ArticleJournal of surgical oncology2023
Interpreting the risk analysis index of frailty in the context of surgical oncology.
Article in Journal of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
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, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Frailty Screening Using the Risk Analysis Index: A User Guide.Joint Commission journal on quality and patient safety · 2025Pooled it
- Preoperative Frailty and Malnutrition in Surgical Oncology Patients Predicts Higher Postoperative Adverse Events and Worse Survival: Results of a Blinded, Prospective Trial.Annals of surgical oncology · 2024Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
BACKGROUND AND
objectivesThe Risk Analysis Index (RAI) accurately predicts adverse postoperative outcomes but the inclusion of cancer status in the RAI has raised two key concerns about its suitability for use in surgical oncology: (1) the potential over classification of cancer patients as frail, and (2) the potential overestimation of postoperative mortality for patients with surgically curable cancers.
methodsWe performed a retrospective cohort analysis to assess the RAI's power to appropriately identify frailty and predict postoperative mortality in cancer patients. We assessed discrimination for mortality and calibration across five RAI models-the complete RAI and four variants that removed different cancer-related variables.
resultsWe found that the presence of disseminated cancer was a key variable driving the RAI's power to predict postoperative mortality. The model including only this variable [RAI (disseminated cancer)] was similar to the complete RAI in the overall sample (c = 0.842 vs. 0.840) and outperformed the complete RAI in the cancer subgroup (c = 0.736 vs 0.704, respectively, p < 0.0001, Max R
conclusionThe RAI demonstrates somewhat less discrimination when applied exclusively to cancer patients, but remains a strong predictor of postoperative mortality, especially in the setting of disseminated cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.