FDA Guidance "Development and Licensure of Vaccines to Prevent COVID-19" - sample size situation for phase 3 studies

Last week, FDA issued its guidance for industry "Development and Licensure of Vaccines to Prevent COVID-19". Unlike the usual FDA guidance where FDA issues the draft guidance with a comment period, this guidance is immediately effective as the final version upon its issuance.

The guidance sets its expectations for the development and licensure of vaccines to prevent coronavirus disease (COVID-19), including considerations for manufacturing, nonclinical and clinical studies, and post-licensure requirements. Also, Dr. Peter Marks, director of the Center for Biologics Evaluation and Research, shed light on the reasoning behind the agency’s 50% efficacy threshold and where the agency stands on challenge trials and emergency use authorizations (EUAs). See the article "Marks on COVID-19 vaccine efficacy, EUAs and challenge trials"

The guidance provided details about the pivotal (phase 3) efficacy and safety study. For phase 3 study, the primary efficacy endpoint should be "the incidence of laboratory-confirmed symptomatic COVID-19" specified in the guidance as the following: 

Section E of the guidance 'Statistical Considerations' provided the specific requirements for the statistical success criteria (i.e., point estimate of vaccine efficacy at least 50% and the lower bound of the alpha-adjusted confidence interval at least 30%). 

What does the vaccine efficacy of 50% mean?

Vaccine Efficacy (VE) = [(COVID-19 attack rate in the unvaccinated group - COVID-19 attack rate in the vaccinated group) / COVID-19 attack rate in the unvaccinated group] * 100%

where the attack rate is equivalent to the incidence rate. 

Using the relative risk (RR) or risk ratio [= (incidence of COVID-19 cases in the vaccinated group) / (incidence of COVID-19 cases in the unvaccinated group)], VE = 1 - RR.

Suppose after 3-6 months observation period post-vaccination, there are 100 cases of laboratory-confirmed symptomatic COVID-19 patients in the unvaccinated group and 50 cases in the vaccinated group, assuming the total follow-up time (person-time) are similar between the unvaccinated and vaccinated groups, the VE will be calculated as (100-50)/100 *100%= 50%.

In practice, the person time (PT) in the vaccinated group and unvaccinated group will be included in the calculation of attack rate or incidence rate where the attack rate = the number of cases observed in the vaccination group or unvaccinated group / Person Time (PT) in the vaccination or vaccination group. If the Poisson regression method is used, the person time will be used in the model as an offset variable. Person time (PT) is the same concept as person-year or patient-year and can be calculated in the same way as the person year with a perhaps different unit. 

VE at least 50% is a point estimate - not dependent on the sample size. For a much smaller trial, if we have 5 cases in the vaccination group and 10 cases in the vaccination group, the VE will still be 50%.

For sample size calculation, we will also need to know the confidence interval. As indicated in the FDA's guidance,  the lower bound of the appropriately alpha-adjusted confidence interval around the primary efficacy endpoint point estimate needs to be greater than 30%.

How to calculate the sample size? Which parameters do we need to calculate the sample size? 

The commercial software (such as EAST, SAS Proc Power, PASS, NQuery Advisor) can all be used to calculate the sample size. In a hypothetic example in the previous post, the sample size was calculated using EAST module for Ratio of Poisson Rates. 

Matthew M. Loiacono had a thesis on "Sample Size Estimation and Power Calculations for Vaccine Efficacy Trials for Exceedingly Rare Diseases" where two SAS macros were developed to estimate the sample sizes: one based on the Exact Conditional Test and one based on the Z Test Normal Approximation.

The sample size calculation will need the following five parameters:

• Incidence of laboratory-confirmed symptomatic COVID-19 cases in the unvaccinated group 
• True efficacy of test vaccine under the alternative hypothesis (according to FDA guidance, this is 50%) 
• Minimum efficacy of test vaccine, under the null hypothesis (according to FDA guidance, this is 30%)
• Power: pre-specified statistical power desired to achieve (usually 80% or 90%) 
• Alpha: pre-specified maximum one-sided level of the test (usually 0.05 for experimental level)

The most critical parameter is the incidence of laboratory-confirmed symptomatic COVID-19 cases - it is difficult to predict; it shifts with geographic location and time; it is impacted by the COVID-19 prevention strategies and policies. In general, the lower the incidence of COVID-19 cases, the larger the sample size is needed for phase 3 study to demonstrate the vaccine efficacy. 

Assuming the incidence of COVID-19 is 0.01 in unvaccinated (placebo) group, with 80% statistical power and alpha = 0.05, using the SAS macro based on Exact Conditional Test method, 33868 volunteers need to be randomized (estimated 254 COVID-19 cases observed) to detect the vaccine efficacy with point estimate at least 50% and lower bound of 95% confidence interval greater than 30%. 

Sample Size for COVID-19 Vaccine Phase 3 Study

Vaccine development for COVID-19 is at historic speed. Several companies have already had vaccines in the early phase of clinical trials. Leading the pack are AstraZeneca / Oxford University and Moderna / NIH who are targeting July for starting the late-stage phase 3 studies. Phase 3 study is pivotal in demonstrating that the vaccine is safe and effective in the general population including those at high risk of contracting COVID-19 and those with underly diseases.

There are quite some discussions about the sample size of the phase 3 study - the sample size for phase 3 study should be adequate to provide sufficient statistical power to demonstrate the vaccine's efficacy in preventing the COVID-19 infection and also adequate for regulatory agencies to assess the safety of the vaccine - sample size should be big enough so that the rare event (if any) can be observed. The sample size is being proposed to be at least 30,000 volunteers.

• FDA Shouldn't Authorize Coronavirus Vaccines Unless They're Tested on at Least 30,000 People: Experts
• Vaccine experts want the FDA to commit to 30,000 people in Covid-19 vaccine trials
• Lawmakers ask FDA to outline COVID-19 vaccine approval process
• Opinion: Here’s why the FDA may approve a Covid-19 vaccine before the November elections, according to Jefferies’ biotech-research team

For pivotal clinical trials, the sample sizes depend on the study design and the primary efficacy endpoint; and estimated based on assumptions.

The study design will be traditionally randomized, double-blinded, placebo- or active-controlled, parallel-group design (not human challenge design even though it has been pushed by some people) - see a previous post "Human Challenge Study Design for Covid-19 Vaccine Clinical Trials?".

• Human challenge trials with live coronavirus aren’t the answer to a Covid-19 vaccine
• Human Challenge Study Design for Covid-19 Vaccine Clinical Trials?

The primary efficacy endpoint is the incidence of symptomatic COVID-19. Moderna has finalized the study design for its phase 3 study and it says that the study will include 30,000 volunteers and the primary and secondary efficacy endpoints as the following:

"The primary objective of the trial, which is set to start in July, is to assess the ability of mRNA-1273 to prevent symptomatic COVID-19 disease. Secondary endpoints will assess the ability of mRNA-1273 to prevent hospitalization and infection with SARS-CoV-2."

