An International Ki67 Reproducibility Study

Polley, Mei Yin; Leung, Samuel; McShane, Lisa M.; Gao, Dongxia; Hugh, Judith; Mastropasqua, Mauro G.; Viale, Giuseppe; Zabaglo, Lila; Penault‐Llorca, Frédérique; Bartlett, John M.S.; Gown, Allen M.; Symmans, W. Fraser; Piper, Tammy; Mehl, Erika; Enos, Rebecca A.; Hayes, Daniel F.; Dowsett, Mitch; Nielsen, Torsten O.

doi:10.1093/jnci/djt306

Cited by 527 publications

(426 citation statements)

References 28 publications

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“…In the case of MM1, no single cutoff can be used to identify statistically significant differences (ie, the curve never dips below the 0.05 line), and indeed the curve fluctuates quite widely-implying limited prognostic value. However, the analysis using the Confirm antibody shows a pronounced dip precisely in the range expected based upon proposed Ki67 cutoffs of clinical relevance, 24 so that a significant difference in overall survival would be seen by applying any cutoff between 7 and 26 (a range encompassing 98 patients and 13 observed events).…”

Section: Survival Analysismentioning

confidence: 85%

“…24,25 Consequently, we incorporated survival analysis after stratifying patients using the cutoff methods described above to ascertain the extent to which DIA and manual scores are each able to independently identify a statistically significant stratification of patients for each biomarker. The results looking at 5-year overall survival are shown in Table 2, along with Kaplan-Meier curves using manual cutoffs in Figure 2 (comparable Kaplan-Meier curves based upon the pathologist's scoring are given in Supplementary Figure 5).…”

Section: Survival Analysismentioning

confidence: 99%

“…Numerous studies have shown poor inter-laboratory, inter-observer and intra-observer reproducibility in the assessment of IHC expression patterns of tissue. 5,6 This variability is slowing the progress of biomarker discovery and delivery of precision medicine.…”

mentioning

confidence: 99%

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Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer

Bankhead

Fernández

McArt

et al. 2018

Laboratory Investigation

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Digital image analysis (DIA) is becoming central to the quantitative evaluation of tissue biomarkers for discovery, diagnosis and therapeutic selection for the delivery of precision medicine. In this study, automated DIA using a new purpose-built software platform (QuPath) is applied to a cohort of 293 breast cancer patients to score five biomarkers in tissue microarrays (TMAs): ER, PR, HER2, Ki67 and p53. This software is able to measure IHC expression following fully automated tumor recognition in the same immunohistochemical (IHC)-stained tissue section, as part of a rapid workflow to ensure objectivity and accelerate biomarker analysis. The digital scores produced by QuPath were compared with manual scores by a pathologist and shown to have a good level of concordance in all cases (Cohen's κ40.6), and almost perfect agreement for the clinically relevant biomarkers ER, PR and HER2 (κ40.86). To assess prognostic value, cutoff thresholds could be applied to both manual and automated scores using the QuPath software, and survival analysis performed for 5-year overall survival. DIA was shown to be capable of replicating the statistically significant stratification of patients achieved using manual scoring across all biomarkers (Po0.01, log-rank test). Furthermore, the image analysis scores were shown to consistently lead to statistical significance across a wide range of potential cutoff thresholds, indicating the robustness of the method, and identify sub-populations of cases exhibiting different expression patterns within the p53 and Ki67 data sets that warrant further investigation. These findings have demonstrated QuPath's suitability for fast, reproducible, high-throughput TMA analysis across a range of important biomarkers. This was achieved using our tumor recognition algorithms for IHC-stained sections, trained interactively without the need for any additional tumor recognition markers, for example, cytokeratin, to obtain greater insight into the relationship between biomarker expression and clinical outcome applicable to a range of cancer types.

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Section: Survival Analysismentioning

confidence: 85%

Section: Survival Analysismentioning

confidence: 99%

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Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer

Bankhead

Fernández

McArt

et al. 2018

Laboratory Investigation

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“…При этом мало сомнений, что измерение индекса Ki-67 обеспечивает надежную прогностиче-скую информацию [25] и высокий его уровень пред-сказывает пользу от дополнительной цитотоксической химиотерапии. Однако определение единственного (стандартного) полезного «разделительного среза» (cut-point) оказалось пока невозможным из-за остаю-щихся аналитических и преаналитических барьеров [26,27]. Область и лечение Состояние исследований / влияние на тактику лечения…”

