Objective The aim of this retrospective study was to evaluate the oral health-related quality of life (oHRQoL) and patient-reported outcome measures (PROMs) after 10 years of supportive periodontal care (SPC). Material and methods Patients were re-examined 120±12 months after active periodontal therapy. Dental and periodontal status and oHRQoL by completing Oral Health Impact Profile-G49 (OHIP-G49) and PROMs by marking a visual analogue scale (VAS) for self-perceived esthetics (VASe), chewing function (VASc), and hygiene ability (VASh) were assessed. Patient- and tooth-related factors (age, insurance status, number of SPC, compliance, change of therapist, smoking, tooth loss, need for surgery or antibiotic intake, bleeding on probing (BOP), periodontal inflamed surface area) influencing oHRQoL and PROMs were evaluated. Results One hundred eight periodontally compromised patients (59 female, mean age 65.4±10.7 years) lost 135 teeth during 10 years of SPC. At re-examination, 1.8% of all sites showed PPD ≥6mm. The mean OHIP-G49 sum score was 17.6±18.5, and VAS resulted in 76.0±22.5 (VASe), 86.3±16.3 (VASc), and 79.8±15.8 (VASh). Linear regression analyses identified a positive correlation with oHRQoL and/or PROMs for private insurance status (OHIP-G49, p =0.015, R 2 =0.204; VASc, p =0.005, R 2 =0.084; VASh, p =0.012, R 2 =0.222) and compliance to SPC (VASe, p =0.032; R 2 =0.204), as well as a negative correlation for active smoking (VASc, p =0.012, R 2 =0.084), increased BOP (VASh, p =0.029, R 2 =0.222) at the start of SPC, and number of lost molars (VASh, p =0.008, R 2 =0.222). Conclusion It is realistic to obtain satisfactory oHRQoL and PROM values in most of the patients after 10 years of SPC. The identified factors may help to predict patient satisfaction in the long-term course of therapy. Clinical relevance Systematic therapy of periodontally compromised patients provides values for oHRQoL and PROMs in a favorable range 10 years after therapy. This should encourage dentists to implement SPC in their daily routine. Clinical trial number NCT03048045

Background Predictive models and assessment tools for disease susceptibility and progression are necessary to enhance personalized medicine. The aim of this study is to assess the predictive accuracy of using the 2018 classification to predict likelihood of tooth loss. Methods A total of 134 patients were screened 10 years after periodontal therapy. Data were extracted from 82 patients' records and periodontal diagnoses were assigned according to the 1999 and 2018 classifications at baseline, whereas patient- and tooth-related parameters were documented at baseline and at reexamination. Statistical analysis included descriptive statistics, hurdle regression with a zero and count model as well as logistic regression. Results Significantly more teeth were lost during SPT in patients with Stage IV or Grade C (P < 0.05). Patients' adherence seems to have an impact on the predictability of the 2018 classification (P < 0.001). In comparison, neither classification system alone (1999 vs 2018) showed a high predictive value for tooth loss (area under the curve [AUC] = 59.2% vs 58.2%). Conclusion Class III and IV/Grade C of the 2018 classification of periodontal diseases show similar predictive accuracy for tooth loss as severe cases in the former classification. Patients adherence seems to influence the prognostic value of the classification.

Objectives: To predict patients' tooth loss during supportive periodontal therapy across four German university centers. Methods: Tooth loss in 897 patients in four centers (Kiel (KI) n = 391; Greifswald (GW) n = 282; Heidelberg (HD) n = 175; Frankfurt/Main (F) n = 49) during supportive periodontal therapy (SPT) was assessed. Our outcome was annualized tooth loss per patient. Multivariable linear regression models were built on data of 75 % of patients from one center and used for predictions on the remaining 25 % of this center and 100 % of data from the other three centers. The prediction error was assessed as root-mean-squared-error (RMSE), i.e., the deviation of predicted from actually lost teeth per patient and year. Results: Annualized tooth loss/patient differed significantly between centers (between median 0.00 (interquartile interval: 0.00, 0.17) in GW and 0.09 (0.00, 0.19) in F, p = 0.001). Age, smoking status and number of teeth before SPT were significantly associated with tooth loss (p < 0.03). Prediction within centers showed RMSE of 0.14 0.30, and cross-center RMSE was 0.15 0.31. Predictions were more accurate in F and KI than in HD and GW, while the center on which the model was trained had a less consistent impact. No model showed useful predictive values. Conclusion: While covariates were significantly associated with tooth loss in linear regression models, a clinically useful prediction was not possible with any of the models and generalizability was not given. Predictions were more accurate for certain centers. Clinical Relevance: Association should not be confused with predictive value: Despite significant associations of covariates with tooth loss, none of our models was useful for prediction. Usually, model accuracy was even lower when tested across centers, indicating low generalizability.

