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Per Hyltoft Petersen

Publications and source records attributed to Per Hyltoft Petersen.

At least 19 recordsLinked to original sources
PubMed2004

Partitioning of nongaussian-distributed biochemical reference data into subgroups.

BACKGROUND: The aim of this study was to develop new methods for partitioning biochemical reference data, covering in particular nongaussian distributions. METHODS: We recently proposed partitioning criteria for gaussian distributions. These criteria relate to proportions of the subgroups outside each of the reference limits of the combined distribution (proportion criteria) and to distances between the subgroup distributions as correlates of these proportions (distance criteria). However, distance criteria do not seem to be ideal for nongaussian distributions because a generally valid relationship between proportions and distances cannot be established for these. RESULTS: Proportion criteria appear preferable to distance criteria for two additional reasons: (a) The prevalences of the subgroup populations may have a considerable effect on stratification, but these are hard to account for by using distance criteria. Two methods to handle prevalences are described, the root method and the multiplication method. (b) Tied reference values, another complication of the partitioning problem, could also be hard to take care of using distance criteria. Some solutions to the problems caused by tied reference values are suggested. CONCLUSIONS: Partitioning of biochemical reference data should preferably be based on proportion criteria; this is particularly true for nongaussian distributions. Both of the described complications of the partitioning problem, the prevalences of the subgroups and tied reference values, are hard to deal with using distance criteria, but the proposed methods make it possible to account for them when proportion criteria are applied.

Clinical Laboratory Techniques↗
PubMed2004

Reference change values and power functions.

Repeated samplings and measurements in the monitoring of patients to look for changes are common clinical problems. The "reference change value", calculated as zp x [2 x (CVI2 + CVA2)](1/2), where zp is the z-statistic and CVI and CVA are within-subject and analytical coefficients of variation, respectively, has been used to detect whether a measured difference between measurements is statistically significant. However, a reference change value only detects the probability of false-positives (type I error), and for this reason, a model to calculate the risk of missing significant changes in serial results from individuals (probability of false-negatives) is investigated in this work by means of power functions. Therefore, when an analyte is being monitored in a patient, power functions estimate the probability of detecting a defined real change by measuring the difference. Thus, when a measured difference is the same as the calculated reference change value, then it will be detected in only 50% of situations.

Analysis of Variance↗
PubMed2004

Graphical interpretation of confidence curves in rankit plots.

A well-known transformation from the bell-shaped Gaussian (normal) curve to a straight line in the rankit plot is investigated, and a tool for evaluation of the distribution of reference groups is presented. It is based on the confidence intervals for percentiles of the calculated Gaussian distribution and the percentage of cumulative points exceeding these limits. The process is to rank the reference values and plot the cumulative frequency points in a rankit plot with a logarithmic (In=log(e)) transformed abscissa. If the distribution is close to In-Gaussian the cumulative frequency points will fit to the straight line describing the calculated In-Gaussian distribution. The quality of the fit is evaluated by adding confidence intervals (CI) to each point on the line and calculating the percentage of points outside the hyperbola-like CI-curves. The assumption was that the 95% confidence curves for percentiles would show 5% of points outside these limits. However, computer simulations disclosed that approximate 10% of the series would have 5% or more points outside the limits. This is a conservative validation, which is more demanding than the Kolmogorov-Smirnov test. The graphical presentation, however, makes it easy to disclose deviations from In-Gaussianity, and to make other interpretations of the distributions, e.g., comparison to non-Gaussian distributions in the same plot, where the cumulative frequency percentage can be read from the ordinate. A long list of examples of In-Gaussian distributions of subgroups of reference values from healthy individuals is presented. In addition, distributions of values from well-defined diseased individuals may show up as In-Gaussian. It is evident from the examples that the rankit transformation and simple graphical evaluation for non-Gaussianity is a useful tool for the description of sub-groups.

Blood Chemical Analysis↗
PubMed2004

Should we maintain the 95 percent reference intervals in the era of wellness testing? A concept paper.

