19.03.2014

Ca 19-9 blood test ovarian cancer

Adriana Unic1*, Lovorka Derek1, Nevenka Stancin2, Tihana Serdar1, Novka Sprajc1, Zeljko Romic1.
Introduction: Monoclonal antibodies are used to detect serum antigens associated with specific malignancies. Materials and methods: CA19-9, CEA and AFP concentrations, using Vitros ECi (Ortho Clinical Diagnostics, Johnson and Johnson, Buckinghamshire, UK), and Cobas e 411 (Hitachi High Technologies Corporation, Tokyo, Japan) immunoassay analyzers, were determined.
Results: The values of commercial controls were within the range declared by the manufacturer for all tumor markers included in the study on both analyzers. Conclusion: Study results showed the best compliance of values for AFP obtained on two studied immunoassay analyzers. As the study results confirmed the observations from daily routine, it is of utmost importance for individual patients to be monitored using the same immunoassay and reagents on the same analyzer. Tumor markers are used for the cancer risk estimation, early detection of the disease, screening, diagnosis, prognosis, prediction of therapy success and detecting the recurrence or monitoring progression of the disease. Carcinoembryonic antigen (CEA) was first described more than three decades ago, when its presence was demonstrated in fetal gut tissue and in tumors from gastrointestinal tract. Carbohydrate antigen (CA) 19-9 is most valuable as a serum marker for pancreatic and biliary cancer, but increased concentrations occur in several other GI malignancies (e.g.
The aim of our study was to perform the analytical evaluation of the inter-assay comparability for tumor markers CA19-9, CEA and AFP on two different automated chemistry analyzers. Methods comparison was conducted using routine patient samples analyzed for the purpose of the standard diagnostic work-up in our hospital.
Concentrations of tumor markers in sera and control samples were determined on the Vitros Eci analyzer with chemiluminiscence assay (imunometric) and on the Cobas e 411 analyzer with electrochemiluminiscence assay according to the manufacturer instructions.
Analytical inaccuracy was shown as bias (%) and day-to-day imprecision as coefeicient of variation CV (%). Quality requirements for the tests were stated according to Westgard rules (derived from biological variations).
Mean, minimal and maximal measured values, as well as the coefficient of variation and bias, were calculated for control samples. Correlation of CA19-9, CEA and AFP results was preformed and Spearman correlation coefficient was calculated. The measured values of commercial control samples were within the range recommended by the manufacturer. The highest deviation from the declared control values was found for CA19-9 on Vitros ECi and for AFP on Cobas e 411 analyzer. The aim of the study was to verify our daily routine experience with comparability of tumor markers concentrations obtained with different methods on different analyzers. It is important to monitor the values of tumor markers of each patient with the same reagents on the same analyzer despite their comparability and high correlations (13-16).
In today’s global world, accurate, reliable and comparable measurement results are of vital importance.
Making the right decision on whether or not some measurement procedure is adequate for a stated use (validation), as well as a realistic estimation of measurement uncertainty, is only possible when a measurement process is well known. Prior to introducing a new, unknown method, every conscientious analyst will first carry out its validation.
Validation experiments spend time and money and therefore it is exceedingly important to plan them well. In real life, most problems for laboratories are posed by setting the acceptance criteria to method performance characteristics, not by their selection. Measurement uncertainty is estimated in line with the internationally and multidisciplinary harmonized Guide to the Expression of Uncertainty in Measurement (GUM) (2) issued in 1993, corrected in 1995.
According to GUM, each uncertainty component is quantified by an estimated standard deviation, called, for this purpose - standard uncertainty.
Type A standard uncertainties are obtained as a standard deviation (of the mean) of replicate measurements, or as a standard deviation from the fit of a calibration curve, characteristic standard deviation from a control chart etc.
