Re: Can you stop Hairloss effectively without risking PFS?
u/drwillpowers
r/DrWillPowers2026-07-30T04:02:01Z
Dr Will Powers’ own statements and theorizing
Mentions treatments or doses — not guidance
Summary (paraphrased)
Powers offered a thought experiment: if a PFS-susceptible man were chemically castrated, given dutasteride for two months, withdrawn, then "uncastrated," he would never develop PFS if the theory is correct — because it is about metabolite load, not just the gene. He stressed the polypharmacy stacking behind susceptibility: testosterone injections plus an SSRI plus slow CYP2D6/3A4 plus a bad ABCC variant plus UGT problems can combine into the catastrophe. He likened onset to an action potential or a sheet of paper catching fire under focused sunlight — a threshold moment, not a process — which explains why timing looks random and why some people crash on one pill (they were already near the barrier). He described his own pharmacogenetics as the opposite extreme: all P450s cranked up except 2C19, normal UGTs, no ABCC defects, and a common 1-in-50 LRP2 mutation, making him effectively immune. He concluded that PFS is the crossing of a threshold into a self-reinforcing biological feedback loop that, unlike most feedback mechanisms, cannot break itself.
Key points (paraphrased)
- Hypothetical: castration during dutasteride exposure should prevent PFS if the metabolite-load theory holds.
- Susceptibility is polyfactorial: genes + concurrent drugs (T, SSRIs, slow CYP2D6/3A4, ABCC, UGT variants).
- Onset = threshold event (action-potential / igniting-paper analogy), not gradual process — explains random timing and one-pill cases.
- Self-described invulnerable genome: fast P450s, normal UGTs, no ABCC defects.
- The stuck state is a self-reinforcing feedback loop that cannot self-terminate.
Why it’s in the corpus
The clearest articulation of the threshold model and its preventive implication — the castration-during-exposure thought experiment is the theory's sharpest testable prediction. Also documents his polypharmacy-stacking view of risk, relevant to drug-interaction aspects of post-drug syndromes.
Context — the post Powers was replying toVerbatim third-party text, shown for context only — not Powers’ statement. Usernames removed.ShowHide
Powers' comment replies to a community member:
Fair, and I take the point that you're filtering on rare high REVEL variants, not the common ones. That answers part of what I wrote.
What I still can't get past is the denominator. You said somewhere else the population frequency of that ABCC2 stop codon is known. So the other number is the one that decides whether the test is worth running: how often does it show up in your patients who took a 5ARI and were fine? You've got genomes on half your DPC panel and plenty of them are on dut.
If it's 40% in crash cases and 1% in everyone else, that's a real screen and I'd pay for sequencing tomorrow. If it's 40% and 15%, it isn't. Do you have any sense of that second number?
(Parent context recovered from the r.genit.al mirror on 2026-10-07; Powers' comment text itself is from John's user-provided export.)
Some fields on this page come from the release’s Markdown edition, which carries text the JSON edition omits.
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