2017
DOI: 10.1016/j.ygyno.2017.04.007
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Reporting ‘Denominator’ data is essential for benchmarking and quality standards in ovarian cancer

Abstract: Denominator data is critical to understanding selection and OS in AOC. Published outcomes of selected cohorts should routinely incorporate outcomes for all women managed within the reporting Centre. This is essential for benchmarking and quality assurance in gynaecological cancer and should be an integral part of any publication on outcomes from AOC.

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Cited by 18 publications
(25 citation statements)
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“…This may reflect the proportion of women having surgery after neoadjuvant chemotherapy, who are selected for such at the multi-disciplinary team meeting. Several studies [11,21,[29][30][31] have demonstrated significantly lower complication rates when neoadjuvant chemotherapy is used, and our approach is now supported by the joint statement of the Society of Gynecologic Oncologists and the American Society of Clinical Oncologists [32,33].…”
Section: A C C E P T E D Mmentioning
confidence: 83%
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“…This may reflect the proportion of women having surgery after neoadjuvant chemotherapy, who are selected for such at the multi-disciplinary team meeting. Several studies [11,21,[29][30][31] have demonstrated significantly lower complication rates when neoadjuvant chemotherapy is used, and our approach is now supported by the joint statement of the Society of Gynecologic Oncologists and the American Society of Clinical Oncologists [32,33].…”
Section: A C C E P T E D Mmentioning
confidence: 83%
“…Our cohort of 536 patients with AOC, of which 215 had diaphragm involvement and 85 underwent diaphragmatic surgery, is one of the largest published on patients managed in the UK and is the only paper with complete denominator descriptors [21]. Since advanced surgical procedures have been introduced at our Cancer Centre, the rate of diaphragmatic surgery has increased from 1.6% to 20.7%.…”
Section: Discussionmentioning
confidence: 99%
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“…Two patients were excluded from the analysis for inadequate morbidity data. Survival outcomes and other outcomes have been previously published . A total of 608 patients were therefore available for analysis.…”
Section: Resultsmentioning
confidence: 99%
“…It is essential that large core outcome data sets are developed with pooling of data to better describe individual patients’ risks of postoperative morbidity. Such data would give an additional way of benchmarking the performance of centres, in addition to general cohort descriptors and survival data …”
Section: Discussionmentioning
confidence: 99%