Preventing Unintentional Unblinding

Transcription

1 s the world s leading IRT specialist, We see things others don t. Cenduit White Paper Series: Issue 3 Preventing Unintentional Unblinding It s well known that clinical trials have become increasingly complex and costly over the past few decades. The globalization of trials, the addition of extraneous protocol procedures and complex study designs are some of the main contributors to the escalation in clinical trial spending. [1,2] In fact, an industry survey published in 2013 reported that the average cost per patient in a Phase II trial has risen to $38,000 and for Phase III that figure is $40,000 to $42,000 per patient. [3] With all the planning and expense required to launch a successful adequate and well-controlled study, attention to every detail, no matter how small, is critical. This includes details that help to make certain that the study is free of any bias. ccording to ICH E9, the most important controls in avoiding bias are randomization and blinding. [4] Randomization was covered in detail in a previous paper and we will now review to study blind, sometimes called the mask, as well methods of avoiding unintentional There are additional unblinding and partial unblinding. potential sources of bias and blinding addresses at linding voids ias least three of these. There are many ways bias could be introduced into clinical research and regulatory agencies have produced guidance on techniques to eliminate these sources. Randomization addresses treatment bias by removing the decision of treatment assignment from the physician. This takes away the temptation of assigning placebo or experimental treatment to stronger, healthier patients

2 while assigning known controls to those who are more ill. There are additional potential sources of bias and blinding addresses at least three of these. Performance bias occurs when a physician administers care to patients unequally. This can easily happen if it is known that one patient is receiving placebo while another is receiving active treatment. Such knowledge can also lead to detection bias, meaning that the medical staff may unequally assess the health conditions of different treatment groups. For example, the staff may be more conservative in indicating improvement in a placebo patient than in one receiving active treatment. On the other hand, an investigator may be more likely to link the cause of an adverse event to the medication for a patient in the active treatment group. nd attrition bias could result if patients are aware of the medications they are receiving. s an example, a patient who knows he or she is on placebo may be more likely to drop out of the study or to take medications that could result in protocol deviations that could make the patient ineligible for analysis. Thus, preserving the study blind is vitally important if these types of bias are to be eliminated. reaking the lind In an emergency situation, a physician may deem it necessary to break the blind in order to determine if a patient s condition is related to a study medication or to make sure that any care given is not contraindicated. In these situations, an Interactive Response Technology (IRT) system is valuable as it allows a healthcare worker to perform the unblinding rapidly and it documents the event automatically. This functionality is part of every welldesigned IRT system and is provided for patient safety. ut what about unintended blind breaks? The study blind must be maintained during the entire course of the clinical trial Partial unblinding occurs until the last site is closed out and all data sets are completely clean and locked. when someone is able to Until then, all investigators, site staff, sponsor teams and their vendors and determine that some most other participants must not be aware of the treatment being given to any patients are receiving the patients. Neither should they be able to determine which patients are on the same treatment. same treatment, such as which ones are in group as opposed to group. Meanwhile, there are often other study participants whose duties require them to see unblinded data, such as those on Data Safety Monitoring oards (DSM). Since an IRT vendor is dealing with data sets that contain information about the blind, it is imperative that the company has the following controls in place, at a minimum: Standard Operating Procedures (SOPs) dealing with all aspects of handling data that may expose or partially expose the blind SOPs on reports and reporting procedures as well as data transfers and associated procedures Well-documented training for all staff on these SOPs and on the topic of maintaining study blind System controls that help to ensure unblinding information is not transferred or reported to any unauthorized person 2

