Ki67 as a Companion Diagnostic: Good or Bad News?

Subspecialized breast pathologists have suboptimal interobserver agreement in Ki-67 evaluation using 20% as the cutoff

PURPOSE

Ki-67 expression levels in breast cancer have prognostic and predictive significance. Therefore, accurate Ki-67 evaluation is important for optimal patient care. Although an algorithm developed by the International Ki-67 in Breast Cancer Working Group (IKWG) improves interobserver variability, it is tedious and time-consuming. In this study, we simplify IKWG algorithm and evaluate its interobserver agreement among breast pathologists in Ki-67 evaluation.

METHODS

Six subspecialized breast pathologists (4 juniors, 2 seniors) assessed the percentage of positive cells in 5% increments in 57 immunostained Ki-67 slides. The time spent on each slide was recorded. Two rounds of ring study (R1, R2) were performed before and after training with the modified IKWG algorithm (eyeballing method at 400× instead of counting 100 tumor nuclei per area). Concordance was assessed using Kendall's and Kappa coefficients.

RESULTS

Analysis of ordinal scale ratings for all categories with 5% increments showed almost perfect agreement in R1 (0.821) and substantial in R2 (0.793); Seniors and juniors had substantial agreement in R1 (0.718 vs. 0.649) and R2 (0.756 vs. 0.658). In dichotomous scale analysis using 20% as the cutoff, the overall agreement was moderate in R1 (0.437) and R2 (0.479), among seniors (R1: 0.436; R2: 0.437) and juniors (R1: 0.445; R2: 0.505). Average scoring time per case was higher in R2 (71 vs. 37 s).

CONCLUSION

The modified IKWG algorithm does not significantly improve interobserver agreement. A better algorithm or assistance from digital image analysis is needed to improve interobserver variability in Ki-67 evaluation.

Evaluation of the international Ki67 working group cut point recommendations for early breast cancer: comparison with 21-gene assay results in a large integrated health care system

PURPOSE

The International Ki67 Working Group (IKWG) has developed training for immunohistochemistry (IHC) scoring reproducibility and recommends cut points of ≤ 5% and ≥ 30% for prognosis in ER+, HER2-, stage I/II breast cancer. We examined scoring reproducibility following IKWG training and evaluated these cut points for selecting patients for further testing with the 21-gene Recurrence Score (RS) assay.

METHODS

We included 307 women aged 50+ years with node-negative, ER+PR+HER2- breast cancer and with available RS results. Slides from the diagnostic biopsy were stained for Ki67 and scored using digital image analysis (IA). Two IHC pathologists underwent IKWG training and visually scored slides, blinded to each other and IA readings. Interobserver reproducibility was examined using intraclass correlation (ICC) and Kappa statistics.

RESULTS

Depending on reader, 8.8-16.0% of our cohort had Ki67 ≤ 5% and 11.4-22.5% had scores ≥ 30%. The ICC for Ki67 scores by the two pathologists was 0.82 (95% CI 0.78-0.85); it was 0.79 (95% CI 0.74-0.83) for pathologist 1 and IA and 0.76 (95% CI 0.71-0.80) for pathologist 2 and IA. For Ki67 scores ≤ 5%, the percentages with RS < 26 were 92.6%, 91.8%, and 90.9% for pathologist 1, pathologist 2, and IA, respectively. For Ki67 scores ≥ 30%, the percentages with RS ≥ 26 were 41.5%, 51.4%, and 27.5%, respectively.

CONCLUSION

The IKWG's Ki67 training resulted in moderate to strong reproducibility across readers but cut points had only moderate overlap with RS cut points, especially for Ki67 ≥ 30% and RS ≥ 26; thus, their clinical utility for a 21-gene assay testing pathway remains unclear.

Ki-67 index after neoadjuvant endocrine therapy as a prognostic biomarker in patients with ER-positive/HER2-negative early breast cancer: a systematic review and meta-analysis

BACKGROUND

Neoadjuvant treatment discriminates responders, but pathologic complete response is uncommon in oestrogen receptor (ER)-positive/HER2-negative early breast cancer. We aimed to assess the prognostic value of Ki-67 index after neoadjuvant endocrine therapy (NET).

METHODS

We conducted a systematic literature search of PubMed, Embase, CENTRAL, and conference proceedings up to 22nd August 2023 to identify studies reporting the association of Ki-67 index after NET with recurrence-free survival (RFS) and/or overall survival (OS) in women with ER-positive/HER2-negative early breast cancer. We combined RFS and OS hazard ratios (HRs) with 95% confidence intervals (CIs).