Section: подтипы рака молочной железыunclassified

“…В то время как высокие и низкие значения Кi-67 воспроизводимы и клини-чески полезны, оказывается, нет оптимального разделительного значения (cut point), по крайней мере предсказывающего pCR только по уровню Кi-67 [76][77][78]. Международное сотрудничество привело к улучшению согласованности в оценке уровня Кi-67 [27,78]. Визуальный анализ может помочь умень-шить различия [79] Неоадъювантная систем-ная терапия Наблюдалось повышение частоты pCR у пациентов с трижды негативным РМЖ, получавших карбоплатин [80,81].…”

Section: внутренние подтипыunclassified

General St. Gallen-2015 guidelines for the treatment of early breast cancer (adapted by the experts of the Russian Society of Breast Oncologists)

Семиглазов¹,

Палтуев²,

Семиглазов³

et al. 2015

Tumors of female reproductive system

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Ki-67, 21-Gene Recurrence Score, Endocrine Resistance, and Survival in Patients With Breast Cancer

Lee,

Bae

et al. 2023

JAMA Netw Open

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ImportanceBoth high 21-gene recurrence score (RS) and high Ki-67 level are poor prognostic factors in patients with estrogen receptor (ER)–positive ERBB2-negative (ER+/ERBB−) breast cancer; however, a discrepancy between the 2 has been noted. Survival differences according to these 2 biomarkers are not well known.ObjectiveTo assess the associations between RS and Ki-67 expression and between Ki-67 expression and recurrence-free survival in patients with ER+/ERBB− breast cancer with low RS.Design, Setting, and ParticipantsThis cohort study included women treated for ER+/ERBB2− breast cancer who underwent the 21-gene RS test from March 2010 to December 2020 in 2 hospitals in Korea.ExposuresRecurrence score and Ki-67 level.Main Outcomes and MeasuresA Cox proportional hazards regression model was used to examine the association of Ki-67 with recurrence-free survival (RFS), while a binary logistic regression model was used to examine the association between Ki-67 and secondary endocrine resistance. High Ki-67 expression was defined as 20% or greater, and low genomic risk as an RS of 25 or less. Secondary endocrine resistance was defined as breast cancer recurrence that occurred after at least 2 years of endocrine therapy and during or within the first year after completing 5 years of adjuvant endocrine therapy.ResultsA total of 2295 female patients were included (mean [SD] age, 49.8 [9.3] years), of whom 1948 (84.9%) were in the low genomic risk group and 1425 (62.1%) had low Ki-67 level. The median follow-up period was 40 months (range, 0-140 months). The RS and Ki-67 level had a moderate correlation (R = 0.455; P &lt; .001). Of the patients with low Ki-67 level, 1341 (94.1%) had low RS, whereas 607 of 870 patients with high Ki-67 level (69.8%) had low RS. In patients with low RS, the RFS differed significantly according to Ki-67 level (low Ki-67, 98.5% vs high Ki-67, 96.5%; P = .002). Among the 1807 patients with low genomic risk who did not receive chemotherapy, high Ki-67 level was independently associated with recurrence (hazard ratio, 2.51; 95% CI, 1.27-4.96; P = .008). Recurrence after 3 years differed significantly according to Ki-67 level (low Ki-67, 98.7% vs high Ki-67, 95.7%; P = .003), whereas recurrence within 3 years did not differ (low Ki-67, 99.3% vs high Ki-67, 99.3%; P = .90). In addition, Ki-67 was associated with secondary endocrine resistance in patients with low RS who did not receive chemotherapy (odds ratio, 2.49; 95% CI, 1.13-5.50; P = .02).Conclusions and RelevanceIn this cohort study of patients with ER+/ERBB2− breast cancer, a moderate correlation was observed between Ki-67 and RS, and high Ki-67 level in patients with low genomic risk was associated with increased risk of secondary endocrine resistance.

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An International Ki67 Reproducibility Study

Abstract: Substantial variability in Ki67 scoring was observed among some of the world's most experienced laboratories. Ki67 values and cutoffs for clinical decision-making cannot be transferred between laboratories without standardizing scoring methodology because analytical validity is limited.

Cited by 527 publications

References 28 publications

Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer

Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer

General St. Gallen-2015 guidelines for the treatment of early breast cancer (adapted by the experts of the Russian Society of Breast Oncologists)

Ki-67, 21-Gene Recurrence Score, Endocrine Resistance, and Survival in Patients With Breast Cancer

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