The reference interval is probably the most widely used decision-making tool in clinical practice, with a modern use aiming at identifying wellness during health check and screening. Its use as a diagnostic tool is much less recognised and may be obsolete. The present study investigates the consequences of the new practice for the interpretation of prospective value, negative vs. positive, the probability of confirming wellness, and number of false results based on selected strategy for reference interval establishment. Calculations assumed normalised Gaussian-distributed reference intervals with analytical variation set to zero and absolute accuracy. Also assumed is the independency of tests. Probability for no values outside reference intervals in healthy subjects was calculated from the formula p(no) outside=(1 - p(single)) and according to the formula for repeated testing: p(one) outside =n x p(single) (1 - p(single))n-1 etc. Here n is the number of tests performed and p(single) is the probability of one result outside reference limits with the general formula p(i) outside n-i=k x p(single)i (1- p(single))n-i, with k being the binominal coefficient and i the number outside the reference intervals. Use of the 99.9 centile for health checks will increase the probability for no false from 60% to 99% for 10 tests, and from 46% to 98% for 15 tests. The probability for one false-positive result in 10 tests in a panel can be reduced from 32% to 1% if the 99.9% centile is substituted for the 95% centile. For two in 10 tests, the probability can be reduced from 8% to below 0.1%. In both cases, selection of the 99.9% centile improves the diagnostic accuracy. Reference intervals are needed as a "true" negative reference for absence of disease, and should cover the 99.9% centile of the reference distribution of an analyte to avoid false positives. For this new use, it is critical that reference persons are absolutely normal without clinical, genetic and biochemical signs of the condition being investigated. However, reference intervals cannot substitute clinical decision limits for diagnosis and medical intervention.

Clinical Laboratory Techniques↗
PubMed2004

Reference intervals for serum proteins: similarities and differences between adult Caucasian and Asian Indian males in Yorkshire, UK.

The aim of this study was to investigate similarities and differences in the distribution of serum concentrations of nine proteins in two racial groups (Caucasian and Asian Indian) of adult males living in the same geographical area (Leeds, Bradford, UK) for at least two generations. This is part of a larger study to determine the need for separating reference intervals for racial and ethnic groups worldwide. The distributions of concentrations for all proteins evaluated in the Indians fit In-Gaussian distributions, indicating probable homogeneity. However, for the Caucasians, the distributions for alpha1-antitrypsin and possibly haptoglobin were not In-Gaussian. In the former case, this is undoubtedly due to the number of Caucasians with lower-concentration phenotypes (Pi MS and MZ). Although haptoglobin differences may be due to genetic variants as well, this is not a complete explanation. In addition, the Indians have lower serum concentrations of orosomucoid (alpha1-acid glycoprotein), as has been reported by others. It is apparent that for some proteins, including alpha1-antitrypsin, orosomucoid, and possibly haptoglobin, the populations show differences that require the use of separate reference intervals. In addition to genetic influences, environmental differences cannot be ruled out as partial causes for some of the differences noted.

Adult↗
PubMed2004

Creation of a low-risk reference group and reference interval of fasting venous plasma glucose.

Reference intervals are recommended for naturally occurring quantities and required in the evaluation of new components in order to provide clinically useful information. The aim of the present study is to present a method for selecting reference individuals for the determination of fasting venous plasma glucose (f-vPG) reference intervals and ways to determine if disease groups can share reference intervals with an ideal reference population. Reference subjects were randomly selected, eligibility was judged according to predetermined inclusion and exclusion criteria. Using the literature we selected risk indicators for diabetes mellitus (DM) and used these indicators to rule out high-risk individuals in order to obtain a reference distribution of f-vPG determined using individuals with low risk of DM. The distribution of f-vPG in the high-risk individuals was compared with that determined for the low-risk group. We then estimated the ability of the high-risk individuals to share the reference interval of the low-risk individuals, and calculated the fraction that was outside this interval. Distributions were also investigated for linearity in the cumulated frequency rankit distribution of In-values. The allowable difference between two reference limits could not exceed 0.375 times the population biological variation. Most risk indicators were powerful predictors of high f-vPG values. Subgroups with these risk indicators should not be included in the homogeneous In-normally distributed reference distribution. Distributions of f-vPG concentrations in individuals with risk factors were not homogeneous and varying percentages of individuals were outside the reference distribution, having f-vPG greater than 7.0 mmol/l. We conclude that randomisation is only useful to recruit candidate reference subjects. To rule out subjects according to clinical risk factors for diabetes, it is necessary to identify a reference population with low risk of exhibiting increased f-vPG concentrations. This method may be used to validate a reference interval for a particular analyte with respect to an investigated disease, and to stratify risk factors of importance.

