Efficacy/Effectiveness of Cervarix against grade 3 cervical intraepithelial neoplasia or worse (CIN3, CIN3+) and cervical cancer. A systematic review and meta-regression analysis (EPI-HPV-101 VE DB 221785)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Effectiveness study (incl. comparative)

Non-interventional study

• Non-interventional study design:
  Systematic review and meta-analysis

Study drug and medical condition

• Name of medicine:
  Cervarix
• Name of medicine, other:
  human papillomavirus vaccine [types 16, 18] (recombinant, adjuvanted, adsorbed)
• Anatomical Therapeutic Chemical (ATC) code:
  (J07BM02) papillomavirus (human types 16, 18)
• Additional medical condition(s):
  Human papillomavirus-related advanced cervical lesions and cervical cancer

Population studied

• Age groups:
  Adolescents (12 to < 18 years)

  Adults (18 to < 46 years)
• Estimated number of subjects:
  296000

Study design details

• Study design:
  Systematic review and meta-regression analysis
• Main study objective:
  To perform a meta-regression analysis to provide estimates of the effect size of GSK’s bivalent HPV vaccine on CIN3+ while adjusting for covariates such as age at vaccination, time since vaccination (time of follow-up), or type of analytical cohort (HPV baseline status), and study design.
• Outcomes:
  Efficacy, effectiveness, or combined efficacy/effectiveness of GSK´s bivalent vaccine on CIN3+ caused by HPV 16/18 or any HPV type.
• Data analysis plan:
  A systematic literature review has been conducted and a quantitative synthesis of the findings was pursued to determine a summary point estimate of the long-term efficacy/effectiveness of GSK’s bivalent HPV vaccine on the selected endpoints. Simple meta-analyses were first performed followed by univariate meta-regression analyses by the variables of interest, and multivariate meta-regression analyses within different scenarios.; Multiparametric meta-regressions adjusting for the following covariates: age at first vaccination, study design (randomized controlled trials vs observational), analytical cohort (Total vaccinated cohort vs Total vaccinated cohort naïve), and time since vaccination (time of follow-up). An Akaike information criterion (AIC) (estimator of prediction error) approach was used to assess the quality of the models for every given dataset allowing a data-driven selection of the best model.

Documents

Study report

Clinical_Study_Report_Anonymised.pdf