Preanalytical Considerations in the Design of Clinical Trials and Epidemiological Studies

Clinical trials and epidemiologic and most types of clinical research include the acquisition of biological samples to be analyzed either immediately after collection or in the future for biomarkers related to the study hypotheses. Tested biomarkers include those used to monitor subjects' health and to detect harmful side effects (e.g., liver and kidney function tests) or to follow the impact of therapeutic interventions. These samples may also be used for biomarker discovery. Whatever the study goals may be, the quality of study outcomes will depend heavily on the quality of the samples obtained and subsequent analysis. Since the largest component of total error in the clinical laboratory has been found to be associated with the preanalytical phase, it is probably safe to assume that the same conclusion applies to clinical trials and epidemiologic studies. Although standardization of preanalytical variables is not a trivial manner, it is essential to ensure successful outcomes of these studies. The competency of personnel performing such testing, and their training and understanding of sample collection and processing procedures, must be assured. Samples must be handled in an identical fashion at all times and in all locations, and procedures must be in place to avoid sample mix-ups. These are only few of the challenges encountered during the preanalytical phase. In this Q&A, 5 experts with a vast experience in national and international biomarker studies provide their insights into the issue of preanalytical variables and how these can impact the design of clinical and epidemiologic studies. Do you think that preanalytical variables are given enough consideration when designing clinical trials or epidemiologic studies? David Morrow: This is an area of vulnerability for biomarker testing in clinical studies. Although some investigators are very experienced and map out the preanalytical considerations thoroughly, in many cases, such planning does not occur either because of insufficient appreciation of preanalytical variables or the retrospective nature of many biomarker studies. Christina Ellervik: Preanalytical standard operating procedures (SOPs) are as important in research as they are for the clinical laboratory. SOPs must be clearly defined in every trial or epidemiologic study, and if specimens do not meet SOP standards they should either be destroyed or flagged. It is important that all preanalytical variations be described for every specimen. Preanalytical errors in a study may cause delays in reporting results because samples have to be recollected. Evan Stein: With the development over the last 2 decades of national and global central laboratories focused on supporting clinical and epidemiological trials, there has been a tremendous, and needed, improvement of all the laboratory related aspects. In clinical laboratories offering analysis for clinical trials the preanalytical variables related to transit time from patient to laboratory are a huge factor. A large amount of our time and effort in the central laboratory was spent on assessing and documenting the effect of sample handling and sample stability under various conditions before analysis. This is something we never even thought of doing in our hospital laboratory. Ann Hsing: In most epidemiologic studies, we give a lot of thought to our design, including covariates such as age, sex, race, socioeconomic status, body size, medication use, and other factors, before we start a biomarker study. We also pay meticulous attention to factors that can potentially affect sample integrity, including time of collection, blood separation and processing, and storage. So, yes, we do give careful consideration to variables, procedures, and QC issues before we start the study, collect samples, or assay samples in the laboratory. For epidemiologic studies, this is a standard practice. Amar Sethi: Unfortunately, I would have to say, no. Laboratory data obtained during clinical trials are affected by the same shortcomings encountered for data generated in the clinical laboratory. The clinician is most likely to question a result if it fails to agree with the patient history and the overall clinical picture. This often leads to the questioning of the analytical rather than the preanalytical integrity of the system. Similar questions may be raised when the mean, median, or trend does not correlate with other related biomarkers. Do you think that preanalytical variables are given enough consideration in the clinical decision-making process when discussing the clinical impact of results from clinical trials or epidemiologic studies? David Morrow: There is substantial variability to the depth of such consideration. In the clinical literature, I believe that the potential impact of preanalytical issues is often given limited consideration and sometimes not recognized at all. Christina Ellervik: Preanalytical variables should be taken into consideration when interpreting results, especially when results differ between similarly conducted studies. Discrepant results may arise from applying different preanalytical SOPs or breaches of SOPs. It's important to remember that medical research is for the patient. Since conclusions may be drawn on diagnosis, staging, prognosis, stratification, etc., the results of a study could actually result in clinical guideline changes; thus, we must assure the highest standards in sample integrity. Otherwise there could be potential harm to patients from incorrect diagnoses or choice of treatment. Evan Stein: As discussed above, there has been significant improvement in consideration and standardization of preanalytical variables into protocols. However, there has