How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction.
Differences between computer-assisted image analysis (CAI) algorithms may cause discrepancies in the identification of immunohistochemically stained immune biomarkers in biopsies of breast cancer patients. These discrepancies have implications for their association with disease outcome. This study a...
| Publicado en: | Histochemistry & Cell Biology Vol. 156; no. 5; pp. 461 - 479 |
|---|---|
| Autores principales: | , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=153683803&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 153683803 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09486143 NQI jtl: Histochemistry & Cell Biology issn: 09486143 maglogo: N pubinfo: dt: Nov2021 vid: 156 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 153683803 151871966 10.1007/s00418-021-02022-8 153683803 ppf: 461 ppct: 18 formats: fmt: @attributes: type: P tig: atl: How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction. aug: au: Lejeune, Marylène Plancoulaine, Benoît Elie, Nicolas Bosch, Ramon Fontoura, Laia de Villasante, Izar Korzyńska, Anna Navarro, Andrea Gras Colón, Esther Sauras López, Carlos affil: Department of Pathology, Oncological Pathology and Bioinformatics Research Group, Hospital de Tortosa Verge de la Cinta, Carrer de les Esplanetes, 14, 43500, Tortosa, Spain sug: ab: Differences between computer-assisted image analysis (CAI) algorithms may cause discrepancies in the identification of immunohistochemically stained immune biomarkers in biopsies of breast cancer patients. These discrepancies have implications for their association with disease outcome. This study aims to compare three CAI procedures (A, B and C) to measure positive marker areas in post-neoadjuvant chemotherapy biopsies of patients with triple-negative breast cancer (TNBC) and to explore the differences in their performance in determining the potential association with relapse in these patients. A total of 3304 digital images of biopsy tissue obtained from 118 TNBC patients were stained for seven immune markers using immunohistochemistry (CD4, CD8, FOXP3, CD21, CD1a, CD83, HLA-DR) and were analyzed with procedures A, B and C. The three methods measure the positive pixel markers in the total tissue areas. The extent of agreement between paired CAI procedures, a principal component analysis (PCA) and Cox multivariate analysis was assessed. Comparisons of paired procedures showed close agreement for most of the immune markers at low concentration. The probability of differences between the paired procedures B/C and B/A was generally higher than those observed in C/A. The principal component analysis, largely based on data from CD8, CD1a and HLA-DR, identified two groups of patients with a significantly lower probability of relapse than the others. The multivariate regression models showed similarities in the factors associated with relapse for procedures A and C, as opposed to those obtained with procedure B. General agreement among the results of CAI procedures would not guarantee that the same predictive breast cancer markers were consistently identified. These results highlight the importance of developing additional strategies to improve the sensitivity of CAI procedures. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|