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PubMed2006

A recessive Mendelian model to predict carrier probabilities of DFNB1 for nonsyndromic deafness.

Mutations in the DFNB1 locus, where two connexin genes are located (GJB2 and GJB6), account for half of congenital cases of nonsyndromic autosomal recessive deafness. Because of the high frequency of DFNB1 gene mutations and the availability of genetic diagnostic tests involving these genes, they are the best candidates to develop a risk prediction model of being hearing impaired. People undergoing genetic counseling are normally interested in knowing the probability of having a hearing impaired child given his/her family history. To address this, a Mendelian model that predicts the probability of being a carrier of DFNB1 mutations, using family history of deafness, has been developed. This probability will be useful as additional information to decide whether or not a genetic test should be performed. This model incorporates Mendelian mode of inheritance, the age of onset of the disease, and the current age of hearing family members. The carrier probabilities are obtained using Bayes' theorem, in which mutation prevalence is used as the prior distribution. We have validated our model by using information from 305 families affected with congenital or progressive nonsyndromic deafness, in which genetic analysis of GJB2 and GJB6 had already been performed. This model works well, especially in homozygous carriers, showing a high discriminative power. This indicates that our proposed model can be useful in the context of clinical counseling of autosomal recessive disorders.

Adult↗
PubMed1985

Instruction in medical decision making. A report of two surveys.

Results of two surveys (D and E) that assessed the current structure and status of instruction in medical decision making are reported. Both samples (Survey D, N = 80; Survey E, N = 92) consisted of members of the Society for Medical Decision Making. A consensus was obtained on topics considered important for teaching an introduction to clinical decision analysis to medical professionals. These topics were Bayes' theorem, decision trees, 2 X 2 tables, test sensitivity and specificity, utility, and ROC analysis. There was little agreement on course structure, level, or the preferred method for teaching decision analysis within medical settings. It was concluded that medical educators are in the process of constructing a knowledge base in decision-analytic techniques within academic medicine. It will soon be time to consider the place of more advanced topics within the continuum of medical education.

Bayes Theorem↗
PubMed1981

Initial findings in the computer-aided diagnosis of cerebral tumours using CT scan results.

This paper describes the initial findings of computer-assisted diagnosis of cerebral tumours using Bayes' Theorem and CT scans. For various sets of signs, tables of accuracy and reliability have been constructed, and a computer versus radiologist analysis for three types of tumour has been made. Based only on the results of CT scans, the computer has produced diagnoses relatively quickly, and overall these are of reasonable accuracy when compared with the radiologists' reports. The worst results occurred in the prediction of meningiomas, the reasons for which will be examined in subsequent work.

Bayes Theorem↗
PubMed1991

Multivariable prediction model for the need for surgery in horses with colic.

A survey of 1,965 equine colic cases was conducted from August 1985 to July 1986 at 10 equine referral centers located throughout the United States. The purpose of this study was to develop and validate a multivariable model for the need for surgery. Two-thirds of the cases were randomly selected for model development (1,336), whereas the remaining cases (629) were used only for subsequent validation of the model. If a lesion requiring surgical correction was found at either surgery or necropsy, the case for the horse was classified as surgical, otherwise the case was classified as medical. Only variables that were significant (P less than 0.05) in an initial bivariable screening procedure were considered in the model development. Because of the large number of missing values in the data set, only variables for which there were less than 400 missing values were considered in the multivariable analysis. A multivariable logistic regression model was constructed by use of a stepwise algorithm. The model used 640 cases and included variables: rectal findings, signs of abdominal pain, peripheral pulse strength, and abdominal sounds. The likelihood ratio for surgery was calculated for each horse in the validation data set, using the logistic regression equation. Using Bayes theorem, the posttest probability was calculated, using the likelihood ratio as the test odds and the prevalence of surgery cases (at each institution) as an estimate of the pretest odds. A Hosmer-Lemeshow goodness-of-fit chi 2 statistic indicated that the model fit the validation data set poorly, as demonstrated by the large chi 2 value of 26.7 (P less than 0.001).(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMedDate not supplied

Assessing disease prevalence from inaccurate test results: teaching an old dog new tricks.