•  Fauci: Moderna’s Phase 3 Covid-19 Vaccine Trial Of 30,000 Individuals Will Begin In July
• Moderna finalizes design of phase 3 COVID-19 vaccine trial ahead of July start
• Exclusive: U.S. plans massive coronavirus vaccine testing effort to meet year-end deadline

AstraZeneca/Oxford's COVID-19 vaccine enters phase 2/3 clinical trial. Their proposed sample size is much smaller than 30,000 subjects mentioned by US experts. We can also notice that they propose to use the vaccine against meningococcal bacteria as the control (instead of placebo). 

"Researchers at the University of Oxford have begun enrolling subjects in a phase 2/3 clinical trial of AstraZeneca-partnered COVID-19 vaccine AZD1222. The next stage of the program, which follows a 1,000-subject phase 1, is set to enroll 10,260 people in the U.K. to generate results to support the first shipments to customers in September."

"Once the vaccine moves into phase 3, the researchers will limit enrollment to people age 18 years and older. Adult participants in the phase 2 and 3 trials will be randomized to receive one or two doses of AZD1222 or a vaccine against meningococcal bacteria that will serve as the control.

The use of an active vaccine as a control is intended to ensure participants are unable to tell whether they received AZD1222 based on side effects such as soreness at the injection site. In the absence of such effects across both groups, participants could determine whether they had received the vaccine and make behavioral changes that skew the results of the study. "

Baseline on the study registration on clinicaltrials.gov "A Phase 2/3 Study to Determine the Efficacy, Safety and Immunogenicity of the Candidate Coronavirus Disease (COVID-19) Vaccine ChAdOx1 nCoV-19", we can see the following:

• The study consisted of different sub-groups (different age groups and different duration of the follow-up period).
• The primary efficacy endpoint is the number of biologically confirmed (PCR positive) symptomatic cases of COVID-19
• The primary safety endpoint is the occurrence of serious adverse events (SAEs) throughout the study duration.

It is not clear what the assumptions are used for estimating the sample size (30,000 subjects for Moderna's phase 3 study or 10,260 subjects for AstraZeneca/Oxford's phase 3 study). Perhaps the sample size is more based on the experiences rather than the calculation based on the solid assumptions.
In order to estimate the sample size, we will need to know the incidence rate of symptomatic COVID-19 in the control group (subjects who receive a placebo or a none anti-COVID-19 vaccine) and then the effect size (how much reduction in the incidence rate of symptomatic COVID-19 in the vaccine group (subjects who receive COVID-19 vaccination) - both of these are difficult to obtain.

• Estimating COVID-19 Prevalence in Symptomatic Americans
• COVID-19 Cases in U.S.

The incidence rate of symptomatic COVID-19 can vary significantly depending on the timing, the location, and the prevention and COVID-19 control strategies (i.e., stay-at-home, quarantine, social distance).

Back in January and February, the incidence rate of symptomatic COVID-19 would be very high. But now the COVID-19 situation in China has been under control. It is no longer feasible to test the efficacy of the COVID-19 vaccine in China. There are reports that COVID-19 vaccine researchers in China are looking for foreign sites to recruit the volunteers to test the efficacy of their vaccine candidate.

In the US, the incidence rate of symptomatic COVID-19 would be very high in New York and New Jersey in March/April time, now the states with high incidence rates have shifted to the southern states such as Texas, Arizona, North Carolina.

For phase 3 study to demonstrate the efficacy against the COVID-19, a sufficient number of subjects need to be included in the study so that (hopefully) a sufficient number of symptomatic COVID-19 cases can be observed (more in the control group and less in COVID-19 vaccine group). If subjects are recruited in areas with a high incidence rate, it will be quicker to accrue the number of symptomatic COVID-19 cases. Ironically, with strict COVID-19 prevention/control strategies, by the time the phase 3 studies start, the situation may be under the control and the incidence rate may be too low to accrue enough symptomatic COVID-19 cases. In the article below, a drop in coronavirus cases was listed as one of the biggest risks for Moderna's phase 3 study.

Here Are the 3 Biggest Risks for Moderna Right Now

"3. A drop in coronavirus cases

Of course, a drop in coronavirus cases is great news for everyone. But in order for Moderna and other vaccine makers to test their investigational products, the virus must be actively circulating. In an outbreak situation, the vaccine or placebo is administered to a group of healthy volunteers. If a high number of placebo participants get sick and those who received the vaccine don't, it's likely the vaccine is working. But if the virus is hardly present, it would be impossible to draw such a conclusion.

In the U.S., coronavirus cases recorded by the Centers for Disease Control and Prevention are cumulative, so they will continue to grow. And some states are still seeing spikes. But nationally, the number of people seeking medical attention for symptoms has been on the decline. If the trend continues, it may present difficulties for Moderna and rivals conducting trials in the U.S. to prove vaccine efficacy.

That doesn't mean the vaccine is doomed, but testing it could become more complicated. If virus circulation drops considerably, researchers may conduct a "challenge" trial. That means healthy volunteers are immunized, then exposed to the virus. There also is the possibility of conducting trials in other areas where the virus is on the rise. At this point, Moderna hasn't said it would turn to either of these alternatives."

The primary efficacy endpoint of "biologically confirmed symptomatic cases of COVID-19" belongs to the count data. Given the incidence rate is very low among the general population, the data can be assumed to follow a Poisson distribution or negative binomial distribution. The sample size calculation will then need to be based on Poisson rates or negative binomial rates. 

Hypothetically, the statements about the sample size for phase 3 COVID-19 vaccine studies can be something like this assuming 50% reduction in symptomatic CIVID-19 cases in the vaccine group:

Assuming that the incidence rate (Poisson mean) of subjects with symptomatic COVID-19 case is 0.003 (0.3%) in control group and 0.0015 (0.15%) in COVID-19 vaccination group, 32,673 subjects needs to be randomized to have 80% statistical power to detect the treatment difference."

In the US, we saw the rise in coronavirus cases - it is bad, really bad, but ironically it is good for vaccine clinical trials - it is easier and quicker to accrue a sufficient number of symptomatic COVID-19 cases and it requires less sample size for phase 3 studies to demonstrate the difference between vaccinated and control groups. As Dr. John Skerritt from the Department of Health, Australia said about the COVID-19 pandemic: "Do not waste a good crisis". 

Neutralizing Antibodies: Active Immunization and Passive Immunization Against Covid-19

Generally speaking, a person achieves immunity to disease through the presence of neutralizing antibodies, or proteins produced by the body that can neutralize or even destroy toxins or other disease carriers.  Active immunization is the process of vaccination to prevent an infectious disease by activating the body’s production of antibodies that can fight off invading bacteria or viruses.

The neutralizing antibodies (so-called because they stop the virus from being able to infect cells) can also be obtained from outside the body and can be given the recipients as a therapy for the prevention or treatment of a disease. Passive immunization is the process of administering the antibodies against a particular infectious agent.

