Screen Fail Rate Calculator

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Screen Fail Rate Calculator

Screening Metrics:

Screen Fail Rate: %

Total Randomized/Enrolled:

Screen-to-Randomization Ratio:

function calculateScreenFailRate() { var totalScreened = parseFloat(document.getElementById('total_screened').value); var screenFailures = parseFloat(document.getElementById('screen_failures').value); var resultArea = document.getElementById('result_area'); if (isNaN(totalScreened) || isNaN(screenFailures) || totalScreened totalScreened) { alert("Screen failures cannot exceed the total number of participants screened."); return; } var failRate = (screenFailures / totalScreened) * 100; var enrolled = totalScreened – screenFailures; var ratio = totalScreened / (enrolled > 0 ? enrolled : 1); document.getElementById('fail_rate_display').innerText = failRate.toFixed(2); document.getElementById('enrolled_display').innerText = enrolled; document.getElementById('ratio_display').innerText = ratio.toFixed(2) + ":1"; resultArea.style.display = "block"; }

Understanding the Screen Fail Rate

In clinical research, the Screen Fail Rate is a critical metric that measures the percentage of prospective participants who undergo formal screening procedures but are found ineligible for the study based on inclusion and exclusion criteria.

How to Calculate Screen Fail Rate

The math behind the screen fail rate is straightforward but essential for trial planning:

Screen Fail Rate = (Number of Screen Failures / Total Participants Screened) × 100

Why This Metric Matters

  • Budgeting: Screening often involves costly lab tests, imaging, or clinician time. A high fail rate significantly increases the cost per randomized subject.
  • Timeline Accuracy: If 50% of screened patients fail, you need to find twice as many potential candidates to meet your enrollment goals.
  • Protocol Feasibility: An unexpectedly high screen fail rate often suggests that the inclusion/exclusion criteria are too restrictive or that the recruitment pool does not match the study requirements.

Example Calculation

Imagine a Phase II oncology trial aiming to enroll 50 patients. If the site screens 80 patients to find those 50 eligible participants, the calculation would look like this:

  • Total Screened: 80
  • Total Enrolled: 50
  • Screen Failures: 30 (80 – 50)
  • Screen Fail Rate: (30 / 80) × 100 = 37.5%
  • Screening Ratio: 1.6:1 (You must screen 1.6 people for every 1 that joins)

Common Causes of High Fail Rates

Frequent "screen fails" often stem from specific lab values (e.g., hemoglobin levels), failure to meet diagnostic thresholds, or the presence of prohibited concomitant medications. Monitoring which specific criteria are causing the most failures allows study teams to potentially amend the protocol or adjust recruitment strategies to target the right patient population more effectively.

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