Biomedical subjects

W Horwitz

Publications and source records attributed to W Horwitz.

At least 37 records · Page 2Linked to original sources

PubMedDate not supplied

Relationship of (known) control values to (unknown) test values in proficiency studies of pesticide residues.

Proficiency studies have been suggested as an alternative source of information for evaluating method performance characteristics when results from interlaboratory method performance studies conforming to internationally recognized protocols are not available. To explore this possibility, results were examined from ongoing proficiency studies of pesticide residue analyses in celery, carrot, and grape purees, and in wine. Statistical performance parameters were calculated from 18 data sets analyzed as unknowns by about 60 analysts for 12 analytes in the 25-1,000 microg/kg range, and from presumably parallel control (spike) analyses conducted by about half of the participants. A surprising finding was that recovery of known, independent control additions by the participant did not correlate with the recoveries determined as unknowns in the exercise. The data suggest that censoring or truncating of control data has occurred. The question of substitution of proficiency data for method performance data cannot be answered until the problem of unbiased reporting of control data is resolved.

Apiaceae↗

PubMedDate not supplied

Examination of proficiency and control recovery data from analyses for pesticide residues in food: sources of variability.

We examined a number of large proficiency and control databases supporting the values reported for pesticide residues in agricultural commodities at fractions of a part per million (mg/kg). The average recovery from >100,000 recovery records in 13 databases was 94%. The overall average single-value relative standard deviation (RSD) of the reported recoveries was 17% at a mean concentration (C) of about 10(-7) (0.1 mg/kg). The average apparent HORRAT value (RSD found/RSDR predicted from the Horwitz formula [2*C(-0.1505)]) was 0.8. Analysis of variance indicated that about 60-70% of the variance could not be associated with any particular factor or combination of factors-analyte, commodity, method, laboratory, concentration, database, or their interactions. The most predominant factor, analyte, and its third-order interaction with laboratory and concentration contributed most of the assignable variance. These findings suggested that most of the variability of trace analysis for pesticide residues is "random" in the sense of being inherent and not assignable to specific factor fluctuations.

Analysis of Variance↗

PubMedDate not supplied

Performance characteristics of methods of analysis used for regulatory purposes. Part II. Pesticide formulations.

The precision parameters of the method-performance (collaborative) studies published in the AOAC Journal from 1915 through 1990 for pesticide formulations have been recalculated on a uniform basis by the International Union of Pure and Applied Chemistry 1987 protocol. About 93% of the 953 accepted assays, which are predominantly gravimetric (G), volumetric (V), and gas (GC) and liquid (LC) chromatographic methods, exhibit relative standard deviations among laboratories (RSDR) that are generally less than 2 times the values predicted from the Horwitz equation: RSDR (%) = 2 exp (1-0.5 log C), where C is the concentration expressed as a decimal fraction. UV, VIS, and IR spectrophotometric (S) methods are somewhat poorer, with about 80% of the reported RSDR values less than twice the predicted RSDR value. The precision parameters of pesticide formulations analyzed by the older methods (G, V, GC) are equivalent to those previously found for drug preparations in the same concentration range; the precision parameters of pesticide formulations analyzed by LC and S are somewhat poorer. Overall, however, the precision parameters of pesticide formulations are generally independent of analyte, method, and matrix, and are primarily a function of concentration. The method-acceptability decisions of the AOAC for pesticide formulations during the past 75 years can be approximated retrospectively by using a criterion for RSDR that is less than 2 times the RSDR calculated from the Horwitz equation.

Databases, Factual↗

PubMedDate not supplied

Precision parameters of methods of analysis required for nutrition labeling. Part I. Major nutrients.

