Ki-67 In Breast Cancer Patients Research Articles

Assessment of the Predictive Role of Ki-67 in Breast Cancer Patients' Responses to Neoadjuvant Chemotherapy.

Neoadjuvant chemotherapy (NAC) in breast cancer (BC) is being considered for a broader range of cases, including locally advanced tumors and situations where downstaging could reduce extensive surgery. Several trials have explored predictive markers of pathological complete response (pCR). The role of Ki-67 as a predictor of pCR has been demonstrated in studies. However, the cut-off remains vague, given the lack of standardization of measurement methods. The aim of our study was to evaluate the predictive value of Ki-67 in response to NAC and to identify the cut-off values that exhibit the strongest correlation with best response. This retrospective study included 187 patients who had undergone surgery following NAC for BC at the CHU Souss Massa of Agadir between January 2020 and January 2023. Logistic regression was used to assess the correlation between Ki-67 and patients' characteristics. Optimal Ki-67 cutoff was identified by receiver operating characteristic curve. Kaplan-Meier curves were used to assess disease-free survival (DFS), and survival comparisons were assessed with the log-rank test. The median age was 51.8±10.7 years and 51.4% of tumors were smaller than 5 cm. Node invasion was found in 55.4%. Luminal B subtype was found in 49.7%, followed by human epidermal growth factor receptor-2 (HER-2)-positive in 27.4%, triple-negative in 14.3% and Luminal A in 8.6%. pCR occurred in 40% of patients overall. Subgroup analysis revealed a significant association between pCR and tumor size (p<0.001), lymph node involvement (p<0.001), grade 2 (p<0.001), vascular invasion (p<0.001), and positive HER-2 status (p = 0.022). In statistical analysis, pathological responses were improved in patients with Ki-67 >35% (p<0.001). DFS was 98.8% at 12 months. No statistical difference was found in DFS according to Ki-67 values and pCR status. Our results indicate that Ki-67 is a predictive marker for response in the neoadjuvant setting in BC patients. Our study showed that a Ki-67 cut-off >35% predicts a better pCR rate in response to NAC. However, this cutoff value remains controversial due to the absence of a standard method of measurement, with inter- and intra-observer variability. It would be necessary to validate this cutoff in other studies.

Use of a Novel Deep Learning Open-Source Model for Quantification of Ki-67 in Breast Cancer Patients in Pakistan: A Comparative Study between the Manual and Automated Methods.

Introduction: Breast cancer is the most common cancer in women; its early detection plays a crucial role in improving patient outcomes. Ki-67 is a biomarker commonly used for evaluating the proliferation of cancer cells in breast cancer patients. The quantification of Ki-67 has traditionally been performed by pathologists through a manual examination of tissue samples, which can be time-consuming and subject to inter- and intra-observer variability. In this study, we used a novel deep learning model to quantify Ki-67 in breast cancer in digital images prepared by a microscope-attached camera. Objective: To compare the automated detection of Ki-67 with the manual eyeball/hotspot method. Place and duration of study: This descriptive, cross-sectional study was conducted at the Jinnah Sindh Medical University. Glass slides of diagnosed cases of breast cancer were obtained from the Aga Khan University Hospital after receiving ethical approval. The duration of the study was one month. Methodology: We prepared 140 digital images stained with the Ki-67 antibody using a microscope-attached camera at 10×. An expert pathologist (P1) evaluated the Ki-67 index of the hotspot fields using the eyeball method. The images were uploaded to the DeepLiif software to detect the exact percentage of Ki-67 positive cells. SPSS version 24 was used for data analysis. Diagnostic accuracy was also calculated by other pathologists (P2, P3) and by AI using a Ki-67 cut-off score of 20 and taking P1 as the gold standard. Results: The manual and automated scoring methods showed a strong positive correlation as the kappa coefficient was significant. The p value was <0.001. The highest diagnostic accuracy, i.e., 95%, taking P1 as gold standard, was found for AI, compared to pathologists P2 and P3. Conclusions: Use of quantification-based deep learning models can make the work of pathologists easier and more reproducible. Our study is one of the earliest studies in this field. More studies with larger sample sizes are needed in future to develop a cohort.

Improved Prediction of Survival Outcomes Using Residual Cancer Burden in Combination With Ki-67 in Breast Cancer Patients Underwent Neoadjuvant Chemotherapy.

