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Updated: Jan 25, 2026

Author Spotlight: Advancing Personalized Medicine in Ovarian Cancer
Published on: February 23, 2024
Pathologic response to neoadjuvant chemotherapy in advanced ovarian cancer: utility of a scoring system to predict
Camilla Nero1, Anna Fagotti2, Gian Franco Zannoni3
1Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Ginecologia Oncologica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italia camillanero@gmail.com.
Background:
Growing evidence supports the role of neoadjuvant chemotherapy in patients with advanced epithelial ovarian cancer. Currently, there is no shared histopathologic scoring system to assess pathologic response in the specimens obtained at interval surgery after neoadjuvant chemotherapy This review aims to summarize the literature on pathologic response, focusing on proposed scoring systems.
Methods:
The systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, focusing on the definition of pathologic response, its prognostic value, possible predictors, and future implications. Eighteen manuscripts focusing on pathologic response in epithelial ovarian cancer were selected for analysis.
Results:
Overall, eight histopathologic scoring systems to evaluate pathologic response have been proposed. There are currently no available markers (serum, radiological, genomic) to select which patients could achieve the highest benefit from neoadjuvant chemotherapy experiencing a complete pathologic response. A three-tier scoring system (CRS) based on omental assessment and which classifies the response to neoadjuvant chemotherapy has been validated in external cohorts of epithelial ovarian cancer. This scoring system demonstrated adequate interobserver reproducibility. Data is limited on the pathologic complete response rate changes according to chemotherapy regimen.
Conclusions:
A histopathologic scoring system endowed with prognostic value could be helpful in personalizing the treatment decision in patients with epithelial ovarian cancer.
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