Major components of foods and feeds are fat, protein, and carbohydrates. Fat and protein are determined by direct measurements that are interpreted as the quantity of the constituent. Carbohydrates are usually calculated by difference. For this calculation, values for moisture/solids, ash, and "fiber" are also needed. The readily available collaborative studies for the determination of these major components are reviewed in an attempt to assign precision parameters to validated methods of analysis. When a number of studies for the same analyte, in the same food, by the same method are available, it is seen that the precision parameters among laboratories (standard deviations, SR; relative standard deviations, RSDR) and the ISO maximum tolerable difference functions (repeatability value, r; reproducibility value, R) are not characterized by any conventional distribution. The precision data are best summarized as a median or average parameter and the interval containing the centermost 90% of reported values. Typically, the precision of methods of analysis can be expressed as a function of concentration only, independent of analyte, matrix, and method. The average RSDR value from each collaborative data set can then be used as the numerator in a ratio containing, as the denominator, the value calculated from the Horwitz equation: RSDR = 2 exp (1 - 0.5 log C) where C is the concentration as a decimal fraction. A series of ratios consistently above 1, and especially above 2, probably indicates that a method is unacceptable with respect to precision. By this criterion, only the protein (Kjeldahl) determination is unqualifiedly acceptable with a 90% interval for RSDR of 1 to 3% at C values above about 0.01 (1 g/100 g). Fat, moisture/solids, and ash are acceptable down to limiting concentrations in the region of 1 to 5 g/100 g, if a test portion large enough to provide at least 50 mg of weighable residue or volatiles is specified. Measurements of individual carbohydrates and fiber-related analytes have unexpectedly poor precisions among laboratories. The variability, although high, may still be suitable for nutrition labeling. Reliability of analyses for the control of labeling of the primary nutrients must be achieved through quality assurance programs that require strict adherence to the directions of empirical methods and the use of suitable reference materials for absolute methods.

Databases, Bibliographic↗

PubMedDate not supplied

Precision parameters of standard methods of analysis for dairy products.

The available collaborative studies for standard methods of analysis for various constituents of milk and milk products were examined in an attempt to assign specific repeatability and reproducibility precision parameters to these methods. The different collaborative assays for the primary constituents (moisture/solids, fat, protein), the nutritionally important elements (calcium, sodium, potassium, phosphorus), and miscellaneous analytes/physical constants (ash, lactose, salt, freezing point) produced different estimates of the precision parameters for the same method. A suitable summary of the precision estimates from collaborative studies is given by the reproducibility relative standard deviation, RSDg, which is relatively constant within a product and permits comparisons across products. An estimate of the variation of RSDR for an analyte from a number of collaborative studies is presented in terms of the median and 90% interval (the range of the centermost 90% of values). These estimates are only informative when a substantial number of independent studies are available for pooling the independent estimates to form a distribution of RSDR values. The RSDR for the determination of the primary constituents of milk and milk products is characterized by a median RSDR of 1% and a 90% interval of 0.3-3%, with RSDR estimates occasionally occurring below 0.3% and above 4%. These overall estimates appear to be independent of analyte, matrix, and method and apply to concentrations of primary constituents that range from about 2 to 80%. The repeatability relative standard deviation, RSDr, is unstable, although it tends to converge to about 0.5-0.7 X RSDR. Too few collaborative assays are available to characterize RSDR for the determination of certain other constituents (acidity, ash, lactose, salt, and the nutritionally important elements) unless RSDR values for different analytes, methods, and matrixes are pooled on the basis of similar analyte concentrations. When pooled, the RSDR values are generally better than predicted from the Horwitz equation, RSDR (%) = 2 exp (1-0.5 log10C), where C is the concentration expressed as a decimal fraction; all but one of 661 RSDR values are within the upper empirical limit of twice this curve.

Animals↗

PubMedDate not supplied

Determination of nitrogen content in milk by the Kjeldahl method using copper sulfate: interlaboratory study.

Copper sulfate was substituted for mercury as the catalyst in the International Dairy Federation (IDF) Standard 20A:1986 method for the determination of nitrogen content in milk. The substitution was supported by results obtained in an interlaboratory study by 24 laboratories in 12 countries. Each laboratory analyzed 12 test samples of milk as blind duplicates in a double split level design with high, medium, and low nitrogen concentrations. The method protocol requires the concurrent analyses of an ammonium salt solution and a tryptophan solution as internal quality control standards with a minimum nitrogen recovery between 99 and 100% for the former and at least 98% for the latter. The repeatability and reproducibility relative standard deviations are 0.5 and 1%, respectively, for the range 0.35-0.70 g N/100 g. The performance of the laboratories that did not meet the required quality control specifications was clearly poorer than that of those that did meet the specifications.

Animals↗

PubMedDate not supplied

Sampling and preparation of sample for chemical examination.

