We analyzed a group of patients who received trimodal treatment – neoadjuvant chemoradiotherapy, followed by surgery and adjuvant chemotherapy – for primary locally advanced rectal cancer.
Overall survival was calculated in months from the date of diagnosis to the first event, including date of the last follow-up or death.
Because Covid-19 death events potentially bias survival estimation, to eliminate skewed data due to Covid-19 death events the observed lifetime of Covid-19 cases was replaced by its corresponding expected lifetime in absence of the Covid-19 event using CoDMI algorithm.
In a traditional Kaplan-Meier approach, patient died of Covid-19 (DoC) can be: i) excluded to the cohort (but this would represent a loss of data), or ii) counted as censored (Cen) (but actually, due to its informative nature, Covid-19 death in a cancer patient cannot be censored as death from other causes), or iii) considered as died of disease (DoD) (but this provides an inappropriate exit cause).
CoDMI algorithm offers an additional, more satisfactory option: iv) DoC events are mean-imputed as no-DoC cases at later follow-up times. With this approach, the observed lifetime of each DoC patient is considered as an “incomplete data” and is extended by an additional expected lifetime computed using the classical Kaplan-Meyer model.