Counterpoint: epidemiology to guide decision-making: moving away from practice-free research.
Analyses of observational data aimed at supporting decision-making are ideally framed as a contrast between well-defined treatment strategies. These analyses compare individuals' outcomes from the start of the treatment strategies under consideration. Exceptions to this synchronizing of the start of follow-up and the treatment strategies may be justified on a case-by-case basis.
Miguel A
MA
Hernán
D015982:Bias; D015984:Causality; D003657:Decision Making; D004812:Epidemiologic Methods; D005500:Follow-Up Studies; D006801:Humans; D064887:Observational Studies as Topic / Q000379:methods; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000379:methods; D012107:Research Design; D013997:Time Factors
causal inference; decision-making; left truncation; survival curves