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Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team
  1. Signe Frahm Bjørn, MD, PhD,
  2. Tine Henrichsen Schnack, MD, PhD,
  3. Henrik Lajer, MD, PhD,
  4. Ib Jarle Christensen, DSc,
  5. Lene Lundvall, MD,
  6. Lotte Nedergaard Thomsen, MD, PhD and
  7. Claus Høgdall, MD, DMSc
  1. * Department of Gynecology, Rigshospitalet, Copenhagen University Hospital;
  2. Department of Pathology, Molecular Unit, Herlev University Hospital, University of Copenhagen; and
  3. Department of Pathology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  1. Address correspondence and reprint requests to Signe Frahm Bjørn, MD, PhD, Department of Gynecology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, DK-2100 Kbh Ø, Denmark. E-mail: Signe.Frahm.Bjoern.01{at}regionh.dk.

Abstract

Objective Proper planning of intervention and care of ovarian cancer surgery is of outmost importance and involves a wide range of personnel at the departments involved. The aim of this study is to evaluate the introduction of an ovarian surgery classification (COVA) system for facilitating multidisciplinary team (MDT) decisions.

Materials and Methods Four hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named “pre-COVA” 1 to 3 classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA performed.

Results The MDT meeting allocated 213 women (51%) to pre-COVA 1, 136 (33%) to pre-COVA 2, and 52 (12%) to pre-COVA 3. At the end of surgery, 168 (40%) were classified as COVA 1, 158 (38%) were classified as COVA 2, and 28 (7%) were classified as COVA 3. Traced individually, 212 (51%) patients were correctly preclassified at the MDT meeting and distributed into 110 (52%) COVA 1, 71 (52%) COVA 2, and 17 (32%) COVA 3. Analyzing the subgroup of patients with cancer, 164 (47%) were correctly preclassified. Regarding the International Federation of Gynecology and Obstetrics (FIGO) stages, the pre-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV.

Conclusions The COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre-COVA classification facilitates well-organized patient care–relevant procedures to be undertaken. Pre-COVA accurately predicts the final COVA in 51% classified women.

  • Ovarian cancer treatment planning
  • COVA classification
  • Multidisciplinary team
  • MDT

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Footnotes

  • The authors declare no conflicts of interest.

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