The majority of clinical trials evaluating cancer treatments for objective response in solid tumors are using RECIST, or Response Evaluation Criteria in Solid Tumors. RECIST is crucial for evaluating the effectiveness of cancer therapies, but it’s not without its challenges.

In this blog, we detail RECIST, how it’s used in statistical analysis, the development of iRECIST for immunotherapy trials, statistical and clinical challenges with RECIST/iRECIST, and best practices for implementing RECIST/iRECIST in oncology trials.

What is RECIST 1.1 and why is it important in oncology?

RECIST (Response Evaluation Criteria in Solid Tumors) 1.1 is a standardized set of rules used to measure tumor response to treatment using imaging. It helps determine whether a tumor is shrinking, stable, or growing, which is crucial for evaluating the effectiveness of cancer therapies. As of today, the majority of clinical trials evaluating cancer treatments for objective response in solid tumors are using RECIST.

What are the key response assessments in RECIST 1.1?

The overall response for a given timepoint is the combination of target lesion response relying on unidimensional measurements, non-target lesion response, and presence/absence of new lesions.

• Complete Response (CR): Disappearance of all target lesions and non-target lesions and no new lesions. Any pathological lymph nodes must have a reduction in short axis to <10mm.
• Partial Response (PR): At least a 30% decrease in the sum of diameters of target lesions, taking as reference the baseline sum diameters, and no progression of non-target lesions and no new lesions.
• Stable Disease (SD): Neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD, taking as reference the smallest sum diameters while on study, and no new lesions.
• Progressive Disease (PD): At least a 20% increase in the sum of diameters and an absolute increase of ≥ 5mm, taking as reference the smallest sum of diameters on-study, or progression of non-target lesions or appearance of new lesions.
• Not Evaluable (NE)

How is RECIST used in statistical analysis?

RECIST is used to derive key endpoints like:

• Objective Response Rate (ORR)
• Disease Control Rate (DCR)
• Progression-Free Survival (PFS)
• Duration of Response (DOR)
• Time to Response (TTR)

RECIST 1.1 criteria state that confirmation of response (CR or PR) is required for non-randomized trials with a response primary endpoint to ensure responses identified are not the result of measurement error. However, in all other circumstances, i.e., in randomized trials (phase II or III) or studies where stable disease or progression are the primary endpoints, confirmation of response is not required since it will not add value to the interpretation of trial results.

The FDA generally expects a confirmed response for ORR in single-arm trials where it is the primary endpoint, especially for accelerated approval. The FDA/EMA may also request confirmation if ORR is a primary of key secondary endpoints or if imaging intervals are long. Nevertheless, this point should be discussed with Health Authorities as this additional confirmatory scan is usually requested 4 weeks later and the protocol might not plan for it; such analyses cannot be conducted ad hoc if the confirmatory assessment is not initially planned in the protocol.

What are the statistical and clinical challenges with RECIST 1.1?

Inter-reader variability

Despite the use of standardized RECIST 1.1 criteria for response, different radiologists may interpret imaging results differently, especially when measuring borderline lesions. This can introduce measurement bias and affect response classification (e.g., PR vs. SD) and therefore impact trial outcomes. As an example, the average discrepancy rate at the patient level was found to be 59.2% in lung cancer trials using RECIST 1.1.1

Lesion selection and measurement errors

• RECIST 1.1 limits the number of target lesions (up to 5 total, max 2 per organ).
• Importance of selecting the same target and non-target lesions to be followed across all timepoints otherwise patient level response will not be valid.
• Small errors in measuring lesion diameters can significantly impact response categorization.

Non-measurable disease

When the patient has only non-measurable disease, the increase must be substantial to lead to an overall response PD, which is relatively subjective.

Handling non-target and new lesions

Non-target lesions are assessed qualitatively, which introduces subjectivity.

The appearance of new lesions automatically triggers PD, even if the overall tumor burden is decreasing. Therefore, the finding of a new lesion should be unequivocal, i.e., not attributable to differences in scanning technique, change in imaging modality, or findings thought to represent something other than a tumor.

RECIST criteria are based on anatomical size, not functional or viable tumor volume

Focuses on unidimensional measurements, regardless of internal characteristics like necrosis or cavitation (common in lung or liver metastases).

Other criteria (e.g., Choi criteria for GISTs) may be more appropriate when necrosis is a key feature of response.

In some tumor types or trials, modified criteria (e.g., mRECIST for hepatocellular carcinoma) are used, which do consider viable tumor (e.g., arterial enhancement) rather than total size.

RECIST does not capture atypical responses

Especially in immunotherapy, tumors respond differently compared with chemotherapy, raising questions about the assessment of changes in tumor burden. In particular, for immunotherapy, RECIST 1.1 may misclassify pseudoprogression as PD.

This has led to the development of iRECIST, but many trials still rely on RECIST 1.1.

Time-to-event endpoint challenges

PFS and DOR depend on accurate and timely assessments.

