What fraction of loss on ecnoglutide is lean mass according to SURMOUNT-5?

The case in front of me: ecnoglutide · SURMOUNT-5.

I would like to know the limits of what can be inferred from this.

What I am trying to avoid is over-reading a single result, which I have done before.

What can I legitimately conclude from this figure?

The relevant detail is that start with the arithmetic, because the answer to the practical question is usually a number and the number is usually achievable.

The first four weeks of loss is substantially fluid and glycogen. Each gram of stored glycogen carries roughly three grams of water, and total glycogen is on the order of 400 to 500 g, so the obligatory water shift alone accounts for a couple of kilograms. This is why the first month looks dramatic and the second looks like a plateau when in fact the fat-loss rate has not changed.

Protein target arithmetic

At roughly 4 kcal per gram, 141 g of protein is about 564 kcal — a substantial fraction of a 900 kcal budget, which is the real constraint.

Absolute strength holds up better than scale weight during a deficit for a straightforward reason: strength is substantially neural and skill-based, and the contractile tissue you retain is being trained harder relative to its size. Grip strength and repetition maxima are therefore lagging indicators of muscle loss rather than leading ones, which is an argument for measuring both.

The STEP 1 extension reported substantial regain in the year after treatment withdrawal, with weight and cardiometabolic variables trending back toward baseline[1].

A maintenance plan written before you need it is worth more than a better loss plan.

The mechanism is worth having straight, because it predicts which interventions can work and which cannot.

DEXA precision is better than people assume for fat mass and worse than people assume for lean mass in a single scan — the least significant change for regional lean mass on a well-maintained scanner is on the order of a few per cent. That means two scans three months apart can differ without anything having happened, and it means a scan sequence needs to be at least three points before a trend is interpretable.

Food noise returning is not obviously tolerance. Receptor desensitisation is one hypothesis; a second is that the initial effect was partly novelty and partly the steep early deficit, and a third is that intake has drifted upward and the signal is being outcompeted rather than weakened. The three make different predictions about what a dose increase would do.

The body-composition substudies in the major programmes consistently report that the proportion of weight lost as fat mass is approximately three quarters or better, with the lean-mass fraction falling within the range seen in dietary weight loss of comparable magnitude[1].

One qualification: none of this is a clinical assessment, and unexplained loss of function rather than of mass is a reason to see someone rather than to adjust a programme.

Train, eat the protein, measure something functional, and give the trend three months before you interpret it.

On the detail: the distinction that resolves this is between proportional loss and functional loss. Losing lean mass in proportion to total mass is what happens in every weight loss intervention. Losing function is not, and function is measurable.

The regain trajectory after stopping is roughly a mirror of the loss trajectory, and it is not primarily a willpower phenomenon. Appetite signalling returns, energy expenditure remains suppressed relative to the original mass, and the two combine. That is an argument for a maintenance plan existing before the stop, rather than an argument against stopping.

Fibre at very low total intake is a trap. Soluble fibre needs water and motility to work; insoluble fibre adds bulk to a slow transit. At 900 kcal a day with delayed gastric emptying, an osmotic agent is more predictable than a bulking one, and adequate fluid is doing more work than either.

The evidence for a higher protein intake preserving lean mass during an energy deficit is reasonably strong in resistance-trained populations and weaker in sedentary ones, with the meta-analytic estimates supporting intakes in the region of 1.6 g/kg over lower intakes when training is present[1].

Worth stating that a DEXA sequence is only as good as its protocol consistency, and most people’s sequences are not consistent enough to support the conclusions drawn from them.

The plateau is arithmetic. Treat it as arithmetic and the response follows.

edited 26 May 2026 by lyoph_cake — added the citation requested in comments

What the data supports is narrower than what gets recommended, so it is worth separating the two.

Cardio does not interfere with lean-mass retention at the volumes anyone here is doing; the interference effect in the literature appears at high concurrent volumes in trained athletes. What cardio does at a large deficit is add to the deficit, which is either the point or a problem depending on the objective.

SURMOUNT-4 provides the cleanest maintenance-versus-withdrawal contrast available in the class, and it is the reference for any claim about what happens after stopping[1].

I would be careful with the supplement literature here; effect sizes are small, the studies are mostly in trained young men, and generalisation to a large deficit is not obviously valid.

Two resistance sessions a week and a protein target you actually hit will do more than any refinement beyond them.

To be exact about it, a plateau at four to six months is the expected shape of the curve, not a failure of it. Energy expenditure falls with mass, and the deficit closes itself unless intake falls further.

The minimum effective resistance-training dose in a deficit is lower than most programmes assume. Two sessions a week covering the major movement patterns, with loads taken close to failure, is sufficient to retain most of what would otherwise be lost. Volume beyond that adds recovery cost that a large energy deficit is poorly placed to pay.

The caveat is that population averages tell you about populations. Your own trajectory is a sample of one and should be read as a trend, not as a deviation from a published mean.

Measure strength as well as mass. It is cheaper, it is less noisy, and it is closer to what you actually care about.

edited 10 Apr 2026 by ines_brandt — added the method parameters