Laboratory values, standardization

The accuracy of an analysis can be determined by several procedures. One common method is to analyze a known sample, such as a standard solution or a quality control check standard solution that may be available commercially, or a laboratory-prepared standard solution made from a neat compound, and to compare the test results with the true values (values expected theoretically). Such samples must be subjected to all analytical steps, including sample extraction, digestion, or concentration, similar to regular samples. Alternatively, accuracy may be estimated from the recovery of a known standard solution spiked or added into the sample in which a known amount of the same substance that is to be tested is added to an aliquot of the sample, usually as a solution, prior to the analysis. The concentration of the analyte in the spiked solution of the sample is then measured. The percent spike recovery is then calculated. A correction for the bias in the analytical procedure can then be made, based on the percent spike recovery. However, in most routine analysis such bias correction is not required. Percent spike recovery may then be calculated as follows ... 

Anklam et al. [7] as well as Ahmed [8] recently published a comprehensive overview of different PCR assays that have been published in the literature. The authors tried to include performance data adding to the value of the review articles. The validation of PCR methods and thus the establishment of such performance criteria is still the subject of much debate. H bner et al. [9] suggested an approach for the validation of PCR assays. In general, it is currently the view of most researchers that validation of a PCR assay should not differ essentially from the validation of other analytical methods. Thus, all principles outlined in the ISO standard 17025 General requirements for the competence of testing and calibration laboratories, ISO standard 5725 Accuracy (trueness and precision) of measurement methods and results as well as the principles as laid down by Codex Alimentarius (http //www.co-dexalimentarius.net), are applicable to PCR. 

Statistics must also project in the IND the magnitude of difference necessary to demonstrate significance in variations between the laboratory values and clinical findings in patients treated with the test agent and those given placebo or standard medication. These determinations, as well as many of the particulars of the selected randomization patterns in the phase 2 and 3 trials, rest on a fundamental ability of statistics, that is to ascertain the likelihood of error in a particular statement and to estimate the confidence that can be placed in any experimental value. 

Another laboratory value that is often obtained in these exposures is serum pseudoeholinesterase. Serum pseudocholinesterase activities are often assessed as normal in children because the reference standards may not be reliable when assessing children. To add to the complexity, the normal range of serum cholinesterase activity is wide (Sofer et al, 1989). Authors have described the limitations of this measurement in determining therapy for children. In fact, it is recommended that a therapeutic and diagnostic trial of atropine should be given whenever there is any possibility of intoxication with these chemicals (Sofer et al, 1989). 

Fuel samples were analysed by independent laboratories using standard methods (C, H and N using Leco elementary analyser, heating value according to ISO 1928-1976). 

In quantitative metal analysis, high purity metals are the best for preparing standards. The use of pure metals instead of compound removes stoichiometry as a factor that needs to be included in calculating the true concentration of the standard solution. These factors are difficult to establish with extreme accuracy for most compounds because of factors such as the stability, number of water molecules, dryness, contamination and reactivity which must taken into account before use. However, if pure metals are not available, metal compounds are used which are usually checked carefully against certified standards. Many metal standard solutions of various concentrations are available through commercial suppliers in solution form but can be very expensive. The common concentration supplied is l.OgL-1 to lO.OgL-1 (or l.Omgml-1, lO.Omgml-1). These values are usually quoted as ppm for convenience and used widely in most laboratories. Commercial standards are normally checked by other methods (e.g. nuclear activation, titration, etc.) and supplied with a Certificate of Analysis to meet most accreditation requirements. Other special concentrations are also available or especially prepared on request and they are also supplied with a Certificate of Analysis. 

Figure 11.4 Effect of laboratory (a) and field (b) exposure on Fulton s condition factor (FCF) and lipid budgets in carp. The FCF is indicated in the line plot and lipid budgets in the vertical bars. Shading indicates effluent percentage from 0% (white) to 100% (black). Grey bars are intermediate effluent percentages. Data are average values standard deviations (n=5).

Differences from local lab to local lab may preclude a sponsor from meaningfully combining data from all participants across a number of Investigative sites. A statistical approach to standardizing laboratory values from a number of different labs (each potentially with their own reference ranges) has been described by Chuang-Stein (1992). However, standardization is time-consuming and the use of a number of local labs can introduce unwanted sources of variability that are neither easily quantified nor accounted for. 

Laboratory values are summarized descriptively for continuous measures by displaying the sample size, measures of central tendency (including the mean and median), the standard deviation, and the minimum and maximum values. A sample of such a descriptive display is provided in Table 9.1. 

