Characteristics and patient-reported outcomes associated to dropout in severely affected oncological patients release_uy22y64mujfbln4c2t2gcmdzcq

Abstract

<jats:title>Abstract</jats:title> <jats:bold>Background</jats:bold>Patient-reported outcome measures (PROMs) are commonly used and are surrogates for clinical outcomes in cancer research. In the research setting of very severe diseases such as cancer, it is difficult to avoid the problem of incomplete questionnaires from drop-out or missing data due to patients who deceased during observation period. We aimed to explore patient characteristics and patient-reported outcomes associated with the time-to-dropout. <jats:bold>Methods</jats:bold>In the Oncological Social Care Project (OSCAR) study the condition of participants was assessed four times within 12 months (t0: baseline, t1: 3 months, t2: 6 months, and t3: 12 months) by validated PROMs. We performed competing-risks regression based on Fine and Gray's proportional sub-distribution hazards model for exploring factors associated with time-to-dropout. Death was considered as competing risk. <jats:bold>Results</jats:bold>Three hundred sixty-two participants were analyzed in the study. 193 (53.3%) completed follow-up at 12 months, 67 (18.5%) patients dropped out, and 102 patients (28.2%) died during the study period. Poor subjective social support was related to higher risk for drop-out (SHR=2.10; 95%CI: 1.01 – 4.35). Lower values in health-related quality of life were related to drop-out and death. The subscales global health status/QoL, role functioning, physical functioning, and fatigue symptom in the EORTC QLQ-C30 were key characteristics associated with early drop-out.<jats:bold>Conclusion</jats:bold>Severely affected cancer patients with poor social support and poor quality of life seem more likely to drop out of studies compared to patients with higher levels of social support and quality of life. This should be considered when planning studies assessing cancer patients. Methods to monitor drop-outs timely and handle missing outcomes might be used. Results of such studies have to be interpreted with caution in light of the particular drop-out mechanisms.
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