Missing health-related quality of life (HRQOL) data in longitudinal studies can reduce precision and power and bias results. Using INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support), we sought to identify factors associated with missing HRQOL data, examine the impact of these factors on estimated HRQOL assuming missing at random missingness, and perform sensitivity analyses to examine missing not at random (MNAR) missingness because of illness severity.Methods and Results—
INTERMACS patients (n=3248) with a preimplantation profile of 1 (critical cardiogenic shock) or 2 (progressive decline) were assessed with the EQ-5D-3L visual analog scale and Kansas City Cardiomyopathy Questionnaire-12 summary scores pre-implantation and 3 months postoperatively. Mean and median observed and missing at random–imputed HRQOL scores were calculated, followed by sensitivity analyses. Independent factors associated with HRQOL scores and missing HRQOL assessments were determined using multivariable regression. Independent factors associated with preimplantation and 3-month HRQOL scores, and with the likelihood of missing HRQOL assessments, revealed few correlates of HRQOL and missing assessments (R2 range, 4.7%–11.9%). For patients with INTERMACS profiles 1 and 2 and INTERMACS profile 1 alone, missing at random–imputed mean and median HRQOL scores were similar to observed scores, before and 3 months after implantation, whereas MNAR-imputed mean scores were lower (≥5 points) at baseline but not at 3 months.Conclusions—
We recommend use of sensitivity analyses using an MNAR imputation strategy for longitudinal studies when missingness is attributable to illness severity. Conduct of MNAR sensitivity analyses may be less critical after mechanical circulatory support implant, when there are likely fewer MNAR data.