been less attention and focus when it comes to interpreting and publishing the results of trials, which are highly dependent on biomarker results. This is often a result of the lack of involvement of reviewers with expertise in laboratory science during the peer review process. Most high-impact journals have for the last few decades included a statistician as a reviewer for all clinical trial publications, but none that I am familiar with include a laboratory professional with knowledge and experience with the analytical aspects of the biomarkers being reported. Amar Sethi: A set approach is often employed that addresses some, but not all preanalytical issues, and the considerations may be exactly the same for all analytes. Specimen type, processing instructions, storage conditions, and stability under predefined conditions are usually considered. However, implementing alternative conditions for analytes that require more stringent preanalytical handling may greatly impact the integrity of the study. For example, if platelet-poor plasma is required for a particular test, the trial sponsor may request an alternative procedure to process the sample, “because the trial site does not have the infrastructure to carry out complex processing protocols.” Although the alternative procedure might not have been studied thoroughly before implementation, the results would be expected to be equally robust as those obtained with the more established approach to sample preparation. These kinds of compromises cause the data obtained to lose statistical integrity and power and jeopardize their potential to adequately address the scientific question under study. What strategies can be used to minimize preanalytical variables in clinical trials or epidemiologic studies? David Morrow: Most important is prospective determination and planning for the potential impact of preanalytical variables on biomarker or other assessments. After this initial planning phase, implementation of a formalized set of operational instructions for sample collection and handling, verification of adequate facilities, and training of study staff, whether single-center or multinational, are all important. Evan Stein: The single best strategy to reduce and anticipate such issues is to incorporate a knowledgeable laboratory professional from an experienced central laboratory in the drafting of the protocol and continue to keep this person involved throughout the trial. A specific laboratory manual and training of clinical sites is also an important aspect of all trials. Christina Ellervik: Conducting a real-time pilot study that includes all the steps from sample collection to storage, retrieval, and analysis often identifies the weak spots, which then can be corrected before the real study begins. Ann Hsing: In epidemiologic studies, we try to learn as much as possible about the determinants of a specific marker or a panel of markers before embarking on an analytic study (i.e., measuring a marker or a panel of markers in cases and controls). This is a standard procedure. For example, we conduct pilot or methodological studies to assess intra- and interperson variation of a specific marker, such as melatonin, sex steroids, or metabolomic profiles/patterns, within and between assay variations, and the impact of covariates on marker concentration or variation. These studies are usually carried out in healthy individuals (controls) first. We then evaluate factors, such as age, race, sex, body size, medication use, chronic conditions, and other factors that might impact the levels of this marker or a panel of markers. Amar Sethi: It is important to realize that statistical analysis of laboratory data must not be based solely on analytical accuracy and precision. If possible, studies should be done to evaluate the effect of preanalytical variations on the resulting accuracy (difference from analyte measurement at collection and analysis) and precision. If a minimal accuracy criterion must be met to avoid exclusion of individuals from further trial participation, more stringent handling and processing procedures should be instituted, especially when the safety of participants is of concern. When higher imprecision is seen as a result of increased variation in preanalytical procedures, such information needs to be considered in statistical power calculations. The effect of variation in specimen processing (e.g., centrifuge speed, platelet contamination, time from collection until processing) or from processing to storage (short-term stability at room temperature, 4 °C, etc.) should be studied. The potential for enzymic (e.g., proteases or nucleases) degradation or for nonspecific loss of the analyte of interest (e.g., binding to the surface of the collection tube) should be investigated and, if possible, remedied by adding stabilizers. Finally, a situation that is usually overlooked in clinical trials is the potential of interference by a novel drug, which can affect the accuracy of determining some analytes. What resources are available for investigators when they begin to design their trials or sample selection processes? David Morrow: For the most part, as I see this as dependent on involvement or consultation of individuals with sufficient experience and expertise. Commercial research laboratories often have well-vetted procedures for standard analytes but may have limited or no experience with investigational assays. Christina Ellervik: The Biospecimen Reporting for Improved Study Quality (BRISQ) report is a useful tool. In this report, critical issues in biospecimen handling are described, and I think you will easily understand, if you're a clinician and not a specialist in clinical chemistry, that consulting a clinical chemistry laboratory is essential in planning a trial