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PubMed2001

Sample size considerations in genetic polymorphism studies.

OBJECTIVES: Molecular studies for genetic polymorphisms are being carried out for a number of different applications, such as genetic disorders in different populations, pharmacogenomics, genetic identification of ethnic groups for forensic and legal applications, genetic identification of breed/stock in animals and plants for commercial applications and conservation of germ plasm. In this paper, for a random sampling scheme, we address two questions: (A) What should be the minimum size of the sample so that, with a prespecified probability, all alleles at a given locus (or haplotypes at a given set of loci) are detected? (B) What should be the sample size so that the allele frequency distribution at a given locus (or haplotype frequency distribution at a given set of loci) is estimated reliably within permissible error limits? METHODS: We have used combinatorial probabilistic arguments and Monte Carlo simulations to answer these questions. RESULTS: We found that the minimum sample size required in case A depends mainly on the prespecified probability of detecting all alleles, while in case B, it varies greatly depending on the permissible error in estimation (which will vary with the application). We have obtained the minimum sample sizes for different degrees of polymorphism at a locus under high stringency, as well as a relaxed level of permissible error. We present a detailed sampling procedure for estimating allele frequencies at a given locus, which will be of use in practical applications. CONCLUSION: Since the sample size required for reliable estimation of allele frequency distribution increases with the number of alleles at the locus, there is a strong case for using biallelic markers (like single nucleotide polymorphisms) when the available sample size is about 800 or less.

Gene Frequency↗
PubMed1999

Identification of childhood psychiatric disorder by informant: comparisons of clinic and community samples.

OBJECTIVE: To compare the identification of psychiatric disorder as informed by parents versus teachers in children aged 6-11 years and parents versus adolescents in youth aged 12-16 years in clinic versus community samples. METHOD: Study data come from parallel surveys in Hamilton, Ontario, of children aged 6-16 years. The surveys included consecutive referrals (N = 1150) between 1989 and 1991 to the region's 2 agencies providing outpatient child mental health services. Also, a simple random sample (N = 1689) was used, drawn in 1989 from students attending public schools. Conduct disorder, hyperactivity, emotional disorder, and somatization disorder were assessed by informants using the original Ontario Child Health Study scales. RESULTS: The percentage of children identified with a disorder was markedly higher in the clinic sample, irrespective of the type of disorder, the age and sex of the child, and who provided the assessment. Also, there was a statistically significant differential shift between parents and teachers in the percentage of children identified with disorder. The ratio of children aged 6-11 years identified with conduct disorder or hyperactivity by parents versus teachers was higher in the clinic sample than in the community sample. Among youth aged 12-16 years, a similar pattern emerged for parents as informants versus the adolescents themselves, but it was statistically nonsignificant. CONCLUSIONS: The data suggest that the relative contribution of informants to the identification of childhood psychiatric disorder varies by sample type: clinic and community. If risk factors for child disorder are influenced by contextually specific factors wedded to informants, then studies conducted in clinic versus community samples may lead to discrepant information about the determinants of psychopathology. The extent of this problem needs to be assessed by comparing the results of parallel studies conducted in clinic versus community samples.

Adolescent↗
PubMed2003

Genomic data sampling and its effect on classification performance assessment.

BACKGROUND: Supervised classification is fundamental in bioinformatics. Machine learning models, such as neural networks, have been applied to discover genes and expression patterns. This process is achieved by implementing training and test phases. In the training phase, a set of cases and their respective labels are used to build a classifier. During testing, the classifier is used to predict new cases. One approach to assessing its predictive quality is to estimate its accuracy during the test phase. Key limitations appear when dealing with small-data samples. This paper investigates the effect of data sampling techniques on the assessment of neural network classifiers. RESULTS: Three data sampling techniques were studied: Cross-validation, leave-one-out, and bootstrap. These methods are designed to reduce the bias and variance of small-sample estimations. Two prediction problems based on small-sample sets were considered: Classification of microarray data originating from a leukemia study and from small, round blue-cell tumours. A third problem, the prediction of splice-junctions, was analysed to perform comparisons. Different accuracy estimations were produced for each problem. The variations are accentuated in the small-data samples. The quality of the estimates depends on the number of train-test experiments and the amount of data used for training the networks. CONCLUSION: The predictive quality assessment of biomolecular data classifiers depends on the data size, sampling techniques and the number of train-test experiments. Conservative and optimistic accuracy estimations can be obtained by applying different methods. Guidelines are suggested to select a sampling technique according to the complexity of the prediction problem under consideration.