The aim of this study was to develop a prognostic tool to estimate long-term tooth retention in periodontitis patients at the beginning of active periodontal therapy (APT). Tooth-related factors (type, location, bone loss (BL), infrabony defects, furcation involvement (FI), abutment status), and patient-related factors (age, gender, smoking, diabetes, plaque control record) were investigated in patients who had completed APT 10 years before. Descriptive analysis was performed, and a generalized linear-mixed model-tree was used to identify predictors for the main outcome variable tooth loss. To evaluate goodness-of-fit, the area under the curve (AUC) was calculated using cross-validation. A bootstrap approach was used to robustly identify risk factors while avoiding overfitting. Only a small percentage of teeth was lost during 10 years of supportive periodontal therapy (SPT; 0.15/year/patient). The risk factors abutment function, diabetes, and the risk indicator BL, FI, and age (≤ 61 vs. > 61) were identified to predict tooth loss. The prediction model reached an AUC of 0.77. This quantitative prognostic model supports data-driven decision-making while establishing a treatment plan in periodontitis patients. In light of this, the presented prognostic tool may be of supporting value. In daily clinical practice, a quantitative prognostic tool may support dentists with data-based decision-making. However, it should be stressed that treatment planning is strongly associated with the patient’s wishes and adherence. The tool described here may support establishment of an individual treatment plan for periodontally compromised patients.

OBJECTIVE:Evaluation of survival of teeth with class III furcation involvement (FI) ≥5 years after active periodontal treatment (APT) and identification of prognostic factors.METHODS:All charts of patients who completed APT at the Department of Periodontology of Goethe-University Frankfurt, Germany, beginning October 2004 were screened for teeth with class III FI. APT had to be accomplished for ≥5 years. Charts were analysed for data of class III FI teeth at baseline (T0), at accomplishment of APT (T1), and at the last supportive periodontal care (T2). Baseline radiographic bone loss (RBL) and treatment were assessed.RESULTS:One-hundred and sixty patients (age: 54.4 ± 9.8 years; 82 females; 39 active smokers; 9 diabetics, 85 stage III, 75 stage IV, 59 grade B, 101 grade C) presented 265 teeth with class III FI. Ninety-eight teeth (37%) were lost during 110, 78/137 (median, lower/upper quartile) months. Logistic mixed-model regression and mixed Cox proportional hazard model associated adjunctive systemic antibiotics with fewer tooth loss (26% vs. 42%; p = .019/.004) and RBL (p = .014/.024) and mean probing pocket depth (PPD) at T1 (p < .001) with more tooth loss.CONCLUSIONS:Subgingival instrumentation with adjunctive systemic antibiotics favours retention of class III furcation-involved teeth. Baseline RBL and PPD at T1 deteriorate long-term prognosis.

AIM:To assess factors contributing to tooth loss 20 years after active periodontal therapy (APT) on tooth level. MATERIALS AND METHODS:After an initial retrospective analysis 10 years after APT, patients were monitored for 10 more years. At clinical re-evaluation 20 years after APT, tooth-related factors (tooth type, location, bone loss, furcation involvement, abutment status) and patient-related factors (gender, smoking, adherence) were investigated. Descriptive statistical analysis and a mixed logistic regression analysis were performed with tooth loss as primary outcome variable. RESULTS:The study included 69 patients (42 female/27 male). 39 patients were non-adherent (56.5%), and 11 were active smokers (15.9%). A total of 198 out of 1611 teeth were lost. Tooth loss was significantly highest (p < .01) in molars (21.1%), multi-rooted teeth with furcation involvement (23.5%) and abutment teeth (fixed: 27.6%, removable: 36.4%). 37.6% of teeth with initial bone loss >60% were lost during 20 years. Adherent patients showed less frequent tooth loss than non-adherent patients (OR 0.371; p < .01). CONCLUSION:Even teeth with an initial bone loss over 60% could be retained in approximately two thirds for 20 years. This should be kept in mind when assigning prognosis and establishing a treatment plan.

