Why is one semaglutide trial 609 and others 62-200?

I noticed that too. 609 active not recruiting is a big jump from 62, 200, and 140 still recruiting. Makes me wonder if they’re different phases.

Or different populations. Registry entries rarely tell you enough.

NCT02079870 completed with 30? That’s tiny. Early safety study, maybe.

Assumptions are how these threads go sideways lol.

Fair. I just want to know why the 609-person one hasn’t posted results yet.

Results can lag forever. I’ve seen completed trials sit for years before anything shows up.

That’s the annoying part. Active, not recruiting, 609 enrolled—feels like it should have something by now.

Maybe it’s ongoing follow-up. Active doesn’t always mean treatment is still happening.

This is why I mostly check new recruiting ones. NCT07401992 at 62 is the one I’m watching.

Why that on?e If it’s still recruiting, it’s probably early. The 200 and 140 ones might be more interesting.

I’m more curious whether it’s oral or injectable. That changes how I read the data.

I used to obsess over enrollmetn numbers, but they only tell you how many people signed up, not what was measured or when. The 609 trial being active-not-recruiting might just mean they’re in the long follow-up tail. The 30-person completed one could be a tiny PK study. Without posted results, we’re guessing. I’d rather wait for actual data than assume what each number means. Still, the gap between 609 and 62 is weird enough that I get why you asked. It doesn’t fit a simple pattern to me. At least not yet.

I did the same rabbit hole thing and started a little spreadsheet. Enrollment size mostly tracks phase and how many sites are running, not how promising anything is. That 30-person completed one with an NCT number starting 02 is just an old early safety study — those were tiny by design. The 609 one is probably a big multi-site trial where dozens of hospitals each pull in 10-20 people, and "active, not recruiting" usually means the last participant is in and they're following everyone out. The 62-200 ones are mid-size and mid-build, so they're still adding sites. My columns are phase, status, first posted date, and enrollment, and honestly the first posted date explains more of the spread than the enrollment does. A 2014 listing and a 2025 listing are basically different eras of how these things get designed.

609 usually means they needed a hard endpoint, not that the drug got 10x stronger. Numbers follow statistics, not vibes.

Funny thing is I spent two months deep in trial registries while completely ignoring my own data. I'd log every study number but weigh myself randomly, no pattern, no time of day. When I finally started tracking daily at the same time each morning, my weight bounced between 187 and 191 for three weeks before dropping to 184 by week 12, and my waist went from 37 to 35 over about 16 weeks. The reversal: the registry research felt productive and the scale felt chaotic, but the scale was the only thing actually giving me a signal. Now I do the boring stuff — same time, same clothes, write it down, watch the 7-day average instead of the daily number. The daily number will wreck your head. Enrollment counts are interesting but they're somebody else's spreadsheet.

@keto_kim said: The daily number will wreck your head.

Honestly, that spread isn't weird at all — I'd argue it's the most normal thing in the registry. What trips people up is treating the enrollment field as final when it's really an estimate that gets quietly edited. I watched one listing sit at 200 for about 14 months, flip to "active, not recruiting," then show 212. Status labels also lag reality by weeks, so "not yet recruiting" can be fully enrolled in the real world. And the newest listings have the shakiest numbers because sites are still being added. Which is kind of your point, I think. I've been tracking my own stuff for 20 weeks now, and the only comparison that ever mattered was me versus me six weeks ago. Someone else's 609 tells you nothing about your own 12-week trend.

I track waist inches more than trial numbers—down 3.5 since March, which feels louder than 609.

Weekends are my real trial—Friday pizza used to add 2 lbs by Monday, now I pre-log a big salad and walk 25 minutes after dinner, and Monday scale only bumps 0.4. Took 11 weeks to trust that pattern, but it changed how I read 'fast' vs 'sustained' results. Big numbers on a page still don't tell me how my jeans fit on a Tuesday.

My sleep tracker was the surprise: 7.5 hrs vs 5.5 changes my morning scale by a full pound.

I quit chasing 10k steps and just did 20 min after lunch—down a belt notch in six weeks.

I fell down the same registry hole and the thing that clicked for me was endpoints, not just phase. A 609-person study is usually powered for something harder like cardiovascular events or kidney outcomes, while a 62-person one is often early safety, tolerability, or how the body handles it. I keep a note on my phone: trial size roughly equals endpoint plus expected effect plus dropout. The weird part is active, not recruiting with 609 doesn't mean it's ahead; it can just mean enrollment closed and they're in the follow-up tail. Meanwhile a 200-person trial still recruiting might be a later-phase study that just opened more sites. NCT02079870 at 30 sounds like an older pilot, so I wouldn't read it as a competing result. Are you sorting by phase or primary endpoint? That column made the spread make sense to me.

I look at completion date as much as enrollment. A 200-person trial still recruiting can be a later-phase study that just opened, while a 609 active-not-recruiting one is likely closed but still collecting events. Bigger isn't automatically better for reading the pipeline; a small old completed study can be the fastest signal.

