Accepted Manuscript Self-reported measures may be useful in surveillance for periodontitis Mark S. Litaker, Ph.D. PII:
S1532-3382(14)00084-0
DOI:
10.1016/j.jebdp.2014.04.020
Reference:
YMED 971
To appear in:
The Journal of Evidence-Based Dental Practice
Please cite this article as: Litaker MS, Self-reported measures may be useful in surveillance for periodontitis, The Journal of Evidence-Based Dental Practice (2014), doi: 10.1016/j.jebdp.2014.04.020. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Article Analysis and Evaluation – Diagnosis/Treatment/Prognosis DECLARATIVE TITLE: Self-reported measures may be useful in surveillance for periodontitis.
RI PT
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Self-reported measures for surveillance of periodontitis. Eke PI, Dye BA, Wei L, Slade GD, Thornton-Evans GO, Beck JD, Taylor GW, Borgnakke WS, Page RC, Genco RJ. J Dent Res 2013; 92(11):1041-7 PURPOSE/QUESTION: The study aim was to evaluate the predictive performance of eight self-reported items for the prediction of periodontitis against clinically determined periodontitis in a US nationally representative sample of adults.
TYPE OF STUDY/DESIGN: Cross-sectional study.
M AN U
REVIEWER NAME and CONTACT INFORMATION: Mark S. Litaker, Ph.D. Associate Professor / Director of Biostatistics Department of Clinical and Community Sciences UAB School of Dentistry, SDB Room 111 1720 2nd Avenue South Birmingham, AL 35294-0007 office: 205-934-1179 fax: 205-975-0603
SC
SOURCE OF FUNDING: The study was funded by the Centers for Disease Control and Prevention as an internal project.
TE D
Summary
Subjects:
AC C
EP
The analysis sample consisted of 3743 individuals age 30 years or older who had complete oral health data obtained in the 2009-2010 cycle of National Health and Nutrition Examination Survey (NHANES), after exclusion of 951 subjects with incomplete oral health data and 343 edentulous subjects. Gender distribution and geographic location of the study subjects are not presented. The sample was obtained through a probability sampling design, weighted to represent 137.1 million civilian non-institutionalized US adults age 30 years and older.
Key Exposure/Study Factor: The primary study factor consisted of eight closed-ended, self-reported survey items regarding oral health.
Main Outcome Measure:
The primary outcome measure was diagnosis of periodontitis, based on Centers for Disease Control and Prevention−American Academy of Periodontology (CDC-AAP) case definitions for surveillance of periodontitis.1 Using these definitions, periodontitis was categorized as mild-, moderate-, severe-, and total periodontitis. Three additional definitions for periodontitis were also analyzed: attachment loss (AL) of 3 mm or more at one or more sites, probing depth (PD) of 4 mm or more at one or more sites, and the European Workshop in Periodontology classifications.2
ACCEPTED MANUSCRIPT
Main Results: Responses to each of the eight oral health survey questions were significantly associated with periodontitis for all of the outcome definitions. Crude odds ratios for the association with CDC/AAP total periodontitis ranged from 1.0843 (95% confidence interval [CI]: 1.0835 – 1.0850) for never using mouthwash to 3.5668 (95% CI: 3.5625-3.5711) for having loose teeth.
RI PT
Multivariable predictive models developed with stepwise variable selection using demographic and risk factor variables and responses to the eight oral-health questions were selected as best-performing. These showed 85% sensitivity, 58% specificity, and area under the receiver operating characteristic curve (AUROC) of 0.81 for total periodontitis, and 76% sensitivity, 58% specificity, and AUROC of 0.75 for PD ≥ 4mm.
SC
Four of the questions were selected into the best predictive model for AL ≥ 3 mm: having self-perceived gum disease, self-rated health of teeth or gums, being told by a dental professional that the participant had bone loss around their teeth, and self-reported use of dental floss. That model showed 94% sensitivity, 31% specificity, and AUROC of 0.82. Models including these four measures showed sensitivity, specificity, and AUROC of 50%, 88.4%, and 0.83, respectively, for severe periodontitis, and 64%, 88% and 0.87, respectively, for extensive periodontitis using the European definitions.
M AN U
Conclusions:
Good performance and cost-effectiveness of self-reported oral health items show potential for use as an alternative to clinical periodontal measures in population surveys where periodontal examination may not be practical.