3 With these protections in mind, where is the greatest risk of direct unblinding? First, information used by the drug supply company must be distributed only on a need-to-know basis. ny packing slips or similar documentation that may link specific kits or packs to a medication type must never be sent to any unauthorized recipient, such as a blinded staff at the clinical site or sponsor study team. Second, as implied by the SOPs and training mentioned above, any system specifications, reports, data transfers, faxes or other correspondence with study participants who should remain blinded must follow strict procedures to make sure no unintended information is included. Experienced drug supply and IRT vendors have many checks and balances to prevent such mistakes. Until now, we ve mainly discussed breaking the blind directly, enabling an unauthorized person to see the specific treatment that a given patient is receiving. More often though, the risk lies in partial unblinding. What does that term mean and how may it happen? voiding Partial Unblinding Partial unblinding occurs when someone is able to determine that some patients are receiving the same treatment. In these cases, it may not be clear exactly which treatment the patients are on, but it certainly makes it easier to make educated guesses. simple example can illustrate how knowledge of treatment groups can be revealed. Imagine if the study drug is packaged in small kits, each containing four vials. If the investigator is told to give the first patient a vial from kit 101, the next patient gets a vial from kit 102 and the third one gets a vial from kit 101. We would readily conclude that kits 101 and 102 contain different products and that the first and third subjects are in one treatment group, but the second subject is in a different group. Over time, as the more patients enroll and as the site staff make more observations on the patients in each group, it will become easier for them to determine what the actual medications are based on their pooled observations of the subjects. Medication Pack Numbering Linked to Randomization List Let s consider how a similar problem may arise if a sponsor decides to package medication supplies based on their randomization list. This scenario is illustrated It is good practice to in Figure 1 which shows sequential drug kit numbers set up in blocks of four with completely detach the equal numbers of drug and drug. Site 1 is the first active site and when the first kit numbers from the subject is randomized (step #1), the system assigns kit 101 (drug ) and the site randomization list so that the supplies at any given supply for drug is therefore reduced by one kit. Within the IRT configuration, the site appear to have trigger level is set to two for this site and the resupply value is three, so the system random numbers. automatically requests two replacements of drug (step #2). (For a full description of trigger and resupply levels, see the white paper on Trial Supply Management (TSM) here: Note, though, that these kits are sequentially numbered, kits 107 and 108. Next, the second subject is randomized and the IRT assigns kit 103 (step #3). Since kit 102 was skipped, the staff can guess that the first two subjects are likely on the same treatment. If the block size of four is known, then the staff can also safely assume that kits 102 and 104 contain the same medication. This is further confirmed 3

4 Figure 1: Packaging ased on Randomization List Site 1 Site 2 Site 3 Rand List Subjects Subject 1 Subject 2 Subject 3 Site Stock Resupply Resupply Resupply Kit List (1) Subject 1 randomized and kit 101 (drug ) is dispensed; (2) trigger level hit and two kits sent to site to resupply stock of drug ; (3) Subject 2 randomized and dispensed kit 103 (drug ), skipping kit 102 and thereby partially unblinding; (4) Subject 1 returns for dose and given kit 107, again skipping unused kits and thereby revealing they contain different medication than kit 107; (5) trigger level hit and two kits sent to resupply drug ; (6) Subject 3 randomized and previously skipped kit 102 is dispensed. Site personnel reason that this patient is on different treatment than first two subjects. (7) Resupply sent to replenish supplies, but gap in kit sequence numbers again indicates different treatments contained. when subject 1 returns for the next dose and kits 102 and 104 are skipped and kit 107 is dispensed (step #4). The system will again order a resupply of drug as the trigger level has been hit once again (step #5). The site staff likely realizes that the replacement kits contain the same medication as those already dispensed. The next patient randomized is assigned kit 102 (step #6) and a resupply of drug is therefore needed. The IRT system automatically includes a pack of drug with the two packs of based on its forecast of the need at the site, but notice the kit numbering in the resupply container. The shipment contains kits numbered 105, 106 and 113. gain it will be rather obvious to the site staff that kits 105 and 106 contain one study medication while kit 113 has the other due to the gap in numbering. We learn from this scenario that it is poor practice to link the medication pack lists to the randomization list; yet, some sponsors have insisted on designing studies in this manner against 4

5 Figure 2: Kit List Sorting 2 2 2C 540 Subject Subject Subject 3 Subject 2 Subject Subject 2 Subject Subject The Kit List in Figure 2 appears to be random, but as subjects are randomized a pattern begins to emerge as shown in Figure 2. The Kit List was clearly sorted by treatment group or a variable related to it. est practice for listings and reports is shown in Figure 2C where the list is simply sorted by kit number. the advice of their IRT vendor. It is good practice to completely detach the kit numbers from the randomization list so that the supplies at any given site appear to have random numbers as shown in Figure 2. Report and Data Sorting Most studies using an IRT system follow a best-practice similar to the one illustrated in Figure 2 so that the inventory appears to have completely random numbering. It is obvious, though, that this apparent randomness has an underlying method and is linked to an unblinded list somewhere in the system so that the IRT can maintain balance throughout the study. If any of the hidden data is ever revealed unintentionally, partial unblinding could occur. For example, consider what would happen if the list in Figure 2 is shown on an inventory report distributed to individuals who are blinded to treatment. Suppose the first four subjects are assigned the following kits in this order: 540, 192, 298, 209. y looking at the report, we begin to see a pattern emerging and can guess that if the next patient receives kit 139, then he or she is in the same treatment group as the patients receiving kits 540 and 209 (see Figure 2). Clearly the kit list report has been sorted by some hidden variable linked to treatment group. Similar partial unblinding could occur if a report or list is sorted by batch number or lot expiry dates. Therefore, best practice would dictate always sorting lists and reports by kit number as shown in Figure 2C. The same applies to other study documentation and communications such as shipment requests and packing lists, site stock reports, IRT system notifications and so on. 5