Registry math gets way less scary once you sort by phase and endpoint.

I started screenshotting site counts and locations because enrollment numbers alone are misleading. A 140-person study at five sites is a totally different recruitment story than 200 at forty sites. The unexpected part for me was that the tiny completed trial can tell you more about early signal than the huge one tells you about real-world results.

The thing that messed with my head was “estimated” vs “actual” enrollment. I clicked one that showed a big number, then the results tab had way fewer actual participants. Also some big numbers include placebo arms and screen failures, so it’s not 609 people all getting the med. Are you filtering by actual enrollment instead of estimated? That changed my whole rabbit hole.

One thing I have noticed is that registry enrollment is often the planned number, and it can include placebo arms and extension phases. So a 609-person study may not mean 609 people received the active treatment, and the same applies to the smaller ones. I track my weekly averages in a spreadsheet, but for trials I now look at the arm breakdown and whether there is an extension. Does the trial page show actual versus estimated enrollment for the studies you are comparing?

I got lost in that same rabbit hole! One thing I do now: check whether the “Enrollment” field says actual or estimated. Some of those bigger numbers are actual/updated, while recruiting ones still show the original target. Also, a few are rollover/extension studies, so the 609 may include folks continuing from another trial, not all new starts. Does NCT07011667 have an extension tag? I keep a dollar-store notebook for water, protein, and steps—helps me feel sane when the pharmacy/insurance stuff gets noisy.

One thing that made those numbers less weird to me: check the Enrollment field detail. It often says Actual vs Estimated, and whether the study is interventional or observational. A 609-person observational registry or extension isn't the same animal as a 62-person randomized trial. Also peek at number of arms/cohorts—sometimes 200 total is split across several groups. Like my scale data, the raw single number is noisy; context is the trend

Honestly, The registry field that cleared this up for me: Enrollment = Actual vs Estimated. A completed 609 is usually actual; a recruiting 62 is a placeholder that can drift. Also check the dropout/screen-fail assumptions in the protocol—one trial can need several times more bodies just to end with enough completers. I keep a tab for actual/estimated, countries, and primary outcome type. Enrollment alone is a vanity metric.

Good catch. One thing I check now is the “Enrollment: Actual vs Estimated” field—sometimes a big number is just the target across all sites, while newer trials list estimated enrollment that keeps changing. Also peek at whether it’s an extension/crossover or includes a placebo arm; those can inflate n without being a bigger standalone efficacy study. What populations are the 62/200/140 ones in? If they’re different indications, comparing raw enrollment is apples-to-oranges.

I’d check the enrollment type: “actual” vs “estimated.” A 609 actual can include rollover from an earlier cohort or a long extension phase, while a 62 estimated is just the randomized core. Also look at arms—crossover designs need fewer bodies than parallel. Does NCT07011667 list an extension/rollover arm? That’s usually the tell.

Totals can be misleading because they’re often planned enrollment, not how many actually got randomized. 609 across 4-5 arms is ~120-150 per arm, which isn’t wild next to a 200-person two-arm study. I also check whether it’s event-driven—some weight trials keep screening until enough people hit the endpoint, so the target can grow. Does the registry page break it down by arm? I tried comparing while hiding from my kids in the pantry with a string cheese and gave up around tab #12.

Not a trial person, but I do the same nerdy spreadsheet thing with prices. The next thing I’d click is the Locations tab and Study Design: a 609-person study is usually multi-site/multi-country, while 62 can be a single-site pilot or a PK/mechanistic substudy. Also check Allocation and Number of Arms—crossover designs can make totals look weird. Sharp question: does NCT07011667 show Phase 3 and the 62-person one Phase 1? That usually kills the “different formulation” theory fast. If they’re all the same phase, I’d side-eye the registry entry itself.

yeah the phase is usually the tell imo. i clicked a couple and the 609 one was phase 3 with a ton of sites, while the 62/140 ones were earlier or single-center. also some smaller ones are combo/mechanism studies where everyone does extra clinic visits and food/activity logs, so they don’t need hundreds. check the Locations count too—if it’s one site, that alone caps enrollment. what phases are the ones you’re looking at? that usually kills the mystery.

Phase column is the first tiebreaker, not raw n. A completed 30 is usually early-phase PK/PD or mechanistic; 62–200 is typical Phase 2 dose-ranging; 600+ suggests pivotal Phase 3. I also look at Allocation/Intervention Model and Number of Arms—adaptive, multi-cohort designs make enrollment look erratic. Are the 62/200/140 trials all the same indication? If not, comparing n is mostly noise. I track my own data in a spreadsheet; same principle: compare like variables or the numbers lie.

The number that usually cracks it for me is phase + arm count. A 609-person trial with 3–4 arms is basically four ~150-person studies wearing a trench coat. Early ones at 30–62 are often single-arm. I keep a spreadsheet with phase, actual/estimated enrollment, arm count, and location count; once you sort by those,

I lift 4x/wk and track protein/sleep, so I nerd out on endpoints more than raw N. The Phase row usually explains it: a completed 30-person study is often early PK/dose-finding, while 600+ is typically powered for a primary weight/body-comp endpoint over 6–12 months. The recruiting 62–200 ones might be phase 2 or sub-studies. Sharp Q: does NCT07011667 list multiple arms plus a long extension? That’s often why enrollment balloons. Also check Primary Outcome—if it’s a combo of several sub-studies, the number stops looking so weird.

