The impact of hysterectomy on survival outcomes of patients with locally advanced cervical cancer: a network meta-analysis
Creators: name: Pergialiotis, Vasilios
name: Haidopoulos, Dimitrios
name: Douligeris, Athanasios
name: Alexandros, Rodolakis
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Obstetrics and Gynecology
subject: Medicine and Health Sciences
subject: Medical Specialties

description: The study will be designed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Both randomized controlled trials (RCTs) and observational cohort studies (prospective or retrospective) are planned to be included. The process for retrieval of articles will be completed in tree distinct steps. Firstly, the titles and abstracts of all electronic records will be initially screened to evaluate their potential eligibility. Articles that meet or are presumed to meet the pre-specified criteria will be retrieved in full-text. Studies that investigate the outcomes of interest will be selected. Case reports, conference proceedings, posters, animal studies and review articles will be excluded. The study selection process will be conducted independently by two authors, while any discrepancies will be resolved by their consensus or with discussion with all authors. Literature search and data collection Literature search will be primarily performed using the Medline, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science and Clinicaltrials.gov databases. Google Scholar database was also searched aiming to recognize articles that were not found by primary databases. In addition, the reference lists of the included studies and of previous systematic reviews in the field will be screened for possible additional articles. The date of the last search will be set at February 10, 2021. The search algorithm will be based on the key-terms: "Cervical cancer; locally advanced; chemotherapy; radiotherapy; hysterectomy; completion hysterectomy; survival; recurrence”. Language and date restrictions were not applied during the literature search. Eligibility criteria Studies will be considered as eligible if they compare the survival outcomes of patients with locally advanced cervical cancer (Stages IB3- IIIC1 according to the FIGO 2018 staging system) treated with hysterectomy (either as primary treatment or completion procedure) to those of patients treated only with any combination of chemo- radiotherapy. Treatment arms are expected to vary among studies included in the international literature according to an earlier systematic review in the field 8; hence, all potential treatments alternatives will be evaluated, provided that the study included outcomes of patients treated with hysterectomy at least in one arm. Exclusion criteria will include patients treated for early stage cervical cancer (Stages IA1 – IB2) and studies that do not investigate the impact of hysterectomy on survival outcomes. Data extraction Taking in mind the latest evidence in the field provided by Shim et al 8 we chose to include the risk of recurrence and of death as primary outcomes, whereas progression free survival and overall survival outcomes at various time-intervals will be included as secondary outcomes. Complication rates will be also selected and investigated Statistical analysis Statistical meta-analysis will be conducted in R-3.6.3 (“pcnetmeta” package). Confidence intervals (CI) will be set at 95%. A random-effects frequentist network meta-analytic model will be fitted to provide pooled estimates of odds ratio (OR) and 95% CI, taking into account both direct and indirect comparisons. Forest plots will be constructed to visualize the estimated effect sizes for all treatments compared to placebo. League tables will be created, depicting the relative effects for all comparisons among antihypertensive agents. Treatments will be ranked according to their P-scores, ranging from 0 to 1, with higher values indicating higher incidence of adverse outcomes and thus worse treatments. Heterogeneity will be quantified by calculating the inconsistency index (I2) between-study variance (τ2), while its impact on outcomes will be assessed by estimating the 95% prediction intervals (PI). Publication bias will be assessed by examining the possible presence of small-study effects through the visual inspection of comparison-adjusted funnel plots. The asymmetry of funnel plots will be evaluated using the Egger’s regression, Begg-Mazumdar’s rank correlation and Thompson-Sharp’s tests. The plausibility of the transitivity assumption will be tested by comparing the distributions of potential confounders across studies grouped by comparison. The potential effect modifiers that will be taken into consideration were: stage of the disease, histologic diagnosis (including tumor grade), patient age and tumor size. The consistency of network was statistically assessed with a global (design-by-treatment interaction) test and a local (Separating Indirect from Direct Evidence-SIDE splitting) test using the Confidence in Network Meta-Analysis (CINeMA) web-application 9, 10. Quality assessment The quality of included RCTs will be judged with the Cochrane Risk of Bias tool and was classified to be low, high or unclear by taking into account the following domains: random sequence generation, blinding, allocation concealment, incomplete outcome and selective reporting. Furthermore, the quality of cohort studies will be evaluated by the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool. In particular, studies were assessed to be at low, moderate, high or critical risk of bias by examining the domains of confounding, selection of participants, classification of interventions, deviation from intended intervention, missing data, measurement and reporting of the outcomes. The credibility of evidence will be appraised with the Confidence In Network Meta-Analysis (CINeMA) approach, which is based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework and evaluates the potential presence of within-study bias, across-studies bias, indirectness, imprecision, heterogeneity and incoherence. Specifically, within-study bias was assessed to be low, uncertain or high according to ROBINS-I or Cochrane risk of bias tool judgments, while the average quality of studies was chosen to summarize risk of bias for each network estimate. Across-studies bias will be judged by the visual inspection of funnel plots and the outcomes of asymmetry tests, while the domain of indirectness assessed the relevance of studies to the research question of the network meta-analysis. Imprecision will be judged by taking into account whether confidence intervals crossed into clinically important effects, defined as a 10% percent increase or decrease in the incidence of the outcome of interest. Heterogeneity will be measured by the 95% predictive intervals, while incoherence represented the statistical expression of intransitivity and was evaluated by the significance of SIDE-splitting test.