An easy example is the antibodies against the rabies. In order to get immunity against rabies virus, we can receive rabies vaccine. Usually 2-3 weeks after the administration of the rabies vaccine (usually several courses), the neutralizing antibodies against rabies will develop in recipient’s body – this is called vaccine-induced active immunity. However, rabies antibodies can also be obtained from the human plasma donated by people in plasma collection centers scattered throughout the United States. The pooled plasma can be fractionated, and rabies antibodies can be obtained – these products are called RIG (Rabies Immune Globulin or hyperimmune globulin against rabies). The RIG can be given to the people to obtain so called ‘passive immunity’. If someone had potential exposure to rabies (for example, bite by wild animals) and had no record of rabies vaccination, the RIG should be immediately given to achieve the passive immunity for short period protection.

The same process of active immunity and passive immunity applies to the Covid-19 situation. Below is a table to compare the active immunity vs. passive immunity in Covid-19 situation:

Active Immunity	Passive Immunity
Relies on neutralizing antibodies against SARS-CoV-2 (the virus causing Covid-19)
active immunity results when exposure to a disease organism triggers the immune system to produce antibodies to SARS-CoV-2	passive immunity results when receiving a therapy containing neutralizing antibodies against SARS-CoV-2
Neutralizing antibodies are generated by our own immune system	Neutralizing antibodies are manufactured or obtained outside the body and then given to the recipients
Active Immunity can be obtained in two ways: Natural Immunity: obtaining immunity because of infection with Covid-19 (whether it is symptomatic or asymptomatic) Vaccine-Induced Immunity: obtaining immunity by receiving the vaccine (vaccination) that won’t make someone sick, but will trigger the body to make neutralizing antibodies), which is known as vaccine-induced immunity	passive immunity is provided when a person is given neutralizing antibodies. Antibody-containing blood products: convalescent plasma obtained from Covid-19 recovered patients Hyperimmune products (containing concentrated neutralizing antibodies) Manufactured antibody products
It will take a while for the body to generate neutralizing antibodies	Off-the-shelf, ready to use
Immunity (once obtained) will be longer	Immunity will be shorter
Companies who are working on vaccines: see previous post “Coronavirus Vaccine Tracker - Developing Vaccines Against Covid-19 “	Key players in the field (examples only): Convalescent plasma – Mayo Clinic Hyperimmune globulin – Grifols Neutralizing antibodies cocktail - Regeneron, Eli Lilly, Sorrento Therapeutics
Clinical trials in ‘healthy’ volunteers	Clinical trials in Covid-19 patients
Clinical trials to demonstrate the effect in prevention (prevent from symptomatic Covid-19)	Clinical trials to demonstrate the effect in treatment (speed up the recovery of the symptomatic Covid-19 patients and decrease the mortality)
The development process is longer	The development process is shorter
Larger sample size for clinical trials required for demonstrating the efficacy in prevention of Covid-19	Smaller sample size for clinical trials required for demonstrating the efficacy in the treatment of Covid-19

References:

• What to Know About Active Vs. Passive Immunity—And Why Both Matter With COVID-19
• Explainer: What are antibody therapies and who is developing them for COVID-19?
• A coronavirus vaccine is still months away, but an antibody treatment could be closer
• Coronavirus Antibody Therapies Raise Hopes—and Skepticism
• "Immunity passports" in the context of COVID-19
• CDC: Immunity Types
• CDC: Rabies 
• China begins phase 1 clinical trials of neutralizing antibody treatment for COVID-19

Coronavirus Vaccine Tracker - Developing Vaccines Against Covid-19

Ultimately, to win the battle against the Covid-19, we will rely on a safe and effective available in very large quantities. Pharmaceutical companies (large or small), biotech companies, academic, and governmental agencies have all rushed into the vaccine development field to fight the Covid-19. We hope that some vaccines will eventually become the winners.

The New York Times has a website for "Coronavirus Vaccine Tracker". The tracker grouped the vaccines into four categories:

• Genetic Vaccines developed by Moderna, BioNTech/Pfizer, Inovio, ...
• Viral Vector Vaccines developed by Oxford/Astrazeneca, CanSinoBIO, Johnson and Johnson,...
• Protein-Based Vaccines developed by Novavax, GSK, Baylor College of Medicine,...
• Whole-Virus Vaccines developed by Sinovac, Sinopharm,...

So far, some vaccines have gone beyond the pre-clinical stage and progressed into the clinical trial stage. Below is a timeline for those vaccines already in human trials: 

Also, this map shows where coronavirus vaccines are being tested around the world.

However, vaccine development is a lengthy process consisting of phase 1 -> phase 2 -> phase 3 clinical trials before the vaccine can be approved for use. In phase 3 study, the candidate vaccine must be demonstrated to be safe in the general public (with different age groups including the population with underly conditions)

With so many clinical trials initiated or to be indicated, there may be a shortage of volunteers for these studies. The extreme measures to control the Covid-19 (guarantee, stay-at-home, face-masks,...) are necessary to prevent the virus spread, however, it will lower the incidence rate of Covid-19 - consequently, the phase 3 studies for vaccines will require larger sample size with more participants in order to have the adequate statistical power and accumulate a sufficient number of Covid-19 infection cases to establish the efficacy of the candidate vaccine. The phase 2 study will include around 1000 volunteers and the phase 3 study will be even bigger with tens of thousands of volunteers. For those vaccines already in the clinical trial stage: the University of Oxford's phase 1/2 trial had a sample size of 1,090 participants. Moderna's vaccine candidate is being tested in phase 2 study with 600 participants. Its phase 3 study is planned to start this July and will include 30,000 participants to test if the vaccine is safe in general population and if the vaccine is effective in preventing symptomatic Covid-19.


Can we really expect to have a safe and effective Covid-19 vaccine available in a year? It is unlikely, but some people are cautiously optimistic. Read the panel discussions below:

Can a Vaccine for Covid-19 Be Developed in Record Time?

A discussion moderated by Siddhartha Mukherjee

Should Drug Safety (or Pharmacovigilence) Group be Provided with the Randomization Schedule for Blinded Studies?

To avoid the conscious and unconscious bias in safety and efficacy assessment, clinical trials are usually designed as double-blinded studies whenever the blinding is feasible. Double-blind indicates that the treatment assignments are concealed to the investigator and the study participants. The blinding is usually extended to the entire study team including the sponsor, CRO, and vendors. If too many study participants are unblinded during the study, the study integrity will be compromised.

However, not everybody is blinded to the treatment assignment. On the Sponsor side, the clinical trial material (CTM) management group is usually unblinded and has full access to the treatment assignments - because they need to make sure that the correct drugs (active or control) are packaged, labeled, shipped, and dispensed. CTM group will track the inventory at the study sites to make sure the study materials are available at all open sites.

The drug safety group or pharmacovigilance group (PVG) may also request for full access to the treatment assignment and they claim the full access to the treatment assignment is needed for serious adverse event reporting.

It is true that the regulations require the drug safety group to report the 'serious and unexpected suspected adverse reaction (SUSAR)' to regulatory agencies, investigators, and IRBs/ECs.

