Differences in Lung Cancer Treatment Preferences Among Oncologists, Patients and Family Members: A Semi-Structured Qualitative Study in China

Differential Characteristics of Fatigue-Pain-Sleep Disturbance-Depression Symptom Cluster and Influencing Factors of Patients With Advanced Cancer During Treatment: A Latent Class Analysis

BACKGROUND

Patients with advanced cancer may experience symptom clusters during treatment (eg, fatigue, pain, sleep disturbance, depression). Understanding the characteristics and factors associated with symptom cluster classes among this patient population is essential for effective symptom management.

OBJECTIVE

The aims of this study were to identify symptom cluster (fatigue-pain-sleep disturbance-depression) classes and explore influencing factors in patients with advanced cancer during the treatment.

METHODS

A cross-sectional survey was conducted in an oncology department of a tertiary hospital in China from September 2020 to March 2021. Cancer patients (stage III/IV) 18 years or older completed the questionnaires on pain, fatigue, sleep disturbance, depression, physical activity, and exercise self-efficacy. Latent class analysis and multinomial logistic regression were used.

RESULTS

Three hundred sixty-five patients who were male (65.2%) and younger than 60 years (59.5%) completed questionnaires. Three symptom cluster classes were identified: class 1 ("low symptom burden" class), class 2 ("fatigue-insomnia" class), and class 3 ("high symptom burden" class), with a percentage of 54.5%, 38.6%, and 6.8%, respectively. The quality-of-life score, introversion/extroversion, economic burden, Karnofsky Performance Status, albumin level, and exercise self-efficacy were significantly different among the 3 classes (P < .05).

CONCLUSION

Patients with advanced cancer were classified into 3 distinct classes, with class 1 having the best function. Results from this study reveal that Karnofsky Performance Status, albumin level, and exercise self-efficacy were significant factors for the latent classes of symptom cluster.

IMPLICATIONS FOR PRACTICE

Exercise self-efficacy is important for personalized interventions and improving symptom management efficiency.

How Do Treatment Preferences of Patients With Cancer Compare With Those of Oncologists and Family Members? Evidence From a Discrete Choice Experiment in China

OBJECTIVES

This study aimed to compare the treatment preference among oncologists, patients with lung cancer, and their family members in China.

METHODS

A face-to-face discrete choice experiment survey was conducted among oncologists, patients, and their family members. Participants completed 13 choice sets describing 6 key attributes, namely, overall survival time, risk of severe adverse effect, severity of pain, appetite, physical functioning status, and monthly cost. Mixed logit model and latent class analysis were used to estimate attribute level preference weights and the relative importance (RI) for attributes. The willingness to pay (WTP) and maximum acceptable risk (MAR) were also estimated. The RI, WTP, and MAR of oncologists, patients, and family members were compared.

RESULTS

A total of 121 oncologists and 161 dyads of patients and family members completed the survey. Overall survival time, physical functioning status, and pain were the 3 most important attributes across all 3 groups. Oncologists and family members had higher RI on overall survival time than patients (48% and 51% vs 38%). Patients had higher RI on physical functioning status and pain (23% and 14%) than oncologists (13% and 12%) and family members (16% and 11%). For extending survival, patients had the least WTP, and family members had the highest MAR. The latent class analysis identified 2 classes in the patient group and 3 classes in oncologist and family member groups.

CONCLUSIONS

There were differences in preferences for survival, risk, quality of life, and costs associated with cancer treatments among patients, oncologists, and family members. This finding highlights the need of involving patients in treatment decision making in China.