Reference adjusted survival measures as an alternative to net survival in population-based cancer studies

Age-standardized marginal net survival is the standard measure for comparing cancer survival across populations, but it is difficult to communicate to patients and clinicians. Reference adjustment has been proposed as an alternative, providing all-cause survival and crude probabilities of death that are both interpretable and comparable across populations by standardizing other-cause mortality to a common reference. In Stata non-parametric net and reference adjusted survival are available using the stpp command. A parametric flexible parametric model-based approach is possible using the stpm3 command followed by the postestimation standsurv command. I will demonstrate the different approaches using data from the Swedish Cancer Register on colon cancer, lung cancer and melanoma. In addition I will describe a simulation study following the ADEMP framework, conducted to assess the statistical properties of net survival and reference adjustment under controlled conditions, including their bias, coverage and power to detect differences between populations, as well as their robustness to errors in the population mortality file. The simulation study demonstrates two main findings. First, non-parametric reference adjustment shows substantially higher power than net survival to detect differences between populations for long-term survival estimates, with the advantage increasing with follow-up time and being most pronounced for cancers with good prognosis. Second, reference adjustment is substantially more robust to proportional errors in the population mortality file than net survival, a consequence of the mathematical structure of the estimator in which individual and reference mortality rates fully or partially cancel. Together these findings suggest that reference adjustment could be a valuable alternative to net survival in population-based cancer research.