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Fulltext - SBU

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Predictor<br />

variables<br />

Validating<br />

criteria<br />

Statistical<br />

methods<br />

Results*<br />

Sensitivity and<br />

specificity<br />

Study<br />

quality and<br />

relevance<br />

Comments<br />

A total of 11: Age,<br />

race, sex, socioeconomy,<br />

sound<br />

surfaces, eruption<br />

status, DMFS, referral<br />

score, fluoride<br />

in drinking water,<br />

defs molar surfaces,<br />

Grainger index<br />

(general level of<br />

tooth decay scores<br />

0–5)<br />

DMFS<br />

increment<br />

(∆DMFS) or<br />

prevalence<br />

(DMFS) level<br />

not stated<br />

Proportion<br />

high risk:<br />

25%<br />

Correlation,<br />

discriminant<br />

analysis<br />

Log regression<br />

Se, Sp,<br />

PPV, NPV<br />

DMFS better than<br />

∆DMFS as outcome.<br />

DMFS<br />

Grade 1<br />

Se: 48%; Sp: 82%<br />

Grade 5<br />

Se: 52%; Sp: 84%<br />

Prediction model<br />

better for non F<br />

than for F<br />

Low<br />

Post hoc data<br />

modelling<br />

dmfs at age 9<br />

Levels: >8, >14<br />

and >17<br />

DMFS at<br />

12–17 years<br />

(mean 15.5):<br />

>5, >8, >15<br />

DMFS<br />

Proportion<br />

high risk: 15,<br />

25 and 50%<br />

Se, Sp<br />

Best for >14 dmfs<br />

and DMFS >15:<br />

Se about 42%;<br />

Sp about 85%<br />

Low<br />

Large range<br />

of followup<br />

years.<br />

Confounder:<br />

improvement<br />

in dental<br />

health<br />

The table continues on the next page<br />

KAPITEL 5 • Riskbedömning<br />

253

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