Patient reported outcomes including quality of life (QoL) assessments are increasingly being included as either primary or secondary outcomes in randomized controlled trials. While making the outcomes more relevant for patients it entails a challenge in cases where death or a similar event makes the outcome of interest undefined. A pragmatic - and much used - solution is to assign diseased patient with the lowest possible QoL score. This makes medical sense, but creates a statistical problem since traditional tests such as t-tests or Wilcox tests potentially looses large amounts of statistical power. In this paper we propose a novel test that can keep the medical relevant composite outcome, but preserve full statistical power. The test is also applicable in other situations where a specific value (say 0 days alive outside hospitals) encodes a special meaning. The test is implemented in an R package which is available for download.