| Title |
Poorly differentiated clusters (PDCs) as a novel histological predictor of nodal metastases in pT1 colorectal cancer
|
|---|---|
| Published in |
Virchows Archiv, April 2014
|
| DOI | 10.1007/s00428-014-1580-z |
| Pubmed ID | |
| Authors |
Valeria Barresi, Giovanni Branca, Antonio Ieni, Luca Reggiani Bonetti, Luigi Baron, Stefania Mondello, Giovanni Tuccari |
| Abstract |
The practical use of histological factors such as submucosal (SM) invasion depth, poor differentiation, presence of lymphovascular invasion (LVI) and tumour budding to establish the risk of nodal dissemination in pT1 colorectal cancer (CRC) is limited by their low standardization and high inter-observer variability. It was recently suggested that the presence in CRC histological sections of poorly differentiated clusters (PDCs), defined as ≥5 cancer cells with no gland formation, may predict the metastatic potential of CRC. In addition, PDC assessment was shown to be more reproducible than the evaluation of the other aforementioned histological predictors. Hence, in this study, we investigated and compared the predictive value of PDC and other histological parameters on the risk of nodal involvement in pT1 CRC. The presence of PDC, SM invasion depth ≥1,000 μm and LVI was significantly associated with N+ status in pT1 CRC (P < 0.0001). Among these parameters, SM invasion depth had the highest sensitivity to identify N+ pT1 CRC but with the lowest specificity. When the analysis was restricted to CRCs with SM invasion depth ≥1,000 μm, the presence of PDC was the only independent risk factor for nodal metastases and allowed the identification of 87.5 % of N+ cancers. In conclusion, in this study, we demonstrate that the presence of PDC is associated with the metastatic potential of pT1 CRC. The combination of this parameter with SM invasion depth may allow identifying most of the pT1 CRC with nodal metastases. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hungary | 1 | 2% |
| Unknown | 42 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 19% |
| Student > Ph. D. Student | 5 | 12% |
| Student > Doctoral Student | 5 | 12% |
| Student > Bachelor | 4 | 9% |
| Other | 4 | 9% |
| Other | 11 | 26% |
| Unknown | 6 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 30 | 70% |
| Biochemistry, Genetics and Molecular Biology | 4 | 9% |
| Arts and Humanities | 1 | 2% |
| Computer Science | 1 | 2% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 6 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 April 2014.
All research outputs
#18,371,293
of 22,754,104 outputs
Outputs from Virchows Archiv
#1,530
of 1,941 outputs
Outputs of similar age
#163,705
of 226,688 outputs
Outputs of similar age from Virchows Archiv
#17
of 22 outputs
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