Computational Biology↗
PubMed2005

Estimating the mean and variance from the median, range, and the size of a sample.

BACKGROUND: Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. METHODS: In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. RESULTS: We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n < or = 15). For moderately sized samples (15 < n < or = 70), our simulations show that the formula range/4 is the best estimator for the standard deviation (variance). For large samples (n > 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. CONCLUSION: Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.

Analysis of Variance↗
PubMed2006

Operating characteristics of full count and binomial sampling plans for green peach aphid (Hemiptera: Aphididae) in potato.

Counts of green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), in potato, Solanum tuberosum L., fields were used to evaluate the performance of the sampling plan from a pest management company. The counts were further used to develop a binomial sampling method, and both full count and binomial plans were evaluated using operating characteristic curves. Taylor's power law provided a good fit of the data (r2 = 0.95), with the relationship between the variance (s2) and mean (m) as ln(s2) = 1.81(+/- 0.02) + 1.55(+/- 0.01) ln(m). A binomial sampling method was developed using the empirical model ln(m) = c + dln(-ln(1 - P(T))), to which the data fit well for tally numbers (T) of 0, 1, 3, 5, 7, and 10. Although T = 3 was considered the most reasonable given its operating characteristics and presumed ease of classification above or below critical densities (i.e., action thresholds) of one and 10 M. persicae per leaf, the full count method is shown to be superior. The mean number of sample sites per field visit by the pest management company was 42 +/- 19, with more than one-half (54%) of the field visits involving sampling 31-50 sample sites, which was acceptable in the context of operating characteristic curves for a critical density of 10 M. persicae per leaf. Based on operating characteristics, actual sample sizes used by the pest management company can be reduced by at least 50%, on average, for a critical density of 10 M. persicae per leaf. For a critical density of one M. persicae per leaf used to avert the spread of potato leaf roll virus, sample sizes from 50 to 100 were considered more suitable.

Animals↗
PubMedDate not supplied

Forecasting the number of soil samples required to reduce remediation cost uncertainty.

Sampling scheme design is an important step in the management of polluted sites. It largely controls the accuracy of remediation cost estimates. In practice, however, sampling is seldom designed to comply with a given level of remediation cost uncertainty. In this paper, we present a new technique that allows one to estimate of the number of samples that should be taken at a given stage of investigation to reach a forecasted level of accuracy. The uncertainty is expressed both in terms of volume of polluted soil and overall cost of remediation. This technique provides a flexible tool for decision makers to define the amount of investigation worth conducting from an environmental and financial perspective. The technique is based on nonlinear geostatistics (conditional simulations) to estimate the volume of soil that requires remediation and excavation and on a function allowing estimation of the total cost of remediation (including investigations). The geostatistical estimation accounts for support effect, information effect, and sampling errors. The cost calculation includes mainly investigation, excavation, remediation, and transportation. The application of the technique on a former smelting work site (lead pollution) demonstrates how the tool can be used. In this example, the forecasted volumetric uncertainty decreases rapidly for a relatively small number of samples (20-50) and then reaches a plateau (after 100 samples). The uncertainty related to the total remediation cost decreases while the expected total cost increases. Based on these forecasts, we show how a risk-prone decision maker would probably decide to take 50 additional samples while a risk-averse decision maker would take 100 samples.

Forecasting↗
PubMed2004

Simulation model for enumeration of Salmonella on chicken as a function of PCR detection time score and sample size: implications for risk assessment.

