Emerging trends in neoadjuvant chemotherapy for ovarian cancer

Ami Patel, Puja Iyer, Shinya Matsuzaki, Koji Matsuo, Anil K. Sood, Nicole D. Fleming

Research output: Contribution to journalReview articlepeer-review

26 Scopus citations

Abstract

Epithelial ovarian cancer remains a leading cause of death amongst all gynecologic cancers despite advances in surgical and medical therapy. Historically, patients with ovarian cancer underwent primary tumor reductive surgery followed by postoperative chemotherapy; however, neoadjuvant chemotherapy followed by interval tumor reductive surgery has gradually become an alternative approach for patients with advanced-stage ovarian cancer for whom primary tumor reductive surgery is not feasible. Decision-making about the use of these approaches has not been uniform. Hence, it is essential to identify patients who can benefit most from neoadjuvant chemotherapy followed by interval tumor reductive surgery. Several prospective and retrospective studies have proposed potential models to guide upfront decision-making for patients with advanced ovarian cancer. In this review, we summarize important decision-making models that can improve patient selection for personalized treatment. Models based on clinical factors (clinical parameters, radiology studies and laparoscopy scoring) and molecular markers (circulating and tumor-based) are useful, but laparoscopic staging is among the most informative diagnostic methods for upfront decision-making in patients medically fit for surgery. Further research is needed to explore more reliable models to determine personalized treatment for advanced epithelial ovarian cancer.

Original languageEnglish (US)
Article number626
Pages (from-to)1-19
Number of pages19
JournalCancers
Volume13
Issue number4
DOIs
StatePublished - Feb 2 2021

Keywords

  • Epithelial ovarian cancer
  • Interval tumor reductive surgery
  • Laparoscopy scoring
  • Molecular markers
  • Neoadjuvant chemotherapy
  • Optimal cytoreduction
  • Personalized treatment
  • Radiology-based models
  • Targeted therapy
  • Tumor-based genetic markers

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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