Unmasking survival biases in observational treatment studies of influenza patients – Wolkewitz, Schumacher

Unmasking survival biases in observational treatment studies of influenza patients – Wolkewitz, Schumacher Announcement Date: February 7, 2017

Abstract

Background
Several observational studies reported that Oseltamivir (Tamiflu) reduced mortality in
infected and hospitalized patients. Due to the restriction of observation to hospital stay
and time-dependent treatment assignment, such findings were prone to common types
of survival bias (length, time-dependent and competing risk bias).

Methods
British hospital data from the FLU-CIN study group were used which included 1391
patients with confirmed pandemic influenza A/H1N1 2009 infection. We used a multistate
model approach with following states: hospital admission, Oseltamivir treatment,
discharge and death. Time origin is influenza onset. We displayed individual data, risk
sets, hazards and probabilities from multi-state models to study the impact of these
three common survival biases.

Results
The correct hazard ratio of Oseltamivir for death was 1.03 (95%-CI: 0.64-1.66) and
for discharge 1.89 (95%-CI: 1.65-2.16). Length bias increased both hazard ratios:
HR(death)= 1.82 (95%-CI:1.12-2.98) and HR(discharge)= 4.44 (95%-CI: 3.90-5.05)
whereas the time-dependent bias reduced them: HR(death)= 0.62 (95%-CI:0.39-1.00)
and HR(discharge)= 0.85 (95%-CI:0.75-0.97). Length and time-dependent bias were
less pronounced in terms of probabilities. Ignoring discharge as a competing event for
hospital death led to a remarkable overestimation of hospital mortality and failed to
detect the reducing effect of Oseltamivir on hospital stay.

Conclusions
The impact of each of the three survival biases was remarkable and it can make NI appear
more effective or even harmful. Incorrect and misclassified risk sets were primary
the source of biased hazard rates.