Evidence map›Paper›PMID 36255721›Full record

ArticleJAMA network open2022

Use of the Cancer and Aging Research Group Predictive Model for Chemotherapy-Related Toxic Effects in a Multiethnic, Older Adult Asian Population.

Angela Pang, Low Jiali, Alex Ng, Joseph Cheng, Meng Wang, Yean Shin Ng, Yao Yao, Meiling Chun, Francis Ho, Jeremy Tey

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 28% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Predictive value of the Cancer and Aging Research Group Score for chemotherapy toxicities in older adults with cancer: a systematic review and meta-analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Pooled it
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  5. Review
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

10 authors at 4 institutions in 1 country.

Angela PangDepartment of Haematology Oncology, National University Cancer Institute, Singapore.
Low JialiDepartment of Haematology Oncology, National University Cancer Institute, Singapore.
Alex NgYong Loo Lin School of Medicine, National University of Singapore.
Joseph ChengYong Loo Lin School of Medicine, National University of Singapore.
Meng WangDepartment of Medicine, National University Hospital, Singapore.
Yean Shin NgDepartment of Haematology Oncology, National University Cancer Institute, Singapore.
Yao YaoDepartment of Pharmacy, National University Hospital, Singapore.
Meiling ChunDepartment of Surgery, Ng Teng Fong General Hospital, Singapore.
Francis HoDepartment of Radiation Oncology, National University Cancer Institute, Singapore.
Jeremy TeyDepartment of Radiation Oncology, National University Cancer Institute, Singapore.
National University Cancer Institute, Singapore · SGNational University Hospital · SGNational University of Singapore · SGNg Teng Fong General Hospital · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The Cancer and Aging Research Group (CARG) prediction model for chemotherapy-related toxic effects has been developed but not yet validated in older Asian adults. In view of differences in drug metabolism and toxic effect reporting in the Asian population, the ability of this tool to guide the cancer treatment decision-making process in older Asian adults needs to be assessed. Objective: To examine the validity of the CARG predictive model in a multiethnic Asian cohort of older adults. Design, Setting, and Participants: In this prognostic study, patients of various Asian ethnicities 70 years or older with a solid tumor diagnosis receiving chemotherapy at the National University Cancer Institute, Singapore, were accrued from June 1, 2017, to January 1, 2019. Their risks of chemotherapy-related toxic effects were calculated using the CARG tool. A geriatric assessment was performed, and the treating oncologist (blinded to the CARG scores) was asked to give an estimated likelihood of toxic effects (low, medium, or high). Chemotherapy-related toxic effects were recorded during each clinic visit. Validation of the prediction model was performed by calculating the area under the receiver operating characteristic curve. Multivariate analyses were performed to identify variables in other domains in the geriatric assessment predicting for severe toxic effects. Main Outcomes and Measures: Grade 3 to 5 toxic effects and hospitalization. Results: The study included 200 patients (median age, 74 years [range, 70-89 years]; 110 [55.0%] male; 177 [88.5%] Chinese, 17 [8.5%] Malay, 4 [2.0%] Indian, and 2 [1.0%] other ethnicities [according to Singapore's national system of race classification]). A total of 137 patients (68.5%) experienced grade 3 to 5 toxic effects, and 131 (65.5%) required hospitalization. The area under the receiver operating characteristic curve for the CARG chemotoxicity prediction model was 0.74 (95% CI, 0.67-0.82), retaining good discrimination in the study population. Conclusions and Relevance: This prognostic study conducted in a multiethnic Asian cohort of older adults supports the validity of the CARG predictive model in this population, predicting which older adults are at risk of chemotherapy-related toxic effects.

Indexed as

Antineoplastic AgentsNeoplasmsOncologistsAgedFemaleGeroscienceHumansMaleRisk AssessmentAntineoplastic Agents

Identifiers

PMID36255721
PMCPMC9579905
OpenAlexW4306733190

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.