Sampling and methods for reducing a laboratory sample to a test sample are discussed, with particular emphasis on sampling peanuts for aflatoxin analysis as a practical example. The only way to control the total error in the analysis of this heterogeneous product is to take and to analyze many and large samples.

Aflatoxins↗

PubMedDate not supplied

Performance characteristics of methods of analysis used for regulatory purposes. I. Drug dosage forms. F. Gravimetric and titrimetric methods.

The original gravimetric and titrimetric methods approved by AOAC for the analysis of pharmaceutical preparations, particularly during the period 1915-1950, show precision, recovery, and outlier parameters approximately the same as those exhibited by the previously reviewed instrumental methods that are currently used. Fifty-nine published collaborative studies utilized gravimetric methods and 85 used titrimetric. The studies of the gravimetric methods encompassed 47 analytes, 95 dosage forms, and 136 assays; the corresponding figures for the titrimetric studies are 72, 112, and 152. An average of approximately 7 laboratories participated per study. The line of best fit of the relative standard deviation between-laboratories (RSDR) plotted against the negative logarithm of the fractional concentration, C, extends from 1.2 and 1.0% for the gravimetric and titrimetric methods, respectively, at 100% concentration to 2.2 and 2.8% at 1.0% concentration. Below this concentration the precision of the titrimetric methods degenerates faster than that of the gravimetric methods. Above about 0.1% concentration the gravimetric and titrimetric methods are somewhat more precise than the instrumental methods in current use for drug analysis. The difference, however, is not statistically significant and the general equation, RSDR = 2 exp(1-0.5 log C), is also applicable to gravimetric and titrimetric methods above a concentration level of about C = 0.001 (0.1%).

Chemical Phenomena↗

PubMedDate not supplied

Harmonization of collaborative study protocols.

The 2 major protocols for the design, conduct, and interpretation of collaborative analytical studies--those from AOAC and the International Organization for Standardization--are already fairly well harmonized. The statistical models are identical and the outlier tests are essentially the same. The major differences are in symbols and terminology and in the specification of the minimum number of laboratories and replicates.

Models, Theoretical↗

PubMedDate not supplied

Performance characteristics of methods of analysis used for regulatory purposes. I. Drug dosage forms. D. High pressure liquid chromatographic methods.

Precision parameters of high pressure liquid chromatographic methods approved by AOAC for the analysis of drug dosage forms were recalculated on a consistent statistical basis, using the computer program "FDACHEMIST." Eleven collaborative studies of 12 compounds in 66 dosage forms analyzed by an average of 9 laboratories per study, with a total of 1150 determinations, were reviewed. For the approved methods and methods awaiting approval (9 studies, 11 compounds, 54 dosage forms, and 959 determinations), the average repeatability relative standard deviation (within-laboratory; RSDo) was 1.0%; reproducibility relative standard deviation (among-laboratories, including within-; RSDx) was 2.5%; the ratio RSDo/RSDx was an unusually low 0.40, with an average outlier rate of 0.6% of the reported values. The line of best fit for RSDx plotted against - log concentration increases with decreasing concentration, extending approximately from RSDx = 2% at 100% concentration to RSDx = 3.6% at 0.01% concentration, a change in RSDx of about 0.4% for each 10-fold decrease in concentration, independent of analyte and matrix.

Chromatography, High Pressure Liquid↗

PubMedDate not supplied

Determination of phosphorus in processed cheese: collaborative study.

A second interlaboratory collaborative study of the determination of phosphorus in processed cheese products by the molybdenum blue method verifies that this method is prone to producing a laboratory-induced systematic error. It would be useless to continue to make minor modifications in the details of the method, which will improve only the within-laboratory precision, until an accuracy control of the final measurement step is incorporated into the method.

Cheese↗

PubMedDate not supplied

Performance characteristics of methods of analysis used for regulatory purposes. I. Drug dosage forms. C. Automated methods.