Estimates of disease prevalence are needed for the interpretation of test results as well as for public health decisions. Assessing prevalence may be difficult if a definitive test is unavailable, impractical, or expensive. A formula derived from Bayes' theorem can calculate the prevalence of disease in a population by incorporating test results with a knowledge of the sensitivity and specificity of a test. This paper reviews this formula and provides examples evaluating the prevalence of HIV disease, the usefulness of ventilation-perfusion scans in diagnosing pulmonary embolism, and settings where screening tests should not be applied. These examples demonstrate that precise yet inexpensive estimates of disease prevalence are possible by enhancing the usefulness of an inaccurate test.

Bayes Theorem↗
PubMed1982

Diagnostic value of HLA-B27 testing ankylosing spondylitis and Reiter's syndrome.

Typing for histocompatibility antigen (HLA)-B27 has been suggested as a clinically valuable diagnostic test for ankylosing spondylitis and Reiter's syndrome, although some decry its use for this purpose. Diagnoses can be made in most patients with these diseases on the basis of the history, physical examination, and roentgenographic findings. The B27 test cannot be used to screen an asymptomatic population to detect these diseases and should not be thought of as a routine diagnostic test. We present probability graphs derived from Bayes' theorem, which show that for certain patients the B27 test, when used properly, is of clinical value as an aid to diagnosis. Proper application of the B27 test in clinical medicine is discussed. The test result does not absolutely confirm or exclude the presence of these diseases; it merely provides a probability statement on their existence in the patient. The test is therefore most useful to physicians who understand the use of probability reasoning in clinical decision making.

Adult↗
PubMed1993

Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. Part II. Application.

Four board-certified radiologists estimated the probability of malignancy in 66 cases of solitary pulmonary nodules. Two other radiologists evaluated the same nodules according to various radiographic and clinical findings. These findings were then used to estimate the probability of malignancy by using previously derived likelihood ratios and the Bayes theorem. The readers using Bayesian analysis performed significantly better than the expert readers (P < .05) when individual radiographs were considered and when all radiologic studies were combined. In addition, the readers using Bayesian analysis misclassified fewer malignant nodules as benign (mean, 6.5) than did the expert readers (mean, 6.5) than did the expert readers (mean, 16.5). The authors conclude that Bayesian analysis may be a useful aid in the evaluation of solitary pulmonary nodules.

Adult↗
PubMed1993

A statistical evaluation of mammography: crucial questions for health systems.

This article reviews data on incidence and mortality rates from breast cancer and provides the results from applications of Bayes' Theorem and a test of homogeneity to investigate the efficacy of mammographic screening for breast cancer. The results of our analyses indicate that the accuracy and effectiveness of mammographic screening for breast cancer are debatable. Consequently, we identify crucial unanswered questions for health systems about the heavy reliance on mammography. We recount the current recommendations, standards of practice, and utilization of mammography for breast cancer screening. Finally, we question the language used to describe the conclusions of these studies.

Adult↗
PubMed1987

[Complex system of differentiated prediction of strokes].

On the basis of the data on 2287 patients with cerebral strokes (CS) and 800 individuals without this disease, and using discriminant and probability methods, the authors have identified 158 supposed risk factors (RF) of CS development. They have also established the specificity of RFs which depends on the nature of CS, as well as ascertained the dependence of informative value of these factors on the size of samples and the degree of percentage reflection by the main demographic indicators of the studied population. RFs are classified as controllable and uncontrollable. The authors have selected 50 risk factors with 2-5 gradations ranging from the normal to the maximal pathology and reflecting various aspects of CS etiopathogenesis. This work has resulted in the creating of a mathematical model of SC development. On the basis of this model and using the Bayes' theorem the authors have developed a system intended for predicting CS and its nature by 50, 25, and 15 RFs which is implemented by means of universal, micro- or minicomputers and tables which make it possible to predict with a 88.8% accuracy the development of CS as well as to determine the most rational individual prophylaxis of threatening stroke which is achieved through an accurate balancing in the system of controllable and uncontrollable RFs.

Adult↗
PubMed2002

Do juries meet our expectations?