A data gap commonly identified in risk assessments is the lack of quantitative information on the contamination of food with pathogens. A simulation model that predicts the incidence and distribution of Salmonella contamination on chicken as a function of PCR detection time score and sample size was developed with data from challenge studies with preenrichment samples that were composed of 25 g of chicken and 225 ml of buffered peptone water inoculated with 10(0.7) to 10(6) Salmonella and incubated at 37 degrees C. At 0, 2, 4, 6, 8, 10, 12, and 24 h of incubation, subsamples were collected and tested for Salmonella by PCR, and a PCR detection time score based on the widths of the bands in the electrophoresis gel was obtained for each preenrichment sample. Standard curves relating PCR detection time score to initial density of Salmonella inoculated were developed for sterile and nonsterile preenrichment samples. Presence of other microorganisms in the preenrichment sample decreased the PCR detection time score at low (<10(2) per 25 g) but not at high (>10(2) per 25 g) initial densities of Salmonella and resulted in a nonlinear standard curve rather than the linear standard curve obtained for sterile samples. The predicted incidence and distribution of Salmonella contamination on chicken increased in a nonlinear manner as sample size increased from 25 to 500 g. The new method reduced the time and cost of Salmonella enumeration by eliminating the selective enrichment, selective plating, and confirmation steps of the traditional most-probable-number method. Results are useful for risk assessment because they consider the uncertainty of the standard curve predictions and because they provide distributions of Salmonella contamination for different size samples of chicken that can be directly used in risk assessment.

Animals↗
PubMed1999

Necessary sample size for method comparison studies based on regression analysis.

BACKGROUND: In method comparison studies, it is of importance to assure that the presence of a difference of medical importance is detected. For a given difference, the necessary number of samples depends on the range of values and the analytical standard deviations of the methods involved. For typical examples, the present study evaluates the statistical power of least-squares and Deming regression analyses applied to the method comparison data. METHODS: Theoretical calculations and simulations were used to consider the statistical power for detection of slope deviations from unity and intercept deviations from zero. For situations with proportional analytical standard deviations, weighted forms of regression analysis were evaluated. RESULTS: In general, sample sizes of 40-100 samples conventionally used in method comparison studies often must be reconsidered. A main factor is the range of values, which should be as wide as possible for the given analyte. For a range ratio (maximum value divided by minimum value) of 2, 544 samples are required to detect one standardized slope deviation; the number of required samples decreases to 64 at a range ratio of 10 (proportional analytical error). For electrolytes having very narrow ranges of values, very large sample sizes usually are necessary. In case of proportional analytical error, application of a weighted approach is important to assure an efficient analysis; e.g., for a range ratio of 10, the weighted approach reduces the requirement of samples by >50%. CONCLUSIONS: Estimation of the necessary sample size for a method comparison study assures a valid result; either no difference is found or the existence of a relevant difference is confirmed.

Clinical Laboratory Techniques↗
PubMedDate not supplied

Sampling grain shipments to detect genetically modified seed.

Using the binomial distribution, the effect of sample size on the variability among sample test results when sampling a lot with 1.0% genetically modified (GM) or biotech seed was evaluated. The coefficient of variation, cv, among 500-seed sample test results taken from a lot with truly 1.0% was computed to be 44.5%. Increasing sample size to 1000 seeds reduced the cv among sample test results to 31.5%. The effects of sample size and accept/reject limits on the buyer's risk (bad lots accepted) and the seller's risk (good lots rejected) was also evaluated assuming a tolerance of 1.0% GM seed. Increasing sample size decreases both the buyer's and seller's risks at the same time. Using an accept/reject limit below the regulatory tolerance decreases the buyer's risk, but increases the seller's risk. Using an accept/reject limit above the regulatory tolerance decreases the seller's risk but increases the buyer's risk.

Analysis of Variance↗
PubMed2005

Determination of rifampicin bioequivalence in a three-drug FDC by WHO and indian protocols: effect of sampling schedule and size.

