Literature DB >> 23713048

Histopathologic changes following neoadjuvant chemotherapy in locally advanced breast cancer.

D Sethi1, R Sen, S Parshad, S Khetarpal, M Garg, J Sen.   

Abstract

AIMS: To compare the clinical and pathologic assessment of response to neoadjuvant chemotherapy and describe the various histopathologic changes observed.
MATERIALS AND METHODS: We studied a group of 40 patients with locally advanced breast cancer who had their initial workup in the form of clinico-imaging assessment of the size and pretreatment biopsy from the lesion. All the patients received two to six cycles of neoadjuvant chemotherapy, either cyclophosphamide 50 to 60 mg/m 2 IV, doxorubicin 40 to 50 mg/m 2 IV and 5-fluorouracil 500 to 800 mg/m 2 IV (CAF) or cyclophosphamide, epirubicin, and 5-fluorouracil (CEF). Clinical and pathologic assessment of response to chemotherapy was done based on the UICC guidelines. RESULT: Complete clinical response (cCR) was seen in 10% cases (4/40), thirty percent patients had (12/40) partial response and 60% (24/40) had stable disease after neoadjuvant chemotherapy. Pathologic complete response (pCR) with no evidence of viable tumor was observed in 20% patients (8/40). Fifteen patients (37.5%) showed partial response and 42.5% patients (17/40) had a stable disease. No patient progressed during the course of chemotherapy. Changes in the tumor type were observed following chemotherapy, most common being the mucinous change. Histologic changes like dyscohesion, shrinkage of tumor cells, elastosis, collagenization, necrosis, lymphocytic reaction, giant cell response are some of the common observations seen following treatment with neoadjuvant chemotherapy.
CONCLUSION: Pathologic assessment of response to neoadjuvant chemotherapy is a better predictor than the clinical response. The chemotherapy drugs can be modified based on the response observed after 1-2 cycles of neoadjuvant, the response being based on both tumor and patient's responsiveness.

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Year:  2013        PMID: 23713048     DOI: 10.4103/0019-509X.112301

Source DB:  PubMed          Journal:  Indian J Cancer        ISSN: 0019-509X            Impact factor:   1.224


  7 in total

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2.  Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies.

Authors:  Khadijeh Saednia; Andrew Lagree; Marie A Alera; Lauren Fleshner; Audrey Shiner; Ethan Law; Brianna Law; David W Dodington; Fang-I Lu; William T Tran; Ali Sadeghi-Naini
Journal:  Sci Rep       Date:  2022-06-11       Impact factor: 4.996

3.  Higher Pathological Complete Response Rate of Less than 10 Total Axillary Lymph Nodes After Axillary Lymph Node Dissection Following Neoadjuvant Chemotherapy in Breast Cancer.

Authors:  Jeeyeon Lee; Nora Jee-Young Park; Byeongju Kang; Jin Hyang Jung; Wan Wook Kim; Yee Soo Chae; Soo Jung Lee; Hye Jung Kim; Ji-Young Park; Ho Yong Park
Journal:  Front Surg       Date:  2022-03-31

4.  Tumor infiltrating lymphocytes in triple negative breast cancer receiving neoadjuvant chemotherapy.

Authors:  Carlos A Castaneda; Elizabeth Mittendorf; Sandro Casavilca; Yun Wu; Miluska Castillo; Patricia Arboleda; Teresa Nunez; Henry Guerra; Carlos Barrionuevo; Ketty Dolores-Cerna; Carolina Belmar-Lopez; Julio Abugattas; Gabriela Calderon; Miguel De La Cruz; Manuel Cotrina; Jorge Dunstan; Henry L Gomez; Tatiana Vidaurre
Journal:  World J Clin Oncol       Date:  2016-10-10

5.  Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities.

Authors:  Ali Sadeghi-Naini; Lakshmanan Sannachi; Hadi Tadayyon; William T Tran; Elzbieta Slodkowska; Maureen Trudeau; Sonal Gandhi; Kathleen Pritchard; Michael C Kolios; Gregory J Czarnota
Journal:  Sci Rep       Date:  2017-09-04       Impact factor: 4.379

6.  Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter.

Authors:  Hanna Piotrzkowska-Wróblewska; Katarzyna Dobruch-Sobczak; Ziemowit Klimonda; Piotr Karwat; Katarzyna Roszkowska-Purska; Magdalena Gumowska; Jerzy Litniewski
Journal:  PLoS One       Date:  2019-03-14       Impact factor: 3.240

7.  Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment.

Authors:  Hamidreza Taleghamar; Hadi Moghadas-Dastjerdi; Gregory J Czarnota; Ali Sadeghi-Naini
Journal:  Sci Rep       Date:  2021-07-21       Impact factor: 4.379

  7 in total

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