Home | About Us | Editorial Board | Current Issue | Archives | Search | Instructions | Subscription | Feedback | e-Alerts | Login 
Journal of Indian Society of Pedodontics and Preventive Dentistry Official publication of Indian Society of Pedodontics and Preventive Dentistry
 Users Online: 57951  
 
  Print this page Email this page   Small font sizeDefault font sizeIncrease font size


 
  Table of Contents    
ORIGINAL ARTICLE
Year : 2020  |  Volume : 38  |  Issue : 3  |  Page : 266-273
 

Comparative evaluation of the predictive value of cariogram and informal caries risk assessment among school-going children in the age group of 8–9 years of Yamuna Nagar District, Haryana


1 Reader, Department of Pedodontics and Preventive Dentistry, P.D.M. Dental College and Research Institute, Sarai Aurangabad, Bahadurgarh, India
2 Professor, Department of Pedodontics and Preventive Dentistry, J.N.Kapoor D.A.V. (C) Dental College & Hospital, Yamuna Nagar, Haryana, India
3 Director/ Principal, Professor and Head, Department of Pedodontics and Preventive Dentistry, J.N.Kapoor D.A.V. (C) Dental College & Hospital, Yamuna Nagar, Haryana, India
4 Professor, Department of Pedodontics and Preventive Dentistry, J.N.Kapoor D.A.V. (C) Dental College & Hospital, Yamuna Nagar, Haryana, India
5 Professor, Department of Pedodontics and Preventive Dentistry, P.D.M. Dental College and Research Institute, Sarai Aurangabad, Bahadurgarh, Haryana, India

Date of Submission05-Aug-2019
Date of Decision21-Feb-2020
Date of Acceptance02-Sep-2020
Date of Web Publication29-Sep-2020

Correspondence Address:
Dr. Jyoti Sharma
H. No. 134.L, Model Town, Rohtak - 124 001, Haryana
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/JISPPD.JISPPD_237_19

Rights and Permissions

 

   Abstract 


Aim: This longitudinal, observational study was conducted in the schools of Yamunanagar, Haryana, to evaluate and compare the predictive value of formal type of caries risk assessment using reduced Cariogram software, including only seven factors and informal type among 8–9 years' school-going children. Materials and Methods: A total of 111 school-going children were included in the study. Risk profile for each child was created using cariogram as well as informal factors. The same children were scheduled for re-examination at an interval of 9 and 18 months. The caries status was recorded again using the Collapsed International Caries Detection and Assessment System (ICDAS) concept. Statistical Analysis: The precoded data were transferred to the computer and analyzed using the SPSS software (version 17.0). Data were analyzed for the identification of children with lesion progression and numbers of lesions progressing using the Transition Scoring System. Results: Cariogram being a multifactorial model gives significant individual weightage to each etiological factor causing dental caries as compared to informal caries risk assessment which though easy to implement yet unstructured unlike cariogram and thus does not guarantee consistent implementation. Conclusion: Cariogram is a perfect option for patient motivation and supports the clinician in decision making for planning preventive strategies for the patients. Along with this, a combination of the factors for informal caries risk assessment can help in making a simple yet multifactorial model which can be applied in daily practice.


Keywords: Caries risk assessment, Cariogram software, informal caries risk assessment


How to cite this article:
Sharma J, Gupta M, Pandit IK, Gugnani N, Mehta LK. Comparative evaluation of the predictive value of cariogram and informal caries risk assessment among school-going children in the age group of 8–9 years of Yamuna Nagar District, Haryana. J Indian Soc Pedod Prev Dent 2020;38:266-73

How to cite this URL:
Sharma J, Gupta M, Pandit IK, Gugnani N, Mehta LK. Comparative evaluation of the predictive value of cariogram and informal caries risk assessment among school-going children in the age group of 8–9 years of Yamuna Nagar District, Haryana. J Indian Soc Pedod Prev Dent [serial online] 2020 [cited 2020 Oct 24];38:266-73. Available from: https://www.jisppd.com/text.asp?2020/38/3/266/296629





   Introduction Top


Dental caries continues to be a universally existing, multifactorial condition which demands expertise and time-consuming professional treatment.[1],[2] Conventionally, the treatment of dental caries has mainly been with the conventional drill and fill technique, but recently, a paradigm shift is observed in the caries management with more intense focus on prevention, early caries detection, and more conservative minimally invasive treatment approaches.[3] To formulate an appropriate management strategy, the identification of risk factors for dental caries is most important as the removal of these identified risk factors in a patient would help in preventing any further progress of the dental caries.