SETTING: To promote the quality assurance of fixed-dose combination (FDC) formulations, the World Health Organization (WHO) has prepared a convenient simplified protocol for the determination of rifampicin (RMP) bioequivalence. During the development of this protocol, it was proved that sampling time up to 8 h can determine the rate and extent of RMP absorption. However, this protocol utilises 20 volunteers in contrast to other local regulatory requirements of a minimum of 12 volunteers. The different sample sizes utilised in these protocols may affect the sensitivity of the bioequivalence outcome. OBJECTIVE: To determine the effect of sampling size and schedule on RMP bioequivalence when two different protocols are used. DESIGN: A bioequivalence trial was conducted with a study design of 20 volunteers and 24 h sampling time, which fulfils the requirements of both the WHO and Indian regulatory protocols. Pharmacokinetic and statistical analysis was done by stepwise reduction in sample size and schedule. RESULT: Bioequivalence limits of RMP were unaffected by a reduced sample size of 12 volunteers and 8 h sampling time. CONCLUSION: Minimising sample size after validation for borderline and poor quality FDC formulations can further reduce the cost of conducting bioequivalence trials.

Absorption↗
PubMed2006

Enumerative and binomial sampling plans for citrus mealybug (Homoptera: pseudococcidae) in citrus groves.

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

Animals↗
PubMed1990

Sample-size guidelines for linkage analysis of a dominant locus for a quantitative trait by the method of lod scores.

Sample-size guidelines for linkage studies of quantitative traits partially determined by a dominant major locus are needed to provide a rough estimate of the amount of pedigree material that should be sampled to map the loci that influence such traits. After pedigrees are sampled, a specific power calculation can be carried out to evaluate the linkage information provided by the sampled pedigrees. Using computer simulation, I provide sample-size guidelines for linkage studies by the method of lod scores of quantitative traits partially determined by a dominant major locus. I consider the effects of a trait model, marker characteristics, and sampling strategy, with particular attention to sampling strategy because it is the one factor which the investigator can fully control. My results suggest that linkage studies of quantitative traits are practical, particularly if the investigator chooses an efficient sampling design and an efficient strategy to select pedigrees for linkage analysis.

Female↗
PubMed1995

Needle size and sample adequacy in ultrasound-guided biopsy of thyroid nodules.

OBJECTIVES: To determine the optimal needle size (23-gauge or 27-gauge) for ultrasound-guided fine-needle aspiration biopsy of thyroid nodules and to compare the interoperator yield for this procedure. PATIENTS AND METHOD: Over an 11-month period, 123 patients underwent biopsy of a thyroid nodule. Three experienced radiologists were assigned at random to sample the nodules. For each nodule, four passes were performed in random order, two with 23-gauge needles and two with 27-gauge needles. If a specific pass yielded no tissue or blood, as determined by visual inspection (i.e., the sample was dry), the procedure was repeated until a satisfactory sample was obtained. After each patient had left the department, the aspirates were reviewed by a cytopathologist (who was not aware of needle size or operator identity) to determine diagnostic adequacy. RESULTS: Among the 123 nodules, 88 were solid, and 35 were complex cysts. There was no significant difference between the two sizes of needle in the adequacy of the samples obtained (102 nodules were adequately sampled with the 23-gauge needle and 95 with the 27-gauge needle; McNemar chi 2 test, p = 0.1456). However, there were significantly fewer dry passes with the larger needle (2 with the 23-gauge needle and 16 with the 27-gauge needle; chi 2 test, p = 0.0022). Sixteen nodules were inadequately sampled with both needles. Eight of these were less than 1 cm in greatest dimension. Only one solid nodule greater than 1 cm in greatest dimension was inadequately sampled. There was no difference in yield among the three radiologists (chi 2 test, p = 0.5192). No significant complications were encountered. CONCLUSIONS: Needles of both 23 and 27 gauge can be used to obtain fine-needle aspiration biopsy samples from thyroid nodules. Using both sizes is recommended, because the number of dry passes is lower with the larger needle, but the diagnostic quality of the aspirate may be better with the smaller one. Experienced physicians can perform fine-needle aspiration biopsy with equal proficiency.

Adult↗
PubMed1997

[Estimation methods in a sampling survey].

