Skip to contents

FastSurvival: Fast Survival Analysis and Simulation for Clinical Trials

Source: R/FastSurvival-package.R
FastSurvival-package.Rd

FastSurvival provides fast alternatives to the standard survival analysis functions in the survival package, together with a simulation layer for designing and evaluating time-to-event trials. Every function is designed for repeated evaluation inside large simulation loops, such as adaptive sample-size re-estimation, probability-of-success calculations, and regional consistency evaluation in multi-regional clinical trials. Core computations are implemented in C++ via Rcpp.

Details

The estimation and testing functions return S3-class objects that are internally named numeric vectors, so a result can be used directly in arithmetic, subsetting, and aggregation after stripping the class with unclass. Each class has a print() method that formats the result similarly to the corresponding survival package output.

Estimation and testing:

survfit_fast

Kaplan-Meier survival probability, standard error, and confidence interval at a single specified time point. The C++ backend locates the evaluation cutoff by binary search and accumulates the Kaplan-Meier product and the Greenwood sum in a single scan over event positions only.

survdiff_fast

Log-rank test for two-group survival data, including Fleming-Harrington, modestly-weighted, Gehan-Breslow, and Tarone-Ware weights, and stratified and stratified-weighted variants. The C++ backend uses a two-pointer merge scan over pooled sorted vectors.

coxph_fast

Closed-form hazard ratio estimator via the Pike-Halley Estimator method, with Wald confidence interval. The estimator anchors at the Pike estimate and applies a single analytic Halley correction to the Cox partial likelihood score.

rmst_fast

Restricted mean survival time for a single group or a two-group comparison, with difference and ratio contrasts.

wmst_fast

Window mean survival time over an interval, generalizing rmst_fast to a nonzero lower window limit.

milestone_fast

Two-group comparison of Kaplan-Meier survival at a milestone timepoint, with Wald, log-log, and MOVER inference methods.

medsurv_fast

Median survival time for a single group or a two-group difference, with a kernel-hazard variance method and a local-constant-hazard method.

maxcombo_fast

Max-combo test over a set of Fleming-Harrington weighted log-rank statistics, with the joint p-value obtained from the implied multivariate normal distribution.

rmw_fast

Robust modestly-weighted log-rank test, the maximum of the standard log-rank and a modestly-weighted log-rank statistic.

wkm_fast

Weighted Kaplan-Meier (Pepe-Fleming) test, the weighted integrated difference between two Kaplan-Meier curves.

ahsw_fast

Average hazard with survival weight, reporting the ratio and difference contrasts.

ahr_fast

Kalbfleisch-Prentice average hazard ratio over a restricted interval, with a test on the group-share scale and an equivalent test and confidence interval on the log scale.

Simulation and sequential analysis:

simdata_fast

Individual patient data simulator for one-group, two-group, and K-arm time-to-event trials. Supports piecewise uniform accrual, piecewise exponential survival and dropout times, subgroups, and correlated two-endpoint illness-death generation. Random number generation uses dqrng.

analysis_fast

Interim and final analyses of simulated trials at a set of information times or calendar cutoffs, returning one row of test statistics per replicate and look.

pairwise_fast

Pairwise comparisons of each experimental arm against a shared control in a multi-arm trial.

simsummary_fast

Aggregation of replicate-level results into operating characteristics, given efficacy and futility boundaries computed elsewhere.

Visualization:

gen_scenario_fast

Design-stage assembly of survival, dropout, and accrual scenarios, with plot() and print() methods.

kmcurve_fast

Analysis-stage Kaplan-Meier curves with a risk table, with plot() and print() methods.

References

Homma, G. (2025). One step from Pike to Cox: a closed-form hazard ratio estimator. Manuscript under review.

Collett, D. (2014). Modelling Survival Data in Medical Research (3rd ed.). Chapman and Hall/CRC.

See also

Useful links:

Author

Maintainer: Gosuke Homma my.name.is.gosuke@gmail.com

Authors: