ArticleJournal of dental, oral and craniofacial epidemiology
From Mouth-level to Tooth-level DMFS: Conceptualizing a Theoretical Framework.
Article in Journal of dental, oral and craniofacial epidemiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A standard set of outcome measures for the comprehensive assessment of oral health and occlusion in individuals with osteogenesis imperfecta.Orphanet journal of rare diseases · 2024Article
- Epidemiological profile of early childhood caries in a sub-urban population in Nigeria.BMC oral health · 2021Article
- Caries-associated oral microbiome in head and neck cancer radiation patients: a longitudinal study.Journal of oral microbiology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
objectiveThere is no dearth of correlated count data in any biological or clinical settings, and the ability to accurately analyze and interpret such data remains an exciting area of research. In oral health epidemiology, the Decayed, Missing, Filled (DMF) index has been continuously used for over 70 years as the key measure to quantify caries experience. The DMF index projects a subject's caries status using either the DMF(T), the total number of DMF teeth, or the DMF(S), counting the total DMF teeth surfaces, for that subject. However, surfaces within a particular tooth or a subject constitute clustered data, and the DMFS mostly overlook this clustering effect to attain an over-simplified summary index, ignoring the true tooth-level caries status. Besides, the DMFT/DMFS might exhibit excess of some specific counts (say, zeroes representing the set of relatively disease-free carious state), or can exhibit overdispersion, and accounting for the excess responses or overdispersion remains a key component is selecting the appropriate modeling strategy. METHODS &
resultsThis concept paper presents the rationale and the theoretical framework which a dental researcher might consider at the onset in order to choose a plausible statistical model for tooth-level DMFS. Various nuances related to model fitting, selection and parameter interpretation are also explained.
conclusionThe author recommends conceptualizing the correct stochastic framework should serve as the guiding force to the dental researcher's never-ending goal of assessing complex covariate-response relationships efficiently.
Indexed as
Identifiers
26618183PMC4662556What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.