Delays in imaging or inconsistent scan intervals can lead to informative censoring or biased survival estimates.

Missing or incomplete data

Patients may miss scans or drop out, leading to missing data that complicates statistical modeling. Interval censoring can be used as sensitivity in that case.

Imputation is difficult due to the non-linear and categorical nature of RECIST outcomes.

Impact on interpretation

Low concordance between Independent Central Review and the Investigator would question the reliability of results.

Why was iRECIST developed and how does it differ from RECIST 1.1?

Traditional RECIST criteria may misclassify immune-related responses as progression. iRECIST was developed to:

• Reflect atypical response patterns in immunotherapy
• Allow continued treatment beyond initial progression
• Improve consistency in trial design and data interpretation

iRECIST is an adaptation of RECIST 1.1 designed for immunotherapy trials. It accounts for pseudoprogression, where tumors may initially appear to grow before shrinking due to immune cell infiltration. iRECIST introduces:

• Unconfirmed Progressive Disease (iUPD)
• Confirmed Progressive Disease (iCPD)

This two-step confirmation helps avoid prematurely stopping effective immunotherapy.

What are the statistical challenges with iRECIST?

Delayed treatment effects

Immunotherapies may show delayed clinical benefits, which violate the proportional hazards assumption used in standard survival analysis (e.g., Cox models). This can complicate sample size estimation, primary analysis, and, in particular, hazard ratio interpretation.

Pseudoprogression and confirmation requirements

iRECIST introduces iUPD and requires a follow-up scan to confirm progression as iCPD, which delays the determination of progression and requires more complex modelling of iPFS. This also introduces interval censoring and time-dependent bias.

The exact time of progression is not precisely known — it lies between the iUPD and iCPD scans. Uncertainty around the exact date of progression, which is already present with RECIST, is larger with iRECIST, given that the second scan is needed to confirm the PD. A specific method like the interval censoring method might be more appropriate than the Kaplan-Meier and Cox models.

Patients who survive long enough and/or are still in the study to get a confirmation scan are not randomly selected — they may be little healthier. This may introduce selection bias and time-dependent confounding.

Endpoint ambiguity

Common endpoints like PFS and ORR are harder to define, which can lead to inconsistent endpoint definitions across trials:

• Should PFS be based on iUPD or iCPD?
• How should iDOR be calculated?
• What if patients drop out before confirmation?
• SAP should clearly define the derivations

Data interpretation and trial comparability

Trials using iRECIST are not directly comparable to those using RECIST 1.1.

Meta-analyses and pooled analyses become more difficult.

The protocol/SAP may plan for both RECIST and iRECIST analyses, increasing complexity.

Increased risk of missing data

Patients may discontinue before confirmation scans for progression.

Imaging schedules may not align with iRECIST requirements: iRECIST requires a follow-up scan (typically within 4–8 weeks) after an initial iUPD to determine if the progression is real or pseudoprogression. However, in many clinical trials or treatment protocols, imaging is scheduled every 8–12 weeks, which may not fit with the expected confirmation window and increase the risk of missing data.

This leads to informative censoring and missing not at random (MNAR) data, which are hard to handle statistically.

Limited validation and standardization

iRECIST is still considered exploratory, especially for phase III trials (as per the guidelines).

There is no consensus on how to incorporate iRECIST endpoints into pivotal trials.

Validation requires large-scale data sharing, which is still limited.

Best practices for implementing RECIST/iRECIST in trials

• Follow published guidelines.
• Ensure the CRF appropriately collects the data (e.g., date of new lesions). Examples are available on the RECIST website.
• Ensure standardized imaging schedules and methods.
• Train radiologists and clinicians on RECIST/iRECIST criteria.
• Consider blinded independent central review to reduce variability, when relevant.
• Plan for additional scans to confirm progression with iRECIST.
• Ensure responses criteria used are clear in SAP, outputs, CSR, and manuscripts.

Where can I learn more or access the guidelines?

Full RECIST guideline

Full iRECIST guideline

RECIST Questions and Clarifications

iRECIST

Final takeaways

RECIST 1.1 is the standard tool for evaluating tumor response in oncology trials, offering a consistent framework based on anatomical measurements. While it has brought uniformity to clinical research, it comes with some limitations — such as subjectivity in lesion selection and inability to capture atypical responses — especially with immunotherapies. To address these challenges, iRECIST was introduced as an adaptation that accounts for immune-related phenomena like pseudoprogression. However, it also brings statistical complexity and remains exploratory and is not yet fully reliable, with limited validation for pivotal trials.

This is precisely where Cytel can bring value to sponsors. By combining deep statistical expertise with operational insight, Cytel helps design and implement robust RECIST and iRECIST strategies — from endpoint definition to handling complex censoring and missing data. Cytel supports sponsors in navigating regulatory expectations, ensuring that trial results are both scientifically sound and submission-ready.

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