ArticleNorth American journal of medical sciences2011
Ki-67 biomarker in breast cancer of Indian women.
Article in North American journal of medical sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Article
- Diagnostic and Prognostic Significance of Ki-67 Immunohistochemical Expression in Surface Epithelial Ovarian Carcinoma.Journal of clinical and diagnostic research : JCDR · 2017Article
- Molecular markers for breast cancer: prediction on tumor behavior.Disease markers · 2014Review
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Authors and funding
4 authors.
Funding
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Abstract
backgroundBiological markers that reliably predict clinical or pathological response to primary systemic therapy early during a course of chemotherapy may have considerable clinical potential.
aimsAims of study to evaluated changes in Ki-67 (MIB-1) labeling index and apoptotic index (AI) before, during, and after neoadjuvant anthracycline chemotherapy in breast cancer in Indian women. MATERIALS AND
methodsBreast cancer tissues were collected from Grant Medical College and Sir J.J. Group of Hospitals, Mumbai, India. Twenty-seven patients receiving neoadjuvant FEC (5-fluorouracil, epirubicin, and cyclophosphamide) chemotherapy for operable breast cancer underwent repeat core biopsy after 21 days of treatment.
resultsThe objective clinical response rate was 56%. Eight patients (31%) achieved a pathological response by histopathological criteria; two patients had a near-complete pathological response. Increased day-21 AI was a statistically significant predictor of pathological response (p = 0.049). A strong trend for predicting pathological response was seen with higher Ki-67 indices at day 21 and AI at surgery (p = 0.06 and 0.06, respectively).
conclusionThe clinical utility of early changes in biological marker expression during chemotherapy remains unclear. Until further prospectively validated evidence confirming the reliability of predictive biomarkers is available, clinical decision-making should not be based upon individual biological tumor biomarker profiles.
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