Blood Glucose↗
PubMed2004

Establishment of a serum thyroid stimulating hormone (TSH) reference interval in healthy adults. The importance of environmental factors, including thyroid antibodies.

It has previously been shown that thyroid antibodies affect thyroid stimulating hormone (TSH) concentrations in men and women and that TSH levels are predictive of future thyroid disease. We investigated the validity of the National Academy of Clinical Biochemistry (NACB) guidelines regarding the TSH reference interval by studying 1512 individuals. Two hundred and fifty had at least one thyroid antibody, 121 were taking medications other than estrogens and occasional analgesics, and 105 reported a family history of thyroid disease. Serum TSH, thyroid peroxidase antibodies (TPOab) and thyroglobulin antibodies (Tgab) were determined on AutoDELFIA and TSHRab by a radioreceptor assay (RRA) from Brahms Diagnostica. For individuals without thyroid antibodies and other risk factors, no effect of age and gender was seen for serum TSH. Neither medication nor the presence of Tgab alone had any influence on serum TSH. TPOab alone or in combination with Tgab were associated with an increased serum TSH level. The 'cumulative percentage distributions' of subgroups, as well as the combined population, was In-Gaussian distributed. The central 95% of the population was within the 95% CI in rankit-plots. Consequently, a common reference interval for serum TSH of 0.58-4.07 mlU/l for all adults between 17 and 66 years of age was established. This reference interval is much higher than expected from the NACB-guidelines.

Adolescent↗
PubMed2004

The clinical impact of screening for gestational diabetes.

Gestational diabetes mellitus (GDM) is defined as carbohydrate intolerance during pregnancy. In Denmark the health service offers selective screening for GDM, i.e., admission to an oral glucose tolerance test (OGTT) after pre-screening with interview for clinical risk factors for GDM, two capillary fasting blood glucose (cFBG) measurements and a urine test for glucosuria. The aim of the present study was to investigate the power of the pre-screening to identify GDM and the screening to predict adverse clinical outcome. A retrospective investigation of pregnant women undergoing screening during 1998 at Vejle County Hospital, Denmark was undertaken. The two most frequent pre-screening criteria for OGTT were body-mass index (BMI) > or = 27 kg/m2 and age > or = 35 years. The highest odds ratio (OR) of 9.07 (95% CI: 2.60 to 63.70) for GDM had glucosuria and the lowest (zero) had cFBG. The frequency of complicated delivery was similar in GDM (58%) compared to non-GDM (56%). The best predictor of complicated delivery was a BMI with OR = 1.50 (95% CI: 0.87 to 2.60) for BMI > or = 27 kg/m2 vs. < 27 kg/m2. The best predictor of adverse neonatal outcome was a capillary blood glucose 120 min after glucose load (cBG(120 min)) > or = 9.0 mmol/l (OR = 3.18, 95% CI: 1.14 to 8.89). The intermediary endpoint GDM was not superior for predicting adverse maternal and neonatal outcome. The cumulative probability distribution of cBG(120 min) after a 75 g glucose load was not homogeneously distributed in groups stratified according to maternal and foetal outcome. A changed slope was seen after cBG(120 min) 9.0 mmol/l. Screening cFBG of 4.1 mmol/l was unable to predict GDM and adverse outcome. Glucosuria was too rare to be effective as a screening tool. Pre-screening did not identify GDM. The best predictor of complicated delivery was a high BMI. The best predictor of foetal adverse outcome was cBG120 miin > or = 9.0 mmol/l after a 75 g glucose load. Identical fraction complications were present in GDM and non-GDM. A refinement of the screening procedure is highly needed, and this has been initiated in Denmark.