Caries risk assessment denotes the process of establishing the probability for an individual patient to develop new enamel or dentin lesions over the near future.[4] Multiple variables according to different age groups have been proposed as caries risk factors based on socioeconomy, behavior, general health, diet, oral hygiene, clinical observations, and past caries experience.[4]

Current methods for caries risk assessment include a range of objective and subjective methods. At one extreme are complex formulae requiring a variety of objective, clinical, and microbiological information that yield a risk score while at the opposite extreme are simple approaches that require only a dentist's subjective assessment of risk level offering little guidance for making that assessment.[5],[6],[7] Although informal caries risk assessment is easy to implement, but it is unstructured, and thus does not guarantee consistent implementation.[8] The inclusion of one criteria or another is based on clinical intuition, rather than concrete data.

For that reason, dental practitioners should conduct a formal caries risk assessment to determine the precise factors involved in the patient's disease progression.[9] Many methodical tools are now available which can make risk assessment more accurate, for example, Cariogram, American Academy of Pediatric Dentistry caries risk assessment tool (CAT), American Dental Association (ADA) CAT.[8] Cariogram software program developed by Professor D. Bratthall, Malmo, Sweden is one such model which assess and illustrates caries risk profile graphically, simultaneously taking into account the interaction of different caries causing factors/parameters of the patient.[6] This model makes it possible to identify individual risk or resistance factors.[10] In spite of their simplicity and ease to use, these tools are not widely used either because of their time-consuming nature and scanty literature supporting their validity.

In a developing country like India where caries is so prevalent, CAT provides the clinician an opportunity to identify the potential risk factors associated with caries for individual patients which can further help in minimizing the occurrence of these lesions. This will allow the implementation of a proper preventive and therapeutic programme to further control its spread. With this background, the present study was planned to evaluate and compare the predictive value of formal type of caries risk assessment using reduced Cariogram software including only seven factors and informal type of caries risk assessment among 8–9 years school-going children in Yamunanagar, Haryana.


   Materials and Methods Top


This longitudinal, observational study [Figure 1] was conducted at the schools of Yamunanagar, Haryana. Prior to inception of the study, ethical approval was sought from the Institutional's Review Board. The informed consent of parents and ascent of children were obtained explaining the aim of the study and asking for their child's participation. A total of 111 school-going children who were 8–9 years of age as per school records and present on the day of the examination were included in the study to evaluate and compare the predictive value of formal type of caries risk assessment using reduced Cariogram software including only seven factors [Table 1][11] and informal type of caries risk assessment [Table 2]. Children with physical limitations which might interfere with tooth brushing, children undergoing orthodontic treatment, and those who were not willing to be a part of the study were excluded from the study. To ensure the participation of children from different socioeconomic groups, the schools were divided into three categories that is low, middle, and high socioeconomic status (SES), as per school fee the students were paying.[12] One school from each category was selected using the simple random sampling and children were equally divided among the selected schools.
Figure 1: Study flowchart

Click here to view
Table 1: Input variables and scores used to complete the cariogram

Click here to view
Table 2: Variables for informal caries risk assessment and their description

