ArticleJournal of the American Geriatrics Society2026
How to Analyze Longitudinal Patient-Reported Outcomes in Populations With High Mortality Rates.
Article in Journal of the American Geriatrics Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Factors independently associated with in-hospital HRQoL in adults treated at a high-complexity institution in a middle-income country.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026Article
- The Association Between Anticholinergic Burden and Treatment-Related Complications in Older Adults with Cancer.Drugs & aging · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalyzing longitudinal patient-reported outcomes (PROs) remains methodologically challenging, particularly in populations with high mortality rates during follow-up. Many PRO studies overlook this issue, potentially leading to biased estimates and limited clinical interpretability. We discuss various methods for analyzing patients who died during follow-up in PRO analyses and examine how these methods affect the interpretation of the study outcomes, using a clinical example in older patients with cancer.
methodsFor our clinical example, we included adults aged
resultsOf the 1218 participants, 321 (26%) died within 12 months. Methods restricted to the 897 survivors at the end of follow-up lead to results that are difficult to interpret due to selection bias. In linear mixed models, EQ-5D scores are implicitly reconstructed for the 321 participants that died, creating a hypothetical view of QoL assuming no patients died. Alternative approaches, such as the "while-alive" strategy or composite endpoint strategies, treating death as the worst possible score on the EQ-5D, produce more complete views of the QoL.
conclusionsThe interpretation of longitudinal PROs strongly depends on the chosen method, associated estimands and how patients that died are addressed: different methods lead to different estimates and conclusions. Properly defining the research question and choosing the most appropriate method is essential for meaningful interpretations for clinicians and patients.
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