Biomaterial Database

Fluoride varnishes (Duraphat): a meta-analysis. 1994

U Helfenstein, and M Steiner

Department of Biostatistics, University of Zurich, Switzerland.

In the present article we analyze a series of studies designed to detect the caries preventive effect of Duraphat by means of meta-analysis. Meta-analysis is a collection of statistical methods designed to investigate and to summarize a series of investigations. It may be a valuable tool to complement traditional narrative reviews. During the last years meta-analysis has attracted increasing interest in sociology, psychology and medicine. In order to find previous studies concerned with the clinical effects of Duraphat we applied a systematic literature search. Papers were included independent of results when they fulfilled a checklist of well defined methodological selection criteria. In order to aggregate the results of the Duraphat-studies we used different complementary statistical approaches: Firstly, the so-called file drawer problem is considered. This may help to get a better insight into the problem of underreporting non-significant results or publication bias. It was found to be very unlikely that underreporting of non-significant results could reverse the conclusion into an overall null-result. After that, the inhomogeneity between studies is investigated. The overall variation of caries reduction R is separated into two components: A between study component of variance and a variance pertaining to the individual studies (random effects model). It was found that the overall variation is dominated by the between studies variation and not by the sampling variation. Due to the pronounced variation between studies the confidence interval of the overall effect size (R = 0.38) is quite large (95%-Cl: 0.19-0.57).(ABSTRACT TRUNCATED AT 250 WORDS)

UI	MeSH Term	Description	Entries
D012044	Regression Analysis	Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.	Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D012107	Research Design	A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly.	Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D003731	Dental Caries	Localized destruction of the tooth surface initiated by decalcification of the enamel followed by enzymatic lysis of organic structures and leading to cavity formation. If left unchecked, the cavity may penetrate the enamel and dentin and reach the pulp.	Caries, Dental,Carious Lesions,Dental Cavities,Dental Cavity,Dental Decay,Dental White Spots,Carious Dentin,Decay, Dental,Dental White Spot,White Spot, Dental,White Spots, Dental,Carious Dentins,Carious Lesion,Cavities, Dental,Cavity, Dental,Dentin, Carious,Dentins, Carious,Lesion, Carious,Lesions, Carious,Spot, Dental White,Spots, Dental White
D004245	DMF Index	"Decayed, missing and filled teeth," a routinely used statistical concept in dentistry.	Decayed, Missing, and Filled Teeth,DMF Indexes,DMF Indexe,DMF Indices,Index, DMF,Indexe, DMF,Indexes, DMF,Indices, DMF
D005460	Fluorides, Topical	Fluorides, usually in pastes or gels, used for topical application to reduce the incidence of DENTAL CARIES.	Fluoride Varnishes,Topical Fluorides,Varnishes, Fluoride
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012969	Sodium Fluoride	A source of inorganic fluoride which is used topically to prevent dental caries.	Fluoristat,Ossin,Zymafluor,Fluoride, Sodium,Fluorides, Sodium,Fluoristats,Ossins,Sodium Fluorides,Zymafluors
D013997	Time Factors	Elements of limited time intervals, contributing to particular results or situations.	Time Series,Factor, Time,Time Factor
D015982	Bias	Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.	Aggregation Bias,Bias, Aggregation,Bias, Ecological,Bias, Statistical,Bias, Systematic,Ecological Bias,Outcome Measurement Errors,Statistical Bias,Systematic Bias,Bias, Epidemiologic,Biases,Biases, Ecological,Biases, Statistical,Ecological Biases,Ecological Fallacies,Ecological Fallacy,Epidemiologic Biases,Experimental Bias,Fallacies, Ecological,Fallacy, Ecological,Scientific Bias,Statistical Biases,Truncation Bias,Truncation Biases,Bias, Experimental,Bias, Scientific,Bias, Truncation,Biase, Epidemiologic,Biases, Epidemiologic,Biases, Truncation,Epidemiologic Biase,Error, Outcome Measurement,Errors, Outcome Measurement,Outcome Measurement Error
D016001	Confidence Intervals	A range of values for a variable of interest, e.g., a rate, constructed so that this range has a specified probability of including the true value of the variable.	Confidence Interval,Interval, Confidence,Intervals, Confidence