Click here to view


The clinical examination was carried out by a single examiner. Children were examined in their respective schools, at a predetermined time schedule, as arranged with the school authorities. Interview-based semistructured questionnaire was used to collect data pertaining to between meal snacks per day, related general diseases, the use of fluoridated toothpaste and other fluoride supplements. Oral hygiene was assessed using Plaque Index according to Silness P and Loe H. The baseline caries status was recorded using the Collapsed ICDAS concept[13] [Figure 2]. Dentocult SM strips (Orion Diagnostica, Espoo, Finland) chair side technique was used to determine the count of Streptococcus mutans in saliva. Instructions were given to the children to swallow excess saliva, and then, rough surface of round tipped strip was pressed against the saliva remaining on the tongue. The strips were then removed from the mouth and placed in the culture vials which were labeled individually for each participant and were incubated at 37°C for 48 h. The presence of colonies was evidenced by dark blue raised colonies on the rough surface of the strip. The number of mutans streptococci per ml saliva was evaluated by comparing the test strips with the evaluation chart provided by the manufacturer and given a score between 0 and 3: class 0: <10,000 CFU/ml, Class 1: <100,000 CFU/ml, class 2: 100,000–1,000,000 CFU/ml, Class 3: >1,000,000 CFU/ml [Figure 3].
Figure 2: The proposed FDI World Dental Federation Caries Matrix system (Collapsed ICDAS)[13]

Click here to view
Figure 3: Streptococcus Mutans (SM) strips after 48 h incubation

Click here to view


Risk profile for each child was created using cariogram as well as informal factors. At baseline, no preventive or therapeutic procedures were done intentionally. However, children were free to get any knowledge or treatment on their own. All 111 children were scheduled for re-examination at their respective schools at an interval of 9 and 18 months. However, 6 children were lost to follow-up because of parents' transfer, so a total of 105 children were re-examined. The caries status was recorded again using the Collapsed ICDAS concept. Data were analyzed for the identification of children with lesion progression and numbers of lesions progressing using the Transition Scoring System (TSS)[14] [Table 3]. The precoded data were transferred to the computer and analyzed using the Statistical Package for the Social Science (v17.0, SPSS Inc., Chicago, USA). To explore the potential associations between cariogram values (actual chance to avoid new cavities) with actual caries increment at 9 and 18 months, Pearson's correlation test was done. For informal factors, odd's ratio and Chi-square test were used to calculate the significance of various factors on individual tooth surfaces [Table 4], [Table 5], [Table 6]. P ≤ 0.05 with 95% confidence interval was set to indicate statistically significant differences among the various factors.
Table 3: Transition scores as per cariogram risk categories at 9 and 18 months

Click here to view
Table 4: Transition scores for tooth surfaces at 9 months for informal caries risk assessment

Click here to view
Table 5: Transition scores for tooth surfaces at 18 months for informal caries risk assessment

Click here to view
Table 6: Caries progression according to different informal factors at 18 months

Click here to view



   Results Top


At baseline, 92.42% of tooth surfaces were sound, 2.01% showed noncavitated enamel lesions, while 4.65% surfaces showed frank open cavitations. 63.96% of the children showed less than good oral hygiene. None of the children showed extremely good oral hygiene. However, 27.03% showed good oral hygiene, whereas 9% showed poor oral hygiene. Caries risk status at baseline according to the cariogram and informal method is shown in [Table 7] and [Table 8].
Table 7: Distribution of the children as per caries risk assessment by cariogram at baseline

Click here to view
Table 8: Distribution of children as per caries risk assessment by informal method at baseline

Click here to view


The value of Pearson's coefficient (r) was found to be 0.977 at 9 months and 0.983 at 18 months which indicates a strong positive correlation between risk categories as predicted by the cariogram at baseline with respect to actual caries increment at subsequent follow-ups.

According to informal factors at baseline, 80.18% children showed evidence of past caries. After 18 months, children with only occlusal caries showed 94.74% increment in caries, whereas in children having both occlusal and smooth surface caries, 98.48% caries increment was seen. When tooth surfaces were considered, children without any previous decay at baseline had 6.25% caries progression at 18 months, whereas those having previous decay had 12% surfaces that showed progression at 18 months. Highly significant difference was observed between the two.

