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Generated by ChatGPT
Overview
Objectives
- Identify adjustment set for removing confounding prevalent in
observational data
- Stratification of adjustment sets
- Use of inverse propensity weights to remove treatment selection bias
Assigned Reading & Learning Material
-
Understanding confounding in observational data
- Propensity Score with Inverse Probability Weights
- Selecting the right predictors
Slides►
YouTube►
Instruction for Submission of Assignments: Submission
should follow these rules:
- Include a statement from your project manager that the work was done
on time and accurately.
- Submit your answers in a Jupyter Notebook
Download►
YouTube►
Slides►
- Submit you answers in Canvas.
Task 1: The overall task is to use output from ChatGPT
to prepare feedback to the patient. You are asked to complete this
task using the following steps:
- This file is obtained from medical history intake. For the
time being create a simulated file containing the medical history of one
patient. Name this file history.csv.
- Most of the variables needed for predicting response to
antidepressants have one to one relationships with conditions,
medications, or procedures mentioned in history.csv file. The
exceptions are the following variables that are calculated from the
entries in the history.csv file:
- ADRM_4DN standing for history of use of an antidepressant
different from the response variable and no remission. Calculate
this variable from reported remission status and agreement between
last antidepressant used and the response variable in the model used
for predicting response to a specific antidepressant. For each
predictive model, the response variable is different and if the
response variable and the history of intake agree, then it is
considered same and otherwise it is considered different.
- ADRM_3DR standing for history of use of an antidepressant
different from the response variable and remission. Calculate this
variable as described above.
- ADRM_2SN standing for history of use of an antidepressant same
as the response variable and no remission. Calculate this variable
as described above.
- ADRM_1SR standing for history of use of an antidepressant same
as the response variable and remission. Calculate this variable as
described above.
- nepi_2+ standing for more than 2 of episodes of depression in
previous year. This variable is based on number of depression
episodes 2-months apart reported by the client.
- nadep_23 standing for 2 or 3 prior antidepressants tried. This
variable is based on count of the previous antidepressants reported
by the client.
- nadep_4 standing for 4 prior antidepressants tried. This
variable is based on count of the previous antidepressants reported
by the client.
- Download the file describing regression coefficients predicting response
to 15 antidepressants and adjustments for missing values. This
file contains the response variable in the regression in the first
column, code for the predictors, text describing the predictor, and
coefficients for the predictors (including intercept) are in subsequent
columns. This file is being updated by others in class.
Download Excel►
- Write code to analyze the data to predict the probability of
response to various antidepressant for a client (Vlad Cardenas's advice on how to
do this in Excel YouTube►)
- The coefficient file contains many regressions. The first
column lists the response variable in the regression. In the first
step, predict the predictors of response to antidepressants.
These are response variables that are not an antidepressant but
either a condition, procedure, or medication used in predicting
response to antidepressants. Independent variables in these
regressions are assumed to be absent (i.e., zero), if the
independent variable is not in the history.csv, and is not predicted
by one of the regressions. Otherwise, if the independent
variable is in history.csv then assign a probability of 1 to it; if
it is predicted by other variables, then assign it the calculated
probability from the regression. The probability of a response
variable is calculated as 1/(1+e-R), where R is the sum
of the product of the variable and the coefficient of the variable.
- Replace any predict value with 1, if the variable is included in
the history.csv file. See a sample file containing 60
regressions for predicting the variables that affect response to
Venlafaxine
Download Excel►
- Predict probability of response to antidepressant using 1/(1+e-R),
where R is the sum of the product of (a) the probability of presence
of the predictor of the antidepressant and (b) the coefficient of
the predictor in coefficient.xlsx.
- Provide a summary of client's
relevant medical history using the following text: "We are assuming that you have major depressive disorder. If you do not, our
advice is not appropriate for you. If you have bipolar disorder, our advice is not appropriate for you. Among the variables you
mentioned during the medical history intake, the following are relevant in selection of appropriate antidepressants: Provide a bullet
list of short text for the variables mentioned in history.csv."
- Provide advice:
- Give a plot of likelihood of responses to different
antidepressants.
- Indicate recommended antidepressant. If all
antidepressants have less than 0.10 probability of response say: "In
our data, we could not find an antidepressant that works well for
patients with your characteristics. All 15 antidepressants we
examined have less than 10 percent chance of success for a patient
with your characteristics. Your primary care provider might be able
to make a more informed advice. In addition, it may be
appropriate to look for other options besides oral antidepressants
for treatment of depression." If a recommendation is
appropriate: Provide the name of the antidepressant with
highest response rate and provide the response rate. If other
antidepressants are within 5% of the recommended antidepressant, add
the second antidepressants to recommendations. Mention to
"take this information to your primary care provider and discuss if
there is a need for change in your medications. Do not change
your medications suddenly as abrupt changes in antidepressants could
be dangerous."
- Provide a link to PubMed for more information on recommended
antidepressant (see examples already created for the 15
antidepressants at web site)
- Give reasons supporting the advice (see examples already created
for the 15 antidepressants)
Prototype Advice►
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