We developed a model for improving the prediction of survival outcome using postoperative Ki-67 value in combination with residual cancer burden (RCB) in patients with breast cancer (BC) who underwent neoadjuvant chemotherapy (NAC). We analyzed the data from BC patients who underwent NAC between 2010 and 2019 at Samsung Medical Center and developed our residual proliferative cancer burden (RPCB) model using semi-quantitative Ki-67 value and RCB class. The Cox proportional hazard model was used to develop our RPCB model according to disease free survival (DFS) and overall survival (OS). In total, 1,959 patients were included in this analysis. Of 1,959 patients, 905 patients were excluded due to RCB class 0, and 32 were due to a lack of Ki-67 data. Finally, an RPCB model was developed using data from 1,022 patients. The RPCB score was calculated for DFS and OS outcomes, respectively (RPCB-DFS and RPCB-OS). For further survival analysis, we divided the population into 3 classes according to the RPCB score. In the prediction of DFS, C-indices were 0.751 vs 0.670 and time-dependent areas under the receiver operating characteristic curves (AUCs) at 3-year were 0.740 vs 0.669 for RPCB-DFS and RCB models, respectively. In the prediction of OS, C-indices were 0.819 vs 0.720 and time-dependent AUCs at 3-year were 0.875 vs 0.747 for RPCB-OS and RCB models, respectively. The RPCB model developed using RCB class and semi-quantitative Ki-67 had superior predictive value for DFS and OS compared with that of RCB class. This prediction model could provide the basis to decide risk-stratified treatment plan for BC patients who had residual disease after NAC.

Correlation between Histological Grade and Ki67 in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

Correlation between Histological Grade and Ki67 in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

Expressions of IGF-1R and Ki-67 in breast cancer patients with diabetes mellitus and an analysis of biological characteristics.

ABSTRACTObjectives:There is a cross-link of insulin and insulin-like growth factor-1 (IGF-1) with each other’s receptors. The present study was carried out to explore the relationship of Type-2 diabetes mellitus (T2DM) with the occurrence and development of breast cancer by analyzing the expression of IGF-1R and Ki-67, as well as the biological characteristics in breast cancer patients with and without diabetes mellitus.Methods:A total of 102 cases of breast cancer patients with T2DM admitted in Hebei General Hospital from January 2019 to December 2020 were selected and grouped in T2DM group. While the control group included 106 cases of breast cancer patients without diabetes mellitus in the same period. Further comparison was conducted focusing on the general data, clinical stage, tumor histological grade, molecular classification and prognosis, and the expressions of IGF-1R and Ki-67 in breast cancer tissue between groups.Results:Compared with control group, patients in T2DM group were elderly and accounted for a larger proportion of post-menopause (p<0.05), yet with no significant difference in body mass and family history (p>0.05). Compared with control group, T2DM group had advanced clinical stage, higher histological grade, and more common molecular type, with statistical differences between groups (p<0.05). Furthermore, there were higher proportions of local recurrence, lymph node metastasis and distant metastasis in T2DM group than those in control group, yet with no statistical significance (p>0.05). While statistical difference was found in the comparison of the 5-year survival rate, which was lower in T2DM group than that in control group (p<0.05). In addition, compared with control group, there were significant increase in both the expressions of IGF-1R and Ki-67 in T2DM group (p<0.05).Conclusions:T2DM may be one of the risk factors affecting the occurrence, development and prognosis of breast cancer, which may decrease the 5-year survival of breast cancer patients. Besides, high expressions of IGF-1R and Ki-67 may be the key factors for poor prognosis of breast cancer patients with diabetes mellitus.

Expression of ER, PR, HER-2 and Ki67 before and after neoadjuvant chemotherapy (NAC) and the relation between their expression and the curative effects of NAC in breast cancer patients

Objectives: To investigate the relationship between the expression of ER, PR, HER-2 and Ki-67 and the effective rates of neoadjuvant chemotherapy (NAC), and to study the influence of NAC on the expression of ER, PR, HER-2 and Ki-67 in breast cancer patients.

216P - Significance of receptors expression, mitotic index and Ki67 in breast cancer patients with Nottingham Prognostic Index (NPI) poor prognosis score

216P - Significance of receptors expression, mitotic index and Ki67 in breast cancer patients with Nottingham Prognostic Index (NPI) poor prognosis score

Prognostic Value of Ki-67 in Breast Cancer Patients with Positive Axillary Lymph Nodes: A Retrospective Cohort Study