• 21CFR 312.32 IND safety reporting
• Directive 2001/20/EC of the European Parliament and of the Council
• Breaking the Blind in Clinical Trials & Reporting to Health Authorities, Investigators & IRBs/Ethics Committees
• Clinical Safety Data Management: Definitions and Standards for Expedited Reporting
• Safety assessment in Clinical Trials and Beyond

Code of Federal Regulation regarding IND Safety Reporting says:

"(i) Serious and unexpected suspected adverse reaction. The sponsor must report any suspected adverse reaction that is both serious and unexpected. The sponsor must report an adverse event as a suspected adverse reaction only if there is evidence to suggest a causal relationship between the drug and the adverse event, such as:

(A) A single occurrence of an event that is uncommon and known to be strongly associated with drug exposure (e.g., angioedema, hepatic injury, Stevens-Johnson Syndrome);

(B) One or more occurrences of an event that is not commonly associated with drug exposure, but is otherwise uncommon in the population exposed to the drug (e.g., tendon rupture);

(C) An aggregate analysis of specific events observed in a clinical trial (such as known consequences of the underlying disease or condition under investigation or other events that commonly occur in the study population independent of drug therapy) that indicates those events occur more frequently in the drug treatment group than in a concurrent or historical control group."

EU has similar regulations. According to EU directive "on the approximation of the laws, regulations and administrative provisions of the Member States relating to the implementation of good clinical practice in the conduct of clinical trials on medicinal products for human use"

Article 17 Notification of serious adverse reactions 1. (a) The sponsor shall ensure that all relevant information about suspected serious unexpected adverse reactions that are fatal or life-threatening is recorded and reported as soon as possible to the competent authorities in all the Member States concerned, and to the Ethics Committee, and in any case no later than seven days after knowledge by the sponsor of such a case, and that relevant follow-up information is subsequently communicated within an additional eight days. (b) All other suspected serious unexpected adverse reactions shall be reported to the competent authorities concerned and to the Ethics Committee concerned as soon as possible but within a maximum of fifteen days of first knowledge by the sponsor. (c) Each Member State shall ensure that all suspected unexpected serious adverse reactions to an investigational medicinal product which are brought to its attention are recorded. (d) The sponsor shall also inform all investigators.

It is true that the drug safety group needs the treatment assignment information to assess the causal relationship of a SUSAR event to the study drug. If a SUSAR occurs in a placebo group, the event will then not be required to be reported.

Unlike the STM group, the drug safety group only needs the treatment assignment for individual subjects at the time when a SUSAR is reported. It is concerning that the drug safety group is given full access to the treatment assignment for all subjects. Drug safety group personnel sometimes can accidentally communicate the treatment assignment information outside the drug safety group (to the investigator and to the blinded study team) and causing the accidental unblinding of the subject.

I just read the FDA’s review document for a Merck product and noticed the review comments mentioning that drug safety staff should be blinded during the study. Given the potential accidental unblinding caused by drug safety staff, it is prudent to restrict drug safety staff’s access to the randomization codes for ongoing blinded studies.  

https://www.accessdata.fda.gov/drugsatfda_docs/nda/2014/204886Orig1s000MedR.pdf

However, the drug safety group should be given emergency access to the randomization codes. In the situation a SUSAR is reported, drug safety personnel who are handling the SUSAR reporting can log into the interactive response technology (IRT) including interactive web response (IWR) and interactive voice response system (IVR) systems, and obtain the randomization information and treatment assignment for the individual subject with SUSAR reported. 

In summary, the drug safety group or PVG should not be given full access to all randomization codes, but should be provided in a controlled way the access to treatment information for individual subjects who have SUSAR reported. 

Binding Antibodies, nonneutralizing antibodies (n-NAbs), and Neutralizing Antibodies (NAbs)

Last Monday, Moderna announced the positive results from its phase I clinical trial for its mRNA vaccine against Covid-19. The study was listed under clinicaltrials.gov as "Phase I, Open-Label, Dose-Ranging Study of the Safety and Immunogenicity of 2019-nCoV Vaccine (mRNA-1273) in Healthy Adults". This phase I study contains 9 cohorts with 3 different vaccine doses (25 mcg, 100 mcg, and 250 mcg) in three different age groups (18-55, 56-70, and 71 or above years of age). The announced results were from three dose groups in 18-55 years of age. The phase I study was the first step to test the safety and the immunogenicity (i.e. vaccine's ability to trigger an immune response in the body) of the vaccine, but the released preliminary results caused a strong reaction from the wall street.

The immunogenicity data indicated that the binding antibodies were detected in all 45 subjects in three dose groups in 18-55 years of age and the neutralizing antibodies were detected in all 8 subjects in the first four subjects in 25 mcg and 100 mcg groups. It is worth discussing what the difference is between the binding antibodies and the neutralizing antibodies.

Moderna Announces Positive Interim Phase 1 Data for its mRNA Vaccine (mRNA-1273) Against Novel Coronavirus

"Immunogenicity data are currently available for the 25 µg and 100 µg dose level (ages 18-55) after two doses (day 43) and at the 250 µg level (ages 18-55) after one dose (day 29). Dose dependent increases in immunogenicity were seen across the three dose levels, and between prime and boost within the 25 µg and 100 µg dose levels. All participants ages 18-55 (n=15 per cohort) across all three dose levels seroconverted by day 15 after a single dose. At day 43, two weeks following the second dose, at the 25 µg dose level (n=15), levels of binding antibodies were at the levels seen in convalescent sera (blood samples from people who have recovered from COVID-19) tested in the same assay. At day 43, at the 100 µg dose level (n=10), levels of binding antibodies significantly exceeded the levels seen in convalescent sera. Samples are not yet available for remaining participants.

At this time, neutralizing antibody data are available only for the first four participants in each of the 25 µg and 100 µg dose level cohorts. Consistent with the binding antibody data, mRNA-1273 vaccination elicited neutralizing antibodies in all eight of these participants, as measured by plaque reduction neutralization (PRNT) assays against live SARS-CoV-2. The levels of neutralizing antibodies at day 43 were at or above levels generally seen in convalescent sera."

Moderna reports positive data on early-stage coronavirus vaccine trial, shares surge

"Moderna’s closely watched early-stage human trial for a coronavirus vaccine produced Covid-19 antibodies in all 45 participants, the biotech company announced Monday, sending the company’s shares surging nearly 20%."

"The vaccine also produced neutralizing antibodies against Covid-19 in at least eight participants, the company said. Experts have said neutralizing antibodies appear to be important in acquiring protection."

Vaccines are examples of antigens in an immunogenic form, which are intentionally administered to a recipient (usually healthy volunteers) to induce the memory function of adaptive immune system toward the antigens of the pathogen invading that recipient. In Covid-19 situation, vaccines are developed against the SARS-Cov-2 (the pathogen (the virus) that caused Covid-19. In phase I studies, besides the safety, we want to see if administering the vaccines can generate the antibodies (first binding antibodies, then neutralizing antibodies). Phase I study can fail if there is a safety issue or if no or not enough antibodies are generated in recipients. 