Examples of uncertainty sources evaluated by type B evaluation are: manufacturer’s quoted error bounds for a measuring instrument, interval of values of measurement standards, data from calibration report etc. Measurement uncertainty is still relatively misunderstood in many areas of measurement and so in the field of medical biochemistry. Measurement uncertainty is a property of measurement result, not of the method, equipment or laboratory and therefore it is to be expected that it is assessed only once the result is obtained. Random errors are estimated via precision experiments and represented as standard deviations (s) or coefficients of variation (CV). Reference value is most commonly the value of certified reference material (CRM) determined with the appropriately low measurement uncertainty and with documented metrological traceability. A prerequisite for the GUM is that “the result of a measurement has been corrected for all recognized significant systematic effects”. To make correction technically feasible and justified, the estimate of bias (b) should be sufficiently accurate, well established, and significant in size. Although GUM (2) strongly recommends the correction of reported results of measurement with a known systematic effect (b), in some cases it might not be practical and feasible or might be too expensive. The scope of validation is a compromise of risks and costs, so the extent of experiments results from this compromise.
Consequently, when measurement uncertainty is assessed on the basis of information on method performance characteristics, it is important to ensure permanent statistic monitoring.
Besides for internal quality control measures, it is important to regularly participate in inter-laboratory testing since sometimes it is the only way to discover systematic effects undetected in a laboratory.
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These tumor markers are most useful for monitoring response to therapy and detecting early relapse, but results obtained by different assays vary, and a change of method during follow-up may cause problems. Between-method correlation was studied in 38 serum samples for CA19-9 and AFP and 39 serum samples for CEA. The highest deviation from the declared control values was found for CA19-9 on Vitros ECi and for AFP on Cobas e411 analyzer.


Regardless of high correlations, Passing-Bablok regression indicated lower comparability between two immunoassays for CEA and CA19-9.
However, there is no tumor marker sufficiently specific and sensitive for healthy population screening. Subsequently, CEA was detected in the circulation of patients and recognized as a serum marker for colorectal cancer. It is used for the diagnosis, prognosis, detecting recurrence of the disease, monitoring of therapy as well as for high-risk population screening for development of hepatocellular malignancy (1,6). Results were obtained on the analyzers Vitros ECi (Ortho Clinical Diagnostics, Johnson and Johnson, Buckinghamshire, UK) and the Cobas e 411 (Hitachi High Technologies Corporation, Tokyo, Japan).
Results of the day-to-day imprecision and bias were in the range of desirable specificiations derived from biological variations. Passing-Bablok regression results for CEA, AFP and CA 19-9 are shown in Figures 1, 2 and 3 and in Table 4. Concentrations of all three markers in control samples obtained on both analyzers (Vitros ECi and Cobas e 411) performed well in terms of target values declared by the manufacturer, but differed between each other.
The biggest problem is the long-term monitoring, because in a course of one year the patient can change hospital or the laboratory can introduce a new method of determination of tumor markers.
Its ‘goodness’ is characterized in terms of random and systematic errors that affect the measurements. This is done out of professional conscience and aspiration to provide reliable measurement results, i.e.
For instance, in methods where the task is to discover weather something exists in the sample or not, the analysts will most probably be interested in the limits of detection and selectivity.
The criteria should be set before carrying out validation experiments, keeping in mind the ability to interpret results thus obtained, i.e. In quantitative terms, this request is described with target measurement uncertainty which represents the greatest allowed uncertainty for a particular usage of that result.
The following international organizations participated in its assembly: Bureau international des poids et mesures (BIPM), International Electrotechnical Commission (IEC), International Federation of Clinical Chemistry (IFCC), International Organization for Standardization (ISO), International Union of Pure and Applied Chemistry (IUPAC), International Union for Pure and Applied Physics (IUPAP) and International Organization of Legal Metrology (OIML). GUM describes two ways of evaluation – type A, estimated by statistical means, and type B, estimated by other means. Despite the fact that type B uncertainties are essentially based on scientific judgement and are therefore subjective and personal, the reliability of some uncertainty estimate does not depend on the way of evaluation, but exclusively on the quality of information which was basis for evaluation. All standard uncertainties thereat are equally mathematically treated, regardless if they were obtained through type A or B evaluations. However, as the evaluation of measurement uncertainty is one of the requirements of ISO 15189, is increasingly accepted that in addition to the method performance characteristics can be one of the quality indicators (3). If the main sources of error would be within the measurement (or testing) process itself, and not for instance caused by a non-homogenous sample, it is possible to make a satisfactory measurement uncertainty estimation using method performance characteristics like precision and trueness estimates. Out of the three precision levels mentioned (repeatability, intermediate precision and reproducibility), the most interesting one in measurement uncertainty assessment (made from validation experiments) is intermediate precision since it includes much wider sources of random errors than it would be the case with repeatability.