Hi, I’m new here too and still learning how to read those pages. Wat helped me was checking the Locations and Arms sections instead of just the enrollment number. Some of the bigger counts seem to come from multi-country trials or studies with an extension/sub-study attached. The 609 one might be counting all those extra cohorts, while the 62/200/140 ones could be smaller phase 2-ish or population-specific. Does NCT07011667 happen to list an extension or several countries? I’m only on week one myself, so I’m mostly tracking water, protein, and a

I’d check the record’s “Enrollment” field first: actual vs estimated. A completed 30-person study usually shows actual, while recruiting records often show estimated totals. If the 609 one says actual, look at “Locations”—if it spans dozens of sites or pooled indications, that can explain the spread without

One thing that trips me up is actual vs estimated enrollment. Some pages list 609 as actual, while recruiting trials usually show estimated targets. I also open the Locations tab—140 people at 3 sites is a totally different beast from 609 across 60 sites. That alone can explain a lot. Is NCT07011667 marked actual or estimated on the page you saw?

Tbh Hi, I’m brand new here too (week one) and these pages make my eyes cross, so sorry if this is obvious. One thing that helped me was checking “Actual” vs “Estimated” enrollment, and how many locations are listed. A 609 number can be less weird if it’s spread across many sites or includes rollover/extension participants, while 62 might be a smaller single-site thing. Does NCT07011667 say “Actual” enrollment or list a ton of locations? I’m not enrolled either, just trying to learn. I track steps and protein too, so I get the nerd-out part.

I always check the “arms” and allocation ratio too—a 609-person trial with 4 arms can be ~150 per arm, not 609 all getting the same thing. Also look at number of sites and whether it’s an extension or sub-study; those often have tiny n by design. I’m just a mom reading these between snack-drawer refills, so I could be off. Are any of the 62/140 ones listed as extension studies? That would explain the spread more than formulation.

I keep a tab of trial N by phase and arm count, and my trendline says the jump usually tracks primary endpoint, not formulation. A 609-person record almost always has a composite/event-driven endpoint or 3+ arms; the

I wonder if you are comparing apples to oranges by indication. The big 609 number may be a cardiovascular outcomes or real-world pragmatic trial, where enrollment is meant to capture event rates; the 62 and 140 may be earlier signal or formulation studies. I usually click “Study Design” and look at primary purpose (treatment vs prevention), masking, and whether enrollment is actual or estimated. Also check locations: a 609-person study across many countries is a different beast from a single-site 30-person completion. Are your NCTs all for weight management, or are some diabetes/CV? I keep weekly averages of my own habits, and that context helps me read the numbers without panicking.

I’ve got a tab for this, because raw enrollment numbers lie without context. I filter by phase, primary purpose, and whether it’s event-driven. A 609-person record

One thing I look at is the primary outcome and condition, not just N. Smaller 60–200 person studies are often PK/PD, dose-finding, or short-term weight/HbA1c endpoints; 609+ usually suggests a phase 3 with a hard clinical endpoint (MACE, kidney outcomes) where event rate drives sample size. Also check “arms” and “masking”—more arms and longer follow-up need more people. Are those newer 62/200/140 all the same indication and phase as NCT07011667? If not, comparing raw enrollment is apples-to-oranges.

I’m a broke dorm rat who tracks grocery protein per dollar in a Google Sheet, so I get the numbers spiral. One thing I do on ClinicalTrials: open the Locations tab. A 609-person study is often a bunch of sites across countries; a 62-person one can be a single clinic with strict local eligibility. Also check “Study Start” vs “Primary Completion”—some tiny ones are early safety/tolerability, so enrollment isn’t apples-to-apples. Sharp question: does anyone know if those counts include screen failures or only randomized folks? That always messes up my mental math.

Welcome to the rabbit hole! One thing I check when the numbers look wildly different is the locations list and eligibility criteria. A 609-person study can be spread across dozens of sites with a broad age/BMI range, while a 62-person one might be single-site or require a specific comorbidity. That can change how fast they fill and who the results represent. Not advice—just my own nerd habit. Are you comparing ones near you, or just trying to understand the landscape? Either way, tracking your own daily habits in a simple note beats NCT scrolling at 1am.

one thing that helped me untangle those numbers: look at whether enrollment is listed as actual vs estimated, and whether the study is interventional or observational. Some big N’s are registries or extension studies that roll prior participants forward, so they’re not really comparable to a fresh 62-person randomized trial. Also check the number of sites/countries—a 200-person study spread over 40 sites can feel very different for dropouts and follow-up. OP, were the newer ones marked estimated or actual? That detail usually explains the jump for me.