A subsection on Clinical Laboratory Evaluations is to describe changes in patterns of laboratory tests with drug candidate use. As mentioned earlier, marked laboratory abnormalities and those that led to a substantial intervention are to be reported in the subsection on SAEs. The appropriate evaluations of laboratory values will usually be determined by the results observed and should include comparison of the treatment and control groups. Normal laboratory ranges, given in standard international units, should be provided for each analyte measured. A brief overview of the major changes in laboratory data (e.g., hematology, clinical chemistry, urinalysis, and other data as appropriate) at each time (e.g., at each clinical visit) over the course of the studies should include information on... 

Laboratory tests may also show a high degree of correlation amongst each other. For example, aspartate aminotransferase (AST) is correlated with alanine aminotransferase (ALT) with a correlation coefficient of about 0.6 and total protein is correlated with albumin, also with a correlation coefficient of about 0.6. Caution needs to be exercised when two or more correlated laboratory values enter in the covariate model simultaneously because of the possible collinearity that may occur (Bonate, 1999). Like in the linear regression case, inclusion of correlated covariates may result in an unstable model leading to inflated standard errors and deflated Type I error rate. 

Note Values in parentheses represent standard deviation of laboratory triplicates. Standard deviations are not given if soil mass was insufficient to replicate analyses. " The sites are coded as follows the first part of the code refers to the distance from the copper smelter in Rouyn-Noranda (0.5 = 0.5 km 2 = 2 km 8 = 8 km) the letter that follows refers to die field replicates. 

Note Values in parenthesis represent standard deviation of laboratory triplicates. Standard deviations are not given if soil mass was insufficient to replicate analyses. The codes for sites and soil component are as in Table 2. 

A normal distribution was assumed, with interlaboratory relative standard deviations (RSD) of 25% assumed at 50 and 100 (xg/kg, and 20% at 200 p.g/kg. These assumptions are based on the Horwitz equation. The nominal means and RSD assumptions were input into the random-number generator to obtain mean laboratory values. 

Intra-laboratory RSD (or repeatability standard deviation, as defined in ISO 5725-2) of 0.5 the interlaboratory standard deviation, and the previously obtained mean laboratory values, were input into the random-number generator to obtain four replicate laboratory values for samples at the three concentrations. The assumption of intra-laboratory standard deviation... 

Figure 8.11 Delamination resistance of symmetric cross-ply carbon fibre—epoxy (IM7/977-2) under quasi-static mode I loading, average initiation (init), average propagation (prop) and maximum prop values (averages from two to five laboratories and standard deviations) for testing from a starter crack thin-film insert and from a mode I precrack.

The melting points are those selected by Gschneidner (1990) except for Nd which is the later Ames Laboratory value of Gschneidner and Beaudry (1991). Although one bar is the standard state pressure, are the normal boiling points at one atmosphere (1.01325 bar) pressure. 

In Tables 4-7, the within-laboratory reproducibility standard deviation (sw), the reproducibility limit (Rw), and the relative standard deviation (RSDw), as well as CV derived from Horwitz equation are given for the contamination levels of 0.1 mg/kg, 0.3 mg/kg, 0.5 mg/kg, and 1.0 mg/kg. The results for sw, Rw and RSDw for each individual trichothecene were calculated from six experiments done in duplicates at the contamination level of 0.1 mg/kg and from ten experiments done in duplicates at the other three contamination levels except those for DON and nivalenol at the concentration levels of 0.3 mg/kg and 1.0 mg/kg which were calculated from nine experiments done in duplicates since one result at each of the two contamination levels was eliminated by the Cochran test. The experimental RSDw values were compared to the CV values derived from Horwitz equation. Majority of experimental RSDw values were lower than reference values, only a few exceeded it. However, they were much lower than upper limits for RSDr given in Regulation (EC) No 401/2006 (European Commission, 2006a) which were 40% for DON and 60% for T-2 and HT-2, thus the determined RSDw are considered acceptable. 

Appropriate Laboratory (Working) Standards To routinely measure samples of interest and determine the true value of the samples relative to certified reference materials. If performed correctly, then the use of reference materials will allow intra-as well as interlaboratory comparisons. Laboratory standards are required that are appropriate for the individual target materials. 

Industries set their own standards for certifying their products based on procedures and requirements in ISO, CIE, ASTM, and other national and international standards. Companies buy physical standards from optical supply houses (64) or SRMs from national laboratories to calibrate their spectrophotometers. Optics filters are sold with certificates certifying their spectral properties. Certificates from national standardizing laboratories hold the highest credibility and are based on international round-robin comparisons (65, 66). Standards from optical supply companies are often identical in material, shape, and size to SRMs from national laboratories. These standards are certified by instruments calibrated using national laboratory standards. The added uncertainty introduced by the second measuring instrument lowers the certified spectral credibility, value, and acquisition time. Usually, if traceability from a company s standards to the... 

---