Binding Antibodies: 
Not all antibodies that bind a pathogenic particle are neutralizing. Binding antibodies, or non-neutralizing antibodies (n-NAb), bind specifically to the pathogen (SARS-Cov-2 virus), but do not interfere with their infectivity. that might be because they do not bind to the right region. Non-neutralizing antibodies can be important to flag the particle for immune cells, signaling that it has been targeted, after which the particle is processed and consequently destroyed by recruited immune cells.

Binding antibodies are produced at high levels throughout the life of an infected individual but are characterized by their inability to prevent viral infection. Even though they do not have impact on virus' infectivity, binding antibodies are useful as diagnostic indicators of whether an individual is infected or not.

Neutralizing Antibodies (NAb):
Neutralizing antibodies on the other hand can neutralize the biological effects of the antigen without a need for immune cells. In some cases, non-neutralizing antibodies or insufficient amounts of neutralizing antibodies binding to virus particles can be utilized by some virus species to facilitate uptake into their host cells.

Binding antibodies and neutralizing antibodies are similarly discussed in therapeutic protein products or biological products including monoclonal antibody (mAb) drug. In vaccine studies, immunogenicity is a good thing and is what we want to see. In biological products (protein therapy or mAb), the immunogenicity is a thing we try to avoid - developing the anti-drug antibody will have impact on the efficacy and safety of a biological product or mAb.

Binding antibodies and neutralizing antibodies are measured with different assays (i.e., binding antibody assay and neutralization assay). According to FDA guidance "Immunogenicity Testing of Therapeutic Protein Products — Developing and Validating Assays for Anti-Drug Antibody (ADA) Detection"

"Screening assays, also known as binding antibody assays, are used to detect antibodies that bind to the therapeutic protein product. The specificity of ADA for the therapeutic protein product is usually established by competition with a therapeutic protein in a confirmatory assay. ADAs are characterized further using titration and neutralization assays. Titration assays characterize the magnitude of the ADA response. It is important to characterize this magnitude with titration assays because the impact of ADA on pharmacokinetics, pharmacodynamics, safety, and efficacy may correlate with ADA titer and persistence rather than incidence (Cohen and Rivera 2010). Neutralizing antibodies (NAbs) refer to those ADA with the ability to interfere with interactions between the therapeutic protein product and its target. Neutralization assays assess ADA for neutralizing activity. It is important to characterize neutralizing activity of ADA because the impact of ADA on pharmacokinetics, pharmacodynamics, safety, and efficacy may correlate with NAb activity rather than ADA incidence"

Pre, During, and Post Pandemic: what are the cut points for defining pandemic start/end?

The Covid-19 pandemic will have a lasting impact on clinical trials. The way how the clinical trials are conducted will forever be changed. For ongoing clinical trials that are impacted by the Covid-19, the regulatory agencies have rushed to publish the guidance/guidelines. Many countries have published their own guidance/guidelines for clinical trials in the middle of Covid-19 pandemic. The most significant ones are those by US FDA and EMA: 

• FDA Guidance on Conduct of ClinicalTrials of Medical Products duringCOVID-19 Public Health Emergency
• Guidance on the Management of Clinical Trials during the COVID-19 (Coronavirus) pandemic

The impact of Covid-19 on the ongoing clinical trials is multi-front. I listened to a webinar organized by DIA "Study and Data Integrity Considerations for Clinical Trials Impacted by COVID-19" and the potential impacts of Covid-19 on clinical trials were listed as the following: 

 The impact of Covid-19 on clinical trials is beyond what the table above can summarize. For example, the psychological impact could change the behavior of subjects who participate in the clinical trials - patients may be less compliant with the study protocol and more difficult to retain in the study - healthy volunteers may be less willing to participate in clinical trials. 

One thing for sure is that the Covid-19 will have impact on the study quality, efficacy evaluation, and safety evaluation of the ongoing clinical trials. How to assess the impact is not an easy task. For the statistical analysis plan (SAP), additional sections will need to be included to describe the impact of the Covid-19 on study quality, efficacy, and safety evaluations.  

EMA also issued guidance (Points to consider) for methodological aspects / statistical analyses.

Points to consider on implications of Coronavirus disease (COVID-19) on methodological aspects of ongoing clinical trials

The Points to consider suggested:

"Sponsors are advised to contemplate an analysis of the accumulating trial data in order to evaluate the implications on recruitment, loss of patients during the trial, ability to record data and ability to interpret the treatment effect in light of the pre-, during and post-pandemic measures phases. "

The suggested approach seems to be reasonable. The subjects in the whole study can be grouped into three categories: subjects who were enrolled into the study and completed the study prior to the pandemic start; subjects who were enrolled into the study and ongoing in the study during the pandemic; and subjects who are enrolled into the study after the pandemic. Statistical comparisons can be performed to compare the differences between these groups regarding the subject characteristics, compliance, efficacy, and safety endpoints. The findings from these comparisons may trigger further actions on how the final analyses should be performed. 

The analysis by pre, during, and post pandemic has been discussed in several webinars - it seems to be an approach that people will adopt in handling the statistical analyses for studies that are impacted by Covid-19 pandemic - until the following question is being asked:

How to define the cut points for deciding pre, during, and post pandemic? 

We know that the Covid-19 outbreak started in Wuhan, China, and then spread to other countries (China -> Neighboring countries of China -> European Countries -> United States -> all over the world). The exact date of the Covid-19 outbreak is still in debate and may not be known forever. 

For clinical trials involving multiple countries, are we going to define a cut point for a pandemic start for each country?   

Officially, WHO declared the Covid-19 as a pandemic on March 11, 2020. But we know that by then, Covid-19 had already spread in so many countries.

If the pandemic start is difficult to define, the cut point for the pandemic end will be even more challenging. Covid-19 may stay with us for a long time (until there is an effective and safe vaccine available). 

Human Challenge Study Design for Covid-19 Vaccine Clinical Trials?

The world is desperate to develop vaccines for Covid-19. Pharmaceutical and biotechnology companies are racing to start the clinical trials for Covid-19 vaccines. With the traditional phased approach for drug development (no exception for vaccine development), after the early phase clinical trials, a pivotal phase III study with thousands of volunteer subjects will need to be conducted to demonstrate the efficacy and safety of the vaccine. It is a very lengthy process that may not be successful. With the Covid-19 pandemic and the urgent situation, an alternative approach is desired to expedite the Covid-19 vaccine development. This is why we see the discussions about 'human challenge studies' heating up recently. On October 20, 2020, we saw the news release that the UK starts the first human challenge study of COVID-19 vaccine "Expert partnership to explore and establish Human Challenge studies of COVID-19 in the UK". The study plans to enroll up to 90 volunteers - much smaller in sample size than the COVID-19 vaccine studies with traditional designs. 

• Dozens to be deliberately infected with coronavirus in UK ‘human challenge’ trials
• Volunteers to Be Infected With Coronavirus in Vaccine-Effectiveness Trials in U.K. - Controversial ‘human challenge’ trial would require injecting healthy humans with virus to gauge effectiveness of vaccines
• U.K. Preparing COVID-19 Vaccine Trials That Deliberately Expose Study Subjects

The Human Challenge Studies may be also called "controlled human infection (CHI) studies". In human challenge studies, volunteer subjects were intentionally infected with the virus or other pathogen. It is supposed to shorten the time of the vaccine development program so that we know the results earlier if a vaccine works or not.   

