Prognostic performance of the 2017 World Workshop classification on staging and grading of periodontitis compared with the British Society of Periodontology's implementation

Dukka, Himabindu; Thränhardt, Dietrich; Saleh, Muhammad H A; Troiano, Giuseppe; Yonel, Zehra; Ravidà, Andrea; Wang, Hom‐Lay; Greenwell, Henry; Chapple, Iain

doi:10.1002/jper.21-0296

Cited by 7 publications

(3 citation statements)

References 37 publications

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“…This is not available if the model is intended for use at baseline—its addition means the model cannot be applied in clinical settings as developed. The importance of compliance as a prognostic factor is underlined in Dukka et al (2022)—the C-index of maintenance sessions alone (as a proxy for compliance) was 0.91, compared to 0.691 for the best-performing model in the study. A multivariate model controlling for compliance was then reported to have a C-index of 0.925—but this has been artificially inflated by the inclusion of compliance, which cannot be known at the time of prediction, and consequently, in practice, we would expect the model performance to be much closer to 0.691 than the almost perfect prediction (0.925) that was reported.…”

Section: Discussionmentioning

confidence: 91%

“…Among the studies focusing on model development, 21 did not report any correction for model overfitting or optimism, 5 used cross-validation (Schwendicke et al 2021; Dukka et al 2022; El Sayed et al 2022; Rahim-Wöstefeld et al 2022; Troiano et al 2022), 2 used bootstrapping (Ravidà et al 2020; Shi et al 2020), and 1 used temporal split sample validation (Santos et al 2021).…”

Section: Resultsmentioning

confidence: 99%

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Systematic Review of Prognosis Models in Predicting Tooth Loss in Periodontitis

Chow,

Tay,

Nascimento

2024

J Dent Res

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This study reviews and appraises the methodological and reporting quality of prediction models for tooth loss in periodontitis patients, including the use of regression and machine learning models. Studies involving prediction modeling for tooth loss in periodontitis patients were screened. A search was performed in MEDLINE via PubMed, Embase, and CENTRAL up to 12 February 2022, with citation chasing. Studies exploring model development or external validation studies for models assessing tooth loss in periodontitis patients for clinical use at any time point, with all prediction horizons in English, were considered. Studies were excluded if models were not developed for use in periodontitis patients, were not developed or validated on any data set, predicted outcomes other than tooth loss, or were prognostic factor studies. The CHARMS checklist was used for data extraction, TRIPOD to assess reporting quality, and PROBAST to assess the risk of bias. In total, 4,661 records were screened, and 45 studies were included. Only 26 studies reported any kind of performance measure. The median C-statistic reported was 0.671 (range, 0.57–0.97). All studies were at a high risk of bias due to inappropriate handling of missing data (96%), inappropriate evaluation of model performance (92%), and lack of accounting for model overfitting in evaluating model performance (68%). Many models predicting tooth loss in periodontitis are available, but studies evaluating these models are at a high risk of bias. Model performance measures are likely to be overly optimistic and might not be replicated in clinical use. While this review is unable to recommend any model for clinical practice, it has collated the existing models and their model performance at external validation and their associated sample sizes, which would be helpful to identify promising models for future external validation studies.

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Section: Discussionmentioning

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Systematic Review of Prognosis Models in Predicting Tooth Loss in Periodontitis

Chow,

Tay,

Nascimento

2024

J Dent Res

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“…To date, few studies have investigated the new classification system of periodontal disease and its predictive value for disease progression. Existing research has mainly focused on tooth loss, and the conclusion is that a higher stage and grade correlate well with a high risk of tooth loss due to periodontitis (Dukka et al, 2022; El Sayed et al, 2021; Ravidà et al, 2020, 2021). However, these studies included older patients with a mean age of 45–47 years at baseline compared with 28 years in our study.…”

Section: Discussionmentioning

confidence: 99%

Periodontitis in young individuals: Important factors for disease progression

Modin,

Rinon,

Faham

et al. 2023

J Clinic Periodontology

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AimTo investigate the progression of periodontitis in young individuals and identify factors that contribute to progression rate and whether periodontitis stage and grade have an impact on disease progression.Materials and MethodsThis retrospective cohort study was based on patients younger than 36 years at two periodontal clinics between 2003 and 2009. At least 10 years later, a clinical and radiographic examination was performed on 215 patients. The marginal bone loss between baseline and follow‐up for the tooth with the most severe bone loss at follow‐up was estimated by radiographic measurements. Linear regression analysis was used to investigate the influence of potential risk indicators on periodontitis progression.ResultsMost patients (83%) were classified as periodontitis stage III at baseline. At follow‐up, 70% of these patients remained in stage III. The frequency of patients with grade C decreased from 79% to 17% at follow‐up. The median (Q25%; Q75%) of the longitudinal marginal bone loss was 0.5 mm (0.0; 2.0). High bleeding on probing (BOP) index at baseline, smoking and interruption of periodontal treatment were found to significantly increase longitudinal bone loss.ConclusionsHigh levels of BOP at baseline, smoking and interruption of periodontal treatment increased the risk of marginal bone loss. The stage and grade at baseline had no significant impact on disease progression.

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