or epidemiologic study. Evan Stein: These resources are now fairly standardized for large NIH and major pharmaceutical trials but are not that easily available for individual researchers or for the many small biotech companies whose main focus and experience have been in preclinical drug development. In my experience, the very large central laboratories actually have limited numbers of professionals with experience in conduct of clinical trials, preanalytical variables, and protocol development and conduct. These aspects are often handled by the central lab's business development, resulting in minimal direct contact or discussion between the laboratory professionals and the pharmaceutical team developing and running the trial. There are fortunately some midsize and smaller central and academic laboratories where such expertise is readily available. Ann Hsing: I rely on my laboratory collaborators. They are the experts in the specific marker we are planning to measure, so I learn from them and tap into their expertise. We work together to design a sound and better study. Collaboration and knowledge sharing are the keys to success. It is critical to share credit fairly with our laboratory collaborators to build a long-term collaborative partnership. I also recommend the National Cancer Institute's Biorepository and Biospecimen Research Branch best practices and SOPs (http://biospecimens.cancer.gov/default.asp); and the International Society for Biological and Environmental Repositories information on best practices (http://www.isber.org/?page=BPR). Amar Sethi: An expert laboratorian with knowledge of and experience in the measurement of the biomarkers to be studied should be consulted and potential preanalytical sources of error should be identified. The data gathered from these efforts should be provided to the investigators and statisticians for incorporation into trial design. Sample and analyte integrity can be a difficult issue in longitudinal studies since samples often are collected long before it is known which markers might be tested. Is there a technology or a process that you recommend for samples being collected now that will improve stability of most analytes so that future investigations will not suffer from poor sample quality? David Morrow: For our studies, in which we are assessing predominantly protein biomarkers, we place an emphasis on short processing times, and we transition to storage at −70 °C as soon as possible. We store longer term in the vapor phase of liquid nitrogen. Use of sampling tubes with protease inhibitors is also an option but can be costly and also may have unanticipated impact for certain analytes. We also aim to dictate appropriate centrifuge times to obtain platelet poor plasma. Christina Ellervik: Technology and processes will depend on the type of samples you collect and what immediate or future downstream analyses you anticipate to carry out. Generally, the less human handling and the more standardization and automation (i.e., in sample processing, transport, storage, and laboratory information systems) the better. Evan Stein: This is an important question. One can never predict what new biomarker will be discovered in the future and what will be the most optimal patient preparation, sample type, sample processing, and storage conditions. One can only suggest that as many types of samples (serum, plasma, etc.) be collected at and other be as as possible, and at −70 °C in This and will a for involved in clinical trials. Ann Hsing: We do not what the future or what markers we will be to in or For example, we not have metabolomic or the knowledge that we would be to in plasma. There will be new technology and new for testing new so it is not possible to have a process that will assure integrity of all markers to be in the The is to be as as possible in our and by processing specimens as soon as possible, usually within to minimize potential from studies are The more we about the stability and of a specific marker, the better we can design our study. For example, certain sex are robust and do not much at °C, require °C storage. Amar Sethi: or may improve stability of some but all analytes from the effects of long-term storage. One retrospective approach for understanding the stability of a novel is to begin long-term stability analysis the preanalytical processes in the study. can the of the analyte the of is identified. This retrospective approach may be it a of to the of the study with to the preanalytical processing, the and the work should be done during of biomarkers for in epidemiologic studies and clinical trials, as as for in the in This work would include studies that the best specimen type, collection, processing, and an and storage protocol and study of and long-term stability of biomarker in the of choice should be of this work could be by the for the NIH a analysis of specimen collection, processing, and storage for a limited of novel biomarkers. laboratories are a potential of samples for biomarker What are the to these types of David Morrow: These samples are often rather than and may at room for These aspects to the of analytes that we can Christina Ellervik: samples are usually not collected for research the preanalytical considerations to these samples should not differ from those in a research these samples, we must as much about the patients as in a specific research study. In some these data can be difficult to but in to or are available them to However, in some issues may these samples from being used for research Evan Stein: laboratories do provide a very potential of samples but such samples major for type of clinical These start with the lack of to these samples for other than what has been by the and the and time to obtain review and for other hospital