The objective of this paper is to present a guide for statistical analysis of a sampling survey. Advantages and disadvantages of classical sampling designs are first discussed. A sampling survey was designed to give more precise estimates of parameters which characterize a targeted well-defined population. Simple sampling design often is impossible in large population and rarely is the optimal solution. According to practical and economic constraints, and to available sampling frames, other strategies (stratification, unequal probabilities, several selection steps) may be necessary or more efficient. Fundamental tools to compute estimators and their confidence intervals are presented. The choice of the sampling method determine for each population unit the probability to include it in the final sample. These inclusion probabilities must be known to formulate estimators, ideally unbiased and with low variance. Difficulties arise from calculating the variance, especially for estimators which are not linear functions of the characteristics of interest. In that case, estimation procedures include Taylor linearization. It is always possible to find at least one linear estimator for a total. The total is the key-parameter in sampling theory, most parameters (such as ratios, means, percentages...), being function of unknown totals. Numerical examples are given.

Confidence Intervals↗
PubMed1997

Minimally-invasive early prenatal diagnosis using fluorescence in situ hybridization on samples from uterine lavage.

A two-phase study was undertaken to examine the efficiency of using transcervical cells (TCCs) collected by uterine lavage and fluorescence in situ hybridization (FISH) for early prenatal diagnosis of fetal chromosome aneuploidy. Uterine lavage was performed in 50 women scheduled for elective termination of pregnancy (TOP, n = 35) or chorionic villus sampling (CVS, n = 15) between 6 and 11 weeks of gestation. TCCS were dissociated by trypsin and collagenase, and interphase FISH was carried out for chromosomes X, Y, 13/21, and 18. The phase I study comprised 36 women. The FISH results were compared with the cytogenetic analysis from long-term culture of villus samples collected at TOP or CVS. Among the 36 samples, 15 had a normal male karyotype and 21 had a normal female karyotype. FISH on TCCs correctly identified 13 out of the 15 pregnancies with a male fetus. In phase II, uterine lavage was performed on 14 women. The samples were first tested for the presence of trophoblasts with an anti-trophoblast antibody, GB25, by immunohistochemical staining. Among 12 GB25-positive samples, the FISH results corresponded to the fetal karyotype. One of the GB25-positive samples had five signals for the chromosome 13/21 probe. The cytogenetic analysis confirmed that the fetus had a karyotype of 47, XX, +21. In the GB25-negative samples, FISH failed to identify one male pregnancy. Follow-up was carried out on 13 ongoing pregnancies and no maternal or fetal complications were discovered. This study demonstrates that fetal chromosome numeration can be carried out using FISH on uterine lavage samples in early pregnancy. However, a specific fetal cell marker, such as specific anti-trophoblast antibody, is necessary to avoid a false-negative result.

Adult↗
PubMed2000

Detection of isolated disseminated tumor cells in bone marrow and blood samples of patients with hepatocellular carcinoma.

BACKGROUND: Patients with hepatocellular carcinoma (HCC) often develop recurrences after curative resection or liver transplantation. Therefore, tumor cell dissemination must have occurred preoperatively or intraoperatively. Current staging methods cannot reliably detect micrometastasis. Reverse transcription-polymerase chain reaction (RT-PCR) for alpha-fetoprotein (AFP) has been used to detect circulating liver cancer cells, but results in blood samples have been contradictory. HYPOTHESIS: AFP-RT-PCR is a specific and sensitive assay for the detection of disseminated tumor cells in central venous blood and bone marrow samples of patients with HCC and has prognostic relevance. DESIGN: Prospective consecutive series. SETTING: University hospital. PATIENTS AND METHODS: We performed preoperative, intraoperative, and postoperative analyses of central venous blood samples and preoperative analysis of bone marrow samples of patients with HCC and patients without malignant disease, using a modified AFP-RT-PCR method. Preoperative serum AFP levels were measured. Clinical follow-up ranged from 4 to 20 months. MAIN OUTCOME MEASURES: Sensitivity and specificity of AFP-RT-PCR, correlation of AFP-RT-PCR results to tumor stage and tumor recurrence. RESULTS: In serial dilution experiments, 50 AFP-expressing HepG2 cells were detected in 10 mL of blood. Peripheral blood samples of 20 healthy volunteers and bone marrow samples of 21 patients with benign diseases consistently tested negative for AFP, whereas 4 of 24 patients with HCC showed AFP expression in bone marrow samples. All these patients had advanced disease; however, correlation of positive RT-PCR results to tumor stage was not significant (P = .07). One of the 4 AFP-positive patients developed an intrahepatic recurrence soon after liver transplantation. Central venous blood of patients with HCC (n = 24) and patients with benign liver diseases (n = 13) equally demonstrated AFP-expressing cells. There was no correlation of RT-PCR results to serum AFP levels. CONCLUSIONS: Perioperative screening for micrometastasis in bone marrow of patients with HCC is sensitive and specific with AFP-RT-PCR and may have prognostic relevance. Alpha-fetoprotein is not a suitable marker for the detection of tumor cells in central venous blood samples.

