et al. (2010) · Journal of the National Comprehensive Cancer Network · doi:10.6004/jnccn.2010.0056 · Cited by 729
Cited by
Sorted by citations
The 2021 WHO Classification of Lung Tumors: Impact of Advances Since 2015
Nicholson, A. G., Tsao, M., Beasley, M. B., Borczuk, A., Brambilla, E. M., Cooper, W. A., Đačić, S., Jain, D., Kerr, K. M., Lantuéjoul, S., et al. (2021) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2021.11.003 · Cited by 1,656
Self-citationIntegrated digital error suppression for improved detection of circulating tumor DNA
Newman, A. M., Lovejoy, A. F., Klass, D. M., Kurtz, D. M., Chabon, J. J., Scherer, F., Stehr, H., Liu, C. L., Bratman, S. V., Say, C., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3520 · Cited by 1,100
Stewart, E., Tan, S. Z., Liu, G., & Tsao, M. (2015) · Europe PMC (PubMed Central) · doi:10.3978/j.issn.2218-6751.2014.11.06 · Cited by 314
Self-citationRodak, O., Peris‐Díaz, M. D., Olbromski, M., Podhorska‐Okołów, M., & Dzięgiel, P. (2021) · Cancers · doi:10.3390/cancers13184705 · Cited by 250
Tan, D. S. W., Yom, S. S., Tsao, M. S., Pass, H. I., Kelly, K., Peled, N., Yung, R. C., Wistuba, I. I., Yatabe, Y., Unger, M., et al. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.05.008 · Cited by 201
Self-citation
Metadata
- Authors
- Shiau, C. J., Babwah, J. P., da Cunha Santos, G., Sykes, J. R., Boerner, S. L., Geddie, W. R., Leighl, N. B., Wei, C., Kamel-Reid, S., Hwang, D. M., & Tsao, M.-S.
- Affiliations
- University Health Network (CA)
- University of Toronto (CA)
- Corresponding author
- Tsao, Ming-Sound
- ORCID
- Venue
- Journal of Thoracic Oncology
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 9
- Issue
- 7
- Pages
- 947-956
- ISSN
- 1556-0864 (ISSN-L)
- OpenAlex
- W2003360283
- Cited by
- 78
- References
- 46
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 2 · 2023: 6 · 2022: 10 · 2021: 7 · 2020: 5 · 2019: 5 · 2018: 10 · 2017: 12 · 2016: 8 · 2015: 5 · 2014: 2
- FWCI
- 7.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Thoracic Oncology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- AstraZeneca Canada
- Ontario Ministry of Health and Long-Term Care
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Keywords
- EGFR mutation testing, non-small cell lung cancer, test failure rate, tumor cellularity, cytology specimens, exon 19 deletion, L858R mutation, retesting
- MeSH terms
- Thyroid Nuclear Factor 1, Base Sequence, Biopsy, Needle, Canada, Carcinoma, Non-Small-Cell Lung, Cytological Techniques, DNA Mutational Analysis, Exons, Female, Genetic Testing, Humans, Lung Neoplasms, Male, Nuclear Proteins, Pneumonectomy, Retrospective Studies, Transcription Factors, Sequence Deletion, ErbB Receptors
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
