How to Read a Clinical Trial Press Release Without Getting Fooled

Every biotech press release has the same structure: a bullish headline, a quote from the CEO, and a table of data buried on page 3. Here’s how to read past the spin and find the numbers that matter.

Step 1: Find the primary endpoint

The primary endpoint is the one the trial was designed to measure. It’s pre-specified — the company committed to it before the trial started. If the press release says the trial “met its primary endpoint,” that’s a pass. If it says the trial “met key secondary endpoints” but is quiet about the primary, that’s a fail.

Red flag: Press releases that bury the primary endpoint result or emphasize secondary endpoints. If the primary endpoint wasn’t met, the drug likely won’t be approved without additional trials.

Step 2: Check the p-value

The p-value tells you whether the result could have happened by chance. The magic number is p < 0.05 — if the p-value is below 0.05, the result is “statistically significant.”

But statistical significance isn’t the same as clinical significance. A trial can show a statistically significant 2% improvement that nobody cares about. Look at the effect size (how big the difference is), not just the p-value.

Step 3: Read the confidence interval

The confidence interval (CI) tells you the range of plausible results. A 95% CI of 0.5–0.7 for a hazard ratio means we’re 95% confident the true effect is between a 30% and 50% risk reduction.

Red flag: A confidence interval that crosses 1.0 (for hazard ratios) or 0 (for differences) means the result is not statistically significant — even if the point estimate looks good. Companies sometimes highlight the point estimate and bury the CI.

Step 4: Look for subgroup analysis

Subgroup analysis is slicing the data by patient characteristics (age, gender, disease stage). It’s useful for understanding who benefits, but it’s also a common way to spin negative data.

Red flag: If the overall trial failed but the press release highlights a subgroup that “showed benefit,” be skeptical. Subgroup analyses are underpowered and can show false positives. The FDA rarely approves drugs based on subgroup analysis of a failed trial.

Step 5: Compare to the control

What did the control arm do? If the drug group had a 30% response rate and the placebo group had a 25% response rate, the drug isn’t doing much. The difference matters more than the absolute number.

Step 6: Read the safety data

Efficacy is half the story. Safety is the other half. Look for:

• Serious adverse events (SAEs): How many patients had life-threatening side effects?
• Discontinuation rate: How many patients quit the trial because of side effects?
• Deaths: Were there more deaths in the drug arm than the control arm?

Red flag: Press releases that say “safety was consistent with the known profile” without providing numbers. Go to the actual data.

Step 7: Check the sample size

A trial of 30 patients can show anything. A trial of 3,000 patients is harder to fool. Small trials are more prone to false positives — if the effect is real, it should replicate in a larger trial.

The takeaway

Biotech press releases are marketing documents. The data is real, but the framing is designed to make you feel good. Your job is to find the primary endpoint, check the p-value, read the confidence interval, and compare to the control. The numbers don’t spin — the headlines do.

For more on trial design and endpoints, see our glossary for definitions of Phase I-III, surrogate endpoints, and more.