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Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Multiparametric assays for risk stratification are widely used in the management of both node negative and node positive hormone receptor positive invasive breast cancer. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. The TEAM pathology study consists of 3284 postmenopausal ER+ve breast cancers treated with endocrine therapy Using genes comprising the following multi-parametric tests OncotypeDx®, Prosigna™ and MammaPrint® signatures were trained to recapitulate true assay results. Patients were then classified into risk groups and survival assessed. Whilst likelihood χ2 ratios suggested limited value for combining tests, Kaplan-Meier and LogRank tests within risk groups suggested combinations of tests provided statistically significant stratification of potential clinical value. Paradoxically whilst Prosigna-trained results stratified Oncotype-trained subgroups across low and intermediate risk categories, only intermediate risk Prosigna-trained cases were further stratified by Oncotype-trained results. Both Oncotype-trained and Prosigna-trained results further stratified MammaPrint-trained low risk cases, and MammaPrint-trained results also stratified Oncotype-trained low and intermediate risk groups but not Prosigna-trained results. Comparisons between existing multiparametric tests are challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. Detailed analysis of the TEAM pathology study suggests a complex inter-relationship between test results in the same patient cohorts which requires careful evaluation regarding test utility. Further prognostic improvement appears both desirable and achievable.

Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX® (Genomic Health.), Prosigna™ (NanoString Technologies, Inc.), MammaPrint® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly computational "modelling" of test results using published algorithms and secondly a "training" approach which used reference results from the commercially supplied tests. We demonstrate the potential for errors to arise when using a "modelling" approach without reference to real world test results. Simultaneously we show that a "training" approach can provide a highly cost-effective solution to the development of real-world comparisons between different multigene signatures. Comparisons between existing multiparametric tests is challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. We present an approach, modelled in breast cancer, which can provide health care providers and researchers with the potential to perform robust and meaningful comparisons between multigene tests in a cost-effective manner. We demonstrate that whilst viable estimates of gene signatures can be derived from modelling approaches, in our study using a training approach allowed a close approximation to true signature results.

Context.--Hormone receptors HER2/neu and Ki-67 are markers of residual risk in early breast cancer. An algorithm (IHC4) combining these markers may provide additional information on residual risk of recurrence in patients treated with hormone therapy. Objective.--To independently validate the IHC4 algorithm in the multinational Tamoxifen Versus Exemestane Adjuvant Multicenter Trial (TEAM) cohort, originally developed on the trans-ATAC (Arimidex, Tamoxifen, Alone or in Combination Trial) cohort, by comparing 2 methodologies. Design.--The IHC4 biomarker expression was quantified on TEAM cohort samples (n = 2919) by using 2 independent methodologies (conventional 3,30-diaminobezidine [DAB] immunohistochemistry with image analysis and standardized quantitative immunofluorescence [QIF] by AQUA technology). The IHC4 scores were calculated by using the same previously established coefficients and then compared with recurrence-free and distant recurrence-free survival, using multivariate Cox proportional hazards modeling. Results.--The QIF model was highly significant for prediction of residual risk (P < .001), with continuous model scores showing a hazard ratio (HR) of 1.012 (95% confidence interval [95% CI]: 1.010-1.014), which was significantly higher than that for the DAB model (HR: 1.008, 95% CI: 1.006-1.009); P < .001). Each model added significant prognostic value in addition to recognized clinical prognostic factors, including nodal status, in multivariate analyses. Quantitative immunofluorescence, however, showed more accuracy with respect to overall residual risk assessment than the DAB model. Conclusions.--The use of the IHC4 algorithm was validated on the TEAM trial for predicting residual risk in patients with breast cancer. These data support the use of the IHC4 algorithm clinically, but quantitative and standardized approaches need to be used. (Arch Pathol Lab Med. 2016; 140:66-74; doi: 10.5858/arpa.2014-0599-OA), With progressively improving outcomes, particularly for patients with estrogen receptor (ER)-positive early breast cancers, personalized risk stratification to direct appropriate therapy is increasingly important. Multiple approaches to the assessment of [...]