Commentary and Analysis
TE D
The results of the study seem to be well-supported. The NHANES sample provides an excellent basis for the development of statistical models, and the reported results show moderate to high levels of AUROC, ranging from levels that have been characterized as “useful for some purposes” (AUROC of 0.7 to 0.9) to those characterized as representing high accuracy (AUROC > 0.9).3
AC C
EP
The results are consistent with a number of previous publications showing similar approaches to the development of multivariable model-based screening tools.4-6 Although they used disparate data sets, those publications reported models based on self-report of periodontal health that yielded very similar performance characteristics. Typically, cross-sectional study designs receive low ratings for strength of evidence. However, for the development of models to be used in screening for a prevalent chronic disease such as periodontitis, this design is appropriate. In this study design, the definitive diagnosis and the variables used in the screening model were evaluated at approximately the same point in time on the same subjects. The applicability of the model will, of course, depend on the study subjects providing an adequate representation of those in the population in which the screening will be implemented. Confidence in the validity of the models would be enhanced by applying the models developed in one study to other samples from the same target population. Screening methods based on multivariable models may not be directly applicable to the practice setting. Instead, such models would likely be more useful in population surveillance, where full periodontal examination might not be practical because of both subject burden and cost considerations. The outcome for this study was the diagnosis of periodontitis. Multiple definitions of periodontitis were used as the outcome measures for developing the predictive models, since there is no general consensus on a single diagnostic definition. This is a clinically relevant outcome because of the high prevalence of periodontitis in adults as well as its potential association with other disease entities. The validity of self-reported responses as screening tools for surveillance of periodontal disease is supported by the development of predictive models for use in this large sample of patients who are representative of the U.S. population. The validation of the screening models using an independent group of patients is not reported, although similar performance from other data sets is referenced. There is potential for a validation approach to be utilized in a
ACCEPTED MANUSCRIPT
subsequent cycle of the NHANES data collection. The achievement of similar performance would provide additional support for the validity of the screening models.
RI PT
More detail regarding the specific variable selection approach used to develop the multivariable models would facilitate replication of this approach in other studies. Parameter estimates for the predictive models that were developed for each of the definitions of periodontitis were not presented, although the variables included in each model are reported. Providing parameter estimates would allow validation of these models using other data sets.
SC
The criterion method of diagnosis for chronic periodontitis, based on a full-mouth examination including six sites per tooth, may be impractical for use in population-based studies for reasons of time, cost, or subject burden. Partial recording protocols provide one approach to reduce the burden of a full assessment, but these have demonstrated bias in estimating periodontal parameters that may vary across sites.7,8 While providing some reduction in burden relative to full-mouth examination, partial recording protocols might still be impractical for large studies. If valid predictive models can be demonstrated, screening for periodontal disease using self-reported oral health information may be useful in large epidemiologic surveys.
M AN U
Strength of Recommendation Taxonomy (SORT) Grading LEVEL OF EVIDENCE: Level 2 – Limited quality, patient-oriented evidence
STRENGTH OF RECOMMENDATION GRADE: Not applicable
TE D
References 1. Page RC, Eke PI. Case definitions for use in population-based surveillance of periodontitis. J Periodontol 2007;78(7 Suppl):1387S-99S. 2. Tonetti MS, Claffey N. Advances in the progression of periodontitis and proposal of definitions of a periodontitis case and disease progression for use in risk factor research. Group C consensus report of the 5th European Workshop in Periodontology. J Clin Periodontol 2005;32(Suppl 6):210-3.
EP
3. Swets JA. Measuring the accuracy of diagnostic systems. Science 1988;240:1285-93.
AC C
4. Gilbert GH, Litaker MS. Validity of self-reported periodontal status in the Florida dental care study. J Periodontol 2007;78(7 Suppl):1429S-38S. 5. Dietrich T, Stosch U, Dietrich D, Kaiser W, Bernimoulin JP, Joshipura K. Prediction of periodontal disease from multiple self-reported items in a German practice-based sample. J Periodontol 2007;78:1421-28. 6. Genco RJ, Falkner KL, Grossi S, Dunford R, Trevisan M. Validity of self-reported measures for surveillance of periodontal disease in two western New York population-based studies. J Periodontol 2007;78(7 Suppl):1439S-54S. 7. Susin C, Kingman A, Albandar JM. Effect of partial recording protocols on estimates of prevalence of periodontal disease. J Periodontol 2005;76(2):262-7. 8. Kingman A, Susin C, Albandar JM. Effect of partial recording protocols on severity estimates of periodontal disease. J Clin Periodontol 2008;35:659-67.