No significant difference was seen at 18 months among the high-risk category children consuming between meal snacks for 1–2 times/day (97.56% increment in caries) and low-risk category children having exposure to between meal snacks >2 times/day (96.15% caries increment). However, highly significant difference was seen in terms of total number of tooth surfaces, 7.02% surfaces progressed further as compared to their baseline score among low risk children, and 13.12% surfaces showed further progression among high risk children.

In the present study, 75.67% children were using fluoridated toothpaste and showed 94.04% progression in caries, whereas among the nonfluoridated toothpaste group, 95.24% caries progression was seen at 18 months. When the effect of toothpaste was evaluated on the total number of tooth surfaces, among the fluoridated toothpaste group, 10.65% surfaces showed progression and nonfluoridated group showed 11.90% caries progression. There was no significant difference. At 18 months, the difference in terms of caries progression between the two risk groups based on the frequency of tooth brushing was significant. 86.36% children showed caries progression among low-risk group, whereas in high-risk group, 98.8% children had new caries.

Out of the total children that were considered at low risk, as they had no visible plaque, 70% showed caries progression. On the other hand, among high-risk children, with visible plaque, 98.82% showed caries progression. In terms of tooth surfaces, highly significant difference was found in children without visible plaque 4.5% surfaces progressed and in children with visible plaque, 12.41% lesions progressed.

There was no significant difference in future risk for caries at 18 months among the children according to their liking for sweets. As low risk group, children showed 90.91% increase in future caries compared to high caries risk group where 98.36% caries increment was seen. In terms of tooth surfaces, highly significant was found at 18 months, as 7.78% surfaces showed caries progression among low risk children, whereas 13.16% surfaces had progressed more toward caries among high risk children.

No significant difference was found in caries progression among low SES, 97.14% children, medium SES, 97.06% children and high SES, 91.67% children. Highly significant difference was observed in terms of caries progression surface wise, in low risk children, 9.76% and high risk children 13.19% at 18 months.


   Discussion Top


Caries risk is not same for all individuals, so an individualized protocol should be followed based on the balance between risk factors and protective factors. Collapsed ICDAS concept was used to measure caries both at baseline and subsequent visits. It helps to measure the surfaces of teeth even in the noncavitated stage, which highlights the need to examine surfaces instead of tooth as a whole as it gives a more detailed picture.

Children between 8 and 9 years were selected for the study primarily because caries activity is observed to be high in this age group due to increased intake of sugars and starchy foods and increased frequency of eating.[15] Child's responses are also well developed at this age period to an extent which facilitates easy communication between child and the dentist.

Among formal caries risk assessment, the Cariogram is a widely available tool that has been validated[16] and has received much attention in the discipline of cariology. It has been used extensively to identify the caries risk factors for a variety of populations globally.[6],[11],[17] Either of the 7 (out of 10) factors can be used to assess caries risk of any individual. In the present study, factors were included in accordance to the study conducted by Holgerson et al., 2009.[11] Mutans streptococci count was included as one of the factor, as it has been proved to be a strong predictor for future caries.[6]

A strong positive correlation was seen between the risk categories as predicted by the cariogram at baseline with respect to actual caries increment at subsequent follow-ups. This could be explained as cariogram is a multifactorial model, it takes multiple factors into consideration and gives individual weightage to each factor and not to the cumulative effect.

As far as informal caries risk assessment is considered, past caries experience has always been considered as a strong predictor for future caries.[18] This signifies the importance of the existing caries experience as a predictor of future caries. The difference in the caries increment in children with only occlusal caries and those with occlusal and smooth surface caries could be attributed to the fact that the presence of active cavitated smooth-surface lesions is one of the key factors for caries risk assessment. This could be explained as individual surface of teeth may provide a more clear picture of the overall effect of the individual factor taken into consideration. In a systematic review conducted by Powell et al. 1998,[19] decayed surfaces were considered to be the best outcome, if the caries prediction model was designed to predict the associations between the independent variables and caries development.

