The ANTENATAL Study: An ecoNomic evaluaTion of pEriodontal treatmeNt in pregnAnt women and identification of responders to Treatment using mAchine Learning" - PROJECT ABSTRACT We aim to evaluate the cost-effectiveness of treating maternal periodontitis and its impact on short and long- term oral health status. Approximately 60-70% of pregnant women in the US report bleeding gums, but only 44% of them visit a dentist during pregnancy. Periodontal inflammation left untreated can lead to further tissue destruction, tooth loss, and have a significant impact on overall maternal and child health. Cost is the major obstacle to dental care access, and poorer women are most likely to require oral care but least likely to receive it. Although the clinical and cost effectiveness of non-surgical periodontal treatment (e.g., scaling and root planning (SRP)) has been established in general adult populations in the US, no such analysis has been conducted among pregnant women. Therefore, a study is required to determine the financial feasibility of providing oral healthcare to all pregnant women, as planned by the Center for Medicare/Medicaid Services. We will use data from the Obstetrics and Periodontal Therapy (OPT) study, where non-surgical periodontitis treatment consisting of SRP or no treatment was randomly assigned to mothers with periodontitis. This study provides detailed clinical measures of oral health, such as data on inflammatory markers and biological pathogens, as well as rich baseline data on demographic characteristics, health behaviors, biomarkers, and medical history. We will evaluate the short-term impact of SRP by assessing the cost per mm of clinical attachment level gain and periodontal pocket depth reduced from SRP versus control. We will also estimate the cost savings from SRP at the end of the OPT study. The long-term impact of periodontal destruction, tooth loss, and tooth life expectancy will be estimated from published studies by converting clinical attachment level and periodontal pocket depth into an expected number of teeth lost over 4 years and tooth life expectancy. The cost of treatment and procedures will be estimated from the Survey of Dental Fees 2022 published by the American Dental Association. To identify responders versus non-responders, we will use machine learning to analyze baseline (pre-treatment) characteristics to predict those who are most likely to benefit from the SRP treatment among pregnant women. A targeted intervention is likely more cost-effective and financially sustainable, so we will then estimate the cost effectiveness of SRP among likely responders versus control. Conducting cost-effectiveness analyses of treating maternal periodontitis can inform policies and programs to facilitate access to oral health care and improve oral health outcomes among expectant mothers, especially those facing financial barriers such as Medicaid-enrolled pregnant women.
