Tumour-infiltrating lymphocytes (TILs) reflect antitumour immunity. Their evaluation of histopathology specimens is influenced by several factors and is subject to issues of reproducibility. ONEST (Observers Needed to Evaluate Subjective Tests) helps in determining the number of observers that would be sufficient for the reliable estimation of inter-observer agreement of TIL categorisation. This has not been explored previously in relation to TILs. ONEST analyses, using an open-source software developed by the first author, were performed on TIL quantification in breast cancers taken from two previous studies. These were one reproducibility study involving 49 breast cancers, 23 in the first circulation and 14 pathologists in the second circulation, and one study involving 100 cases and 9 pathologists. In addition to the estimates of the number of observers required, other factors influencing the results of ONEST were examined. The analyses reveal that between six and nine observers (range 2-11) are most commonly needed to give a robust estimate of reproducibility. In addition, the number and experience of observers, the distribution of values around or away from the extremes, and outliers in the classification also influence the results. Due to the simplicity and the potentially relevant information it may give, we propose ONEST to be a part of new reproducibility analyses.

• Publication type
• Journal Article MeSH

Several models have previously been proposed to predict the probability of non-sentinel lymph node (NSLN) metastases after a positive sentinel lymph node (SLN) biopsy in breast cancer. The aim of this study was to assess the accuracy of two previously published nomograms (MSKCC, Stanford) and to develop an alternative model with the best predictive accuracy in a Czech population. In the basic population of 330 SLN-positive patients from the Czech Republic, the accuracy of the MSKCC and the Stanford nomograms was tested by the area under the receiver operating characteristics curve (AUC). A new model (MOU nomogram) was proposed according to the results of multivariate analysis of relevant clinicopathologic variables. The new model was validated in an independent test population from Hungary (383 patients). In the basic population, six of 27 patients with isolated tumor cells (ITC) in the SLN harbored additional NSLN metastases. The AUCs of the MSKCC and Stanford nomograms were 0.68 and 0.66, respectively; for the MOU nomogram it reached 0.76. In the test population, the AUC of the MOU nomogram was similar to that of the basic population (0.74). The presence of only ITC in SLN does not preclude further nodal involvement. Additional variables are beneficial when considering the probability of NSLN metastases. In the basic population, the previously published nomograms (MSKCC and Stanford) showed only limited accuracy. The developed MOU nomogram proved more suitable for the basic population, such as for another independent population from a mid-European country.

• MeSH
• Algorithms MeSH
• Sentinel Lymph Node Biopsy MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Lymphatic Metastasis diagnosis   pathology   MeSH
• Breast Neoplasms ethnology   pathology   MeSH
• Nomograms MeSH
• Predictive Value of Tests MeSH
• ROC Curve MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Comparative Study MeSH
• Geographicals
• Czech Republic MeSH