Accuracy of risk assessments in practice


Accuracy ofrisk assessments in practice

A perfectrisk marker would have a sensitivity of 100% and a specificity of 100%, implying noerrors in risk assessment. Consequently, the false-positive and falsenegative rates wouldbe 0%, and positive and negative predictive values would be 100%.Having perfect accuracy means that the predicted high-risk group would consist ofonly true high-risk individuals and that only true low-risk individuals would be includedin the predicted low-risk group. Unfortunately, no such marker is availablefor the assessment of caries risk. A certain proportion of errors have to be accepted.However, there are no generally accepted rules of what the acceptable level of errormight be. 


It has beensuggested that, in a risk model, the sum of sensitivity and specificity be at least 160%before a caries risk marker can be considered a legitimate candidate for targetingindividualized prevention (Kingman, 1990). This is in agreement with an alternativesuggestion that a sensitivity and specificity of 80% would be acceptable forpractical use in the community. Although neither of these suggestions takesinto account thefact that errors related to poor sensitivity do have consequences that are differentfrom those related to poor specificity, both proposals can be used as a startingpoint for evaluating the performance of proposed markers for high caries risk. 


What woulda combined sensitivity and specificity of 160% mean in practice? If both the sensitivityand specificity were 80%, every fifth individual with a true high risk wouldremain undetected in a risk assessment and thus fail to receive the intensified protectionagainst caries that he or she needs. Correspondingly, every fifth individual with a truelow risk would erroneously be included in the high-risk group and receive preventivemeasures to no or little purpose. Thus, even the proposed minimum acceptablelevel of accuracy would result in an uninvitingly high rate of



If theproportion of caries-risk individuals in a population is close to half or more,this clearlyimplies that the occurrence of caries is not low enough to justify the effortand expense ofidentifying key-risk individuals. In such a situation, the preventive efforts should betargeted to the whole population. 


Theproportion of the target population that can be given individual protectionagainst furthercaries development naturally varies from one setting to another. In most cases, risk groupsof a size exceeding 30% seem to be unworkable. In a thorough review by Hausen etal (1994), an effort was made to compare the predictive power of risk markers ina situation where the aim was to select the 30% of the target population with the highestrisk of developing new lesions. For none of the markers aimed at assessingthe risk for coronal caries did the predictive power reach the proposed combinedsensitivity and specificity of 160% (Kingman, 1990). This level was surpassedin one study only, where a combination of several predictors had been used forassessing the risk of root caries (Scheinin et al, 1992).



Thedifficulty of predicting caries is not unexpected. The multifactorialetiological

andmodifying factors of dental caries make it likely that even the mostsophisticated

risk modelswill be of limited value in predicting future caries development very

accurately.Furthermore, even a perfect marker is capable of predicting a person ‘s

futurecaries experience only if the conditions on which the prediction is basedremain

stable. Inmost industrialized countries, where virtually all the prediction studies have

beenconducted, the populations are exposed to a variety of professional prevention

andtreatment regimens as well as self-care, which, if applied selectively, most

probablyreduce the observed power of such studies. The living conditions and oral

healthbehaviors may change over time, thus modifying a person’s caries risk in either

direction.In addition, the rational and ethical consequence of risk prediction in

clinicalpractice is to introduce needs-related measures for caries prevention and

cariescontrol. The optimal outcome therefore should be no new carious lesions. For

thesereasons, it is not likely that, even in the future, caries risk can be assessed

accuratelyby using one single risk marker.

Past cariesexperience (caries prevalence¾the number of decayed, missing, or filled

teeth andsurfaces¾and caries incidence¾the number of new carious teeth and

surfaces ina year) has so far been the most powerful single predictor for future caries

incidence,at least in children and young adults. That is because carious lesions

representthe sum result of all the etiologic and modifying risk factors to which the

individualhas been exposed.

Forexample, in a recent 3-year longitudinal study, Bjarnason and Kohler (1997)

achieved89% sensitivity value in a group of Swedish adolescents by comparing the

prevalenceof non-cavitated enamel caries and DFS at the baseline as predictors.

Together,the sensitivity and specificity values reached 160% or more. High salivary

MS andlactobacilli scores resulted in 71% sensitivity and 75% specificity,

respectively(cutoff level for high caries risk was 5 or more new carious surfaces in 3

years).However, only baseline values of incipient enamel caries were significantly

correlatedto the caries incidence.

The use ofpast caries experience as an indicator of future incidence has justly been

criticizedby the argument that the aim should be to determine the high-risk

individualsbefore there are any signs of past caries experience. In other words, efforts

shouldfocus on primary prevention instead of secondary prevention. In particular this

isimportant in infants and children with erupting permanent teeth. Wendt et al(1994)

found thatthe caries incidence in infants and toddlers aged 1 to 3 years was strongly

correlatedto the plaque scores and oral hygiene regimens even at 1 year of age.

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Articles for theme “caries”:
Prediction of Caries RiskPrinciples of risk predictionSome basic principles have to be followed for successful and cost-effective cariesprediction, caries prevention, and caries control:1. The higher the risk of developing caries for most of the population, the moresignificant the effects of one single preventive measure and the stronger thecorrelations between one single etiologic or modifying risk factor and the risk forcaries development.2. In populations in which only a minority of the people will develop new cariouslesions, it is necessary to use accurate risk predictive measures to select at-riskindividuals and introduce needs-related combinations of caries-preventive measures,in other words, a “high-risk strategy.
Cariogenicity of other bacteriaThere are overwhelming data from experimental and clinical studies in humans showing that S mutans and S sobrinus and lactobacilli are strongly correlated to caries etiology. However, the use of selective substrates in most of these studies may have introduced some bias. For example, Sansone et al (1993) found that plaque samples with and without MS and lactobacilli were equally acidogenic when cultured at low pH and in the presence of excess glucose.
EvidenceLactobacillus counts have been used to predict the incidence of new carious lesions. Crossner (1981) studied a group of children, who had been given dental treatment at baseline so that no open lesions were present at the bacterial sampling. Two subgroups in this material are of special interest: those with very low or very high lactobacillus counts. Very few individuals in the low lactobacillus group developed new carious lesions over a 64-week period. In the high lactobacillus group, many, but not all, developed new lesions.
Cariogenicity of lactobacilliAccording to the specific plaque hypothesis, some strains of lactobacilli are considered to be major caries pathogens along with S mutans and S sobrinus. Lactobacilli are acidogenic and even more aciduric than MS. Mutans streptococci are strongly correlated to the etiology of initial enamel and root surface lesions, because they can adhere to and colonize the tooth surfaces. Lactobacilli are more dependent on retentive sites for heavy colonization: Mutans streptococci are regarded as the pioneers, followed by lactobacilli in the succession toward more cariogenic plaque.
Methods of samplingAs mentioned earlier, the correlation between salivary MS counts and the number of MS-colonized tooth surfaces is relatively good (Lindquist et al, 1989), and simple salivary sampling methods are a more convenient and realistic means of assessing the severity of MS infection than sampling from individual tooth surfaces. Laboratory methods. Saliva is collected, mixed with a proper transport medium, and forwarded to a microbiologic laboratory. After incubation using a selective medium, mutans colonies are counted and the results are expressed as the number of colonyforming units per milliliter of saliva.