RESULTS

Twelve studies including 7897 patients were analysed. Most studies were clinical trials (n = 7547) including only postmenopausal women (n = 3953) treated with aromatase inhibitor (n = 3359). Three studies evaluated Ki-67 in a preplanned core biopsy at 2-4 weeks of NET (n = 3348), while nine evaluated Ki-67 in the surgical specimen (n = 4549) after 2-24 weeks of NET. Median follow-up ranged between 37 and 95 months for RFS and 62-84 months for OS. High Ki-67 index after NET was significantly associated with worse RFS (HR 2.48, 95% CI 1.86-3.30) and OS (HR 2.66, 95% CI 1.65-4.28). A sensitivity analysis including three studies that measured Ki-67 in a preplanned core biopsy showed similar association with RFS (HR 2.41, 95% CI 1.77-3.30).

CONCLUSIONS

High Ki-67 after NET is associated with worse survival outcomes, even after a short course of NET, emphasising the prognostic value of this biomarker in women with ER-positive/HER2-negative early breast cancer.

Finding the (biomarker-defined) subgroup of patients who benefit from a novel therapy: No time for a game of hide and seek

An important element of precision medicine is the ability to identify, for a specific therapy, those patients for whom benefits of that therapy meaningfully exceed the risks. To achieve this goal, treatment effect usually is examined across subgroups defined by a variety of factors, including demographic, clinical, or pathologic characteristics or by molecular attributes of patients or their disease. Frequently such subgroups are defined by the measurement of biomarkers. Even though such examination is necessary when pursuing this goal, the evaluation of treatment effect across a variety of subgroups is statistically fraught due to both the danger of inflated false-positive error rate from multiple testing and the inherent insensitivity to how treatment effects differ across subgroups.Pre-specification of subgroup analyses with appropriate control of false-positive (i.e. type I) error is recommended when possible. However, when subgroups are specified by biomarkers, which could be measured by different assays and might lack established interpretation criteria, such as cut-offs, it might not be possible to fully specify those subgroups at the time a new therapy is ready for definitive evaluation in a Phase 3 trial. In these situations, further refinement and evaluation of treatment effect in biomarker-defined subgroups might have to take place within the trial. A common scenario is that evidence suggests that treatment effect is a monotone function of a biomarker value, but optimal cut-offs for therapy decisions are not known. In this setting, hierarchical testing strategies are widely used, where testing is first conducted in a particular biomarker-positive subgroup and then is conducted in the expanded pool of biomarker-positive and biomarker-negative patients, with control for multiple testing. A serious limitation of this approach is the logical inconsistency of excluding the biomarker-negatives when evaluating effects in the biomarker-positives, yet allowing the biomarker-positives to drive the assessment of whether a conclusion of benefit could be extrapolated to the biomarker-negative subgroup.Examples from oncology and cardiology are described to illustrate the challenges and pitfalls. Recommendations are provided for statistically valid and logically consistent subgroup testing in these scenarios as alternatives to reliance on hierarchical testing alone, and approaches for exploratory assessment of continuous biomarkers as treatment effect modifiers are discussed.

The Biomarker Ki-67: Promise, Potential, and Problems in Breast Cancer

Ki-67 is a nuclear protein serendipitously discovered by monoclonal antibody selection in the early 1980s. While it has been applied for decades in the context of breast cancer as a putative prognostic and, more recently, predictive, biomarker, even after all this time there is incomplete agreement as to the validity of the immunohistochemical assays employed for Ki-67 assessment, given possible effects of the disparate methodologies employed and possible confounding preanalytical, analytical, and interpretive variables. In this brief review, the history of Ki-67 and the problems, particularly with the analytical and interpretive variables, are highlighted through a selective review of the published literature. The contributions of the International Ki-67 Breast Cancer Working Group are highlighted, and in particular, the recommendations made by this group are reviewed. The potential of Ki-67 as a biomarker for breast cancer has not yet been fully realized, but an understanding of the power as well as the limitations of the methods of Ki-67 assessment are important if this biomarker can realize its potential.

Machine Learning Approach for the Determination of the Best Cut-off Points for Ki67 Proliferation Index in Adjuvant and Neo-adjuvant Therapy Breast Cancer Patients

BACKGROUND

This study aims to evaluate Ki67 cut-off points for differentiating low and high-risk patients based on survival and recurrence and find the best Ki67 cut-off points in breast cancer patients undergoing adjuvant and neoadjuvant therapy using machine learning methods.