Although daily tooth brushing with fluoridated toothpaste has shown a strong evidence in preventing caries in children and adolescents, but in our present study, the difference in caries increment between fluoridated and nonfluoridated toothpaste group was not quite significant. This may partly be attributed to the fact that many behavioral factors could influence the efficacy of fluoride toothpaste in caries prevention, including the amount of toothpaste applied, technique of brushing, duration of brushing, and the time of day.[20] The response of those children who could not recall the toothpaste they were using, were placed in the nonfluoridated toothpaste group. This might also have affected the overall result. Frequency of tooth brushing is another important aspect regarding oral health care. The frequency of brushing was not found to be a significant factor at 9 months but the significance increased at 18 months which may be explained as new carious lesions take time to occur.

The evidence that sugars play a fundamental role in caries initiation and progression can be overwhelming. In our study, liking for sweets was found to be a nonsignificant factor in terms of children affected with caries at 9 and 18 months. However, the results were highly significant when tooth surfaces were examined for caries increment at 18 months. This might be because of the response bias from the children at the time of filling the questionnaire as they might have had a biased response toward a better answer i.e., they did not like sweets. These results suggest that caries risk is not always directly correlated to fermentable carbohydrate consumption but also to its multifactorial etiology.

Frequency of sugar consumption and caries prevalence has been shown to vary with socioeconomic factors. Although, in our study, no significant difference was found between the children of different SES in terms of caries progression at 9 and 18 months, but when individual tooth surfaces were examined, the data were highly significant. We used school fee as a criterion for SES but SES is a broad measure of individual or family's relative economic and social ranking with regard to the factors such as income, education, and occupation.[21] School fee may not be a true indicator for the actual SES of children. We had used Collapsed ICDAS for caries recording, the examination was carried out in schools under natural light conditions without proper air drying which might have affected the overall caries recording. If we had done the caries recording using proper air drying and light conditions, we could have got more precise results.

As dental caries is a microbiological disease, a prerequisite for caries development is the presence of dental plaque on the teeth, and unless, this biofilm is present caries will not occur, regardless of any other risk factors.[9] The present study showed a strong association between the presence of dental plaque, high indices of caries and active white enamel lesion.


   Conclusion Top


Changing trends and practices in the modern dentistry have evolved toward the “Concept of Prevention.” In a developing country like India, caries risk assessment with the help of Cariogram is one such tool which offers the clinicians a scope for preventing future lesions in a growing child. Practical applicability of this tool because of its affordability, user-friendliness, and economical factor makes it the perfect option for patient motivation and supports the clinician in decision-making for planning preventive strategies for the patients. As per the present study, all the factors selected for informal caries risk assessment except for toothpaste used and frequency of tooth brushing showed statistically significant results over a period of 18 months. A combination of these factors can help in making a simple yet multifactorial caries risk assessment model which can be applied in the daily practice. Further studies with longer follow-ups would be recommended to assess the validity of these methods.

Acknowledgment

The author would like to thank the children and the school authorities for their willingness to participate in the study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Petersen GH, Twetman S. Caries risk assessment in young children and adults a 3 year validation of the Cariogram model. BMC Oral Health 2015;15:17-22.  Back to cited text no. 1
    
2.
Bagramian RA, Garcia-Godoy F, Volpe AR. The global increase in dental caries. A pending public health crisis. Am J Dent 2009;21:3-8.  Back to cited text no. 2
    
3.
Young DA, Featherstone JD, Roth JR. Curing the silent epidemic: Caries management in the 21st century and beyond. J Calif Dent Assoc 2007;35:681-5.  Back to cited text no. 3
    
4.
Twetman S, Fontana M, Featherstone JD. Risk assessment – Can we achieve consensus? Community Dent Oral Epidemiol 2013;41:64-70.  Back to cited text no. 4
    
5.
Dodds MW, Suddick RP. Caries risk assessment for determination of focus and intensity of prevention in a dental school clinic. J Dent Educ 1995;59:945-56.  Back to cited text no. 5
    
6.
Hänsel Petersson G, Twetman S, Bratthall D. Evaluation of a computer program for caries risk assessment in schoolchildren. Caries Res 2002;36:327-40.  Back to cited text no. 6
    