Adult↗
PubMed2003

Fasting and post-glucose load--reference limits for peripheral venous plasma glucose concentration in pregnant women.

Recently both the American Diabetes Organization (ADA) and World Health Organization (WHO) have revised the diagnostic recommendations for gestational diabetes mellitus (GDM), however, they did not not reach agreement on the criteria for diagnosis, the referral criteria for the confirmatory oral glucose tolerance test (OGTT), its standardization, and diagnostic cut-off point. The aims of this study were to investigate if the fasting venous plasma glucose mmol/l (f-vPG) and the 2-hour venous plasma glucose mmol/l (2h-vPG) after a WHO standardized 75 g oral glucose tolerance test (OGTT) in a non-risk group of pregnant women during first and third trimester of pregnancy deviated from that of risk groups, to establish a reference interval for f-vPG and 2h-vPG, and to investigate the predictive role of f-vPG for the 2h-vPG glucose concentration. This is a population-based case-control study where a consecutive number of pregnant women were invited to screening irrespective of their risk factors for GDM. All women filled in a questionnaire of the Danish national screening program on risk factors and had f-vPG and the 2h-vPG measured. By ruling out women with GDM and risk factors, we isolated a non-risk reference class. The In f-vPG parametric 97.5 centile was less than 5% higher during week 32 of pregnancy than during week 20, and therefore these groups were combined. The f-vPG 95% reference interval was from 4.01 mmol/l (95% CI: 3.96 to 4.07 mmol/l) to 5.26 mmol/l (95% CI: 5.19 to 5.34 mmol/l). "The true upper normal limit", the 99.9 centile, was 5.69 mmol/l (95% CI: 5.59 to 5.80 mmol/l). The f-vPG was 0.6 mmol/l lower over the whole range in pregnant women compared to age-matched non-pregnant women. The distribution of 2h-vPG concentrations at week 20 was non-Gaussian and therefore considered non-homogeneous, while it was Gaussian distributed and homogeneous at week 32. The 2h-vPG 95% reference interval of the combined weeks was from 2.80 mmol/l (95% CI: 2.56 to 3.04 mmol/l) to 7.58 mmol/l (95% CI: 7.34 to 7.82 mmol/l), and the upper limit of normal (99.9 centile) was 8.96 mmol/l (95% CI: 8.63 to 9.29 mmol/l). Distributions of f-vPG and 2h-vPG were distinct in our defined risk classes. In individual cases, no systematic correlation was found between the f-vPG concentration at week 20 and week 32. The f-vPG concentrations at any of the weeks did not predict the 2h-vPG level and no single clinical risk factor was decisive for the presence of GDM.

Blood Glucose↗
PubMed2003

The effect of the new ADA and WHO guidelines on the number of diagnosed cases of diabetes mellitus.

In the new lowered diagnostic discriminator for diabetes mellitus (DM) from the American Diabetes Association (ADA), fasting peripheral venous plasma glucose (f-vPG) of 7.0 mmol/l is identical to the 99.9 centile of f-vPG (7.05 mmol/l, 95%CI: 6.91-7.20 mmol/l) in a low-risk reference population. We investigated its diagnostic concordance with other diagnostic discriminators. As no index test is available for DM we used the ADA discriminator as gold standard. We isolated a low-risk reference population (n = 424) from a randomised general population (n = 726) by ruling out of all cases with clinical and biochemical risk indicators for DM. We based our analysis on measurements traceable to primary standard concentration, a bias of < 1.5% and CV% < 2.5. The distribution of the fasting capillary whole blood glucose (f-CBG; mmol/l) in the reference population was in Gaussian with the 99.9 centile of 6.62 mmol/l (95% CI 6.47-6.77 mmol/l) and the 97.5 centile of 5.92 mmol/l (5.82-6.02 mmol/l). The 6.1 mmol/l f-CBG WHO limit corresponds approximately to the 97.6 centile, and this limit is thus not traceable to the ADA discriminator, which corresponds to f-CBG of 6.4 mmol/l. This is the case in groups only, as recalculation will introduce unpredictable errors. Thus, in our general population a varying number of subjects will be at risk of DM as a mere consequence of different limits. The f-CBG limit of 6.1 mmol/l will thus lead to 2.4% false-positive diagnoses or, in EU, to around 44 x 10(6) adults being diagnosed. The number of cases at risk of DM vary from 5.4 x 10(6) to 44 x 10(6) in EU. We conclude that application of different diagnostic limits results in highly variable number of diagnosed DM cases, and therefore one diagnostic discriminator is needed to provide reproducible diagnoses.