PATIENTS AND METHODS

Patients with breast cancer treated at 2 referral hospitals between December 2000 and March 2021 who had invasive breast cancer entered this study. There were 257 patients in the neoadjuvant group and 2139 in the adjuvant group. A decision tree method was used to predict the likelihood of survival and recurrence. The 2-ensemble technique of RUSboost and bagged tree were imposed on the decision tree method to increase the accuracy of the determination. 80 percent of the data was used to train and validate the model, and 20% was used as a test.

RESULTS

In adjuvant therapy breast cancer patients with Invasive ductal carcinoma (IDC) and Invasive lobular carcinoma (ILC) the cutoff points for survival were 20 and 10, respectively. For luminal A, luminal B, Her2 neu, and triple-negative adjuvant therapy patients' the cutoff points for survival were 25, 15, 20, and 20, respectively. For neoadjuvant therapy luminal A and luminal B group, survival cutoff points were 25 and 20, respectively.

CONCLUSION

Despite variability in measurement and cut-off points, the Ki-67 proliferation index is still helpful in the clinic. Further investigation is needed to determine the best cut-off points for different patients. The sensitivity and specificity of Ki-67 cutoff point prediction models in this study could further prove its significance as a prognostic factor.

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.

Correlation of the Ki67 Working Group prognostic risk categories with the Oncotype DX Recurrence Score in early breast cancer

BACKGROUND

The relationship between Ki67 assessed by immunohistochemistry (IHC) and the Oncotype DX Recurrence Score (RS) is unclear. The objective of this study was to determine the correlation between the 21-gene RS and IHC-measured Ki67 with the prognostic classification groups recommended by the International Ki67 Working Group (IKWG).

METHODS

The authors performed a retrospective chart review of women who had hormone receptor (HR)-positive, human epidermal growth factor receptor 2-negative early breast cancer with zero to three positive lymph nodes and both Ki67 and the 21-gene RS performed at their institution from 2013 to 2021. Patients were categorized into low (≤5%), intermediate (6%-29%), and high Ki67 groups (≥30%) according to IKWG recommendations. Overall agreement and risk-stratified agreement between Ki67 and RS were assessed with the proportion of agreement and the κ statistic.

RESULTS

The study included 525 patients with HR-positive breast cancer. Among the 49% of patients with intermediate Ki67 values of 6%-29%, the distribution of low (0-10), intermediate (11-25), and high RS (26-100) was 19%, 66%, and 15%, respectively. There was slight agreement (κ = 0.01-0.20) between Ki67 and RS (κ = 0.027) in the overall population, although this was not significant (p = .1985). There was fair agreement (κ = 0.21-0.40) between high Ki67 and RS values (κ = 0.280; p < .0001). A higher progesterone receptor percentage was associated with lower RS values (p > .0001) but not lower Ki67 values. A positive nodal status and a larger tumor size were associated with higher Ki67 values (p = .0059 and p < .0001) but not with RS.

CONCLUSIONS

In this group of patients selected to have a 21-gene RS, there was no significant correlation between Ki67 and RS in the overall population, and there was fair agreement between high Ki67 and high RS values.

LAY SUMMARY

In patients with early-stage, hormone receptor-positive breast cancer, decisions on adjuvant chemotherapy are based on certain biological features of the cancer and genomic assays such as the Oncotype DX Recurrence Score (RS). The goal of this study was to determine the correlation between Ki67, a marker of proliferation, and the Oncotype DX RS, a 21-gene assay demonstrated to be predictive of an adjuvant chemotherapy benefit in patients with early-stage breast cancer. In 525 patients, the authors did not find a significant correlation between Ki67 and RS.

Update Breast Cancer 2022 Part 3 - Early-Stage Breast Cancer

This review summarizes recent developments in the prevention and treatment of patients with early-stage breast cancer. The individual disease risk for different molecular subtypes was investigated in a large epidemiological study. With regard to treatment, new data are available from long-term follow-up of the Aphinity study, as well as new data on neoadjuvant therapy with atezolizumab in HER2-positive patients. Biomarkers, such as residual cancer burden, were investigated in the context of pembrolizumab therapy. A Genomic Grade Index study in elderly patients is one of a group of studies investigating the use of modern multigene tests to identify patients with an excellent prognosis in whom chemotherapy may be avoided. These and other aspects of the latest developments in the diagnosis and treatment of breast cancer are described in this review.