• Infecting Subjects May Speed Covid Vaccine Studies, WHO Says
• Should scientists infect healthy people with the coronavirus to test vaccines?
• Is it worth risking lives to speed up a coronavirus vaccine?
• Infect volunteers with Covid-19 in the name of research? A proposal lays bare a minefield of issues
• Studies that intentionally infect people with disease-causing bugs are on the rise

When I see the discussions about the human challenge studies, I immediately ask myself: is it ethical to intentionally infect people just to speed up the vaccine development program? Some infamous studies came to my mind: Guatemala syphilis experiments, Holmesburg Prison, Tuskegee syphilis experiment even though the ethical issues with these studies were mainly lack of informed consent. 

However, human challenge studies were not new and had been used in other vaccine developments. Here are some examples: 

• Collins et al (2015) First Human Challenge Testing of a Pneumococcal Vaccine Double-Blind Randomized Controlled Trial - Healthy adults were randomly assigned to pneumococcal conjugate vaccine (PCV) or hepatitis A (control) vaccination, and then inoculated with Streptococcus pneumonia (pathogen causing pneumonia)
• Cohen et al (2002) Randomized, Controlled Human Challenge Study of the Safety, Immunogenicity, and Protective Efficacy of a Single Dose of Peru-15, a Live Attenuated Oral Cholera Vaccine - Volunteers were randomly assigned to receive a single oral dose of either vaccine Peru-15 or placebo; and then 3 months later, inoculated with vibrio cholerae, the bacterium that causes cholera.
• Balasingam and Wilder-Smith (2016) Randomized controlled trials for influenza drugs and vaccines: a review of controlled human infection studies - 26 studies with human challenge design were included in the review. In these studies, healthy volunteers were inoculated with influenza A and/or influenza B virus

Human challenge studies were also mentioned in FDA guidance for industry:

• Clinical Data Needed to Support the Licensure of Pandemic InfluenzaVaccines 

"To date, prospectively designed studies to evaluate the effectiveness of influenza vaccines have not identified a specific HI antibody titer associated with protection against culture-confirmed influenza illness. Some studies of influenza infection, including human challenge studies following vaccination, have suggested that HI antibody titers ranging from 1:15 to 1:65 may be associated with protection from illness in 50% of subjects and that protection from illness is increased with higher titers. Evaluations of seroconversion and GMT have been used as measures of vaccine activity." 

• General Principles for the Development of Vaccines to Protect Against Global Infectious Diseases 

"B. Human Challenge Studies
In some situations, it may be possible to conduct challenge studies in human subjects during early development or in lieu of clinical trials in an endemic area. Such studies may be conducted to demonstrate “proof of concept” of the vaccine antigen early in clinical development (e.g., Plasmodium falciparum sporozoite challenge of malaria-naïve U.S. volunteers previously administered a candidate malaria vaccine). Human challenge studies may also be conducted to demonstrate the efficacy of the vaccine. For example, in 1993 and 1998, the Agency convened the Vaccines and Related Biologics Products Advisory Committee meetings to consider whether data from human challenge studies in U.S. subjects could be sufficient to demonstrate efficacy of a cholera vaccine in travelers to endemic areas, who are at high risk for contracting the disease. In 1998, the committee agreed that human challenge studies could suffice to demonstrate efficacy of a cholera vaccine provided that studies were adequate and well-controlled and conducted under the provisions of GCP (Ref. 13). Of note, use of challenge studies to demonstrate efficacy does not preclude the requirement for adequate safety data. As human challenge studies may present unique considerations, we recommend that the sponsor discuss its development plan with CBER prior to initiation of such studies for either proof of concept or vaccine efficacy."

What does a human challenge study for Covid-19 vaccine look like? 

Here are the excerpts from the article "A Challenge to Accept The FDA should allow testing Covid-19 vaccines through deliberate human infection" to describe what the conventional phase III trial and the human challenge trial look like:

"In Phase III trials, thousands of volunteers get the vaccine or a placebo, are checked for immediate adverse reactions to the vaccine, and then are tracked for a few months as they go about daily life, to ascertain the vaccine’s efficacy. Once enough trial participants have been infected, if a large enough difference in infection rates exists between the vaccinated and control groups, then the vaccine can enter general use. This comparison, the Times notes, is especially difficult to make once the spread of a disease has slowed: “The scientists [making the vaccine] would declare victory,” the Times says, “if as many as a dozen participants who are given a placebo become sick with Covid-19 compared with only one or two who receive the inoculation.” But if too few test subjects get infected to make a valid comparison, the researchers will simply “have to try again elsewhere,” repeating the time-consuming process."

 "In human-challenge trials, volunteers are given either a candidate vaccine or a placebo and then deliberately infected with the disease that the vaccine should prevent, and closely monitored, often in medical isolation. Such trials have been conducted in exigent circumstances for several diseases, including cholera, malaria, typhoid, and dengue fever."

In another article "Human challenge trials,” where healthy volunteers would be exposed to Covid-19, explained", the human challenge study for Covid-19 vaccine was described as the following:

A human challenge trial replaces that process with one in which all of the trial volunteers are exposed to the virus that causes Covid-19 after being dosed with a vaccine or placebo. That way, you get a much clearer sense of how the vaccine performs when actually confronted with the disease it’s intended to guard against.

"To allow for a high portion to get exposed, the standard trial would have to take at least several months," Eyal, the bioethicist who co-authored the Journal of Infectious Diseases article calling for human challenge trials, told me. "By contrast, in a coronavirus challenge ... the success or failure of the vaccine to protect against the disease becomes apparent much faster."

What’s more, a human challenge trial could be conducted with fewer people than a standard Phase III trial. A Covid-19 vaccine being developed at Oxford, for instance, aims to have 5,000 volunteers for Phase III. A human challenge trial, Eyal argues, could happen with only about 100 people. The total number of participants needed would likely be higher than that, since (among other reasons) multiple vaccine candidates need to be tested, but the total would be much lower compared with a conventional study.

I drafted two diagrams to illustrate what the conventional design and the human challenge study design look like (for illustration only, SARs-Cov-2 is the virus that causes Covid-19).

Will the human challenge study be feasible for Covid-19 vaccine studies? 

There are people who push for conducting human challenge study to speed up the vaccine development - the argument is to sacrifice the few for the many.

• Infecting healthy people in vaccine research can be ethical and necessary
• First, do harm
• Volunteers Are Lining Up to Be Infected With the Coronavirus

However, the human challenge studies that had been done so far were for those pathogens that the resulted diseases were either not severe enough (for example influenza) or could be treated or cured (for example, cholera).

For Covid-19, the human challenge study design is not feasible for the following reasons:
Safety: currently there is no effective treatment for Covid-19. For healthy volunteers who are inoculated with SARs-Cov-2, they could end up in ICU or death.

