A comprehensive approach to assigning periodontal prognosis

Martinez-Canut, Pedro; Llobell, Arturo

doi:10.1111/jcpe.12857

Cited by 7 publications

(10 citation statements)

References 21 publications

(59 reference statements)

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“…Overall, 9 studies showed high ROB related to outcomes, with some of them being suspected to multiple biases. Of the 34 identified studies, 3 did not use a prespecified or clear outcome definition (Prince et al 2016; Su et al 2017; Martinez-Canut and Llobell 2018).…”

Section: Resultsmentioning

confidence: 99%

“…Of the 16 studies that categorized continuous variables, 12 classified age into 5-y age groups ( n = 7) or larger categories ( n = 5). Three studies categorized pocket probing depth and/or level of bone loss (Martinez-Canut et al 2018; Martinez-Canut and Llobell 2018; Schwendicke et al 2018), and 2 studies categorized laboratory test results, such as low-density lipoprotein (OuYang et al 2017; Peng et al 2018).…”

Section: Resultsmentioning

confidence: 99%

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Examining Bias and Reporting in Oral Health Prediction Modeling Studies

Haag

Song

et al. 2020

J Dent Res

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Recent efforts to improve the reliability and efficiency of scientific research have caught the attention of researchers conducting prediction modeling studies (PMSs). Use of prediction models in oral health has become more common over the past decades for predicting the risk of diseases and treatment outcomes. Risk of bias and insufficient reporting present challenges to the reproducibility and implementation of these models. A recent tool for bias assessment and a reporting guideline—PROBAST (Prediction Model Risk of Bias Assessment Tool) and TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis)—have been proposed to guide researchers in the development and reporting of PMSs, but their application has been limited. Following the standards proposed in these tools and a systematic review approach, a literature search was carried out in PubMed to identify oral health PMSs published in dental, epidemiologic, and biostatistical journals. Risk of bias and transparency of reporting were assessed with PROBAST and TRIPOD. Among 2,881 papers identified, 34 studies containing 58 models were included. The most investigated outcomes were periodontal diseases (42%) and oral cancers (30%). Seventy-five percent of the studies were susceptible to at least 4 of 20 sources of bias, including measurement error in predictors ( n = 12) and/or outcome ( n = 7), omitting samples with missing data ( n = 10), selecting variables based on univariate analyses ( n = 9), overfitting ( n = 13), and lack of model performance assessment ( n = 24). Based on TRIPOD, at least 5 of 31 items were inadequately reported in 95% of the studies. These items included sampling approaches ( n = 15), participant eligibility criteria ( n = 6), and model-building procedures ( n = 16). There was a general lack of transparent reporting and identification of bias across the studies. Application of the recommendations proposed in PROBAST and TRIPOD can benefit future research and improve the reproducibility and applicability of prediction models in oral health.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Examining Bias and Reporting in Oral Health Prediction Modeling Studies

Haag

Song

et al. 2020

J Dent Res

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“…Their tooth-prognosis system was associated with tooth loss in a retrospective analysis with at least 5 years of follow-up. Other authors proposed prediction models of tooth loss determined by patient and tooth factors (Avila et al 2009;Martinez-Canut & Llobell, 2018).…”

Section: Introductionmentioning

confidence: 99%

Comparison of the efficacy of periodontal prognostic systems in predicting tooth loss

Saydzai

Buontempo

Patel

et al. 2022

J Clinic Periodontology

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“…In regard to periodontal disease, several prognostic tools have been suggested in the literature [5,6]. A commonly used one is the McGuire and Nunn Classification [6].…”

Section: Introductionmentioning

confidence: 99%

Self-reported tooth and implant prognosis evaluation based on radiographic bone loss: a cross sectional study

Clark-Perry

Baybrook

Catunda

et al. 2020

Acta Stomatologica Marisiensis Journal

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Introduction: Tooth prognosis evaluation involves continual assessments to guide patient-centered treatment plans. This means that the tooth prognosis may dictate whether a tooth is restored, extracted, or maintained.Aim of study: The aim of this work was to evaluate current trends in tooth prognosis evaluation based on radiographic bone loss amongst dental practitioners.Material and Methods: A survey including demographic questions and ten radiographs (vertical bitewings or peri-apical) showing bone loss around teeth and implants were distributed to dental practitioners. Practitioners were asked to determine the prognosis of the tooth or implant and suggest a percentage describing the likelihood of the tooth or implant surviving for ten years.Results: One of the ten radiographs provided for assessment was given good to fair prognosis by 100% of the participants. Only three out of the ten radiographs presented had strong suggestions for tooth retention. Recommendation for extraction by dental practitioners varied from 1-66% across the radiographs. Furthermore, practitioners predicted a 0% chance of ten-year survival for many of the teeth.Conclusions: Assessing prognosis based on radiographs only, is insufficient and clinical data provides invaluable information to establishing tooth prognosis. Dental professionals should understand that compromised teeth can outlive dental implants and our role as dental professionals is to prevent and treat oral diseases to preserve the dentition as long as possible.

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A comprehensive approach to assigning periodontal prognosis

Cited by 7 publications

References 21 publications

Examining Bias and Reporting in Oral Health Prediction Modeling Studies

Examining Bias and Reporting in Oral Health Prediction Modeling Studies

Comparison of the efficacy of periodontal prognostic systems in predicting tooth loss

Self-reported tooth and implant prognosis evaluation based on radiographic bone loss: a cross sectional study

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