7.
Helderman WH, Mulder J, van'T Hof MA, Truin GJ. Validation of a Swiss method of caries prediction in Dutch children. Community Dent Oral Epidemiol 2001;29:341-5.  Back to cited text no. 7
    
8.
Considerations for Caries-Risk Assessment in an Essential Health Benefits Dental Plan for Children. American Academy of Pediatric Dentistry Pediatric Oral Health Research Policy Center. Technical Report 1; 2012.  Back to cited text no. 8
    
9.
Kidd EA. Caries management. Dent Clin North Am 1999;43:743-64.  Back to cited text no. 9
    
10.
Bratthall D, Hänsel Petersson G. Cariogram – A multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol 2005;33:256-64.  Back to cited text no. 10
    
11.
Holgerson PL, Twetman S, Stecksèn-Blicks C. Validation of an age-modified caries risk assessment program (Cariogram) in preschool children. Acta Odontol Scand 2009;67:106-12.  Back to cited text no. 11
    
12.
Goyal A, Gauba K, Chawla HS, Kaur M, Kapur A. Epidemiology of dental caries in Chandigarh school children and trends over the last 25 years. J Indian Soc Pedod Prev Dent 2007;25:115-8.  Back to cited text no. 12
[PUBMED]  [Full text]  
13.
Fisher J, Glick M, FDI World Dental Federation Science Committee. A new model for caries classification and management: The FDI World Dental Federation caries matrix. J Am Dent Assoc 2012;143:546-51.  Back to cited text no. 13
    
14.
Ismail AI, Lim S, Sohn W. A transition scoring system of caries increment with adjustment of reversals in longitudinal study: Evaluation using primary tooth surface data. Community Dent Oral Epidemiol 2011;39:61-8.  Back to cited text no. 14
    
15.
Mariri BP, Levy SM, Warren JJ, Bergus GR, Marshall TA, Broffitt B. Medically administered antibiotics, dietary habits, fluoride intake and dental caries experience in the primary dentition. Community Dent Oral Epidemiol 2003;31:40-51.  Back to cited text no. 15
    
16.
Petersson GH. Assessing caries risk – Using the Cariogram model. Swed Dent J Suppl 2003;158:1-65.  Back to cited text no. 16
    
17.
Campus G, Cagetti MG, Sacco G, Benedetti G, Strohmenger L, Lingström P. Caries risk profiles in Sardinian schoolchildren using Cariogram. Acta Odontol Scand 2009;67:146-52.  Back to cited text no. 17
    
18.
Zero D, Fontana M, Lennon AM. Clinical applications and outcomes of using indicators of risk in caries management. J Dent Educ 2001;65:1126-32.  Back to cited text no. 18
    
19.
Powell LV. Caries prediction: A review of the literature. Community Dent Oral Epidemiol 1998;26:361-71.  Back to cited text no. 19
    
20.
Davies RM, Ellwood RP, Davies GM. The rational use of fluoride toothpaste. Int J Dent Hyg 2003;1:3-8.  Back to cited text no. 20
    
21.
Burt BA, Eklund SA. Dentitsry, Dental Practice, and the Community. 5th ed. Philadelphia: W.B. Saunders Company; 1999. p. 212-36.  Back to cited text no. 21
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]



 

Top
Print this article  Email this article
 

    

 
  Search
 
  
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Article in PDF (1,403 KB)
    Citation Manager
    Access Statistics
    Reader Comments
    Email Alert *
    Add to My List *
* Registration required (free)  


    Abstract
   Introduction
    Materials and Me...
   Results
   Discussion
   Conclusion
    References
    Article Figures
    Article Tables

 Article Access Statistics
    Viewed63    
    Printed0    
    Emailed0    
    PDF Downloaded14    
    Comments [Add]    

Recommend this journal


Contact us | Sitemap | Advertise | What's New | Copyright and Disclaimer 
  2005 - Journal of Indian Society of Pedodontics and Preventive Dentistry | Published by Wolters Kluwer - Medknow 
Online since 1st May '05