CIC_reconstruct function

Reconstruct cumulative incidence curves

In competing risks situations, papers may provide one overall KM plot for the composite outcome of event 1 or event 2 as well as cumulative incidence plots for the each event separately. We can use these three plots to reconstruct individual level data with event-specific labels (censored, event 1, or event 2). Can also handle the case when the CIC for event 2 is not given. Run this separately for each arm.

CIC_reconstruct(overallIPD, clicks1, arm, clicks2 = NULL)

Arguments

• overallIPD: The individual patient data from the overall (composite outcome) plot that has already been processed through reconstructKM. Should have three columns: time, status, and arm.
• clicks1: A data.frame with "time" and "cuminc" columns that are output from the digitizing software, similar to what you would input for reconstructKM except it's a cumulative incidence function for a specific event, not a survival function (make sure first click is (0,0)).
• arm: The arm corresponding to clicks1 and possibly clicks2.
• clicks2: Same as clicks1 but for the second event if it's provided. Default is null.

Returns

An augmented version of overallIPD that additionally gives the cause of the event (cause 1 or cause 2) as a fourth "event" column.

Examples

data(pembro_clicks)
data(pembro_NAR)
augTabs <- format_raw_tabs(raw_NAR=pembro_NAR, raw_surv=pembro_clicks)
reconstruct <- KM_reconstruct(aug_NAR=augTabs$aug_NAR, aug_surv=augTabs$aug_surv)
IPD <- data.frame(arm=1, time=reconstruct$IPD_time, status=reconstruct$IPD_event)
clicks1 <- dplyr::mutate(pembro_clicks, cuminc=1-survival)
CIC_reconstruct(overallIPD = IPD, clicks1 = clicks1, arm=1, clicks2=NULL)