The opportunities and challenges of quality-of-life data in esophageal cancer treatment

The article by Chen et al. recently published in this journal provides important empirical evidence on the quality-of-life (QoL) of patients treated for esophageal cancer (1). The primary results demonstrate the differential impact that treatments have on patients’ long-term general health, as measured by the EQ-5D-3L health utility scores. These data, collected from esophageal cancer survivors in rural China, are used to develop several predictive models of patients’ QoL and quality-adjusted life years (QALYs) depending on treatment and the numbers of years since that treatment. These results advance our understanding of the lasting impact of esophageal cancer treatment. In addition to the results, this work sheds light on the opportunities and challenges in QoL data for esophageal cancer care.

The work by Chen et al. offers an opportunity to help shape patients’ expectations and goals for esophageal cancer treatment. However, this will be heavily influenced by how QoL is defined and measured. The Chen et al. study define QoL through a general health lens, as measured using EuroQoL’s EQ-5D-3L. Other studies investigating esophageal cancer patients’ long-term post-treatment QoL have used a disease-specific lens. Notable is how the results differ between the two lenses. In a study by Darling et al., the QoL of patients undergoing one of several types of esophageal cancer treatments was measured using both the Functional Assessment of Cancer Therapy-General (FACT-G) and the European Organization for Research on Treatment of Cancer (EORTC) QLQ-C30 (2). With both instruments, patients reported a decrease in QoL the first month after treatment. But by 1-year post-treatment, QoL was equal to, or exceeding, where it was prior to treatment. A study by Katz et al. reported an even quicker recovery in QoL—within 3- to 6-month post-surgery the average patient reported a QoL equal to or better than that pre-surgery (3). Katz et al. measured the QoL in patients exclusively undergoing esophagectomy using the FACT-G. In the results reported by Chen et al., on the other hand, QoL never recovers to baseline, even 9 years after surgery. Similar differences between general versus disease-specific QoL measures were observed in a systematic review by Parameswaran et al. (4). It is reasonable to assume that patients’ expectations for treatment will differ depending on the perspective with which they consider QoL.

Inherent in the work by Chen et al. is the opportunity to use QoL data to facilitate greater communication between patients and their clinicians. Research has demonstrated that eliciting QoL data from patients opens the door to a wider conversation about their values and preferences for care, which, in turn, can help inform the clinician about the best course of action for treating and managing the disease (5,6). Chen et al. propose that their prediction models can be used by clinicians to communicate the potential risk of different treatments to patients. Clinicians can use this as a starting point to engage patients in a broader discussion about what they hope to gain from treatment and what they are willing to trade-off. The importance that esophageal cancer patients place in these discussions and a shared decision-making process has been reported in an adjunct study to the Dutch SANO-trial by Hermus et al. (7). In this study, patients who were considered “clinically complete responders” after neoadjuvant chemoradiotherapy for esophageal cancer were asked to decide between active surveillance or esophagectomy. Based on qualitative interviews and survey results, the authors conclude that clinicians have a critical role to play in informing patients’ decisions and providing them with objective and accurate information, particularly early on the decision-making process. In a second study by Hermus et al., patients and their partners report wanting more personal guidance and support that is tailored to their unique circumstances (8). The prediction models developed by Chen et al. offer a first step toward personalizing the provision on information for setting more realistic expectations of treatment and making more informed decisions.

However, the opportunities of QoL data to shape esophageal cancer patients’ treatment expectations and improve communication are not without challenges. A critical consideration is how these QoL data should be interpreted and used in the clinical management of patients. While Chen et al. suggest that their results can be used to help guide management decisions, the clinical audience would have benefited from an example of how the authors envisioned this working in practice. It is challenging to envision how a utility value or a QALY—the two outputs generated by Chen et al.’s predictive models—would be translated in this regard. As previously noted by Kneuertz et al., clinicians need to be able to interpret QoL data in such a way that is supportive of a care plan (9). Absent this ability, QoL data has very little clinical utility and is of limited value at the point-of-care. In general, this is where research in QoL of esophageal cancer falls short. More study linking changes in QoL to the long-term symptom management and care of esophageal cancer is needed if these data are to have an impact on the real-world management of patients.

As treatments for esophageal cancer continue to improve, so too will the need for more empirical evidence on the impact they are having on patients’ QoL. The study published by Chen et al. addresses an important knowledge gap and advances our understanding of how QoL data can be used for managing patients with esophageal cancer. With this comes opportunities to influence treatment expectations and enhance communication with patients. The challenge is figuring out how this should happen in practice. For this, further research is needed. Those in the esophageal cancer care community should work as a collective to encourage rigorous studies in this area to realize the full potential of QoL data.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Esophagus. The article has undergone external peer review.

Peer Review File: Available at https://aoe.amegroups.org/article/view/10.21037/aoe-24-26/prf

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://aoe.amegroups.org/article/view/10.21037/aoe-24-26/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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