Surveys of public opinion indicate that people have high expectations for juries. When it comes to serious crimes, most people want errors of convicting the innocent (false positives) or acquitting the guilty (false negatives) to fall well below 10%. Using expected utility theory, Bayes' Theorem, signal detection theory, and empirical evidence from detection studies of medical decision making, eyewitness testimony, and weather forecasting, we argue that the frequency of mistakes probably far exceeds these "tolerable" levels. We are not arguing against the use of juries. Rather, we point out that a closer look at jury decisions reveals a serious gap between what we expect from juries and what probably occurs. When deciding issues of guilt and/or punishing convicted criminals, we as a society should recognize and acknowledge the abundance of error.

Bayes Theorem↗
PubMed2005

[A method for measuring the contribution of individual factor to disease caused by multiple risk factors].

OBJECTIVE: To evaluate the contribution of individual risk factor to a disease on someone with several risk factors. METHODS: A method based on epidemiological theory and Bayes' theorem was established to measure the contribution of individual risk factor, using the relative risk (RR) or odds ratio (OR) value obtained from population-based cohort studies or meta-analysis. RESULTS: The proportional contribution for individual risk factor to disease in one person can be measured or estimated. CONCLUSION: This method can be applied to risk assessment in a patient with more than one risk factor, and the results also contribute to our etiological study and clinical decision-making strategy.

Bayes Theorem↗
PubMed1984

Weighted criteria for the diagnosis of systemic lupus erythematosus.

The preliminary American Rheumatism Association (ARA) criteria for classification of systemic lupus erythematosus (SLE) were evaluated for sensitivity and specificity in 87 patients with SLE and 73 without SLE from a rheumatology population. Using these data, Bayes' theorem was employed to weight the criteria so that a scoring system could be developed, allowing more accurate use of the criteria in diagnosis. Combinations of serologic test results were evaluated in a similar manner. Comparison of weighted scores with criteria counts showed greater sensitivity and specificity of the former whether the 1971 or modified 1982 ARA criteria were used. Weighted criteria may be more useful in clearly defining patient populations for studies of SLE.

Antibodies, Antinuclear↗
PubMedDate not supplied

Evaluation and presentation of forensic DNA evidence in European laboratories.

The first part of this article describes Bayes' theorem and its practical application to scientific evidence. Secondly, statements proposed by European DNA laboratories are presented, analysed and commented upon. Finally, the authors reiterate their proposal of adopting a likelihood ratio framework justified by the usefulness of the approach in practical context of DNA cases. Note that this framework underlines the main questions the experts have to answer at trial: to what degree does the evidence support the prosecutor's hypothesis? and to what degree does the evidence support the defence's hypothesis?

Bayes Theorem↗
PubMed1993

Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. Part I. Theory.

Only two radiographic findings allow reliable distinction of benign from malignant solitary pulmonary nodules. Intuitively, it is clear that other radiographic and clinical findings should also be important in making this distinction. Subjectively incorporating these other findings into the decision of whether a nodule is benign or malignant is difficult. Likelihood ratios, which indicate the degree of malignancy or benignity represented by a test result or clinical finding, can be combined by means of the Bayes theorem to quantitate the probability of malignancy of a given nodule. From a literature survey, likelihood ratios were derived for six radiographic and four clinical characteristics associated with solitary pulmonary nodules. There were a total of 15 malignant and 19 benign findings, the most important of which were radiographic characteristics. For malignant nodules, the most important radiographic characteristics were thickness of the cavity wall spicular edge, and diameter of over 3 cm. For benign nodules, the most important radiographic characteristics were benign growth rate and a benign pattern of calcification.

Adult↗
PubMed2005

Inference of protein function from protein structure.

Structural genomics has brought us three-dimensional structures of proteins with unknown functions. To shed light on such structures, we have developed ProKnow (http://www.doe-mbi.ucla.edu/Services/ProKnow/), which annotates proteins with Gene Ontology functional terms. The method extracts features from the protein such as 3D fold, sequence, motif, and functional linkages and relates them to function via the ProKnow knowledgebase of features, which links features to annotated functions via annotation profiles. Bayes' theorem is used to compute weights of the functions assigned, using likelihoods based on the extracted features. The description level of the assigned function is quantified by the ontology depth (from 1 = general to 9 = specific). Jackknife tests show approximately 89% correct assignments at ontology depth 1 and 40% at depth 9, with 93% coverage of 1507 distinct folded proteins. Overall, about 70% of the assignments were inferred correctly. This level of performance suggests that ProKnow is a useful resource in functional assessments of novel proteins.