Reference material should have a matrix as close as possible to the matrix of the material subjected to measurement. Examples of such components are contribution of sampling effects, sample preparation, sample inhomogenity etc. The correction of results may require modifications to existing software and “paper and pencil” corrections can be time consuming and prone to error.
Laboratories should choose the one that can be easily interpreted by the user and that will not give a wrong insight into the magnitude of the uncertainty of measurement.
This monitoring proves the reality of estimation of the method performance characteristics, and thereby also the validity of measurement uncertainty estimation and recognizing the changes thereof. International Vocabulary of Metrology – Basic and General Concepts and Associated Terms (VIM 3), JCGM 200:2008. Monoclonal antibodies are used for determination of specific serum antigen, produced by the tumor cells or cells induced by host tumor cells (1). This tumor marker has not been advocated as a screening test for colorectal cancer; however a preoperative CEA serum level is useful for diagnosis and prognosis of recurrence and survival in colorectal cancer patients. The concentration of tumor markers depends on the biological and analytical variation (7,8).
The tested samples were from hospitalized patients with clinical suspicion or confirmed diagnosis of gastrointestinal carcinomas admitted to the Department of Nuclear Medicine, Dubrava University Hospital in the period of March 21st to March 31st 2009. Passing-Bablok regression was used for method comparison for each tumor marker, including the Cusum test for linearity.
Declared and measured values of control samples, as well as their bias and CV% from day-to-day imprecison are presented in the Tables 1 and 2. Ideally, the results obtained by different methods should be fully comparable, but as the outcome of this study shows, that is not noted in practice. The clinical relevance of the tumor marker CA19-9 in the diagnosing and monitoring of pancreatic carcinoma. Clinical evaluation of serum alpha-fetoprotein-IgM immune complexes on the diagnosis of primary hepatocellular carcinoma. Biological variation and reference change values of CA 19-9, CEA, AFP in serum of healthy individuals. Serum tumor markers in monitoring patients: interpretation of results using analytical and biological variation. Performance of immunoassays for CA19-9, CA 15-3 and CA 125 tumor markers evaluated from an international quality assessment survey.
Cobas Core CA 19-9 II EIA: new CA 19-9 enzyme immunoassay with high correlation to radioimmunoassays. Comparison of an immunoradiometric and an immunoluminometric assay for the evaluation of the tumour associated antigens CA 19-9 and CA 125. Experiments conducted in order to validate a method can give good insight into their magnitude and also into their sources and therefore can be used for measurement uncertainty estimation. If they have to determine the cause (identification), selectivity will be of critical significance.
The result is usually reported with expanded uncertainty which is the multiplication of combined standard uncertainty of result and factor k which ensures the agreed coverage probability, usually P = 95 %.


Initial information on this method performance characteristics are obtained by performing validation experiments. Bias could also be determined using another method of higher metrological order, but this is rarely possible in real life. In such very special circumstances when a known correction b for systematic effect cannot be applied, the “uncertainty” assigned to the result can be enlarged by it.
In order for a laboratory to get a good approximation of intermediate precision, it has to recognize the factors which will cause errors in measurement and simulate them in the course of validation.
Passing-Bablok regression slope and y-axis intercept included 1 and 0 only for AFP comparative assays. Serum CA 19-9 concentrations are elevated in 70-90% of patients with pancreatic cancer; the concentrations reflect tumor burden and high concentrations are associated with adverse outcome. Using the reagents from different manufacturers can result in a different test result in the same sample, even if the method of determination is the same (including the use of standardized antibodies). Each serum was divided into two aliquots immediately after centrifugation – one to determine the concentration of markers on the Vitros ECi analyzer at the Department of Nuclear Medicine, Dubrava University Hospital, and the other to determine the concentration of the markers on Cobas e 411 analyzer at Clinical Department for Laboratory Diagnostics, Dubrava University Hospital.
