Deriving Meaningful Aspects of Health Related to Physical Activity in Chronic Disease: Concept Elicitation Using Machine Learning-Assisted Coding of Online Patient Conversations

OBJECTIVES

Clinical outcome assessment (COA) developers must ensure that measures assess aspects of health that are meaningful to the target patient population. Although the methodology for doing this is well understood for certain COAs, such as patient-reported outcome measures, there are fewer examples of this practice in the development of digital endpoints using mobile sensor technology such as physical activity monitors. This study explored the utility of social media data, specifically, posts on online health boards, in understanding meaningful aspects of health related to physical activity in 3 different chronic diseases: fibromyalgia, chronic obstructive pulmonary disease, and chronic heart failure.

METHODS

We used machine learning and manual coding to summarize the content of posts extracted from 4 online health boards. Where available, patient age and sex were retrieved from post content or user profiles. We utilized analytical approaches to assess the robustness of findings to differences in the characteristics of online samples compared to the true patient population. Finally, we assessed concept saturation by measuring the convergence of autocorrelations.

RESULTS

We identify a number of aspects of health described as important by patients in our samples, and summarize these into concepts for measurement. For chronic heart failure, these included purposeful walking duration and speed, fatigue, difficulty going upstairs, standing, and aspects of physical exercise. Overall and age-adjusted results did not differ considerably for each disease group.

CONCLUSIONS

This study illustrates the potential of performing concept elicitation research using social media data, which may provide valuable insight to inform COA development.

Patient-Reported Outcomes in Metastatic Breast Cancer: A Review of Industry-Sponsored Clinical Trials

INTRODUCTION

Patient-reported outcome (PRO) measures serve to capture vital patient information not otherwise obtained by primary study endpoints. This paper examines how PROs are utilized as endpoints in industry-sponsored metastatic breast cancer clinical trials.

METHODS

A search was conducted in the clinicaltrials.gov web site for trials involving common treatments for metastatic breast cancer. Thirty-eight clinical trials were identified which included a PRO endpoint in the study, and data were extracted and summarized.

RESULTS

Overall, 17 unique PRO questionnaires and 14 concepts of measurement were identified as secondary or exploratory endpoints. The Functional Assessment of Cancer Therapy-Breast was the most frequently utilized questionnaire, commonly implemented to assess quality of life. The EORTC QLQ-C30 was also frequently used to measure quality of life or pain.

CONCLUSION

This review shares insights into the role of PROs in trials for metastatic breast cancer from which treatment developers and other stakeholders can enhance successful implementation of the patient voice into future trials.