For analysis of drug dosage forms, precision measures of AOAC approved automated methods, usually containing a spectrophotometric or fluorometric measurement step, were recalculated on a consistent statistical basis, using a computer program "FDACHEMIST." Ten collaborative studies of 14 compounds in 38 materials, consisting of various dosage forms, usually in 10 replications by an average of 7 laboratories, with a total of 2461 determinations, were reviewed. The average relative standard deviations within-laboratory (RSDo) and among-laboratories (RSDx) were 1.1 and 1.9%, respectively, and the ratio of RSDo/RSDx was 0.57, with an average outlier rate of 0.57% of the reported values. The line of best fit for RSDx plotted against - log concentration increases slightly with decreasing concentration, extending from an RSDx of about 1.6% at 100% concentration to an RSDx of 2.2% at 0.1% concentration, a change in RSDx of about 0.2% for a 10-fold decrease in concentration, independent of analyte and matrix.

Autoanalysis↗

PubMedDate not supplied

Comparison of the Volhard and potentiometric methods for the determination of chloride in meat products: collaborative study.

A collaborative study of the determination of chloride in meat products was conducted by the International Organization for Standardization (ISO) to compare the ISO 1841 method (Volhard titration) with the FAO/WHO Codex Alimentarius Committee method (potentiometric titration). Five canned luncheon meat products containing 0.25-2.0% sodium chloride at 4 different spiking levels were analyzed by 11 laboratories. The data were analyzed by ISO statistics (ISO 5725) and by AOAC statistics (Youden-Steiner), the major differences being in the rejection of outliers and in the statement of precision parameters. Good agreement was found between the mean chloride contents of the products as determined by both methods and with the added amounts, although statistically significantly higher sodium chloride recoveries were obtained with the potentiometric method. The within-laboratory variability (repeatability) is greater for the Volhard method, especially for chloride levels below 1.0%. Therefore it is proposed to set the lowest level of determination for the Volhard method at about 1.0% sodium chloride. The among-laboratories variability (reproducibility) of the potentiometric method was comparable with the results from the collaborative studies for chloride in cheese, giving acceptable values for relative standard deviations of 1.5-3.0% for meat products with 0.3-2.0% added sodium chloride. It is recommended that further work be conducted to reduce or eliminate the systematic error present with the potentiometric method as applied to meat and meat products.

Animals↗

PubMedDate not supplied

Performance characteristics of methods of analysis used for regulatory purposes. I. Drug dosage forms. E. miscellaneous methods.

Precision parameters of miscellaneous methods for the analysis of drug dosage forms approved by AOAC since 1972, and not previously reviewed in this series, were recalculated on a consistent statistical basis by using the computer program FDACHEMIST. Seventeen published collaborative studies were reviewed; the studies encompassed 19 analytes in 80 different materials (dosage forms), 102 collaborative assays, approximately 10 laboratories per study, and principally direct spectrophotometric, polarographic, and spectroscopic methods, for a total of 1451 determinations. The average repeatability relative standard deviation (within-laboratories, RSDo) for the instrumental methods was 1.5%; the reproducibility relative standard deviation (among-laboratories, including within-, RSDx) was 2.6%; the ratio RSDo/RSDx of the averages was 0.57, with an average outlier rate of 2.7% of the reported determinations. The line of best fit of RSDx for the instrumental methods plotted against the negative logarithm of the concentration increases slightly with decreasing concentration, extending from an RSDx of approximately 2.0% at 100% concentration to an RSDx of 3.4% at 0.001% (10 ppm) concentration; this represents an RSDx change of approximately 0.3% (absolute) for each 10-fold decrease in concentration, independent of analyte, matrix, and method. A method for determining precipitated allergenic protein by the micro-Kjeldahl technique appeared to be outside this general relation, showing an RSDx of about 13% at a concentration of 0.015% (150 ppm) nitrogen.

Allergens↗

PubMedDate not supplied

Performance characteristics of methods of analysis used for regulatory purposes. I. Drug dosage forms. B. Gas chromatographic methods.

Gas chromatographic methods for the analysis of drug dosage forms consist of a simple extraction, dilution with an internal standard solution, and injection, or, even simpler, dilution with the internal standard solution and injection. These methods were used in 7 collaborative studies of the determination of 12 pharmaceuticals, published in the Journal of the AOAC during 1973-1983. A total of 43 individual materials consisting of various dosage forms were each analyzed, usually in duplicate, by an average of 8 laboratories, with a total of 582 reported determinations. The average within-laboratory coefficient of variation (CVo) was 1.25% and the average among-laboratories coefficient of variation (CVx) was 2.41%, for a CVo/CVx ratio of 0.52, at an average outlier rate of 1.4% of the reported values. The line of best fit for CVx plotted against concentration increases with decreasing concentration, extending from a CVx of approximately 1.8% at 100% concentration to a CVx of approximately 3.2% at 1% concentration. The change in CVx for a 10-fold decrease in concentration is approximately 0.7% CVx, independent of analyte and matrix.

