Leveraging the Potential Synergy Between Patient‐Reported Outcomes and Body Composition Analysis in Patients with Cancer

Introduction

Patient‐reported outcomes (PROs) assessing patients’ symptom burden and quality of life (QOL) as well as body composition analysis represent important independent predictors of clinical outcomes in oncology [1–5]. Specifically, studies suggest that PROs correlate with treatment tolerability and survival, whereas patients’ body composition is associated with physical function, well‐being, treatment toxicity, and survival [6–8]. PROs are increasingly used in both clinical trials and routine practice to enhance care delivery and improve outcomes [9]. Moreover, computed tomography (CT) scans frequently obtained as part of routine care can provide important body composition data. However, the relationship between PROs and body composition in patients with cancer remains understudied, with uncertainty regarding the use of these assessments in combination to better predict patient outcomes, such as treatment tolerability, health care utilization and survival (Fig. 1). In the future, automated CT scan segmentation using artificial intelligence may improve the ability to quickly and reliably capture body composition data [10, 11]. This will facilitate prospective investigations exploring the potential synergy between PROs and body composition analysis for predicting and potentially improving clinical outcomes for patients with cancer.

Patient‐Reported Outcomes in Oncology

Patients with cancer frequently experience many symptoms that are often under‐recognized and thereby undertreated. PROs enable patients to self‐report important clinical information, such as their symptoms (e.g., pain, fatigue, nausea) and QOL. Prior studies investigating the utility of PROs have demonstrated that allowing patients to self‐report their concerns often provides more accurate information than estimates from clinicians and/or caregivers [11]. In particular, data suggest that clinicians often underappreciate the frequency and severity of patients’ symptoms, likely owing to suboptimal patient–clinician communication and inadequate detection or inconsistent assessment of symptoms [12–14]. By failing to reliably capture patients’ symptoms, clinicians miss opportunities to address problematic issues, which could have downstream effects on patients’ QOL, treatment tolerability, and survival outcomes [1]. Thus, PROs represent an important method for assessing and addressing patients’ symptom burden.

Prior studies support the integration of PROs into routine oncology care to improve patients’ symptom management, QOL, and potentially survival [1, 14, 15]. Routine collection of PROs allows patients to report their symptoms earlier and more frequently, increasing the window of opportunity for clinicians to intervene and enhance symptom management [6, 16]. Additionally, prior work has highlighted that patient‐reported QOL tools provide significant independent prognostic information in patients with cancer [3, 15]. Thus, researchers have begun testing interventions using PROs with the goal of improving patients’ symptoms, QOL, health care use, and survival. For example, in a multicenter randomized trial of patients with incurable, solid tumors, patients assigned to a symptom‐monitoring intervention experienced a significant reduction in their symptoms compared with the control group [16]. Another randomized trial investigating a symptom‐monitoring intervention demonstrated that patients assigned to the intervention had better QOL and lower likelihood of requiring emergency department visits compared with those not reporting their symptoms [15]. In a secondary analysis of this study, patients receiving the symptom‐monitoring intervention also experienced improved survival compared with the group receiving usual care [2]. Thus, mounting evidence supports that integrating PROs into clinical oncology practice may enhance the patient experience, improve QOL, and optimize clinical outcomes.

Body Composition Analysis in Oncology

Patients with cancer often experience body composition changes, including loss of skeletal muscle to the point of sarcopenia [17]. Estimates suggest that body composition changes may play a role in approximately 20% of all cancer deaths [18]. Body composition changes emerge from a combination of factors, including deficits in intracellular anabolic signaling pathways involved in muscle and whole‐body protein synthesis [17].

The study of cancer‐related body composition changes has evolved over time [17]. Early studies relied on body weight alone and demonstrated that weight loss correlated with worse survival [4, 18]. More recent studies demonstrate that CT‐derived body composition metrics can reliably capture body composition changes, as weight alone cannot differentiate between loss of muscle and adipose tissue, fluid accumulation, and change in tumor burden [6, 7, 19]. Additionally, researchers have sought to better define sarcopenia based on cross‐sectional muscle area below a prespecified threshold measured by CT scan [17]. Expanding the analysis of CT images beyond tumor burden to include body composition metrics historically required considerable time and technical expertise [5]. However, automated body composition analysis of CT scans obtained for routine care is becoming increasingly available [10].

Studies have demonstrated that body composition changes correlate with patient outcomes, such as tolerance to chemotherapy, health care use, and survival in various cancer populations [4, 5, 7, 17, 19, 20]. Several reviews of cancer‐related body composition changes have highlighted that, across various cancer types (e.g., gastrointestinal, lung, renal) and stages (e.g., resectable, metastatic), patients with adverse body composition changes often experience poor survival outcomes [4, 5]. Therefore, body composition analysis provides valuable prognostic information in oncology, and changes in body composition may help predict patients at risk for poor outcomes.