OBJECTIVES:In this retrospective study, we compared tooth loss between patients receiving periodontal therapy (PT) in four German university centres, stratified according to periodontal treatment phase.MATERIALS AND METHODS:Overall, 896 patients (Kiel (KI) n = 391; Greifswald (GW) n = 282; Heidelberg (HD) n = 174; Frankfurt a.M. (F) n = 49) were examined initially (T0), after active periodontal therapy (APT, T1) and after supportive periodontal therapy (SPT, T2). Descriptive analyses and multivariable negative binomial regression models were performed.RESULTS:Follow-up periods differed significantly between the centres, ranging between 6.7 ± 3.0 (GW) and 18.2 ± 5.5 (KI) years (p < 0.001). At T0, age, gender, smoking and diabetes showed notable regional distinctions (p < 0.001). However, the number of teeth per patient was similar (between 24.0 ± 4.6 (F) and 24.5 ± 4.1 (HD); p = 0.27). During PT, the number of extracted teeth differed significantly between centres, with greater differences during SPT (0.9 ± 1.8 (GW) to 2.3 ± 2.8 (KI), p < 0.001) compared to APT (0.4 ± 0.9 (F) to 1.0 ± 2.1 (KI), p = 0.02). Annual tooth loss during SPT remained low in all centres (between 0.10 ± 0.14 (F) to 0.15 ± 0.30 (HD), p < 0.001).CONCLUSION:Within the limitation of the study, PT leads to a low risk of tooth loss in all university centres irrespective of patients' baseline characteristics.CLINICAL RELEVANCE:Within the limitations of this retrospective investigation, long-term tooth retention seems to be feasible for most patients, as long as a systematic and structured treatment approach is applied.

AimThe aim of this meta-review was to evaluate whether there is a meaningful clinical benefit regarding the use of systemic adjunctive antibiotics in the treatment of patients with periodontitis. Additionally, a consensus regarding possible recommendations for future administration of antibiotics should be reached.MethodsA structured literature search was performed by two independent investigators focusing on systematic reviews (SR) covering adjunctive systemic antibiosis during non-surgical periodontal therapy. Additionally, recent randomized clinical trials (RCT, July 2015 to July 2017) were searched systematically to update the latest SR. Results were summarized and discussed in a plenary to reach a consensus.ResultsMostly, systematic reviews and RCTs showed a significant positive effect of adjunctive systematic antibiosis compared to controls. These positive effects gain clinical relevance in patients with severe periodontal disease aged 55years and younger.ConclusionSystemic antibiotics as an adjunct to non-surgical periodontal therapy should be sensibly administered and restrictively used. Only certain groups of periodontitis patients show a significant and clinically relevant benefit after intake of systemic antibiosis during periodontal therapy.Clinical relevanceAvoiding antibiotic resistance and possible side effects on the human microbiome should be a focus of dentists and physicians. Thus, a sensible administration of antibiotics is mandatory. This manuscript suggests guidelines for a reasonable use.

AIM:To assess tooth loss in patients with aggressive periodontitis (AgP) 10-35 years after active periodontal therapy (APT) in a private practice and to detect possible factors influencing tooth loss.MATERIAL AND METHODS:In 100 patients with AgP, tooth loss was recorded over a median follow-up period of 25.5 years after APT, retrospectively. Patient- and tooth-level factors were assessed with a Cox frailty regression model.RESULTS:Of 2,380 teeth, 227 were lost during a median follow-up time of 25.5 years (2.3 ± 3.6 teeth/patient, range 0-17 teeth), resulting in a mean tooth loss rate of 0.09 teeth/patient/year. At patient-level, statistically significant factors for tooth loss were smoking (p = .039) and the baseline diagnosis generalized AgP (p < .001). Influencing factors at tooth-level were location in the maxilla (p = .003), baseline bone loss (p < .001), molars (p < .001) and premolars (p < .001) as well as abutment teeth (p = .009).CONCLUSION:Tooth loss occurred rarely in patients with AgP treated in a private practice over a long-time period. Annual tooth loss rates are comparable with those described in university settings. Smoking, generalized form of AgP, location/type of tooth, baseline bone loss and abutment status could be detected as factors impacting upon tooth loss.

