Evidence map›Paper›PMID 38136321›Full record

ArticleCancers2023

Defining an Abnormal Geriatric Assessment: Which Deficits Matter Most?

Anthony Carrozzi, Rana Jin, Susie Monginot, Martine Puts, Shabbir M H Alibhai

Abstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anthony CarrozziDepartment of Medicine, Toronto General Hospital, University Health Network, Toronto, ON M5G 2C4, Canada.
Rana JinDepartment of Nursing, Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada.
Susie MonginotDepartment of Nursing, Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada.
Martine PutsLawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON M5T 1P8, Canada.ORCID 0000-0002-0710-1854
Shabbir M H AlibhaiDepartment of Medicine, Toronto General Hospital, University Health Network, Toronto, ON M5G 2C4, Canada.ORCID 0000-0001-7815-6046

Funding

Princess Margaret Cancer Foundation N/AUniversity Health Network & Sinai Health Geriatrics Summer Scholars Program N/A
6 · The paper itself

Abstract

At present, there is no clear definition of what constitutes an abnormal geriatric assessment (GA) in geriatric oncology. Various threshold numbers of abnormal GA domains are often used, but how well these are associated with treatment plan modification (TPM) and whether specific GA domains are more important in this context remains uncertain. A retrospective review of the geriatric oncology clinic database at Princess Margaret Cancer Centre in Toronto, Canada, including new patients seen for treatment decision making from May 2015 to June 2022, was conducted. Logistic regression modelling was performed to determine the association between various predictor variables (including the GA domains and numerical thresholds) and TPM. The study cohort (n = 736) had a mean age of 80.7 years, 46.1% was female, and 78.3% had a VES-13 score indicating vulnerability (≥3). In the univariable analysis, the best-performing threshold number of abnormal domains based on area under the curve (AUC) was 4 (AUC 0.628). The best-performing multivariable model (AUC 0.704) included cognition, comorbidities, and falls risk. In comparison, the multivariable model with the sole addition of the threshold of 4 had an AUC of 0.689. Overall, an abnormal GA may be best defined as one with abnormalities in the domains of cognition, comorbidities, and falls risk. The optimal numerical threshold to predict TPM is 4.

Indexed as

cancerfrailtygeriatric assessmentgeriatric assessment domainsgeriatric oncologygeriatricsolder adultsoncologytreatment decision makingtreatment plan modification

Identifiers

PMID38136321
PMCPMC10742229

What OpenQuestion holds

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Registered trials

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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.