{ettbc} emulates a target trial of screening mammography for breast cancer, using the clone-censor-reweight methodology of García-Albéniz et al. (2020). That study estimated the effect of continuing (vs. stopping) annual screening mammography on breast cancer mortality in Medicare beneficiaries older than 70.

The package provides the analytic building blocks of that pipeline:

• clone_censor() — clone each participant into the STOPBASE and CONTINUE arms and apply each arm’s censoring rule.
• expand_to_long() — expand the cloned data to one row per participant-arm-month for discrete-time survival analysis.
• compute_ipw_weights() — stabilized inverse-probability-of-censoring weights.
• fit_outcome_hr() — IPW-weighted pooled logistic regression for the arm hazard ratio.
• predict_survival_unadjusted(), predict_survival_baseline_adjusted(), predict_survival_ipw() — g-computation marginal survival curves.
• bootstrap_ci() — percentile bootstrap confidence intervals.
• false_positives() — false-positive rates for histological evaluations.
• extract_screening_mammograms() and companions — templates for extracting mammogram events from Medicare claims by HCPCS code.

The package is experimental and not yet an end-to-end reproduction of the published analysis; see the open issues for the remaining gaps.

You can install the development version of {ettbc} from GitHub with:

# install.packages("pak")
pak::pak("ucdavis/ettbc")

{ettbc} ships three synthetic datasets (cohort, screening_mammograms, diagnostic_mammograms) that mimic the structure of the original study data. The clone-censor step turns the one-row-per-participant cohort into two rows per participant — one for each trial arm:

library(ettbc)

cloned <- clone_censor(
  cohort,
  screening_mammograms,
  diagnostic_mammograms
)

nrow(cloned) # two rows per participant
#> [1] 200
head(cloned[, c("id", "arm", "start_month", "end_month", "fup", "bc_died")])
#>   id      arm start_month end_month fup bc_died
#> 1  1 STOPBASE          26        38  13       0
#> 2  2 STOPBASE          33        45  13       0
#> 3  3 STOPBASE          28        42  15       0
#> 4  4 STOPBASE           1        12  12       0
#> 5  5 STOPBASE          17        28  12       0
#> 6  6 STOPBASE          40        52  13       0

expand_to_long() then prepares the data for the inverse-probability-weighted survival analysis:

long <- expand_to_long(cloned)
head(long[, c("id", "arm", "month", "month2", "dead_t1")])
#>   id      arm month month2 dead_t1
#> 1  1 STOPBASE    26      0       0
#> 2  1 STOPBASE    27      1       0
#> 3  1 STOPBASE    28      2       0
#> 4  1 STOPBASE    29      3       0
#> 5  1 STOPBASE    30      4       0
#> 6  1 STOPBASE    31      5       0

See the article “Using ettbc” for the full walkthrough.

This package uses altdoc with Quarto to build its documentation site. To build and preview the documentation locally:

# Load the package
pkgload::load_all()

# Render the documentation
altdoc::render_docs()

# Preview the site
altdoc::preview_docs()

The documentation is automatically built and deployed to GitHub Pages via GitHub Actions when changes are pushed to the main branch.

Please note that the {ettbc} project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.