• Ethical issue: even though the subjects sign the informed consent to participate in the human challenge study voluntarily, inoculating the subjects with the deadly and extremely contagious virus of SARs-Cov-2  
• Uncertainties about SARs-Cov-2: for human challenge studies, extensive modeling needs to be performed to understand the characteristics of the virus and appropriate virus load (sort of dose level) to be used for inoculation. 
• Timeline: it is arguable if it is true that using human challenge design will actually speed up the vaccine development. Covid-19 is new and a lot of unknowns need to be learned. Significant leading time may be needed to do the modeling to decide what the appropriate virus load for inoculation before the study can be initiated. 
• Recruitment: it is still uncertain whether there will be difficulties in recruiting the volunteers to participate in the human challenge study knowing that the volunteers will be infected with the potentially deadly virus that has no effective treatment so far. There is a website "one day sooner" that tracks the volunteers who are willing to participate in human challenge study for Covid-19. At the time I check, 14183 volunteers from 102 countries have signed up. 
• Generalization: if the human challenge study is conducted in volunteers who are young adults, the results may not be generalized to the vulnerable groups (elderly, with underlying diseases).  

In a digital event organized by STATNEWS.com, Tal Zaks, chief medical officer, Moderna answered the question about the human challenge study design. He argued against the use of human challenge design in Covid-19 vaccine development for issues in practicality, timeline (may not save time), and ethical (justification the risk for the benefit we gain).

Interpreting Hazard Ratio: Can we say "percent reduction in risk"?

For time to event variable, the most commonly used statistics is hazard ratio. Hazard ratio is the ratio of hazards and equals to the hazard rate in the treatment group ÷ the hazard rate in the control group. Hazard rate represents the instantaneous event rate, which means the probability that an individual would experience an event at a particular given point in time after the intervention. While the hazard rate is associated with the event rate or median survival time, the hazard rate itself does not have a lot of meaning in interpreting the clinical trial results (see a previous post "Some Explanations about Survival Analysis or Time to Event Analysis"). However, we use hazard ratio (HR) to measure the treatment effect (i.e., the effect of an intervention on an outcome of interest over time comparing to the control group). Hazard ratio is reported most commonly in time-to-event analysis or survival analysis (i.e. when we are interested in knowing how long it takes for a particular event/outcome to occur). Hazard ratio can be obtained and calculated from the Cox regression - or Cox proportional hazard regression model.

The event outcome could be an adverse/negative outcome, for example, progression-free survival (PFS) and overall survival (OS) in oncology studies or a positive outcome, for example, time to cure/discharge/conceive/heal/virus not detectable. The very publicized trial by NIAID "A Multicenter, Adaptive, Randomized Blinded Controlled Trial of the Safety and Efficacy of Investigational Therapeutics for the Treatment of COVID-19 in Hospitalized Adults" demonstrated the benefit of Remdesivir in treatment of Covid-19 through the primary efficacy endpoint of 'time to recovery' where the event of recovery is a positive outcome defined as "the first day on which the subject satisfies one of the following three categories from the ordinal scale: 1) Hospitalized, not requiring supplemental oxygen - no longer requires ongoing medical care; 2) Not hospitalized, limitation on activities and/or requiring home oxygen; 3) Not hospitalized, no limitations on activities."

How to interpret the hazard ratio in lay language? 

According to ScienceDirect.com, The hazard ratio is the ratio of (chance of an event occurring in the treatment arm)/(chance of an event occurring in the control arm). The HR has also been defined as, the ratio of (risk of outcome in one group)/(risk of outcome in another group), occurring at a given interval of time.

While these interpretations of the hazard ratio may be clear to the statisticians, they are not straight forward to the public and non-statisticians. 

As described in an article by Sashegyi and Ferry "On the Interpretation of the Hazard Ratio and Communication of Survival Benefit", people would like to use an interpretation of hazard ratio in lay language. 

For a study with time to event variable where the event is a negative outcome, a hazard ratio < 1 is desirable for a successful trial. The hazard ratio will be interpreted as "percent reduction in risk". The hazard ratio is converted into "percent reduction in risk" using: 

     (1 − HR) ×100%

We could find many examples where that hazard ratio (and its 95% confidence interval) was used in the scientific papers, but "percent of reduction in risk" was used in the press releases or public announcements. 

In an article by de Bono et al (2020) "Olaparib for Metastatic Castration-Resistant Prostate Cancer", the result for PFS was presented as:

In cohort A, imaging-based progression-free survival was significantly longer in the olaparib group than in the control group (median, 7.4 months vs. 3.6 months; hazard ratio for progression or death, 0.34; 95% confidence interval, 0.25 to 0.47; P less than 0.001); a significant benefit was also observed with respect to the confirmed objective response rate and the time to pain progression.

In Sponsor's press release, "Submission based on PROfound, the first positive Phase III trial testinga targeted treatment in biomarker-selected prostate cancer patients"

Results of the PROfound trial showed Lynparza significantly reduced the risk of disease progression or death by 66% based on a hazard ratio of 0.34 (p less than 0.0001) vs. abiraterone or enzalutamide in patients with BRCA1/2 or ATM-mutated mCRPC, the primary endpoint of the trial.

In an article by Kato et al (2019) "Nivolumab versus chemotherapy in patients with advanced oesophageal squamous cell carcinoma refractory or intolerant to previous chemotherapy (ATTRACTION-3): a multicentre, randomised, open-label, phase 3 trial"

overall survival was significantly improved in the nivolumab group compared with the chemotherapy group (median 10·9 months, 95% CI 9·2–13·3 vs 8·4 months, 7·2–9·9; hazard ratio for death 0·77, 95% CI 0·62–0·96; p=0·019).

However, in the sponsor's press release, "% reduction in risk of death" was also added in addition to HR:

Opdivo demonstrated a 23% reduction in the risk of death and 2.5-month improvement in median overall survival compared to chemotherapy.

Opdivo demonstrated a statistically significant improvement over chemotherapy, with a 23% reduction in risk of death [Hazard Ratio (HR) 0.77; 95% Confidence Interval (CI): 0.62 to 0.96; p=0.019] and a 2.5-month improvement in median OS [10.9 months (95% CI: 9.2 to 13.3)] compared to patients treated with chemotherapy [8.4 months (95% CI: 7.2 to 9.9)]. The safety profile of Opdivo in this trial was consistent with previously reported studies in ESCC and other solid tumors.

The press release by BMS: "Phase III CheckMate -067 Trial Demonstrates Superior Progression-Free Survival of Opdivo+Yervoy Regimen or Opdivo Monotherapy vs. Yervoy Monotherapy in Previously Untreated Patients with Advanced Melanoma":

The Opdivo+Yervoy regimen demonstrated a 58% reduction in the risk of disease progression vs. Yervoy (hazard ratio: 0.42; 99.5% CI, 0.31 to 0.57; P less than 0.0001), while Opdivo monotherapy demonstrated a 43% risk reduction versus Yervoy monotherapy (hazard ratio: 0.57; 99.5% CI, 0.43 to 0.76; P less than 0.00001).

