# A pragmatic risk index evaluating the elderly with comorbidity for oral health event times

> **NIH NIH R21** · VIRGINIA COMMONWEALTH UNIVERSITY · 2022 · $210,461

## Abstract

With the rising cost of dental healthcare spending, future professional dental treatment plans will seek to utilize
efficient prognosis to weigh the long-term outlook of tooth retention against the costs involved. This is in context
when tooth loss (due to caries, or periodontal disease, or both) continues to remain a major oral health burden
in the US, while the Affordable Care Act, although covering the pediatric population, is not mandated for the
adults. Furthermore, elderly people with additional comorbidities, such as Type-2 diabetes (T2D) and disparities
in oral health access to care, are often at an elevated risk of compromised oral health. With recent significant
advances in data storage capabilities, huge oral health epidemiologic databases, such as those generated from
the AxiUm and Epic management systems, or national surveys containing a wealth of risk information, oral health
biomarkers, and associated time to event (TTE) information are at our disposal. However, their comprehensive
exploration has mostly gone untapped, mainly due to the unique statistical complexities they pose that are often
beyond the capabilities of existing statistical tools and software packages. These include, but not limited to (a)
an extremely multi-level setup, (b) very high level of censoring patterns, (c) bottlenecks accommodating time-
varying biomarkers, (d) informative sampling in national surveys, and (e) no consensus on the ‘effective’ and
‘clinically interpretable’ summary of the complex effects of predictors, and their confounders, on these TTE
endpoints. The goals of this project are to address these complexities, and perform a comprehensive statistical
analysis of available TTE endpoints from 3 rich databases comprising the U.S. Midwest and Southeast
population, and a nationally-representative NHANES database. Our proposal has three broad aims of practical
interest to oral epidemiologists and practitioners: (a) construct a pragmatic risk index for estimation and dynamic
prediction of the median residual lifetime of a tooth for the T2D/Non-T2D elderly, (b) refine that index to estimate
a tooth’s time to landmark events in NHANES, and (c) effective dissemination of these new tools to clinical
practitioners. Specifically, we propose to develop a well-documented, free, web-application, where a
user/clinician can plug-in values of a subject’s characteristics to calculate the corresponding index determining
tooth TTEs. This proposal is expected to generate new knowledge on evaluating national-level risk assessments
of tooth survival via this comprehensive and unique index. To the best of our knowledge, this idea of creating a
tooth TTE index is the first of its kind, and will provide a set of data analytic tools that are readily generalizable.
When ‘nationally-representative’ longitudinal databases are made available (from the ongoing NHANES studies),
the proposed methods can be readily adapted to inform interventions and treatment decisions.

## Key facts

- **NIH application ID:** 10593634
- **Project number:** 1R21DE031879-01A1
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** Dipankar Bandyopadhyay
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $210,461
- **Award type:** 1
- **Project period:** 2022-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10593634

## Citation

> US National Institutes of Health, RePORTER application 10593634, A pragmatic risk index evaluating the elderly with comorbidity for oral health event times (1R21DE031879-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10593634. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*