OBJECTIVES:To assess OHRQoL in patients with aggressive periodontitis (AgP) after periodontal treatment using the Oral Health Impact Profile-49 (OHIP-49) and compare to patients' dental status.MATERIAL AND METHODS:More than 5 years after therapy, 71 patients were examined and answered the OHIP-questionnaire. The dental and periodontal status were assessed according to the SSO (Swiss Dental Society) criteria. Descriptive statistics were performed with SPSS, correlation analysis and tests for differences using R 3.2.2.RESULTS:More than 90% of all patients showed no probing depths (PD) >5 mm, a bleeding on probing (BOP) index below 35%, and a sufficient function. Four patients showed no visible plaque, PDs ≤ 3 mm, a BOP below 10%, and an optimum function. Non-smoking and compliant patients exhibited a more favourable status. The OHIP-49 added up to 24.9 points, representing a comparatively high satisfaction of AgP-patients with their oral status. The subscale which most patients reported impairment in was "functional limitation." A correlation between quality standard and the OHIP-49G could only be shown in the psychological disability subscale.CONCLUSION:After treatment, a moderate to high quality level can be retained over more than 5 years. Most patients are satisfied with their oral health. Correlations between the objective and subjective view could not be found, apart from the subscale "psychological disability."

BACKGROUND To assess oral health-related quality of life (OHRQoL) after long-term (20 years) periodontal treatment in patients with chronic periodontitis (ChP) and to compare it with the current clinical outcome and oral health status. METHODS Twenty years after therapy, 63 patients were reexamined. The dental and periodontal status and OHRQoL using the Oral Health Impact Profile-G49 (OHIP-G49) were assessed. Descriptive statistics, correlation analysis, and tests for differences were calculated. RESULTS Up to 75% of patients showed no probing depths > 5mm, bleeding on probing (BOP) ≤25%, no pain and satisfactory function. A comparatively low perceived oral impact of ChP was represented by an OHIP-G49 overall score of 18.89 ± 21.66. The most common reported impairment was physical pain followed by "functional limitation." A correlation between oral quality standard and the OHIP-G49 was limited to the physical pain subdomain. CONCLUSIONS Satisfaction with oral status was perceived high by most patients treated for chronic periodontitis. A comparably high OHRQoL can be achieved and retained long-term after periodontal treatment. The objective and subjective evaluation of oral health only correlated in the subscale "physical pain."

AIM:To assess tooth loss in periodontally compromised patients 20 years after active periodontal therapy (APT) and to detect potential influencing factors for tooth loss on patient level.MATERIAL AND METHODS:From a total of 100 patients, who were re-evaluated ten years after APT, 70 could be re-examined 20 years ± 12 months after APT. Tooth loss during 20 years was detected and based on regression analyses the impact of patient-levelled factors was estimated.RESULTS:Of 1.639 teeth, 201 were lost (mean 2.87 teeth/patient, range 0-19 teeth, SD 3.49), resulting in a mean tooth loss rate of 0.14 teeth/patient/year during 20 years. Mean tooth loss per patient was higher during the second ten years of supportive periodontal therapy (SPT) compared to the first (1.20 vs. 1.67 teeth/patient). As influencing factors age (p < 0.001), smoking (p < 0.001), compliance to SPT (p < 0.001), marital status (p < 0.001), presence of diabetes (p < 0.001) and heart diseases (p = 0.001) could be detected.CONCLUSION:Over 20 years of follow-up, a low number of teeth were lost in mostly severely compromised periodontal patients. Smoking, non-compliance to SPT, age, living as a single and systemic diseases like diabetes or cardiovascular diseases negatively influence tooth loss on the long run.