Bone Marrow↗
PubMed1997

Enzyme-linked immunosorbent assay-IgG antibody avidity test for single sample serologic evaluation of measles vaccines.

A measles-specific enzyme-linked immunosorbent assay (ELISA)-IgG avidity test for serologic evaluation of the efficacy of measles vaccines with only one blood sample was evaluated after vaccination with three measles vaccine strains. Avidity indices were determined by the urea elution technique in samples presenting antibody titers > or = 100 mIU/ml. All 127 sera collected 2-8 weeks after primary vaccination with Biken-CAM70 measles vaccine had low avidity indices (LAI, when < or = 29%) with a time-dependent increase in avidity. In samples collected 6-10 weeks after vaccination with Edmonston-Zagreb, LAI were also observed in all 31 sera tested (mean = 15%) and in 233/242 (96.3%) filter paper samples from primary vaccination with Schwarz vaccine (mean = 14%). There was no difference in the mean avidity among the three groups of primary vaccinees, although the Schwarz group had higher antibody titers. In contrast, only 1/36 (2.8%) serum samples from children who were seropositive at the time of measles vaccination had LAI (mean = 56%), despite the fact that they were collected early (2-5 weeks after vaccination). Of 90 serum samples from children vaccinated in the past with two doses and of 42 cord blood serum samples, none had LAI. It is concluded that this test is a good tool for evaluating serologically the efficacy of a single dose schedule of measles vaccine. With only one postvaccination sample, the test can discriminate nonresponders (antibody titers below 100 mIU/ml), primary responders (antibody titers > or = 100 mIu/ml with LAI), and those previously immunized (antibody titers > or = 100 mIU/ml with high avidity indices). The seroconversion rate can be calculated after excluding the latter.

Adult↗
PubMed1998

Shell-vial culture and pp65 antigenemia assay in the detection of cytomegalovirus in the first blood sample of renal transplant recipients.

The aim of the study was to compare the efficacy of pp65 antigenemia assay and the shell-vial culture (SVC; viremia) for the diagnosis of cytomegalovirus (CMV) infection in renal transplant recipients, comparing the results obtained in the first blood sample and the total number of blood samples analyzed in this group of patients. During the study period, 70 renal transplant recipients were studied: 44 (62.8%) with CMV infection. The method of sedimentation in a dextran solution for leukocyte extraction was used in the pp65 antigenemia assay. The MRC-5 shell-vial assay was used for CMV isolation from leukocytes (viremia). Eighty blood samples were examined from 70 renal transplant recipients: Of the 44 positive samples studied, in 77.5% of cases, both the antigenemia assay and the SVC were positive. In 16.2%, only the antigenemia assay was positive, and, in 6.2%, only the SVC was positive. In all blood samples studied, the antigenemia was present in 93.7% of cases, and the SVC was present in 83.7% (P = 0.04). If the results obtained in only the first blood sample taken for the diagnosis are studied, then we observe that the antigenemia assay was positive in 39 patients (88.6%), whereas the SVC was positive in 41 patients (93.1%), although the difference was not statistically significant (P = 0.39). It is concluded that the inoculation of all of the leukocytes extracted from blood samples in the SVC seems to produce a slight increase in the sensitivity of the cell culture and that the SVC becomes positive before the antigenemia for the detection of CMV in peripheral blood, especially in the first blood sample.

Antibodies, Monoclonal↗