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The cloud does not represent data points, it is a visual representation of the uncertainty in the model itself and it underestimates the total uncertainty. It only captures the uncertainty of something akin to a population mean, or more precisely the uncertainty over the parameters of the deterministic estradiol curve. It does not capture the full distribution of outcomes in the population at large. This is bound to change in the future once a better representation of this uncertainty gets implemented (which would include the additional population variability around the deterministic curve).
The emerging consensus is that the pharmacokinetics of estradiol ester depots is highly variable and depends on many factors that are not well understood and rarely taken into account. Those factors can lead to vastly different outcomes and are not well represented, if at all, in the current models. Those include, among others, the ester concentration, the type of oil used, the proportion and type of excipients such as benzyl benzoate that are present in the formulation, the injection site, whether the depot is injected intramuscularly or subcutaneously, the injection depth, individual differences in metabolism, and the presence of other drugs. Some of those confounding factors are sometimes captured to an extent in the uncertainty of the models, but only when the data is abundant and spans multiple studies done under different conditions. This is, of course, generally not the case. Several of those factors also apply to transdermal, oral, and sublingual estradiol. I am actively working to improve and generalize the current models in ways that will better capture this variability, but ultimately their accuracy and scope will always be limited by the data available.
All data for estradiol benzoate, valerate, enanthate, and cypionate intramuscular depot models (ev im, een im, ec im, eb im) have been digitized from scratch from the original studies mentioned in the tfs meta-analysis. Data was further reprocessed by splitting per-patient data into individual datasets when possible, and by using the uncertainty reported in the studies. Note that the data for estradiol enanthate is unusually sparse and comes entirely from studies of Perlutan from the 80s and 90s.
The data behind the estradiol undecylate model for intramuscular depots using castor oil (eun im) was entirely reprocessed from scratch using the per-patient data found in Geppert 1975 together with the data and uncertainty reported in Vermeulen 1975. This data is extremely sparse and incomplete and thus the model is highly uncertain.
The data behind the estradiol undecylate model for subcutaneous depots using castor oil (eun casubq) was inferred on top of the eun im model by augmenting it with very sparse self-reported community data. Its predictions are also highly uncertain.
The once-weekly patch model (patch ow) was inferred using data found in drug labels of once-weekly Climara and Menostar patches. The twice-weekly patch model (patch tw) was inferred using data taken from two 2003 studies by Houssain et al. looking at twice-weekly Estradot and Menorest patches, and in the drug label of twice-weekly Mylan patches. In light of knowledge gathered from self-reported community data, please be advised that both models excessively underestimate the uncertainty which should be close to 10 times larger. The models will be improved to better reflect this in the future. Currently there is no way to change the wearing period of the patch in the interface (i.e. they are fixed at 3½ and 7 days) but it is planned for the future.
The data for the menstrual cycle comes from Stricker et al. 2006. Download the E2/P/LH/FSH data.
Data for target ranges is based on guidance from WPATH Standards of Care, Version 8 in addition to the Endocrine Society's Clinical Practice Guideline.
Note regarding "inapproprite WPATH regimens" presets
In the WPATH Standards of Care (Appendix C, page S254), several hormone replacement therapy (HRT) regimens for transfeminine people are listed. However, some of these recommendations might not align with WPATH's own guidelines and could even be harmful. Here's a breakdown of the issues.
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