Introduction: Patients with hemophilia still experience significant burden of disease despite the growing availability of efficacious treatment options. Presented here are the final patient-reported data from a non-interventional study of treatment and disease burden in US patients with hemophilia A without inhibitors (HAwoI). Methods: Patients with HAwol were recruited to the PicnicHealth research platform using digital marketing, referrals and community partnerships. PicnicHealth collects and extracts medical records on behalf of the patient, provides them with their records and invites them to participate in recurring patient-reported outcome surveys. Hemophilia severity reported here was based on baseline factor values and medical records. Two validated questionnaires, Hemophilia Treatment Experience Measure (Hemo-TEM)(Brod, M. et al., J Patient Rep Outcomes. 2023) and Patient-Reported Outcomes Measurement Information System (PROMIS)-29 Profile v2.0 (Hays, R.D., et al., Qual Life Res. 2018)were used to collect data on treatment and disease burden. Patients were also asked about their prophylactic medication, if any, as well as two independent questions on anxiety and/or worry concerning bleed protection with current treatment. All surveys were administered between April 2022 and April 2023, with the most recent survey included in this analysis for patients who completed multiple surveys during the study period. Hemo-TEM domain scores were transformed onto a 0 to 100-point scale with higher scores indicating greater burden. PROMIS-29 scores were transformed into T-scores, based on a reference sample with a mean of 50 and standard deviation of 10, except for the pain intensity score, which was rated 0-10. The directionality of impact was specific for each domain (Hays, R.D., et al., Qual Life Res. 2018). Results are presented as proportions, median and interquartile range (IQR, Q1-Q3). Informed consent was obtained. Results: Out of 230 patients with HAwol (91% male; median age: 33.3 years; IQR: 23.9-41.7), 147 (64%) had severe, 41 (18%) had moderate and 42 (18%) had mild hemophilia. Use of prophylactic FVIII was reported by 74 (50%), 16 (39%) and 13 (31%) patients with severe, moderate and mild hemophilia, respectively, while prophylactic non-factor replacement therapy use was reported by 64 (44%), 8 (20%) and 5 (12%) patients, respectively (treatment classes are not mutually exclusive). Treatment class was unspecified (includes patients who did not report prophylactic medication use) for 58 (25%) patients. Treatment burden was observed through Hemo-TEM scores across all subgroups of disease severity and treatment class (n=223), with the strongest drivers being physical impact (median: 25 [IQR: 12-38]), treatment bother (21 [9-32]) and emotional impact (21 [6-38]) domains (Table 1). The PROMIS-29 scores and its directionality shown in Figure 1 demonstrated comparable disease burden in all domains regardless of disease severity or treatment class (n=228). Patients with severe disease on prophylactic FVIII/prophylactic non-factor replacement therapy reported scores of 42 (37-50)/46 (39-57) in physical functioning and 51 (49-61)/49 (46-55), 57 (52-64)/56 (42-60) and 52 (48-56)/52 (46-56) in domains of fatigue, pain interference and sleep disturbance, respectively. Impact on mental well-being for these patients were shown by scores of 56 (49-61)/54 (41-59) and 58 (51-63)/56 (51-61) in domains of depression and anxiety, respectively. Pain intensity for all patients with severe disease was 4 (2-6) out of 10. In response to two independent survey questions, patients with severe HAwol reported feeling anxious (42%) and/or worried (39%) at least sometimes that their current treatment might not adequately protect them from bleed. Conclusion: Patients with HAwoI continue to experience treatment and disease burden, across treatment class and disease severity subgroup. Despite improved outcomes with current treatment strategies, there remains a need to continue to address disease burden. Greater understanding is required of the driving factors behind similar treatment and disease burden between the subgroups to facilitate individualized care.