Amino Acid Motifs↗
PubMed2003

[A critical review of the pragmatic clinical trial].

Schwartz and Lellouch proposed in 1967 to differentiate between pragmatic and explanatory clinical trials. The pragmatic approach has been understood in different ways and has also been the object of some criticism. Yet different authors have asked to perform pragmatic clinical trials, especially in issues requiring a therapeutical decision. In order to clarify the present situation of the pragmatic trial, a bibliographic review has been performed. Between 1976 and 2002, 95 original articles on clinical trials conducted following a pragmatic design have been found. Only four followed strictly the approach developed by Schwartz et al. In a pragmatic clinical trial, it is usually not possible to blind the interventions and for this reason randomization is imperfect. This limitation casts doubts about the validity of the frequentistic methods in the intention-to-treat evaluation of the results of a pragmatic trial. This experimental approach demands an evaluation according to the decision-making theory. Following the Bayes theorem, the credibility and the previous probability of a hypothesis conditions its posterior probability. It has been agreed that Bayesian statistics is a suitable instrument for the evaluation of a pragmatic clinical trial, but the lack of adequate informatics' programs has limited seriously its application. Recently,some new programs (WinBUGS, TreeAge) have been developed and applied to the decision analysis in some primary care therapeutic questions. It seems possible to predict that, thanks to the new informatics'programs on Bayesian statistics, the pragmatic clinical trial will experience, in the short term, an important revival.

Bayes Theorem↗
PubMed1984

Evaluation problems of a long-term study on evolving pulmonary arterial hypertension in chronic non specific lung disease.

After having collected a sufficient number of standardized data checked for reliability from patients with chronic non specific lung disease, the following subgroups of pulmonary arterial mean pressure were defined: A = PAP less than 2.7 kPa [= 20 mmHg]; B = 2.7 less than PAP less than 4 kPa; C = PAP greater than 4 kPa [= 30 mmHg]. Within these subgroups a diagnostic classification was also carried out: chronic obstructive lung disease, thrombo-embolic lung disease, diffuse interstitial lung disease. The aims of data processing were: clustering correctly individual cases in one of the I-II-III subgroups based on non-invasive variables only; To define equations predictive of quantitative values of pulmonary arterial mean pressure from non-invasive data; To find regularity of evolution of elevated pulmonary arterial mean pressure in chronic non specific lung disease and detect risk factors and/or beneficial interventions if such exist at all. Two different statistical methods were applied: conditional probability (Bayes theorem) and discriminant analysis. The predictive power of each depends mainly on the seriousness of signs and symptoms denoted by the medical user. Three probability-functions have been defined between severity of single variables and their specificity, sensitivity and probability of pulmonary hypertension. By application of these functions the user can select different quantitative values of variables which determine the proportion of false/true, positive/negative cases. After having chosen the desired values of these proportions, multivariate equations are defined by stepwise regression analysis optimized for predictive power.(ABSTRACT TRUNCATED AT 250 WORDS)

Bayes Theorem↗
PubMed1998

Making the diagnosis of osteomyelitis. The role of prevalence.

Clinicians may have poor sensitivity in determining whether a given diabetic patient with a foot ulcer has osteomyelitis. Thus many turn to diagnostic tests. The literature was reviewed and data on the sensitivity and specificity of five commonly used diagnostic tests were compiled. Using Bayes' theorem, the authors' analysis suggests that pretest probability may be more important in the decision-making process than individual test characteristics. Also, a positive probe-to-bone test is as predictive of osteomyelitis as the other four tests. A negative magnetic resonance imaging test most likely rules out osteomyelitis. Interpretation of any test result is greatly influenced by the pretest probability of disease. Future work needs to focus on aiding the clinician in determining the patient's probability of disease prior to testing in order to optimize patient care.

Bayes Theorem↗