Patient-reported outcomes (PRO) endpoints in phase 2/3 trials can indicate additional benefits to patients and provide supplementary evidence for registration. Our statisticians and psychometricians work collaboratively to conduct analyses of HRQOL outcomes and make the most of your data. We have experience with multiple scales, scoring algorithms, and application of analytical techniques to account for the nuances of specialized data types. For example, HRQOL data is often subject to “informative missingness” that should be accounted for using methods that do not rely on missing at random (MAR) assumptions. We can apply longitudinal analysis methods and pattern mixture models to fully explore the power of the information you have collected.
Q-TWiST Analyses (Quality-Adjusted Time without Symptoms or Toxicities)
Even if patient-reported QOL data was not collected in oncology studies, we can apply the Q-TWiST method to quantitatively assess the benefit/risk tradeoff of a new treatment regimen. Q-TWiST provides information about the patient experience within the context of clinical outcomes related to a disease and its treatment. Quality-adjusted survival is an understandable concept that can help individual patients make informed treatment decisions based on the relative importance they place on different health outcomes.