Objectives: The aim was to evaluate the intra-test agreement of pooled samples from the deepest periodontal pocket of each quadrant with a commercially available test kit based on hybridization of 16S rRNA.Material and methods: Plaque samples of 50 patients with generalized severe chronic periodontitis before therapy were pooled in two separate vials in order to detect and compare counts of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola. Cohen's and interclass correlation coefficients were calculated to judge intra-test agreement.Results: Cohen's for detection and counts of Tannerella forsythia and Treponema denticola showed a perfect agreement. Porphyromonas ginigivalis was identified in both tests with a substantial agreement, whereas detection of Aggregatibacter actinomycetemcomitans varied in eight patients resulting in a good agreement. Possible confounding factors could not be identified statistically.Conclusion: Test results of the commercial 16S rRNA test are perfectly reproducible regarding detection of red complex pathogens. Intra-test agreement concerning detection of Aggregatibacter actinomycetemcomitans was less favorable.Clinical relevance: Detection of certain periodontal pathogens may alter the treatment and lead to prescription of antibiotics parallel to mechanical debridement. It is quite important not to use antibiotics excessively. Thus, the basis for decision-making in favor of antibiotics should be solid.

We thank the author of the letter for reading our paper carefully and emphasizing a very important statistical methodology which is indeed often applied in a wrong way. The author stresses two points about our analysis: first, it is stated that the ICCC instead of the ICC should be used and, second, that the j statistic is not a valid tool to assess reliability but a weighted j should be calculated. We want to present our point of view and show the validity of our analysing strategy: The first issue refers to the ICC. Obviously, we did not apply Pearson’s correlation coefficient (r) as stated by the author of the letter (which would not be a valid approach to assess reliability but is only a measure of correlation). Instead, we used the intraclass correlation coefficient (ICC), which is distinctly different from Pearson’s r and did not calculate an ‘inter-class correlation’ (this term was never used in our article). The author of the letter states that we should not use the ‘inter-class correlation’ but the ‘intra-class correlation coefficient’ using the acronym ‘ICCC’ and the article by Lawrence [1] as reference. However, Lawrence introduced an alternative approach to the ICC: the concordance correlation coefficient. The acronym ‘CCC’ is commonly used for this measure (not ‘ICCC’) [2]. This does not equal the ICC as clearly described in Lawrence’s article. Secondly, the ICC is a standard approach to analyse reliability [3–5], and as stated above, not equal to Pearson’s r. Furthermore, the CCC and the ICC both lead to very similar results. An overview can be found in the article by Watson and Petrie [3]. The second issue about the j-statistic is a very interesting and important concern. It is true that there is a lot of discussion about that measure. The author mentioned two of the common criticisms: The dependency of the j-statistic on the marginal prevalence and the on the number of categories. However, these criticisms cannot be applied to all situations. For example, Vach (2005) [6] states that we should stop criticizing the j-statistic: Besides other issues, Vach addresses the problem of the dependency on the prevalence (and the main criticism stated by the author of the letter) and explains that the j-statistic is a good measure of reliability able to adjust for imbalances in marginal prevalence. Regarding the dependency of the j-statistic on the observed prevalence, Vach states that ‘this type of dependence does not, however, indicate any drawback or weakness of the j-statistic. It merely reflects the basic aim of the j-statistic’ (p. 656). We certainly agree with this statement as the statistic measures the amount of agreement observed on top of the agreement by chance. Furthermore, Vach says that ‘the expected amount of agreement by chance depends on the marginal prevalences, and so the correction depends on it’ (p. 656). He summarizes ‘it is the aim of the j-statistic that identical agreement rates should be judged differently in the light of the marginal prevalences, which determine the expected amount of chance agreement. Hence, it makes no sense to criticize j for exactly fulfilling this property’ (p. 659). The comparability of the results of a reliability analysis between different variables with different numbers of categories might be questionable in general. In our article, we exclusively check variables with only two categories for reliability. Therefore, we think that this issue does not apply to our article. Furthermore, the weighted j does not solve this problem because it is only applicable to ordinal data and it also depends on the number of categories as described by Benner and Kliebisch [7]. Obviously, different analysts have different opinions about the use of the j-statistic. However, we agree with Vach on the properties of j. We aimed at correcting the measure of agreement for the marginal prevalence and, hence, the j-statistic is a valid tool to analyse the data. We thank the author of the letter for stressing this important topic and do not wish to criticize his opinion. Indeed we are thankful for the opportunity to discuss the characteristics of the applied statistical approach. We hope that we were able to show the validity of our analysing strategy.