S1532-3382(14)00084-0
DOI:
10.1016/j.jebdp.2014.04.020
Reference:
YMED 971
To appear in:
The Journal of Evidence-Based Dental Practice
Please cite this article as: Litaker MS, Self-reported measures may be useful in surveillance for periodontitis, The Journal of Evidence-Based Dental Practice (2014), doi: 10.1016/j.jebdp.2014.04.020. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Article Analysis and Evaluation – Diagnosis/Treatment/Prognosis DECLARATIVE TITLE: Self-reported measures may be useful in surveillance for periodontitis.
RI PT
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Self-reported measures for surveillance of periodontitis. Eke PI, Dye BA, Wei L, Slade GD, Thornton-Evans GO, Beck JD, Taylor GW, Borgnakke WS, Page RC, Genco RJ. J Dent Res 2013; 92(11):1041-7 PURPOSE/QUESTION: The study aim was to evaluate the predictive performance of eight self-reported items for the prediction of periodontitis against clinically determined periodontitis in a US nationally representative sample of adults.
TYPE OF STUDY/DESIGN: Cross-sectional study.
M AN U
REVIEWER NAME and CONTACT INFORMATION: Mark S. Litaker, Ph.D. Associate Professor / Director of Biostatistics Department of Clinical and Community Sciences UAB School of Dentistry, SDB Room 111 1720 2nd Avenue South Birmingham, AL 35294-0007 office: 205-934-1179 fax: 205-975-0603
SC
SOURCE OF FUNDING: The study was funded by the Centers for Disease Control and Prevention as an internal project.
TE D
Summary
Subjects:
AC C
EP
The analysis sample consisted of 3743 individuals age 30 years or older who had complete oral health data obtained in the 2009-2010 cycle of National Health and Nutrition Examination Survey (NHANES), after exclusion of 951 subjects with incomplete oral health data and 343 edentulous subjects. Gender distribution and geographic location of the study subjects are not presented. The sample was obtained through a probability sampling design, weighted to represent 137.1 million civilian non-institutionalized US adults age 30 years and older.
Key Exposure/Study Factor: The primary study factor consisted of eight closed-ended, self-reported survey items regarding oral health.
Main Outcome Measure:
The primary outcome measure was diagnosis of periodontitis, based on Centers for Disease Control and Prevention−American Academy of Periodontology (CDC-AAP) case definitions for surveillance of periodontitis.1 Using these definitions, periodontitis was categorized as mild-, moderate-, severe-, and total periodontitis. Three additional definitions for periodontitis were also analyzed: attachment loss (AL) of 3 mm or more at one or more sites, probing depth (PD) of 4 mm or more at one or more sites, and the European Workshop in Periodontology classifications.2
ACCEPTED MANUSCRIPT
Main Results: Responses to each of the eight oral health survey questions were significantly associated with periodontitis for all of the outcome definitions. Crude odds ratios for the association with CDC/AAP total periodontitis ranged from 1.0843 (95% confidence interval [CI]: 1.0835 – 1.0850) for never using mouthwash to 3.5668 (95% CI: 3.5625-3.5711) for having loose teeth.
RI PT
Multivariable predictive models developed with stepwise variable selection using demographic and risk factor variables and responses to the eight oral-health questions were selected as best-performing. These showed 85% sensitivity, 58% specificity, and area under the receiver operating characteristic curve (AUROC) of 0.81 for total periodontitis, and 76% sensitivity, 58% specificity, and AUROC of 0.75 for PD ≥ 4mm.
SC
Four of the questions were selected into the best predictive model for AL ≥ 3 mm: having self-perceived gum disease, self-rated health of teeth or gums, being told by a dental professional that the participant had bone loss around their teeth, and self-reported use of dental floss. That model showed 94% sensitivity, 31% specificity, and AUROC of 0.82. Models including these four measures showed sensitivity, specificity, and AUROC of 50%, 88.4%, and 0.83, respectively, for severe periodontitis, and 64%, 88% and 0.87, respectively, for extensive periodontitis using the European definitions.
M AN U
Conclusions:
Good performance and cost-effectiveness of self-reported oral health items show potential for use as an alternative to clinical periodontal measures in population surveys where periodontal examination may not be practical.
