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Contents
1. Background
1.1 Sample errors may be difficult to identify.
1.2 Sample errors may be irrelevant or carry major clinical consequences.
1.3 Sample errors carry implications that extend beyond the immediate care of the
patient.
2. The frequency of sample errors
3. Managing the risk of sample errors
4. Who has responsibility for avoiding sample errors?
5. Conclusion
6. References
1. Background
The majority of errors in medical testing are not analytical but reflect events that occurred outside the laboratory, including errors in sample collection. In many settings, the collection and identification of samples for medical testing are carried out by personnel who are not employed by or accountable to the testing service. External quality assurance programs may not identify these external events.
1.1 Sample errors may be difficult to identify.
An erroneous test result can often be identified by it being inconsistent with other current or historical information about the patient. In the absence of evidence corroborating a test result, there may be little to suggest to the pathologist or clinician that the wrong sample has been analysed. This is of particular concern in genetic testing of an unaffected person to determine whether they carry a mutation identified in an affected relative. In such testing, there is, by definition, no other evidence to corroborate the result of the genetic test.
1.2 Sample errors may be irrelevant or carry major clinical consequences.
If the prior probability of a two unrelated patients having a mutation in a specific gene is low, then a sample swap may still yield the correct result i.e. normal, on this basis alone.
However, the probability of a sample error being clinically significant rises as the prior probability of an abnormal result increases. This is relevant in genetic testing of relatives for a Mendelian disorder.
1.3 Sample errors carry implications that extend beyond the immediate care of
the patient.
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The incorrect identification of a mutation in a person may result in major decisions that carry lifelong consequences. The incorrect conclusion that a person does not carry the family’s mutation means that their children will not be aware of their risk and not seek genetic testing. The potential for this is exacerbated by the trust that patients and clinicians place in the new paradigm of genetic testing.
2. The frequency of sample errors
Non-analytical errors occur at the same rate in genetic versus non-genetic testing laboratories
( Am J Clin Pathol 1999
(http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/10396281) ).
Studies of pre-transfusion testing have revealed that 0.5-0.8 samples per thousand are blood from the wrong patient ( Vox Sang 2003
(http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/12823729) ).
Studies of samples used for microarray genetic testing have documented that 0.6 samples per thousand are blood from the wrong patient ( Cytogenet Genome Res 2011
(http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/21934286) ).
The risk of sample errors has been shown in increase in certain settings ( summarised in J Clin
Pathol 2012
(http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/22259179) ): the collection of samples during a _ medical procedure the simultaneous collection of samples from relatives (a common occurrence in clinical genetics), and the collection of samples with incomplete (yet accurate) labelling.
3. Managing the risk of sample errors
There are a number of strategies that could be considered to reduce the risk of a sample error, or to identify a sample error should it occur. It may be possible to corroborate a test result by referring to other clinical information of the patient or the results of relatives’ genetic tests.
It may be simple to use a modified paternity panel to confirm that the stated relationship between relatives matches the biological relationship between the samples.
For tests based on DNA sequencing, the simplest strategy may be to request a second, independent sample from the patient. Diagnostic DNA sequencing typically involving sequencing both strands of the DNA, Instead of splitting a single sample for these two reactions, a separate sample could be used for each reaction, with the concordance of the sequences being confirmed before a result is issued.
These considerations are not unique to genetics. There are specific collection protocols for samples destined for pre-transfusion testing, and duplicate sampling and testing is routine for tissue typing prior to transplant.
This is not suggest that every medical genetic test requires a special sample protocol. The usual sample requirement for medical testing i.e. a single, unsigned sample with two or more identifiers that are congruent with the request form, is appropriate for genetic testing for somatic (nonheritable) variants, for pharmacogenetic testing, and for population screening for autosomal recessive disorders as these results do not carry significant clinical implications for the patient’s relatives.
There are also settings in which corroboration may be difficult and a duplicate sample cannot be obtained e.g. prenatal testing. A single signed sample with the identity being confirmed by the collector or parent represents a suitable compromise for fetal samples. Duplicate sampling cannot be justified because of the associated risk to the fetus.
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4. Who has responsibility for avoiding sample errors?
The decision to implement a more stringent sample protocol is principally dictated by the clinical setting. The collector, laboratory scientist, and pathologist are not necessarily aware of these factors. The decision to implement the more stringent protocol must be made by the clinician requesting the investigation. On the other hand, the laboratory report should remind the requesting clinician of the sampling recommendations, perhaps with a disclaimer to emphasise the medico-legal consequences of undetected sample errors.
The wording of such a warning could be along these lines:
Genetic tests results may have significant medical implications for both the patient and relatives.
Corroboration of this result by reference to other clinical or laboratory information or by repeat testing may be warranted.
5. Conclusion
The goal of every medical laboratory is to provide the right result for the right patient in a timely fashion every single time. But the reality is that errors do and will occur. Sample errors are much more common than reports of adverse incidents would suggest. In genetic testing, the clinical significance of such errors can vary widely according to the clinical setting. For this reason, it is not appropriate to define one sample protocol for all genetic tests. Nonetheless, it is essential that each laboratory develop sample requirements for medical genetic tests.
All of those involved in the provision of medical testing have a fundamental responsibility to reduce the risk of sample errors. The core principles of accurate, complete, and legible labelling of request forms and samples remain paramount. In addition, corroboration of results that are significant for management of the patient or relatives should be sought.
Every intervention to minimise risk in the provision of medical testing represents an additional cost. Risk management is now an accepted component of the infrastructure costs for medical laboratories. The additional costs of reducing the risk of sample errors necessary to achieve the professional goal of maximizing benefit and minimizing harm to patients in the context of finite laboratories resources.
6. References
The issue of sample requirements in genetic testing is discussed in the Journal of Clinical
Pathology 2012
(http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/22259179) and in the articles cited therein.
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