Two data frames, plaque_psoriasis_ipd and plaque_psoriasis_agd,
containing (simulated) individual patient data from four studies and
aggregate data from five studies (Phillippo 2019)
.
Outcomes are binary success/failure to achieve 75%, 90%, or 100% reduction in
symptoms on the Psoriasis Area and Severity Index (PASI) scale.
Format
The individual patient data are contained in a data frame
plaque_psoriasis_ipd with 4118 rows, one per individual, and 16 variables:
- studyc
study name
- trtc_long
treatment name (long format)
- trtc
treatment name
- trtn
numeric treatment code
- pasi75
binary PASI 75 outcome
- pasi90
binary PASI 90 outcome
- pasi100
binary PASI 100 outcome
- age
age (years)
- bmi
body mass index (BMI)
- pasi_w0
PASI score at week 0
- male
male sex (TRUE or FALSE)
- bsa
body surface area (percent)
- weight
weight (kilograms)
- durnpso
duration of psoriasis (years)
- prevsys
previous systemic treatment (TRUE or FALSE)
- psa
psoriatic arthritis (TRUE or FALSE)
The aggregate data are contained in a data frame plaque_psoriasis_agd with 15
rows, one per study arm, and 26 variables:
- studyc
study name
- trtc_long
treatment name (long format)
- trtc
treatment name
- trtn
numeric treatment code
- pasi75_r, pasi75_n
PASI 75 outcome count and denominator
- pasi90_r, pasi90_n
PASI 75 outcome count and denominator
- pasi100_r, pasi100_n
PASI 75 outcome count and denominator
- sample_size_w0
sample size at week zero
- age_mean, age_sd
mean and standard deviation of age (years)
- bmi_mean, bmi_sd
mean and standard deviation of BMI
- pasi_w0_mean, pasi_w0_sd
mean and standard deviation of PASI score at week 0
- male
percentage of males
- bsa_mean, bsa_sd
mean and standard deviation of body surface area (percent)
- weight_mean, weight_sd
mean and standard deviation of weight (kilograms)
- durnpso_mean, durnpso_sd
mean and standard deviation of duration of psoriasis (years)
- prevsys
percentage of individuals with previous systemic treatment
- psa
percentage of individuals with psoriatic arthritis
An object of class data.frame with 15 rows and 26 columns.
References
Phillippo DM (2019). Calibration of Treatment Effects in Network Meta-Analysis using Individual Patient Data. Ph.D. thesis, University of Bristol. Available from https://research-information.bris.ac.uk/.