Background: Ovarian cancer (OC) patients experience a high incidence of sleep disturbance and fatigue, which impacts their health-related quality of life (HRQoL). PROMIS short forms are important tools to assess sleep disturbance and fatigue in OC patients and identify the need for additional intervention. However, these frequently used short forms (SFs) may not capture the diversity and range of issues OC patients experience. Methods: In this mixed-methods study, data were collected from stage III/IV OC patients diagnosed within 3 years with diverse treatment trajectories, race/ethnicity, and locations, including semi-structured interviews with 20 patients and surveys of 200 patients. In addition to their medical history, participants were asked to complete PROMIS Sleep Disturbance SF 8b, and Fatigue SF 8a to evaluate their current symptom burden. Participants were also asked to retrospectively assess their fatigue and sleep during each type of treatment they received with a set of custom sleep and fatigue items from the PROMIS bank. Qualitative data were used to determine the best custom survey items in the PROMIS bank to match the issues raised by patients. Construct validity was evaluated with code prevalence from interview data. Cronbach’s Alpha coefficient was used to assess the scale reliability based on survey testing. Results: Sleep disturbance SF 8b does not capture 3 prominent issues OC patients reported as disrupting their sleep: pain, anxiety, and rumination at bedtime. Related PROMIS items were tested in the survey: trouble getting in a comfortable sleeping position (Sleep 71), stress disturbing sleep (Sleep 78), and trouble stopping thoughts during bedtime (Sleep 69). Significant fatigue issues included forcing oneself to get up and do things (FATIMP47), being frustrated by being too tired to do things they want to do (AN15), feeling like fatigue made them slowed down in their thinking (FATIMP2), feeling less effective at work (FATIMP37), and having to limit social activities because of fatigue (FATIMP18). For custom items, Cronbach’s α ranged from 0.898 to 0.946 for sleep and from 0.939 to 0.985 for fatigue when asked for experience during each treatment type, suggesting a possible increase in robustness of the measures over the SFs. Conclusions: Interviews with OC patients identified significant issues not captured in common PROMIS sleep and fatigue short forms. Testing use of custom PROMIS items better matching the OC patients’ profile with a survey of 200 OC patients showed excellent reliability (α≥ 0.9). Customizing the menu of PROMIS measures used to assess symptom burden among OC patients may improve identification of sleep disturbance and fatigue issues for this patient population. Further research could help identify the best fitting set of questions for a clinical setting when screening advanced OC patients, as well as other patient groups with long term sleep and fatigue issues.