laboratories have limited and storage and none to samples at −70 °C for of In hospital laboratories keep samples for at 4 °C and then A issue is that the information technology and are not for clinical trials. the and expertise to and patient to and out specific samples are not a and are as adding to laboratory this is by the and personnel and storage our clinical trial work in a large hospital academic as a to resources for training it soon that to do patient and clinical research and to our to focus on clinical trials. Ann Hsing: Samples from hospital clinical samples, are resources for biomarker They often in as pilot samples and are useful for certain clinical assessments. The of these samples on the research question. If we are in of certain or of a biomarker as sex or in the or concentration in a or certain these clinical samples would not be the best Since these samples from individuals the for certain conditions or the would be and not of those seen or in the Amar Sethi: The kinds of novel biomarkers that are often employed in clinical trials are not under the handling and processing used in hospital If specimens from are collected for testing, they are to be useful for of many complex and many the discussed issues with sample integrity and storage, are there preanalytical issues related to the information that David Morrow: There can In variability in of analyte resulting from preanalytical issues to and the We are much more likely to an important than to detect a However, the of an analyte a can be by preanalytical For example, of from of tubes or handling at higher might to the of in an of Christina Ellervik: have to and all the preanalytical variations that to be taken into consideration and for samples in studies. I think the in this is that possible variation in the preanalytical process that you can think of will impact the study the of all preanalytical analytical and biological variation will impact study thus, equally important to address the potential preanalytical issues and of their Evan Stein: This is an important question that can impact the and of the results. For example, it is important in and trials to the time of the last before sample collection as this blood and used in These which these are often and by the central may also impact patient or exclusion in a clinical trial. Ann Hsing: For most samples used in epidemiologic studies, we usually require information on time of collection, whether the blood was collected during the time between blood collection and processing, used or blood processing storage and and procedure used during collection or We also whether the samples are or are These factors may with the assay of specific markers. We also about and during to ensure that specimens are before the For all of our studies, we include to evaluate and assay variation. This is a standard QC procedure in epidemiologic studies. If variation by is on the biological nature of the we would request If an assay does not require much we usually for for and then the of the 2 for analysis. This is not possible as samples from prospective studies are and every needs to be used with and Amar Sethi: In to the discussed issues, information about the of the the specimen can be very when whether data from a particular sample should be collected or included in a study. For example, drug and status, and time of collection are essential to if or variation could impact results. a of data could be especially in the epidemiologic issue related to potential errors is the of storage in which a specimen might be The type and of and could be important in some you give an of an I thought of experience from of trials or studies? David Morrow: We have many with our platelet studies. of the of platelet markers during of it is important to obtain platelet-poor plasma if to assay concentration of a is a of a biomarker where very results are obtained from there is substantial during plasma, and platelet poor plasma. In my it was the with preanalytical variables that to the of to be useful studies and to substantial for researchers in the Christina Ellervik: the preanalytical issues be an the preanalytical considerations are the of the If you the preanalytical process in study, Evan Stein: Unfortunately, collected and a sample, an sample, or a different plasma or at −70 °C of is a over the We never what biomarkers or markers will be discovered in the 5 or and often we appropriate samples, collected and that we could out of the and we would to collect every type of sample possible, and store them under optimal conditions, this is not possible to and human should be considered by the as as investigators and laboratory professionals very on in the planning of all trials. Ann Hsing: The process and quality of the samples are usually but I I could have collected more of blood for testing or the resources to include more samples for testing, so we would have sufficient power to a about certain For example, in many of our studies, we often do not have a large enough sample for including or it difficult to the to these important In epidemiologic studies, for example, for metabolomic studies, we large samples to have sufficient power to out Since resources are it is important to be highly and meticulous in what we do to the of these Amar Sethi: It is the of those the work in the laboratories testing for clinical trials and epidemiologic studies to investigators of the preanalytical issues that could affect the quality of their studies. I the of times investigators have to our laboratory the results they obtained from a study not meet After analysis of their study we to them about the potential for status, or a stability issue that was not and which likely affected their study study from I thought of we to our about the issues we have discussed