UC Davis

e21515 Background: While cancer is the leading cause of non-accidental death in children and AYAs, factors associated with delays in diagnosis in young patients with cancer are poorly understood; we sought to fill this knowledge gap. Methods: Using the OptumLabs Data Warehouse’s claims data for commercially insured enrollees in a large US health plan—we identified pediatric [0-14 years (y)] and AYA (15–39 y) patients diagnosed with soft tissue sarcomas (STS), bone tumors (BT) and germ cell tumors (GCT) during 2001–17 and continuously enrolled 6 months prior to diagnosis. Time to diagnosis was calculated as days between first medical encounter associated with a possible cancer symptom and diagnosis date. Median times from first symptom to diagnosis were compared using Wilcoxon Rank Sum test. Multivariable logistic regression identified sociodemographic and clinical factors associated with longer time ( > 3 months) from symptom to diagnosis. Results: Of the 11,395 patients, 86% presented to medical care with symptoms prior to diagnosis [STS: 2,228 (89%); BT: 1,565 (87%); GCT: 5,904 (84%)]. The most common symptoms were pain and swelling. STS had the longest median days to diagnosis (92), followed by BT (91) and GCT (49). There was a significant difference (p < 0.001) in median days to diagnosis by age for BT (0–14y: 69; 15–21y: 77; 22–39y: 105) and GCT (0–14y: 96; 15–21y: 34; 22–39y: 49), but not for STS. Patients in households with ≥ a college degree (OR 1.96, 95% CI 1.06–3.64, vs < high school) and seeing a specialist (excluding oncologists) (OR 2.54, CI 2.03–3.19, vs primary care) at first symptom presentation was associated with a longer delay, while older age (22–39y: OR 0.77, CI 0.63–0.94, vs 0-14y) and male sex (OR 0.58, CI 0.51–0.66) were associated with a shorter delay in diagnosis. Conclusions: This study demonstrates that, in a commercially insured population, time to diagnosis varies by cancer type and is impacted by clinical and sociodemographic factors. Shorter time to diagnosis may represent delays in presenting to medical care or more acute presentations of symptoms, therefore patient-reported symptoms and barriers to care data should be collected to better define strategies to reduce delays in diagnosis.