"Medivation and Astellas Announce The Phase 3 PREVAIL Trial of Enzalutamide Meets Both Co-Primary Endpoints of Overall Survival and Radiographic Progression-Free Survival in Chemotherapy-Naïve Patients With Advanced Prostate Cancer":

30% Reduction in the Risk of Death, Hazard Ratio=0.70 (p less than0.0001)

81% Reduction in the Risk of Radiographic Progression or Death, Hazard Ratio=0.19 (p less than 0.0001)

We can see from these examples that when an event is a negative outcome, it is pretty common to interpret the hazard ratio to "percent reduction in risk".

Similarly, when an event is a positive outcome, a hazard ratio greater than 1 is desirable for a successful trial. We may interpret the hazard ratio as "increase the probability of ...by xx%" or "increase the chance of [event] by xx%".

 xx% =  ( HR - 1) ×100%

In an article by Statnews "Data for Gilead’s potential coronavirus therapy are coming soon. Here’s what you need to know", it says the following about the hazard ratio:

If people who take the placebo show clinical improvement after 16 days, remdesivir would have to track at 13 days to demonstrate superiority with statistical significance, Raffat said. This would be described in what researchers call a “hazard ratio.” The magic number would be 1.2, meaning that patients do 20% better on remdesivir than placebo.

If the median time to event can be calculated, it is also straight forward to list the median time to event. It is easy for people to compare the median time to event between treatment groups to determine which group performs better. For example, if the overall survival (OS) is the endpoint and if at least 50% patients die in both treatment groups, the median survival times can be calculated using the Kaplan-Meier approach and the group with longer median survival time performs better.

The issue with this approach is that a lot of clinical trials with time to event variable as efficacy endpoint, the median time to event may not be calculable because of the low frequency of the events. 

Similarly, "percent reduction in risk" may also come from the odds ratio or risk ratio. In a recent press release by Gilead "Comparative Analysis of Phase 3 SIMPLE-Severe Study and Real-World Retrospective Cohort of Patients Diagnosed with Severe COVID-19 Receiving Standard of Care", remdesivir treatment was associated with significantly improved clinical recovery and a 62 percent reduction in the risk of mortality compared to standard of care. The '62 percent reduction...' was based on the odd ratio.

The mortality rate for patients treated with remdesivir in the analysis was 7.6 percent at Day 14 compared with 12.5 percent among patients not taking remdesivir (adjusted odds ratio 0.38, 95% confidence interval 0.22-0.68, p=0.001).

For multi-center, open label clinical trials, can individual investigation sites disclose results from their sites while study is ongoing?

The golden standard for clinical trials is RCT (randomized, control trials) including three key components: randomization, including a control group (preferably concurrent control), and blinding (or concealment of the treatment assignment). The blinding can minimize the biases (conscious or unconscious) introduced into the study by investigators, patients, and the study team.

However, in some situations, blinding is not possible or is very difficult to implement. A randomized, open-label study may be more appropriate. In the randomized, open-label study, while patients are randomized assigned to receive the experimental new drug or control, the investigator, patients, (in some cases the sponsor study team) are aware of the treatment assignment. 

In an early posting "Some Blinding Techniques in Clinical Trial", some blinding techniques can be applicable even for the randomized, open-label study. On the conservative side, the sponsor can follow the same procedures in handling the randomization, open-label study as the double-blind study - i.e., establishing a firewall to keep the sponsor study team or anyone with the capability to do the aggregate analyses and decision making from accessing the data during the study. 

With a randomized open-label study, both site investigators and patients participating in the study know which treatment group the patient is receiving - knowing the treatment assignment itself may cause biases in efficacy and safety assessments, in concomitant medication selection, in subsequent therapy selection,...

In the last several days, we see an extreme case (presumably due to the special situation in fighting the Covid-19 pandemic). In multi-center, randomized, open-label studies for remdesivir, while the studies are ongoing, the individual sites start to disclose the results / experiences from patients in their perspective sites. 

Statnews.com (04/16/2020) Early peek at data on Gilead coronavirus drug suggests patients are responding to treatment  

"The University of Chicago Medicine recruited 125 people with Covid-19 into Gilead’s two Phase 3 clinical trials. Of those people, 113 had severe disease. All the patients have been treated with daily infusions of remdesivir."

"The best news is that most of our patients have already been discharged, which is great. We’ve only had two patients perish,” said Kathleen Mullane, the University of Chicago infectious disease specialist overseeing the remdesivir studies for the hospital.

 Komo News (04/21/2020) Experimental anti-viral drug Remdesivir used to treat COVID-19 patients

Dr. Vinay Malhotra said at his hospital, 40 patients have been treated with the anti-viral drug.

According to Dr. Malhotra, 32 patients were in severe condition. 8 were in moderate condition. Of the 40 patents treated, Malhotra said 17 of them have already been discharged.

“Everyone is talking about the discharge of these patients. Everyone is talking about how good the effect is in three days,” Malhotra said. "We were fortunate to be chosen for this trial. And that has helped our population tremendously."

Both the University of Chicago Hospital in Illinois and the Multicare Institute for Research and Innovation in Tacoma, Washington are investigation sites participating in two pivotal clinical trials sponsored by Gilead:

• A Phase 3 Randomized Study to Evaluate the Safety and Antiviral Activity of Remdesivir (GS-5734™) in Participants With Severe COVID-19
• A Phase 3 Randomized Study to Evaluate the Safety and Antiviral Activity of Remdesivir (GS-5734™) in Participants With Moderate COVID-19 Compared to Standard of Care Treatment

Both studies (one for severe Covid-19 and one for moderate Covid-19 patients) were designed as randomized, open-label studies with one group receiving Remdesivir (on top of standard of care) and one group receiving standard of care only. According to clinicaltrials.gov, there are 179 and 178 investigation sites for these two studies.

If all sites do the same as the University of Chicago hospital and Multicare Institute for Research and Innovation to disclose their experiences, we could see many reports: some may be good, some may not be very good. The sites with good results may be eager to get their information out; the sites with results not very good may keep silent.

In both of these reports, there was no mention of how many patients in the control group (receiving standard of care) - maybe these patients in the control group are doing pretty well too (unless there are selection biases in determining which patients are allocated to receiving remdesivir or not receiving remdesivir (standard of care)). 

It is not clear if there is an agreement between the sponsor (Gilead) and the investigation sites about disclosing the data while the study is ongoing. Disclosing the data for individual sites while the study is still ongoing should certainly be discouraged or prohibited even in the public health emergency situation. The better way will be that the sponsor designs the study as group sequential design and perform the interim analyses using the data from all sites - if the results are indeed great, the pre-specified boundaries may be crossed and the sponsor may be able to stop the study for efficacy. In this way, the study results may be disclosed earlier while the study integrity is maintained. 

There are already reports that the motive and wrongdoing should be investigated: 

• Congressman calls on SEC to look into leaked remdesivir data: report
• Congressman calls for SEC investigation into leak about possible coronavirus drug

There are also reports that criticize the study design (no adequate control group and no blinding) for Gilead's designed studies: 

The world wants answers on Gilead’s Covid-19 drug. Experts worry next studies may increase uncertainty