OBJECTIVES

In Germany, there are an estimated 4,500 new cervical cancer cases each year, and 1,500 deaths. Recently, screening programs have become widely established, employing either a cytology (Pap) or human papilloma virus (HPV) test, or combination (co-testing). In November 2018, the Gemeinsamer-Bundesausschuss (G-BA) in Germany released new guidelines (in force from January 2020), that women should attend co-testing screening every 3 years from age 35. As part of this development, an economic model was developed to predict the clinical and economic benefits of 3-yearly screening with mRNA-based HPV co-testing, versus DNA-based HPV co-testing, in Germany.

METHODS

A Markov cohort model with ancillary decision trees was built from a healthcare payer perspective, with a lifetime time horizon (from age 35) and 3% discount rate for costs/outcomes. The simulated treatment algorithm accounted for HPV, Pap grade and cervical intraepithelial neoplasia (CIN) distribution within the population, and screening compliance. Model inputs were informed by recent models published in the disease area, targeted literature reviews and clinical validation. Screening costs were micro-costed from estimated future laboratory costs. Diagnosis and treatment costs were from national tariffs and reimbursement codes.

RESULTS

Co-testing with mRNA-based HPV reduced the total number of colposcopies by 12% (50,320) compared to DNA-based HPV co-testing, due to the increased specificity. Of these, more than 99% (50,180) were negative colposcopies that could have been avoided. In addition, mRNA-based HPV co-testing was cost-saving per patient (mRNA 212.76€ versus DNA 223.58€). There was little difference (<2% change) between screening strategies for clinical outcomes, including detection of CIN 2/3 cases and invasive cervical cancer.

CONCLUSIONS

The model predicted mRNA-based HPV testing to be cost-saving compared to DNA-based HPV testing when used in a co-testing setting. Furthermore, it resulted in fewer colposcopies per patient, whilst maintaining similar clinical outcomes regarding detection of disease.