Molecular Classification of Unknown Primary Cancer
Seminars in Oncology, ISSN: 0093-7754, Vol: 36, Issue: 1, Page: 38-43
2009
- 54Citations
- 32Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations54
- Citation Indexes53
- 53
- CrossRef47
- Policy Citations1
- Policy Citation1
- Captures32
- Readers32
- 32
Article Description
The diagnosis of unknown primary carcinoma is often the result of the failure of light microscopy and immunohistochemistry to elucidate the origin of adenocarcinoma or poorly differentiated carcinoma. Recent advances in gene expression profiling using either reverse transcription polymerase chain reaction (RT-PCR) or microarray have enabled researchers to develop expression profiles unique to a wide variety of well-characterized primary cancers and to compare these unique signatures with those from unknown primary cancers. As the gene expression profile is frequently conserved when the tumor metastasizes, it is often possible to analyze a biopsy specimen and genomically identify its tissue of origin. In fact, the overall accuracy of genomic cancer classification in patients with known primary cancers is 80% to 90%. This new system of molecular classification might be considered as “genomic taxonomy.” The genomic classification is then available to the pathologist and clinician to aid in both the patient's diagnosis and treatment planning. The impact of this new technology on patient outcomes is currently under study.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0093775408002157; http://dx.doi.org/10.1053/j.seminoncol.2008.10.002; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=58549117539&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/19179186; https://linkinghub.elsevier.com/retrieve/pii/S0093775408002157; https://dx.doi.org/10.1053/j.seminoncol.2008.10.002
Elsevier BV
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