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Merge pull request #1886 from ihmeuw/Alz_treatment_update
Treatment Updates for Alzheimer's
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docs/source/models/concept_models/vivarium_alzheimers/concept_model.rst

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@@ -366,6 +366,9 @@ scenario, and input draw.
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- Treatment completion stratification for transitions to `Full treatment effect` state allows us to validate the 10% discontinuation rate.
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Note that the diagram states `Full treatment effect LONG` and `Full treatment effect SHORT` are both considered the same status (`Full treatment effect`),
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but are stratified by completion status.
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* - Months on treatment
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-
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- Only needed for simulants who discontinue treatment as others are definitionally 0 or 9.
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* - Treatment status person-time
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- Status (`In treatment/ Waiting for treatment`, `Full treatment effect`, `Waning treatment effect`, `No treatment effect`).
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Also stratify by treatment completion (completed, discontinuated) from transition observer

docs/source/models/intervention_models/alzheimers/hypothetical_treatment.rst

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@@ -94,12 +94,12 @@ Vivarium Modeling Strategy
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in_treat [label="Receiving treatment", style=dashed, shape=box]
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no_treat [label="No treatment effect [permanent]"]
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treat [label="Full treatment effect LONG [5 y]"]
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wane [label="Waning treatment effect LONG (update each step) [9 y]"]
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treat_short [label = "Full treatment effect SHORT [6 mo]"]
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wane_short [label = "Waning treatment effect SHORT (update each step) [2.5 y]"]
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treat [label="Full treatment effect LONG [6 y]"]
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wane [label="Waning treatment effect LONG (update each step) [11 y]"]
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discon_time [label = "Months to discontinuation D_t", style=dashed, shape=box]
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treat_short [label = "Full treatment effect SHORT [(Months on Treatment/9) * 6 y]"]
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wane_short [label = "Waning treatment effect SHORT (update each step) [(Months on Treatment/9) * 11 y]"]
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el -> test [label = "tested"]
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el -> el [label = "not tested"]
@@ -113,7 +113,9 @@ Vivarium Modeling Strategy
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wait -> in_treat [label = "begins treatment"]
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in_treat -> treat [label = "completes (90%)", style=dashed]
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in_treat -> treat_short [label = "discontinues (10%)", style=dashed]
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in_treat -> discon_time [label = "discontinues (10%)", style=dashed]
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discon_time -> treat_short
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treat_short -> wane_short
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wane_short -> no_treat
@@ -140,6 +142,11 @@ on a time step, they should also immediately continue to the next state during t
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For example, a simulant in `BBBM test eligible` who is tested and moves to `BBBM test received` would then immediately move to one of
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that state's two sinks, and would even move directly to another state during the same transition/ time step on a positive test.
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The "Months to discontinuation" state randomly assigns a number of months the simulant will be on treatment
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before discontinuing. The number of months then determines the duration of time with full and waning treatment effect.
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For example, if a simulant discontinues after 4 months, they would have (4/9) * 6 years of
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full effect, or 2.67 which we round to the nearest 6 month interval, which is 2.5 years.
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Below are tables with details on how to model these states and transitions, and necessary data values.
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The value of :math:`i_{MCI}` in the :ref:`cause model <2021_cause_alzheimers_presymptomatic_mci_transition_data_table>` is now updated
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to be equal to :math:`h_{adj} = h_{MCI} \cdot R_h`, where :math:`h_{adj}` is the intervention-adjusted hazard rate used for progression to MCI,
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- Lower value means more likely to initiate testing. Independent from testing propensities.
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* - :math:`I`
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- Time- and location-specific treatment initiation rate
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- Lilly: "The percent of patients with a positive BBBM test who initiate treatment will vary by location and over time – but will not vary by age or sex. In the US: 30% of eligible patients initiate (constant 2030-2100); Japan: 80% of eligible patients initiate (constant 2030-2100); all other countries: 40% of eligible patients initiate in 2030, increasing linearly to 70% by 2035, remaining constant at 70% until 2100.""
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- The percent of patients with a positive BBBM test who initiate treatment will vary over time – but will not vary by age, sex, or location. We will use a piecewise linear ramp-up with knots at the following (year, level) values: `(2022.0, 0), (2027.0, 0), (2035.5, 30), (2100.0, 80), (2101.0, 80)`.
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-
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* - :math:`D_t`
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- Months to discontinuation
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- A full course of treatment is 9 months. We assume simulants discontinue evenly for each monthly injection. The months to discontinuation will be assigned a uniformly distributed whole number between 1 and 8 inclusive.
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-
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* - :math:`R_h`
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- Effect hazard ratio
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* - Receiving treatment
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- Treatment period is instantaneous. See :ref:`alzheimers_intervention_treatment_assumptions` for info about treatment/discontinuation timing.
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- Zero duration. Random draw
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* - Months to discontinuation
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- Period is instantaneous. See above notes for selection of months to discontinuation.
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- Zero duration. Random draw.
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* - Full treatment effect LONG
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- Treatment takes effect exactly 6 months after receiving a positive BBBM test (if :math:`\text{prop}_I < I`)
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- On transition to this state, :math:`R_h = R_d`. Set :math:`h_{adj} = R_h \cdot h_{MCI}`, slowing progression to MCI.
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Transition from this state after the fixed duration.
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* - Full treatment effect SHORT
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-
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- Same effect size as in `Full treatment effect LONG` but with a shorter fixed duration
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- Same effect size as in `Full treatment effect LONG` but with a shorter fixed duration. The duration is dependent on the time of discontinuation, as outlined above.
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* - Waning treatment effect LONG
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-
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- On every time step where the simulant ends the time step in this
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this state after the fixed duration.
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* - Waning treatment effect SHORT
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-
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- Same effect size as in `Waning treatment effect LONG` but with a shorter fixed duration
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- Same effect size as in `Waning treatment effect LONG` but with a shorter fixed duration. The duration is dependent on the time of discontinuation, as outlined above.
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* - No treatment effect
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-
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- :math:`R_h` should equal 1 on the first time step the simulant spends in this state.

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