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Abstract Background Breast cancer is one of the most common cancers in women. Patient-reported outcome measures are used to evaluate patients’ health-related quality of life in clinical breast cancer studies. This study evaluated the structure, validity, reliability, and responsiveness of the National Comprehensive Cancer Network-Functional Assessment of Cancer Therapy-Breast Cancer Symptom Index (NFBSI-16) subscales in a clinical trial featuring patients with advanced/metastatic breast cancer (aBC), and estimated NFBSI-16 meaningful change thresholds. Methods Data from 101 patients with aBC enrolled in a phase II trial (Xenera-1) were included for psychometric evaluation of the NFBSI-16. Subscale structure was evaluated by assessing inter-item correlations, item-total correlations, and internal consistency (cycles 2 and 5). Validity was assessed using scale-level convergent validity (cycles 2 and 5) and known-groups (Baseline). Reliability was analysed via test-retest at cycles 3–4, and responsiveness to improvement and worsening was evaluated at cycles 5, 7, and 9. Meaningful change thresholds were estimated using anchor-based methods (supported by distribution-based methods) at cycles 5, 7, and 9. Results NFBSI-16 internal consistency was acceptable, but item-total correlations suggested that its subscales and the GP5 item (side-effect of treatment) scores may be preferred over a total score. Convergent and known-groups evidence supported NFBSI-16 validity. Test-retest reliability was good to excellent for Total and DRS-P (disease-related symptoms: physical) scales, and moderate for the GP5 item. Responsiveness to worsening was generally demonstrated, but responsiveness to improvement could not be demonstrated due to limited observed improvement. Anchor-based meaningful change thresholds were estimated for DRS-P and Total scores. Conclusion This study provides evidence that the NFBSI-16 has desirable psychometric properties for use in clinical studies in aBC. It also provides estimates of group- and individual-level meaningful change thresholds to facilitate score interpretation in future aBC research.

Abstract Background Published in 2019, a new addendum to the ICH E9 guideline presents the estimand framework as a systematic approach to ensure alignment among clinical trial objectives, trial execution/conduct, statistical analyses, and interpretation of results. The use of the estimand framework for describing clinical trial objectives has yet to be extensively considered in the context of patient-reported outcomes (PROs). We discuss the application of the estimand framework to PRO objectives when designing clinical trials in the future, with a focus on PRO outcomes in oncology trial settings as our example. Main We describe the components of an estimand and take a naïve PRO trial objective to illustrate how to apply attributes described in the estimand framework to inform construction of a detailed clinical trial objective and its related estimand. We discuss identifying potential post-randomization events that alter the interpretation of the endpoint or render its observation impossible (also defined as intercurrent events) in the context of PRO endpoints, and the implications of how to handle intercurrent events in the construction of the PRO objective. Using a simple objective statement, “What is the effect of treatment X on patient’s quality of life?”, we build up an example estimand statement and also use a previously published phase III oncology clinical trial to illustrate how an estimand for a PRO objective could have been written to align to the estimate framework. Conclusion The use of the estimand framework, as described in the new ICH E9 (R1) addendum guideline will become a key common framework for developing clinical trial objectives for evaluating effects of treatment. In the context of considering PROs, the framework provides an opportunity to more precisely specify and build the rationale for patient-focused objectives. This will help to ensure that clinical trials used for registration are designed and analysed appropriately, enabling all stakeholders to accurately interpret conclusions about the treatment effects for patient-focused outcomes.