Commentary and Analysis
TE D
The results of the study seem to be well-supported. The NHANES sample provides an excellent basis for the development of statistical models, and the reported results show moderate to high levels of AUROC, ranging from levels that have been characterized as “useful for some purposes” (AUROC of 0.7 to 0.9) to those characterized as representing high accuracy (AUROC > 0.9).3
AC C
EP
The results are consistent with a number of previous publications showing similar approaches to the development of multivariable model-based screening tools.4-6 Although they used disparate data sets, those publications reported models based on self-report of periodontal health that yielded very similar performance characteristics. Typically, cross-sectional study designs receive low ratings for strength of evidence. However, for the development of models to be used in screening for a prevalent chronic disease such as periodontitis, this design is appropriate. In this study design, the definitive diagnosis and the variables used in the screening model were evaluated at approximately the same point in time on the same subjects. The applicability of the model will, of course, depend on the study subjects providing an adequate representation of those in the population in which the screening will be implemented. Confidence in the validity of the models would be enhanced by applying the models developed in one study to other samples from the same target population. Screening methods based on multivariable models may not be directly applicable to the practice setting. Instead, such models would likely be more useful in population surveillance, where full periodontal examination might not be practical because of both subject burden and cost considerations. The outcome for this study was the diagnosis of periodontitis. Multiple definitions of periodontitis were used as the outcome measures for developing the predictive models, since there is no general consensus on a single diagnostic definition. This is a clinically relevant outcome because of the high prevalence of periodontitis in adults as well as its potential association with other disease entities. The validity of self-reported responses as screening tools for surveillance of periodontal disease is supported by the development of predictive models for use in this large sample of patients who are representative of the U.S. population. The validation of the screening models using an independent group of patients is not reported, although similar performance from other data sets is referenced. There is potential for a validation approach to be utilized in a
ACCEPTED MANUSCRIPT
subsequent cycle of the NHANES data collection. The achievement of similar performance would provide additional support for the validity of the screening models.
RI PT
More detail regarding the specific variable selection approach used to develop the multivariable models would facilitate replication of this approach in other studies. Parameter estimates for the predictive models that were developed for each of the definitions of periodontitis were not presented, although the variables included in each model are reported. Providing parameter estimates would allow validation of these models using other data sets.
SC
The criterion method of diagnosis for chronic periodontitis, based on a full-mouth examination including six sites per tooth, may be impractical for use in population-based studies for reasons of time, cost, or subject burden. Partial recording protocols provide one approach to reduce the burden of a full assessment, but these have demonstrated bias in estimating periodontal parameters that may vary across sites.7,8 While providing some reduction in burden relative to full-mouth examination, partial recording protocols might still be impractical for large studies. If valid predictive models can be demonstrated, screening for periodontal disease using self-reported oral health information may be useful in large epidemiologic surveys.
M AN U
Strength of Recommendation Taxonomy (SORT) Grading LEVEL OF EVIDENCE: Level 2 – Limited quality, patient-oriented evidence
STRENGTH OF RECOMMENDATION GRADE: Not applicable
TE D
References 1. Page RC, Eke PI. Case definitions for use in population-based surveillance of periodontitis. J Periodontol 2007;78(7 Suppl):1387S-99S. 2. Tonetti MS, Claffey N. Advances in the progression of periodontitis and proposal of definitions of a periodontitis case and disease progression for use in risk factor research. Group C consensus report of the 5th European Workshop in Periodontology. J Clin Periodontol 2005;32(Suppl 6):210-3.
EP
3. Swets JA. Measuring the accuracy of diagnostic systems. Science 1988;240:1285-93.
AC C
4. Gilbert GH, Litaker MS. Validity of self-reported periodontal status in the Florida dental care study. J Periodontol 2007;78(7 Suppl):1429S-38S. 5. Dietrich T, Stosch U, Dietrich D, Kaiser W, Bernimoulin JP, Joshipura K. Prediction of periodontal disease from multiple self-reported items in a German practice-based sample. J Periodontol 2007;78:1421-28. 6. Genco RJ, Falkner KL, Grossi S, Dunford R, Trevisan M. Validity of self-reported measures for surveillance of periodontal disease in two western New York population-based studies. J Periodontol 2007;78(7 Suppl):1439S-54S. 7. Susin C, Kingman A, Albandar JM. Effect of partial recording protocols on estimates of prevalence of periodontal disease. J Periodontol 2005;76(2):262-7. 8. Kingman A, Susin C, Albandar JM. Effect of partial recording protocols on severity estimates of periodontal disease. J Clin Periodontol 2008;35:659-67.