OBJECTIVES:To assess the influence of endodontic status on retention of molars in patients under supportive periodontal treatment (SPT).MATERIAL & METHODS:A total of 136 subjects with 1015 molars at baseline were examined retrospectively, including 188 endodontically treated molars in 90 patients. Multilevel Cox regression analysis identified factors contributing to loss of molars.RESULTS:Root canal treatments contributed significantly to loss of molars during on average 13.2 years of SPT (Hazard ratio: 2.98, 95% CI: 1.74-5.1, p < 0.001). Endodontic treatment was more frequently present in first molars (p < 0.001) and in the maxilla (p = 0.01). In endodontically treated molars, degree III furcation involvement could be detected more often compared to molars without root canal treatment (p < 0.001). Among the root canal-treated molars, several patient and tooth-related factors showed an impact on tooth retention, but only molars with a periapical index of 4 and 5 (labelled "diseased") were significantly more often lost.CONCLUSION:The retention of molars in periodontally compromised patients after periodontal treatment is influenced by periodontal as well as endodontal factors. On a long-term basis, it is feasible to retain these teeth via active periodontal treatment and SPT for more than 10 years.

AIM To identify risk factors for loss of molars during supportive periodontal therapy (SPT). MATERIALS AND METHODS A total of 136 subjects with 1015 molars at baseline were examined retrospectively. The association of risk factors with loss of molars was assessed using a multilevel Cox regression analysis. Furcation involvement (FI) was assessed clinically at start of periodontal therapy and assigned according to Hamp et al. (1975). RESULTS Fifty molars were extracted during active periodontal therapy (APT) and 154 molars over the average SPT period of 13.2 ± 2.8 years. FI degree III (HR 4.68, p < 0.001), baseline bone loss (BL) > 60% (HR 3.74, p = 0.009), residual mean probing pocket depth (PPD, HR 1.43, p = 0.027), and endodontic treatment (HR 2.98, p < 0.001) were identified as relevant tooth-related factors for loss of molars during SPT. However, mean survival time for molars with FI III or BL > 60% were 11.8 and 14.4 years, respectively. Among the patient data, age (HR 1.57, p = 0.01), female gender (HR 1.99, p = 0.035), smoking (HR 1.97, p = 0.034), and diabetes mellitus (HR 5.25, p = 0.021) were significant predictors for loss of molars. CONCLUSION Overall, periodontal therapy results in a good prognosis of molars. Degree III FI, progressive BL, endodontic treatment, residual PPD, age, female gender, smoking, and diabetes mellitus strongly influence the prognosis for molars after APT.

AimsIn spite of the remarkable success of current preventive efforts, periodontitis remains one of the most prevalent diseases of mankind. The objective of this workshop was to review critical scientific evidence and develop recommendations to improve: (i) plaque control at the individual and population level (oral hygiene), (ii) control of risk factors, and (iii) delivery of preventive professional interventions.MethodsDiscussions were informed by four systematic reviews covering aspects of professional mechanical plaque control, behavioural change interventions to improve self-performed oral hygiene and to control risk factors, and assessment of the risk profile of the individual patient. Recommendations were developed and graded using a modification of the GRADE system using evidence from the systematic reviews and expert opinion.ResultsKey messages included: (i) an appropriate periodontal diagnosis is needed before submission of individuals to professional preventive measures and determines the selection of the type of preventive care; (ii) preventive measures are not sufficient for treatment of periodontitis; (iii) repeated and individualized oral hygiene instruction and professional mechanical plaque (and calculus) removal are important components of preventive programs; (iv) behavioural interventions to improve individual oral hygiene need to set specific Goals, incorporate Planning and Self monitoring (GPS approach); (v) brief interventions for risk factor control are key components of primary and secondary periodontal prevention; (vi) the Ask, Advise, Refer (AAR) approach is the minimum standard to be used in dental settings for all subjects consuming tobacco; (vii) validated periodontal risk assessment tools stratify patients in terms of risk of disease progression and tooth loss.ConclusionsConsensus was reached on specific recommendations for the public, individual dental patients and oral health care professionals with regard to best action to improve efficacy of primary and secondary preventive measures. Some have implications for public health officials, payers and educators.