Background: Breast-conserving surgery, adjuvant systemic therapy, and radiotherapy are the standard of care for most women with early breast cancer. There are few reports of clinical outcomes beyond the first decade of follow-up of randomised trials comparing breast-conserving surgery with or without radiotherapy. We present a 30-year update of the Scottish Breast Conservation Trial., Methods: In this randomised, controlled, phase 3 trial across 14 hospitals in Scotland, women aged younger than 70 years with early breast cancer (tumours ≤4 cm [T1 or T2 and N0 or N1]) were included. They underwent breast-conserving surgery (1 cm margin) with axillary node sampling or clearance. Oestrogen receptor (ER)-rich patients (≥20 fmol/mg protein) received 20 mg oral tamoxifen daily for 5 years. ER-poor patients (<20 fmol/mg protein) received chemotherapy (cyclophosphamide 600 mg/m 2 , methotrexate 50 mg/m 2 , and fluorouracil 600 mg/m 2 every 21 days intravenously in eight courses). Stratification was by menstrual status (within or more than 12 months from last menstrual period) and ER status (oestrogen concentration ≥20 fmol/mg protein, <20 fmol/mg protein, or unknown) and patients were randomly assigned (1:1) to high-dose (50 Gy in 20-25 fractions) local or locoregional radiotherapy versus no radiotherapy. No blinding was possible due to the nature of the treatment. We report the primary endpoint of the original trial, ipsilateral breast tumour recurrence, and the co-primary endpoint, overall survival. Clinical outcomes were compared by the log-rank test. Hazard ratios (HRs) are reported, with no radiotherapy as the reference group. Failures of the proportional hazards assumption are reported if significant. All analyses are by intention to treat., Findings: Between April 1, 1985, and Oct 2, 1991, 589 patients were enrolled and randomly assigned to the two treatment groups (293 to radiotherapy and 296 to no radiotherapy). After exclusion of four ineligible patients (two in each group), there were 291 patients in the radiotherapy group and 294 patients in the no radiotherapy group. Median follow-up was 17·5 years (IQR 8·4-27·9). Ipsilateral breast tumour recurrence was significantly lower in the radiotherapy group than in the no radiotherapy group (46 [16%] of 291 vs 107 [36%] of 294; HR 0·39 [95% CI 0·28-0·55], p<0·0001). Although there were differences in the hazard rate for ipsilateral breast tumour recurrence in the first decade after treatment (HR 0·24 [95% CI 0·15-0·38], p<0·0001), subsequent risks of ipsilateral breast tumour recurrence were similar in both groups (0·98 [0·54-1·79], p=0·95). There was no difference in overall survival between the two groups (median 18·7 years [95% CI 16·5-21·5] in the no radiotherapy group vs 19·2 years [16·9-21·3] in the radiotherapy group; HR 1·08 [95% CI 0·89-1 ·30], log-rank p=0·43)., Interpretation: Our findings suggest that patients whose biology predicts a late relapse a decade or more after breast-conserving surgery for early breast cancer might gain little from adjuvant radiotherapy., Funding: Breast Cancer Institute (part of Edinburgh and Lothian Health Foundation) and PFS Genomics (now part of Exact Sciences)., Competing Interests: Declaration of interests We declare no competing interests., (© 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Aims: The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections., Methods and Results: Adjacent sections from 30 primary ER + breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI ≥ 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively., Conclusions: The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further., (© 2019 John Wiley & Sons Ltd.)

Pathological analysis of the nuclear proliferation biomarker Ki67 has multiple potential roles in breast and other cancers. However, clinical utility of the immunohistochemical (IHC) assay for Ki67 immunohistochemistry has been hampered by unacceptable between-laboratory analytical variability. The International Ki67 Working Group has conducted a series of studies aiming to decrease this variability and improve the evaluation of Ki67. This study tries to assess whether acceptable performance can be achieved on prestained core-cut biopsies using a standardized scoring method. Sections from 30 primary ER+ breast cancer core biopsies were centrally stained for Ki67 and circulated among 22 laboratories in 11 countries. Each laboratory scored Ki67 using three methods: (1) global (4 fields of 100 cells each); (2) weighted global (same as global but weighted by estimated percentages of total area); and (3) hot-spot (single field of 500 cells). The intraclass correlation coefficient (ICC), a measure of interlaboratory agreement, for the unweighted global method (0.87; 95% credible interval (CI): 0.81-0.93) met the prespecified success criterion for scoring reproducibility, whereas that for the weighted global (0.87; 95% CI: 0.7999-0.93) and hot-spot methods (0.84; 95% CI: 0.77-0.92) marginally failed to do so. The unweighted global assessment of Ki67 IHC analysis on core biopsies met the prespecified criterion of success for scoring reproducibility. A few cases still showed large scoring discrepancies. Establishment of external quality assessment schemes is likely to improve the agreement between laboratories further. Additional evaluations are needed to assess staining variability and clinical validity in appropriate cohorts of samples., Competing Interests: J.M.S.B. has consulted for Insight Genetics and BioNTech and received compensation. T.O.N. has consulted for Nanostring and received compensation. C.K.O. has consulted for Astra Zeneca, Genentech and NanoString and received compensation. The remaining authors declare no conflict of interest.