An interesting fact is that the largest deviation from the declared values for Vitros ECi analyzer was in the normal and slightly elevated range of values of the control sera (Level 1 and 2). In cases where the latter is not possible, when changing the methods and analyzers, it is necessary to define a new baseline concentration of tumor markers for monitoring each patient. The scope of performed experiments surpasses the need for the assessment of measurement uncertainties.
In line with the definition from the new vocabulary in metrology VIM 3 (1), a validation of an item (e.g. But, when they have to issue a quantitative result, all the above stated method performance characteristics become interesting, except for the limits of detection. Unfortunately, in most cases the criteria are set based on results obtained through validation experiments.
In practice, the change of two factors is applied most frequently: staff and time, meaning the repetition in measurement is usually done by different personnel over the course of several days.
Post-therapeutic monitoring of marker levels provides information on treatment response and recurrence (3-5). Sera were obtained after centrifuging at 1006 x g for 10 minutes in Hettich Rotina 35 R (Hettich, Tuttlingen, Germany) centrifuge.
That does not include CEA that showed the largest deviation in the normal and high range of the control sera (Level 1 and 3). They are used to explore method behavior in all realistic operational conditions, to finds its weak points, prove coordinated work of personnel as well as to prove selectivity or check limits of detection etc.
The frequently used slogan whereby the scope of validation is a compromise of costs and risks does not pertain to the selection of performance characteristics, but only to the number and scope of experiments to be estimated. The statement written at the end of the validation stating that the method complies with a particular usage makes no sense then. GUM (1) describes a method when such enlarged “uncertainty” is the sum of expanded uncertainty and a known systematic effect (b).
Later, it is regularly proven that actual precision is a great deal lower than determined by validation experiments. Afterwards, it is essential to monitor their performance characteristics in order to prove the validity of assessment. Due to these reasons, when determining the concentration of tumor markers, quality requirements must be fulfilled, and the method of determination must be reported with the results. In addition to analyzing the samples on Vitros ECi analyzer, values of BioRad, Lypochek Immunoassay Plus (Bio-Rad Laboratories, Marnes-la-Coquette, France; Control lot 40200 - Level 1, 2 and 3) control samples were obtained for CEA and AFP. It is important to emphasize that the correlation coefficients for all three markers showed a high correlation of their specific concentration obtained on both analyzers.
Even though it will not have a major impact on the information about measurement accuracy, it will ensure more reliable work, easier detection of errors in work and a higher level of confidence in results’ accuracy. Should it be noticed that the performance characteristics have changed, it is necessary to update the assessment with new data. If the method of determination needs to be changed, it is recommended to perform simultaneous determination, using both methods (4,9,10). For CA19-9, Vitros Immunodiagnostic Product Oncology Controls (Ortho Clinical Diagnostics, High Wycombe, UK; Control lot 220) were obtained. Data obtained using Passing-Bablok regression showed concentrations of CEA and CA 19-9 not to be aligned nor to follow the same linearity (slope and y-axis intercept did not include 1 or 0), while the concentrations of AFP obtained on two analyzers were aligned and followed the same linearity (slope and y-axis intercept included 1 or 0). From these data we can conclude that there is no proportional difference between the results of CEA and CA19-9.
Therefore, comparability of the concentration of tumor markers on two different analyzers is not satisfactory. Concentrations of AFP obtained on two analyzers met the preferences of Passing-Bablok regression; the slope was very close to 1, and y-axis intercept was very small.
Regardless of high correlations, it is evident that there are differences in values obtained with different methods on different analyzers, and that cannot be ignored. Previous studies in this field indicate that CA 19-9 assay shows significant differences between methods and that results cannot be extrapolated from one analytical tehnique to another (4,11,12). Differences in values for CEA and AFP could be explained with the usage of antibodies with different specificities.
For of CA19-9, both methods use the same antibody (1116-NS-19-9), which suggests that differences in CA19-9 results obtained on two different analyzers are the consequences of the calibration and method design (e.g. From all the presented results we can conclude that there are significant differences in the results of tumor markers concentrations for individual patients tested on different analyzers and with different methods. Considering the number of studied samples is very small to make any strong conclusions, this limitation should be taken into consideration when interpreting our results.



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