6 Event Driven Drug Supply huge advantage of IRT systems is the ability to automatically drive the clinical supply chain to make sure that sites and depots don t run out of stock. However, if the resupply strategy is tied directly to specific events, then study team members may begin to see patterns developing that could partially unblind the treatment. For example, suppose we are running a trial with an expensive active drug and comparator in a ratio of 2:1, respectively, and that the initial supply to each site is only three kits (two active, one comparator). If the first site randomizes a patient and immediately, a resupply request is issued for one replacement kit, site staff and sponsor teams will likely guess that the single resupply kit is the same treatment as the kit just used; further, if another randomized patient receives that resupply kit, it will be evident that the new patient and the first one are on the same treatment. Now suppose that a patient is randomized at the second site and no resupply is ordered. Study team members and anyone else viewing the blinded inventory shipment reports will be able to guess that the patient just randomized must have received the active drug since no resupply was immediately ordered; they realize that a second active kit is still at the site. Thinking back to the first site, they would now have additional information to help them guess that the patient randomized there is on the comparator. Otherwise the system would not have ordered a resupply kit right away. Such an event-driven set-up is obviously too transparent and creates too many risks regarding the integrity of the study blind. To overcome this potential problem, the IRT and drug supply vendors will recommend a variety of options, such as including an extra comparator kit in each initial shipment to the sites or a similar strategy that will preserve the blind. y recommending appropriate solutions and best practices, an experienced IRT vendor can provide the necessary guidance to help ensure the quality and integrity of the study design and its execution throughout the trial s lifecycle. Stock-out Issues nother potential problem that could lead to partial unblinding involves a site stock-out for one drug. Suppose patient C arrives at a site where there are still two packs of study drug in inventory, but the IRT tells the investigator that the patient cannot be randomized at this time and will have to return to the site at a later date. Then another patient, DEF, arrives at the same site and is successfully randomized and assigned one of the two kits at the site. The site staff will realize that these two patients were assigned to different treatment groups. They will also realize that any patient assigned the remaining kit in the site inventory is on the same treatment as the most recent patient, DEF. To avoid such partial unblinding, there are at least two solutions that the IRT can easily implement. The first solution would be to freeze all randomizations whenever a stock-out of one type of medication occurs. Randomizations would then restart once a resupply shipment is received. It s also worth noting that it is good practice in these situations to include more than one drug type in the resupply shipment to make it more difficult for site staff or those seeing shipment reports to link the resupply to any treatments already dispensed. The IRT system can easily be configured to ensure that each shipment includes more than one drug type. second solution would be to use forcing. s described in a previous paper, forcing means that if a patient 6

7 is randomized to a treatment that is currently not in stock at the site, the IRT automatically assigns the patient to a treatment that is currently available. Then the system assigns a higher probability that the next patient in the study will be assigned to the treatment group that was just skipped due to the stock-out. While forcing is not technically random, it is permitted by regulators as long as it is not occurring frequently. y recommending appropriate solutions and best practices, an experienced IRT vendor can provide the necessary guidance to help ensure the quality and integrity of the study design and its execution throughout the trial s lifecycle. [5] Conclusion Maintaining the study blind is a critical part of maintaining the integrity and validity of any clinical trial. Experienced IRT providers have a variety of SOPs, system controls and well-trained members of staff to ensure that all blinded reports, data transfers and study documentation and communications are sanitized and free of any sorting or data that could even partially reveal the study medications in inventory or those assigned to patients. There are also a number of best practices that your IRT vendor should recommend in order to avoid unintentional partial unblinding. Some of these methods include using completely randomized kit or pack list numbering schemes, avoiding single pack dispensing events, dealing with stock-out issues effectively and always including at least two drug types in any shipment. We have addressed some of the more common partial unblinding scenarios that may arise and it is not feasible to list every conceivable way in which the study blind could be compromised. However, it is clear that sponsors should seek the advice of an experienced IRT provider when designing the supply chain to make certain that all of their significant investment in their drug development research will result in an adequate and well-controlled study of the highest caliber. Endnotes [1] Getz, Kenneth., M; Campo, Raphael., S; Kaitin, Kenneth I., PhD; Variability in Protocol Design Complexity by Phase and Therapeutic rea, Drug Information Journal, [2] Kaitin, Kenneth I., PhD et al, Tufts Center for the Study of Drug Development, Outlook [3] Clinical Development and Trial Operations Protocol Design and Cost per Patient enchmarks, Cutting Edge Information, [4] ICH E9: Guidance for Industry: Statistical Principles for Clinical Trials, [5] rief Synopsis of Modern Randomization Methodologies and Technologies, Cenduit White Paper, Contact us, and learn how Cenduit sees things others don t. corp.communication@cenduit.com web: s the world s leading IRT specialist, we see things others don t. ringing together expertise, technology, innovation, and vision Meeting all randomization, trial supply, and patient management needs Seeing exactly what our customers need and how to help them succeed