Background:There are limited data on surgical outcomes in gynaecological oncology. We report on predictors of complications in a multicentre prospective study.Methods:Data on surgical procedures and resulting complications were contemporaneously recorded on consented patients in 10 participating UK gynaecological cancer centres. Patients were sent follow-up letters to capture any further complications. Post-operative (Post-op) complications were graded (I–V) in increasing severity using the Clavien-Dindo system. Grade I complications were excluded from the analysis. Univariable and multivariable regression was used to identify predictors of complications using all surgery for intra-operative (Intra-op) and only those with both hospital and patient-reported data for Post-op complications.Results:Prospective data were available on 2948 major operations undertaken between April 2010 and February 2012. Median age was 62 years, with 35% obese and 20.4% ASA grade ⩾3. Consultant gynaecological oncologists performed 74.3% of operations. Intra-op complications were reported in 139 of 2948 and Grade II–V Post-op complications in 379 of 1462 surgeries. The predictors of risk were different for Intra-op and Post-op complications. For Intra-op complications, previous abdominal surgery, metabolic/endocrine disorders (excluding diabetes), surgical complexity and final diagnosis were significant in univariable and multivariable regression (P<0.05), with diabetes only in multivariable regression (P=0.006). For Post-op complications, age, comorbidity status, diabetes, surgical approach, duration of surgery, and final diagnosis were significant in both univariable and multivariable regression (P<0.05).Conclusions:This multicentre prospective audit benchmarks the considerable morbidity associated with gynaecological oncology surgery. There are significant patient and surgical factors that influence this risk.
Background:Most studies use hospital data to calculate postoperative complication rates (PCRs). We report on improving PCR estimates through use of patient-reporting.Methods:A prospective cohort study of major surgery performed at 10 UK gynaecological cancer centres was undertaken. Hospitals entered the data contemporaneously into an online database. Patients were sent follow-up letters to capture postoperative complications. Grade II–V (Clavien–Dindo classification) patient-reported postoperative complications were verified from hospital records. Postoperative complication rate was defined as the proportion of surgeries with a Grade II–V postoperative complication.Results:Patient replies were received for 1462 (68%) of 2152 surgeries undertaken between April 2010 and February 2012. Overall, 452 Grade II–V (402 II, 50 III–V) complications were reported in 379 of the 1462 surgeries. This included 172 surgeries with 200 hospital-reported complications and 231 with 280 patient-reported complications. All (100% concordance) 36 Grade III–V and 158 of 280 (56.4% concordance) Grade II patient-reported complications were verified on hospital case-note review. The PCR using hospital-reported data was 11.8% (172 out of 1462; 95% CI 11–14), patient-reported was 15.8% (231 out of 1462; 95% CI 14–17.8), hospital and verified patient-reported was 19.4% (283 out of 1462; 95% CI 17.4–21.4) and all data were 25.9% (379 out of 1462; 95% CI 24–28). After excluding Grade II complications, the hospital and patient verified Grade III–V PCR was 3.3% (48 out of 1462; 95% CI 2.5–4.3).Conclusion:This is the first prospective study of postoperative complications we are aware of in gynaecological oncology to include the patient-reported data. Patient-reporting is invaluable for obtaining complete information on postoperative complications. Primary care case-note review is likely to improve verification rates of patient-reported Grade II complications.
Clinical factors, including age, smoking, treatment history, and status of surgical margins, could help to determine the risk of dysplasia recurrence and facilitate patient follow-up based on risk stratification.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.