Efforts to address body composition and prevent adverse changes are needed. To date, no single pharmacologic agent has emerged as the proven standard, but ongoing work continues [7, 18]. Plausibly, developing a combination of pharmacologic strategies and novel fitness and nutrition interventions to address patients’ body composition changes could help improve outcomes such as PROs and survival [4, 20]. Additionally, patients experiencing body composition changes, such as sarcopenia, may represent a population who could benefit from earlier involvement with palliative care and targeted symptom management.

Future Directions

Individually, PROs and body composition analysis provide important information regarding patient outcomes in oncology. With growing data espousing the benefits of PRO‐monitoring interventions, PROs are increasingly being implemented into real‐world settings. Meanwhile, integration of automated body composition analysis of routine CT scans may soon enable body composition data to accompany each scan. These developments suggest that leveraging PROs and body composition analysis is becoming increasingly feasible and closer to being realized. Yet, additional work remains to evaluate the potential synergy between PROs and body composition analysis in the care for patients with cancer, including some key questions outlined here.

What Is the Relationship Between PROs and Body Composition?

Clinically, patients who experience adverse body composition changes, such as sarcopenia, also frequently experience a high symptom burden (e.g., appetite loss, fatigue, distress) and vice versa. In a secondary analysis of data from a randomized trial of early palliative care, more than half of patients with newly diagnosed, incurable cancer met the international consensus definition of sarcopenia, and these patients experienced worse QOL and mood symptoms [6, 17]. Another study of patients with hematologic malignancies demonstrated that patients with sarcopenia experienced a more rapid decline in physical function and QOL over time than those without sarcopenia [8]. However, data are lacking describing the underlying mechanisms and potential relationships between PROs and body composition changes. Although patients’ symptoms often clinically correlate with body composition changes, formal studies are lacking. For example, little information exists regarding differences between PROs and body composition across cancer subpopulations (i.e., age, cancer type) and settings (i.e., inpatient and outpatient care).

Does the Combination of PROs and Body Composition Analysis Improve Prediction of Patient Outcomes (QOL, Health Care Use, Survival)?

Increasing evidence suggests that patients with high symptom burden and those with adverse body composition changes are at risk for poor clinical outcomes. Yet, little work has investigated the ability to combine these assessments to better predict clinical outcomes, such as health care use and survival. Importantly, PROs exist that explicitly seek to assess for body composition syndromes (SarcoPRO, FACT‐Cachexia) [20]. PROs like these, and those used more broadly to assess physical and psychological symptoms, in addition to tools designed to evaluate physical, mental, and social function, could potentially provide synergistic and/or complementary information when combined with body composition metrics [20]. Furthermore, patients’ symptoms and body composition may moderate and/or mediate the impact of interventions or anticancer therapies on patient outcomes, but this requires additional investigation [6, 16]. An improved understanding of the relationships between symptom burden, body composition, and clinical outcomes may inform intervention development and study design as well as guide patient–clinician discussions regarding treatment goals in oncology.

Can PROs and Body Composition Analysis Be Combined with Other Factors (Tumor Markers, Circulating Tumor DNA, Physical Function) to Improve Prognostication and/or Predict Treatment Response?

Oncologists often use prognostic factors (e.g., tumor markers, performance status) to guide care, and additional work is needed to enhance the accuracy and reliability of prognostication in oncology. As our ability to integrate PROs into routine practice improves and the potential increases to monitor body composition on CT scans obtained for routine clinical care, researchers need to investigate how these tools perform in comparison with (or in conjunction with) established prognostic markers. Moreover, as more contemporary biomarkers (e.g., circulating tumor DNA) emerge and become integrated into clinical practice, we can evaluate the relationships between PROs, body composition, and these novel biomarkers, assessing their unique contribution in prognostication and/or predicting treatment response. Collectively, PROs and body composition analysis in combination with other biomarkers may help inform patient–clinician discussions regarding prognosis and anticipated treatment response.

Conclusion

Ultimately, to achieve the highest‐quality oncology care for patients with cancer, additional research should focus on understanding the link between PROs, body composition, and clinical outcomes. Efforts to evaluate the potential synergy between PROs and body composition analysis may inform the development of interventions aimed at addressing the unique and multifaceted supportive care needs of patients with cancer.

Disclosures

Florian J. Fintelmann: BTG Ltd (RF), Jounce Therapeutics (SAB); Eric J. Roeland: BASF, Heron Therapeutics, American Imaging Management, Asahi Kasei Pharma, Napo, Imuneering, Vector Oncology (C/A), Prime Oncology DSMB – Oragenics (H). The other authors indicated no financial relationships.

(C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment; (ET) Expert testimony; (H) Honoraria received; (OI) Ownership interests; (IP) Intellectual property rights/inventor/patent holder; (SAB) Scientific advisory board

References

Author notes