Understanding the patient experience in hepatocellular carcinoma: a qualitative patient interview study

Abstract

Purpose This study aimed to elucidate the patient experience of hepatocellular carcinoma (HCC) to guide patient-centered outcome measurement in drug development. Methods Patients with HCC participated in qualitative interviews to elicit disease-related signs/symptoms and impacts, using discussion guides developed from literature searches and discussions with oncologists. Interview participants rated the disturbance of their experiences (0–10 scale). A conceptual model was developed and mapped against patient-reported outcome (PRO) instruments identified from database reviews. Results Interviews were conducted with 25 individuals with HCC (68% were men; median age: 63 years; 12% Barcelona clinic liver cancer (BCLC) stage A; 32% stage B; and 56% stage C) in the USA. Fifty-one HCC-related concepts were identified from the interviews and were grouped into eight sign/symptom categories (eating behavior/weight changes; extremities [arms, legs]; fatigue and strength; gastrointestinal; pain; sensory; skin; other) and four impact categories (emotional; physical; cognitive function; other) for the conceptual model. The most prevalent and disturbing experiences across the disease stages were fatigue/lack of energy and emotional impacts such as frustration, fear, and depression. Abdominal pain and skin-related issues were particularly common and disturbing in individuals with HCC stage C. The EORTC QLQ-C30 and HCC18 were identified as commonly used PRO instruments in HCC studies and captured the relevant signs/symptoms associated with the patient experience. Conclusion Patients with HCC reported a range of signs/symptoms and impacts that negatively affect daily functioning and quality of life. Including PRO measures in HCC clinical trials can provide meaningful patient perspectives during drug development.

Hepatocellular carcinoma and its impact on quality of life: A review of the qualitative literature

“…The studies also linked symptom burden to functional impacts on patients' lives. Pain, fatigue and dizziness were cited as symptoms causing the most functional limitation (Kaiser et al, 2014 ; Kimbell et al, 2015 ; Patel et al, 2022 ). As a result, many patients were no longer able to do normal activities of daily living (Gill et al, 2018 ; Patel et al, 2022 ), had to quit their jobs (Fan & Eiser, 2012 ; Gill et al, 2018 ; Kimbell et al, 2015 ) and spent more time confined to bed (Kaiser et al, 2014 ; Patel et al, 2022 ).…”

“…Pain, fatigue and dizziness were cited as symptoms causing the most functional limitation (Kaiser et al, 2014 ; Kimbell et al, 2015 ; Patel et al, 2022 ). As a result, many patients were no longer able to do normal activities of daily living (Gill et al, 2018 ; Patel et al, 2022 ), had to quit their jobs (Fan & Eiser, 2012 ; Gill et al, 2018 ; Kimbell et al, 2015 ) and spent more time confined to bed (Kaiser et al, 2014 ; Patel et al, 2022 ). Conversely, when patients had better physical health, they fared better overall (Fan & Eiser, 2012 ; Kaiser et al, 2014 ; Patel et al, 2022 ).…”

Patient‐reported outcomes in HCC: A scoping review by the Practice Metrics Committee of the American Association for the Study of Liver Diseases

“…Patel et al found in interviews with 25 patients with BCLC stages that the most prevalent and disturbing experiences were fatigue, frustration, fear, and depression. [ 38 ] Abdominal pain and skin complaints were common and disturbing for BCLC‐C patients.…”

Natural Language Processing for Automated Classification of Qualitative Data From Interviews of Patients With Cancer

“…Manual processing of HCC and BTC interview data sets has previously been reported. 48,54 Participant demographics and clinical characteristics for each data set are listed in the Appendix in the Supplemental Materials found at https://doi.org/10.1016/j. jval.2022.06.004.…”

“…42 Previous interview-based studies in oncology using manual processing identified symptoms of importance to guide the development of standardized PROs that adequately assess outcomes. [43][44][45][46][47][48] Both within and outside of the field of oncology, studies have investigated the use of NLP to detect and analyze symptom information from freetext formats in electronic health records for capturing symptoms, classifying or characterizing disease, and studying adverse events and clinical outcomes. [49][50][51][52] Nevertheless, knowledge of NLP application to improve cancer-related symptoms and their impact on QoL from qualitative patient interview data is limited.…”