Adolescent↗
PubMed2002

[Resistance tests in general practice. Validity can be improved by standardized procedures].

INTRODUCTION: Susceptibility testing of bacteria in urine is one of the commonest laboratory tests in general practice in Denmark. It is quick and easy to perform, but recent studies have shown low validity when the test is performed in general practice. If it is to continue as a diagnostic tool in general practice, its quality should be improved. The aim of this study was to investigate the effect of an intervention to improve the quality of susceptibility testing in general practice. MATERIAL AND METHODS: Twenty-three randomly selected general practices took part in the study. The intervention consisted of visits by laboratory technicians who instructed the practitioners in standardised procedures for susceptibility testing. Before and after the intervention, urine specimens containing monocultures of typical uropathogenic bacteria were sent to the practices. The practitioners performed susceptibility testing by the Sensicult and the Iso-Resagar methods, and the validity of the results before and after the intervention was compared. Results from susceptibility testing at the bacteriological laboratory, Odense University Hospital, were used as the gold standard. RESULTS: The median frequency of correct results increased from 82% to 98% for susceptibility testing by the Sensicult method (p = 0.001) and from 90% to 96% by the Iso-Resagar method (p = 0.05). DISCUSSION: The validity of susceptibility testing in general practice improves when preceded by instruction in standardised procedures.

Anti-Infective Agents, Urinary↗
PubMed2002

Relative importance of genetic effects in rheumatoid arthritis: historical cohort study of Danish nationwide twin population.

OBJECTIVE: To determine the relative importance of environmental and genetic effects in the development of rheumatoid arthritis. DESIGN: Historical cohort study with record linkage between a twin registry and the Danish discharge registry as well as the Danish national registry of deaths used to estimate completeness. SETTING: Two population based nationwide twin birth cohorts. PARTICIPANTS: 37 338 twins were sent a questionnaire about rheumatic diseases. Self reported rheumatoid arthritis was verified by clinical examination and from medical records. MAIN OUTCOME MEASURES: The probandwise concordance rate of rheumatoid arthritis in monozygotic and dizygotic twins. RESULTS: The response rate was 84.7%. Rheumatoid arthritis was verified in 13 monozygotic and 36 dizygotic twins. There were no concordant monozygotic twin pairs and two concordant dizygotic twin pairs. Based on capture-recapture methods the probability of ascertainment was 78.3%. The probandwise concordance rate was 0 (95% confidence interval 0 to 24.7) in monozygotic twins and 8.8 (1.9 to 23.7) in dizygotic twins. CONCLUSION: Genes are of minor importance in the development of rheumatoid arthritis.

Adult↗
PubMed2002

Serum lactate dehydrogenase isoenzyme 1 in patients with seminoma stage I followed with surveillance.

Serum lactate dehydrogenase isoenzyme I catalytic concentration (S-LD-1) was measured in patients with testicular seminoma clinical stage I followed with surveillance after orchiectomy. The serum samples were obtained before orchiectomy in 110 patients (group A) and soon after orchiectomy in 55 patients (group B). In group A, 60 patients (55%) had elevated S-LD-1 and 10 patients (9%) had elevated serum human chorionic gonadotropin concentrations (S-hCG). In group B, median S-LD-1 was lower than that of group A and decreased with increasing time after orchiectomv (p = 0.001, Jonckheere-Terpstra test, one-sided). After a median follow-up of 5.1 years, 23 patients (21%) in group A had relapses. The patients with elevated S-LD-1 and those with normal S-LD-1 had a similar relapse-free survival (p = 0.79, log-rank test). Thus patients with seminoma stage I had elevated S-LD-1 more often than elevated S-hCG but an elevation in S-LD-1 did not predict a relapse during follow-up with surveillance. Further studies are required to elucidate the value of S-LD-1 in monitoring the surveillance of patients with seminoma stage I.