Chromatography, Gas↗

PubMedDate not supplied

Reliability of mycotoxin assays--an update.

The precision parameters of the method-performance (collaborative) studies for mycotoxins published in the literature through 1991 have been recalculated on a uniform basis by following the International Union of Pure and Applied Chemistry protocol. About 80% of the 793 accepted assays for mycotoxins, almost all of which have been conducted by thin-layer chromatography (TLC), liquid chromatography (LC), and enzyme-linked immunosorbent assays (ELISA), exhibit relative standard deviations among laboratories (RSDR) that are less than 2 times the values predicted from the Horwitz equation: RSDR, % = 2(1-0.5log10C) where C is the concentration expressed as a decimal fraction. The precision of TLC and LC methods is about the same, but that of ELISA is somewhat poorer. For those commodities for which sufficient data exist to provide a meaningful comparison, the methods applied to cottonseed products have the best precision and corn the worst, with peanuts intermediate. Overall, however, the primary factor affecting RSDR is concentration, more or less independent of analyte, method, matrix, and age of the study. If it is assumed that the test results are normally distributed and that an RSDR of 50% is the point where effective control of the results begins to be lost (a value equivalent to the production of 2% false-negative values), then relying on the Horwitz curve, the limit of quantitative measurement is the single digit, i.e., 5, micrograms/kg (10(-9); ppb) concentration for solid food commodities. Such a value must be considered as a limit applicable to a single analyte, aflatoxin B1, and not as a mean, and not applicable to the sum of the individual components, each of whose associated standard deviation would lie in the unacceptable region. Enforcement of a 5 micrograms aflatoxin B1/kg limit, under the assumptions made, requires that a responsible manufacturer and a prudent regulator operate at opposite extremes of tolerance limits: e.g., the producer at 2 micrograms/kg and the consumer at 10. A proposed Codex "maximum level" of 0.05 micrograms aflatoxin M1/kg milk cannot be supported by the available data applied in an interlaboratory enforcement environment. These conclusions are also supported by an examination of the reported data from the ongoing, large-scale proficiency studies routinely performed by the American Oil Chemists' Society and the International Agency for Research on Cancer.

Databases, Factual↗

PubMedDate not supplied

Reliability of the determinations of polychlorinated contaminants (biphenyls, dioxins, furans).

Precision performance parameters from results of 34 interlaboratory performance studies of polychlorinated aromatic ring compounds (biphenyls, dioxins, and furans) (PCCs) have been recalculated by using the international Union of Pure and Applied Chemistry-1987 harmonized protocol. Most studies of 1052 test samples, 56 analytes, 19 matrixes, and 2 types of detectors (electron capture and mass spectrometers) provide among-laboratories relative standard deviations (RSDRS), that are considerably better than those predicted from the Horwitz equation at fractional concentrations of 10(-5) down to 10(-15). The explanation suggested is that supplying common reference calibration solutions, as was done in many of these studies, does not reflect realistic operating conditions. Furthermore, the ability to repeat, discuss, and reassess aberrant reported values results in underestimating the true RSDR. The commonly reported problems of preparation of standard calibrating solutions, instability of the detection system, and failure to follow quality control instructions and good laboratory practices may be important sources of interlaboratory variability in PCC determinations.

Benzofurans↗

PubMedDate not supplied

Incomplete data sets: coping with inadequate databases.

Three problems arise in handling numerical values in databases: bad data, missing data, and sloppy data. The effects of bad data are mitigated by using statistical subterfuges such as robust statistics or outlier removal. Missing data are replaced by creating a substitute through interpolation or by using statistics appropriate to unbalanced designs. Sloppy, semiquantitative data are relegated to innocuous positions by using nonparametric, rank, or attribute statistics. These techniques are illustrated by the telephone directory, a database of carcinogenicity test results, and a database of precision parameters derived from method performance (collaborative) studies.

Carcinogenicity Tests↗