Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

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Standard

Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team. / Bjørn, Signe Frahm; Schnack, Tine Henrichsen; Lajer, Henrik; Christensen, Ib Jarle; Lundvall, Lene; Thomsen, Lotte Nedergaard; Høgdall, Claus.

I: International Journal of Gynecological Cancer, Bind 27, Nr. 2, 02.2017, s. 382-389.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Bjørn, SF, Schnack, TH, Lajer, H, Christensen, IJ, Lundvall, L, Thomsen, LN & Høgdall, C 2017, 'Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team', International Journal of Gynecological Cancer, bind 27, nr. 2, s. 382-389. https://doi.org/10.1097/IGC.0000000000000876

APA

Bjørn, S. F., Schnack, T. H., Lajer, H., Christensen, I. J., Lundvall, L., Thomsen, L. N., & Høgdall, C. (2017). Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team. International Journal of Gynecological Cancer, 27(2), 382-389. https://doi.org/10.1097/IGC.0000000000000876

Vancouver

Bjørn SF, Schnack TH, Lajer H, Christensen IJ, Lundvall L, Thomsen LN o.a. Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team. International Journal of Gynecological Cancer. 2017 feb.;27(2):382-389. https://doi.org/10.1097/IGC.0000000000000876

Author

Bjørn, Signe Frahm ; Schnack, Tine Henrichsen ; Lajer, Henrik ; Christensen, Ib Jarle ; Lundvall, Lene ; Thomsen, Lotte Nedergaard ; Høgdall, Claus. / Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team. I: International Journal of Gynecological Cancer. 2017 ; Bind 27, Nr. 2. s. 382-389.

Bibtex

@article{f9a858ee96284367b5c663832ba44655,
title = "Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team",
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.",
keywords = "COVA classification, MDT, Multidisciplinary team, Ovarian cancer treatment planning",
author = "Bj{\o}rn, {Signe Frahm} and Schnack, {Tine Henrichsen} and Henrik Lajer and Christensen, {Ib Jarle} and Lene Lundvall and Thomsen, {Lotte Nedergaard} and Claus H{\o}gdall",
year = "2017",
month = feb,
doi = "10.1097/IGC.0000000000000876",
language = "English",
volume = "27",
pages = "382--389",
journal = "International Journal of Gynecological Cancer",
issn = "1048-891X",
publisher = "Lippincott Williams & Wilkins, Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

AU - Bjørn, Signe Frahm

AU - Schnack, Tine Henrichsen

AU - Lajer, Henrik

AU - Christensen, Ib Jarle

AU - Lundvall, Lene

AU - Thomsen, Lotte Nedergaard

AU - Høgdall, Claus

PY - 2017/2

Y1 - 2017/2

N2 - 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.

AB - 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.

KW - COVA classification

KW - MDT

KW - Multidisciplinary team

KW - Ovarian cancer treatment planning

U2 - 10.1097/IGC.0000000000000876

DO - 10.1097/IGC.0000000000000876

M3 - Journal article

C2 - 28114238

AN - SCOPUS:85011665791

VL - 27

SP - 382

EP - 389

JO - International Journal of Gynecological Cancer

JF - International Journal of Gynecological Cancer

SN - 1048-891X

IS - 2

ER -

ID: 187312042