IntroductionKi-67 expression is a biomarker for proliferation. Its prognostic value is recognized in breast cancer (BC) patients with negative axillary nodes, but is less clear in BC patients with positive axillary lymph nodes.MethodsWe retrospectively reviewed the medical records of 1131 Chinese BC patients treated from January 2002 to June 2007 and 450 patients met the inclusion criteria: positive nodes, adjuvant therapy, and complete biomarker profile (estrogen receptor (ER), progesterone receptor (PR), HER2, p53, Ki-67). Univariate and multivariate regression analysis were used to correlate biomarkers and tumor characteristics with metastasis free survival (MFS) and overall survival (OS).ResultsMedian follow-up time was 46 months (range 5–76 months). The Ki-67 expression was associated significantly with histological grade, ER, PR, HER2, and P53 status (P<0.05). Tumor stage, nodal stage, and ER status were independent prognostic factors for MFS. Ki-67 status was associated significantly with OS but not MFS. To determine whether the extent of LN involvement in the BC patients influenced the role of Ki-67 in survival rates, we compared these variables in patients with 1–3 positive lymph nodes (N1) to those of patients with ≥4 positive lymph nodes. Ki-67 status was an independent prognostic factor for MFS (Hazard Ratio, 3.27, P = 0.026) and overall survival (HR, 10.64, P = 0.007) in patients with 1–3 positive nodes (N1).ConclusionsThe possibility that Ki-67 expression together with clinical factors can improve prediction of the prognosis of BC patients with 1∼3 positive axillary lymph nodes warrants further studies.

Ki67 in breast cancer: a useful prognostic marker?

<h2>ABSTRACT</h2> The prognostic role of Ki67 in breast cancer patients remains unclear when we considered a normal population. Composition of population in clinical practice is sometimes different in comparison with population in the trial.

Standardized Assessment of Ki-67 in Breast Cancer Patients Using Virtual Slides and an Automated Analyzer in Comparison to Central/Local Pathological Assessments

Purpose: To standardize the methods to measure Ki-67, there is an interest in automating the assessment of Ki-67. Therefore, we reviewed the possibility of introducing an automated analyzer to standardize the Ki-67 evaluation method. Methods: We retrospectively reviewed a clinical database of patients who underwent surgery for early breast cancer at Tokyo-West Tokushukai Hospital. Among them, those who underwent preoperative core needle biopsy (CNB) were enrolled. The concordance rates of estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki-67 by local pathologists were reviewed (valuations made by local pathologists), and nonmatching cases (from August 2008 to October 2011) were reassessed both by central review and using an automated analyzer with virtual slides. The results were compared with the evaluations made by local pathologists, and we reexamined the concordance rate by using central review and the automated analyzer. Results: The concordance rate of Ki-67 evaluations made by local pathologists in the preoperative CNB and surgical specimens was 78.7% in 287 cases pathologically assessed from October 2008 to March 2013. This rate was significantly lower (p in clear improvement in matching of 22 (92.1%) and 24 (93.1%) of 37 cases, respectively. Conclusion: The concordance rate of Ki-67 in preoperative CNB and surgical specimens was lower than that of other biological markers; however, they were nearly equal by reassessment using central review and an automated analyzer.

Hormonal Receptor, Human Epidermal Growth Factor Receptor-2, and Ki67 Discordance between Primary Breast Cancer and Paired Metastases: Clinical Impact

Objective: As hormone receptor and human epidermal growth factor receptor-2 (HER-2) expression in primary breast tumors frequently differs from that of paired metastases, we first evaluated the discordance rate (DR) of estrogen receptor (ER), progesterone receptor (PgR), HER-2, and Ki67 in breast cancer patients and then assessed the discordance effect on prognosis. Methods: Of 145 cases reviewed, 120 with samples available from both primary tumors and paired metastases were included in the study. For each receptor, the DR was calculated as the proportion of discordant cases with respect to the total number of patients. Results: A change in ER status was observed in 19 cases (DR 16.4%), while PgR status was modified in 48 cases (DR 41.7%). HER-2 was altered in 21 cases (DR 17.5%), and Ki67 in 33 patients (DR 38.8%). Patients with Ki67 <20% had a significantly higher postrecurrence survival (PRS) compared to patients with Ki67 ≥20% (p = 0.0006). Patients with ER-positive tumors showed a trend towards higher PRS (p = 0.064) compared to ER-negative patients. No differences in PRS were seen among patients with altered PgR or HER2 status. Conclusions: Changes in the cell biology of breast cancer metastasis would seem to occur and biopsy could potentially guide the choice of treatment and provide useful information on prognosis.

269 Ki67 in Breast Cancer Patients and Its Correlation with Clinico Pathological Factors

269 Ki67 in Breast Cancer Patients and Its Correlation with Clinico Pathological Factors