Adult↗
PubMed2002

Combination of analytical quality specifications based on biological within- and between-subject variation.

At a conference on 'Strategies to Set Global Analytical Quality Specifications in Laboratory Medicine' in Stockholm 1999, a hierarchy of models to set analytical quality specifications was decided. The consensus agreement from the conference defined the highest level as 'evaluation of the effect of analytical performance on clinical outcomes in specific clinical settings' and the second level as 'data based on components of biological variation'. Here, the many proposals for analytical quality specifications based on biological variation are examined and the outcomes of the different models for maximum allowable combined analytical imprecision and bias are illustrated graphically. The following models were investigated. (1) The Cotlove et al. (1970) model defining analytical imprecision (%CVA) in relation to the within-subject biological variation (%CV(W-S)) as: %CVA < or = 0.5 x %CV(W-S) (where %CV is percentage coefficient of variation). (2) The Gowans et al. (1988) concept, which defines a functional relationship between analytical imprecision and bias for the maximum allowable combination of errors for the purpose of sharing common reference intervals. (3) The European Group for the Evaluation of Reagents and Analytical Systems in Laboratory Medicine (EGE Lab) Working Group concept, which combines the Cotlove model with the Gowans concept using the maximal acceptable bias. (4) The External Quality Assessment (EQA) Organizers Working Group concept, which is close to the EGE Lab Working Group concept, but follows the Gowans et al. concept of imprecision up to the limit defined by the model of Cotlove et al. (5) The 'three-level' concept classifying analytical quality into three levels: optimum, desirable and minimum. The figures created clearly demonstrated that the results obtained were determined by the basic assumptions made. When %CV(W-S) is small compared with the population-based coefficient of variation [%CV(P) = (%CV2(W-S) +%CV2(B-S))(1/2)], the EGE Lab and EQA Organizers Working Group concepts become similar. Examples of analytical quality specifications based on biological variations are listed and an application on external quality control is illustrated for plasma creatinine.

Bias↗
PubMed2002

Objective criteria for partitioning Gaussian-distributed reference values into subgroups.

BACKGROUND: The aim of this study was to develop new and useful criteria for partitioning reference values into subgroups applicable to gaussian distributions and to distributions that can be transformed to gaussian distributions. METHODS: The proposed criteria relate to percentages of the subgroups outside each of the reference limits of the combined distribution. Critical values suggested as partitioning criteria for these percentages were derived from analytical bias quality specifications for using common reference intervals throughout a geographic area. As alternative partitioning criteria to the actual percentages, these were transformed mathematically to critical distances between the reference limits of the subgroup distributions, to be applied to each pair of reference limits, the upper and the lower, at a time. The new criteria were tested using data on various plasma proteins collected from approximately 500 reference individuals, and the outcomes were compared with those given by the currently widely applied and recommended partitioning model of Harris and Boyd, the "Harris-Boyd model". RESULTS: We suggest 4.1% as the critical minimum percentage outside that would justify partitioning into subgroups, and 3.2% as the critical maximum percentage outside that would justify combining them. Percentages between these two values should be classified as marginal, implying that nonstatistical considerations are required to make the final decision on partitioning. The correlation between the critical percentages and the critical distances was mathematically precise in the new model, whereas this correlation is rather approximate in the Harris-Boyd model because focus on the difference between means in this model makes high precision hard to achieve. The application examples suggested that the new model is more radical than the Harris-Boyd model. CONCLUSIONS: New percentage and distance criteria, to be used for partitioning gaussian-distributed data, have been developed. The distance criteria, applied separately to both reference limit pairs of the subgroup distributions, seemed more reliable and correlated more accurately with the critical percentages than the distance criteria of the Harris-Boyd model. As opposed to the Harris-Boyd model, the new model is easily adjustable to new critical values of the percentages, should they need to be changed in the future.

Clinical Laboratory Techniques↗