Why Block Size Should Not Appear in the Protocol or SAP

Allocation concealment is not the same as blinding and publishing block size can compromise the integrity of randomization.

randomization

trial design

Author

Fei Zuo

Published

November 30, 2025

Modified

March 4, 2026

🎧 1-minute summary

Narration generated using OpenAI.fm.

In randomized clinical trials, we talk a lot about blinding. But an equally important and subtly different concept is allocation concealment.

They are not the same thing.

Blinding protects against bias after treatment is assigned (e.g., preventing biased outcome assessment).
Allocation concealment protects against bias at the moment of enrollment before treatment is assigned (e.g., preventing foreknowledge of upcoming treatment assignment).

Because allocation concealment depends on unpredictability at the time of enrollment, certain operational details such as block size can weaken that protection if widely disclosed.

Regulatory and Reporting Standards Emphasize Concealment, Not Disclosure of Block Size

Major regulatory and reporting guidance documents are clear about the importance of allocation concealment. Notably, they do not require disclosure of block size in protocols or SAPs.

ICH E9 (Statistical Principles for Clinical Trials)

ICH E9 emphasizes that randomization protects against selection bias and provides a valid basis for statistical inference. This protection depends on the allocation sequence remaining unpredictable at the time of enrollment.

Unpredictability is the core principle. If the block size is known to investigators, predictability can arise — directly conflicting with this requirement.

ICH E6 (Good Clinical Practice)

ICH E6 emphasizes safeguarding the randomization process:

“The investigator should follow the trial’s randomization procedures, if any, and should ensure that the code is broken only in accordance with the protocol.”

Maintaining control of the randomization schedule including operational details like block size is part of preserving its integrity.

CONSORT 2010 Statement

CONSORT distinguishes clearly between:

Sequence generation
Allocation concealment mechanism

Item 9 of the CONSORT 2010 checklist requires:

“Mechanism used to implement the random allocation sequence (such as sequentially numbered containers), describing any steps taken to conceal the sequence until interventions were assigned.”

CONSORT focuses on how concealment was ensured, not on revealing details that would undermine it.

The Purpose of Block Randomization

Block randomization is used to maintain approximate treatment balance throughout enrollment.

For example, in a 1:1 trial with block size 4, each block contains:

2 assignments to Treatment A
2 assignments to Treatment B

The order of assignments within each block is randomly permuted. Since each block contains equal numbers of assignments for each treatment, treatment counts remain balanced throughout enrollment, reducing the risk of large imbalances if the trial stops early.

The Problem: Predictability

If investigators know the block size, allocation can become predictable.

Imagine:

1:1 randomization
Block size = 4
Three patients in a block have already been assigned: A, B, A

What is the fourth assignment?

It must be B.

At that point, allocation is no longer random in practice. It is deducible.

The mere ability to anticipate the next assignment can influence enrollment decisions in small but systematic ways:

Delaying enrollment of a “difficult” patient
Accelerating enrollment of a “good prognosis” patient
Selectively enrolling borderline-eligible patients

This introduces selection bias, even in a formally randomized trial. That is a failure of allocation concealment.

Allocation Concealment ≠ Blinding

Even in an open-label trial (no blinding), allocation concealment must still be protected.

Blinding protects:

Outcome assessment
Patient behavior
Investigator expectations

Allocation concealment protects:

The integrity of who gets assigned what

You can have:

A blinded trial with broken allocation concealment
An open-label trial with perfect allocation concealment

They are conceptually distinct safeguards.

Why Block Size Does Not Belong in the Protocol or SAP

The protocol and SAP are often widely distributed:

Investigators
Coordinators
Sponsors
Regulators
Data monitoring committees

If the block size is written there, it is no longer protected.

Best practice is:

The protocol states that blocked randomization will be used.
The SAP describes the randomization method in general terms.
The actual block size (and any random variation in block size) is known only to:
- The unblinded statistician
- The randomization unit/vendor/system

This protects allocation concealment while still maintaining transparency about the design.

Fixed Block Sizes

Using a fixed block size makes predictability easier.

A better approach is:

Randomly varying block sizes (e.g., 2, 4, and 6)

This dramatically reduces predictability. But even then, disclosing the possible block sizes weakens protection.

Randomization terminology

Simple randomization
Each subject is assigned independently (e.g., coin flip) using a chance mechanism. Balance is achieved on average, but temporary imbalances can occur.

Permuted block randomization — fixed block size
Assignments are balanced within blocks of a constant size (e.g., all blocks size 4), and the order within each block is randomly permuted.

Permuted block randomization — varying block sizes
The block size itself is randomly selected from a prespecified set (e.g., 2, 4 and 6). Each block remains internally permuted. This reduces predictability compared with fixed small blocks.

Do:
- Use permuted blocks to maintain balance during enrollment.
- Prefer varying block sizes to protect allocation concealment.
- Ensure block size is a multiple of the allocation ratio (e.g., multiple of 2 for 1:1 allocation).
- Restrict knowledge of block sizes to the unblinded randomization statistician/system.

Do not:
- Use small fixed block sizes when assignments could be inferred.
- Disclose block size in widely distributed protocol or SAP documents.
- Confuse allocation concealment with blinding.

The Statistical Consequences of Broken Allocation Concealment

Empirical evidence shows that trials with inadequate allocation concealment:

Systematically overestimate treatment effects
Are more likely to report statistically significant results
Introduce selection bias at enrollment

What the Protocol Should Say

Instead of specifying block size, a protocol can say:

Participants will be randomized in a 1:1 ratio using a centralized, computer-generated permuted block randomization schedule. Details of the randomization sequence will be maintained by the unblinded statistician to ensure allocation concealment.

That is sufficient. Regulators do not require disclosure of block size in public-facing documents.

Takeaway

Block size is an operational detail. Its disclosure does not improve reproducibility, transparency, or statistical validity. But it can undermine allocation concealment.
And once allocation concealment is compromised, the trial is vulnerable to selection bias even if it remains fully blinded.
Protecting allocation concealment is protecting the integrity of randomization itself.
Block size should be known only to the unblinded randomization statistician or system.
Regulators do not require disclosure of block size in public-facing documents.

References

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. (1998). ICH E9: Statistical principles for clinical trials.

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. (2019). ICH E9(R1) addendum on estimands and sensitivity analysis in clinical trials.

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. (2016). ICH E6(R2): Guideline for good clinical practice.

Schulz, K. F., Altman, D. G., & Moher, D., for the CONSORT Group. (2010). CONSORT 2010 statement: Updated guidelines for reporting parallel group randomized trials. BMJ, 340, c332. https://doi.org/10.1136/bmj.c332

Schulz, K. F., Chalmers, I., Hayes, R. J., & Altman, D. G. (1995). Empirical evidence of bias: Dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA, 273(5), 408–412. https://doi.org/10.1001/jama.1995.03520290060030

Schulz, K. F., & Grimes, D. A. (2002). Allocation concealment in randomised trials: Defending against deciphering. The Lancet, 359(9306), 614–618. https://doi.org/10.1016/S0140-6736(02)07750-4

Moher, D., Pham, B., Jones, A., Cook, D. J., Jadad, A. R., Moher, M., Tugwell, P., & Klassen, T. P. (1998). Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses? The Lancet, 352(9128), 609–613. https://doi.org/10.1016/S0140-6736(98)01085-X

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