Introduction to RECIST 1.1 (3)

How Doctors Measure Cancer Treatment Success

If you have ever looked at a clinical trial report or a radiology result for a cancer patient, you likely encountered the term RECIST 1.1. This stands for Response Evaluation Criteria in Solid Tumors. It is the gold standard used by researchers and doctors to determine if a patient is responding to treatment, staying stable, or if the disease is progressing[cite: 8, 26, 64].

Here is a logical breakdown of how these guidelines work and why they matter.


1. The Starting Point: Baseline and Target Lesions

Before treatment begins, a "map" of the cancer is created. [cite_start]Doctors identify Target Lesions, which are the specific tumors they will track throughout the study[cite: 177, 182].

  • Selection Limit: A maximum of five total lesions are tracked, with no more than two per organ[cite: 29, 182].

  • The Sum of Diameters: This is a single number calculated by adding up the measurements of all target lesions[cite: 198, 200]. [cite_start]This number serves as the "Baseline Sum" against which all future progress is measured[cite: 198, 200].


2. Why Dimensions Matter: Longest vs. Shortest (Non-Nodal Lesions vs. Lymph Nodes)

One of the most common points of confusion is why different tumors are measured differently. RECIST 1.1 categorizes disease into two primary types for measurement:

Non-Nodal Lesions (Solid Tumors in Organs)

These are solid tumor masses found within organs or tissues, such as a tumor in the lung, liver, or bone (its soft tissue component)[cite: 99, 114, 129].

  • Measurement: Doctors measure the longest diameter of the lesion in the plane of the image[cite: 114, 550].

  • Why? Since these masses are entirely composed of abnormal tissue, the longest diameter is the most direct way to track the overall reduction or increase in the "bulk" of the tumor.



Malignant Lymph Nodes

Lymph nodes are normal, bean-shaped structures of the immune system found throughout the body. They become "pathological" (enlarged due to cancer) if they are invaded by tumor cells[cite: 119, 189, 192].

  • Measurement: Lymph nodes are always measured using their short axis[cite: 31, 120, 191].

  • Why the Short Axis? Normal lymph nodes can be naturally elongated. A node can have a long "longest diameter" but still be healthy if its "short axis" is small. Research has shown that the short axis is a much more reliable indicator of malignancy; when a node is cancerous, it tends to become more "round" and thicken across its short axis[cite: 192, 421].

  • Threshold for Measurability:

    • Target Lesion: A lymph node qualifies as a target lesion if its short axis is mm[cite: 119, 190]. Only these are included in the "Sum of Diameters."

    • Non-Target Lesion: A lymph node is considered a non-target lesion if its short axis is mm but mm[cite: 196]. These are noted qualitatively but not measured in the sum.

    • Normal: Nodes with a short axis mm are considered normal and are not tracked[cite: 197].





3. Defining the Outcome: CR, PR, SD, or PD?

At each follow-up scan, the new "Sum of Diameters" is compared to the baseline to assign a response status[cite: 200, 206, 284]. Non-target lesions and new lesions are also assessed.

  • Complete Response (CR):

    • Target Lesions: Disappearance of all target lesions.

    • Lymph Nodes: Any target lymph nodes must shrink to a short axis of mm.

    • Non-Target Lesions: Disappearance of all non-target lesions.

    • New Lesions: No new lesions.

    • Example: Baseline sum 7.5 cm. After treatment, all tumors are gone, and lymph nodes are less than 1 cm short axis.

  • Partial Response (PR):

    • Target Lesions: At least a 30% decrease in the sum of diameters compared to the baseline sum.

    • Non-Target Lesions: Persistence of non-target lesions is allowed, but no "unequivocal progression."

    • New Lesions: No new lesions.

    • Example: Baseline sum 7.5 cm. Smallest sum recorded is 4.5 cm (a 40% decrease). This qualifies as a PR.

  • Progressive Disease (PD):

    • Target Lesions: At least a 20% increase in the sum of diameters and an absolute increase of at least 5 mm compared to the smallest sum recorded during the study (the "nadir"). OR

    • Non-Target Lesions: Unequivocal progression of existing non-target lesions. OR

    • New Lesions: Appearance of one or more new lesions.

    • Example: Baseline sum 7.5 cm. Smallest sum was 4.5 cm. Current sum is 6.0 cm. This is a 33% increase from the nadir (6.0-4.5)/4.5 = 0.33) AND an absolute increase of 1.5 cm (15 mm), thus qualifying as PD.

  • Stable Disease (SD):

    • Neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD.

    • Example: Baseline sum 7.5 cm. Current sum is 7.0 cm. Not a 30% decrease (PR) and not a 20% increase (PD). This is SD.


4. Key Metrics for Clinical Trials

Beyond individual patient response, RECIST 1.1 provides the data for broader trial endpoints[cite: 52, 99]:

  • Objective Response Rate (ORR): The percentage of patients who achieved a confirmed PR or CR[cite: 100, 353, 394].

  • Progression-Free Survival (PFS): The time from the start of treatment until the cancer grows (PD) or the patient passes away[cite: 349, 366, 381].

  • Duration of Response (DOR): For those who did respond, how long that response lasted before the disease began to grow again[cite: 351, 359, 360].


5. Imaging Standards

To ensure these measurements are accurate, RECIST 1.1 sets strict rules for imaging[cite: 41, 145, 451]:

  • CT Scans: These are the preferred method and should use a slice thickness of 5 mm or less[cite: 115, 153, 154].

  • Consistency: Patients must be scanned using the same modality (e.g., always CT or always MRI) throughout the study to avoid "fake" progression caused by different machine sensitivities[cite: 145, 487, 537].

  • New Lesions: The appearance of even one clearly new malignant lesion is considered automatic Progressive Disease (PD)[cite: 40, 213, 238].

Comments

Popular posts from this blog

Understanding Binding vs. Non-Binding Futility Analysis in Clinical Trials

Use FDA Suggestions on Missing Data and Sensitivity Analyses

Analysis of Repeated Measures Data using SAS (1)