Extended Data Fig. 2: Effect of censoring nonmalignant deaths on the estimation of disease-specific survival, and prognostic value of clinical covariates at different disease states.

a, Cumulative incidence computed as 1 − Kaplan–Meier (KM) estimator, using only disease-specific death as an end point and censoring other types of death. b, Cumulative incidence computed using a competing-risk model that takes into account different causes of death. The bias of the 1 − Kaplan–Meier estimator is visible. c, Distribution of age at the time of diagnosis for ER-negative and ER-positive patients. The number of patients in each group is indicated in all panels. This analysis was done with the full dataset. Box plots were computed using the median of the observations (centre line). The first and third quartiles are shown as boxes, and the whiskers extend to the ±1.58 interquartile range divided by the square root of the sample size. Outliers are shown as dots. d, log hazard ratios calculated using the multistate model stratified by ER status (n = 3,147) for different covariates, namely grade, lymph-node (LN) status, tumour size (size), time from surgery and time from local relapse (LR). log hazard ratios are shown for different states, including post-surgery (PS; hazard ratio of progressing to relapse or DSD), locoregional recurrence (LR; hazard ratio of progressing to distant relapse or DSD) and distant recurrence (DR; hazard ratio of cancer-specific death). 95% confidence intervals are shown. This analysis was done with the full dataset.