Evidence map›Paper›PMID 37637033›Full record

ArticleFrontiers in oncology2023

Validation of the FACT-G7 in patients with hematologic malignancies.

Xinwen Du, Ling Mao, Yamei Leng, Fengjiao Chen

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

4 authors.

Xinwen DuDepartment of Hematology, West China Hospital/West China School of Nursing, Sichuan University, Chengdu, China.
Ling MaoDepartment of Hematology, West China Hospital/West China School of Nursing, Sichuan University, Chengdu, China.
Yamei LengDepartment of Hematology, West China Hospital/West China School of Nursing, Sichuan University, Chengdu, China.
Fengjiao ChenDepartment of Hematology, West China Hospital/West China School of Nursing, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: It is essential to evaluate the quality of life in patients with hematologic malignancies to reflect the therapeutic effect and prognosis, but lengthy assessments are often burdensome. The 7-Item Functional Assessment of Cancer Therapy-General (FACT-G7) is a brief, easy, and rapid index for evaluating quality of life. Nevertheless, there is no report about its application in Chinese patients with hematologic malignancies. Objective: The purpose of this study was to validate the Chinese version of the FACT-G7 for patients with hematologic malignancies. Methods: This study is a cross-sectional study. A total of 855 patients with hematologic malignancies completed the Functional Assessment of Cancer Therapy-General (FACT-G) and were scored the Eastern Cooperative Oncology Group Performance Status (ECOG-PS) by nurses. Cronbach's alpha, confirmatory factor analyses, Pearson's correlation, and one-way analysis of variance were conducted to evaluate internal consistent reliability, structural validity and concurrent validity. Results: The FACT-G7 showed acceptable internal consistency, as indicated by a Cronbach's alpha of 0.73. The confirmatory factor analyses test for single-factor model fit for the FACT-G7 scale was almost adequate. The satisfactory correlations between the FACT-G7 and the FACT-G and its subscales, and ECOG-PS groups differed in FACT-G7 scores demonstrating concurrent validity. Conclusion: This study suggested that the Chinese version of the FACT-G7 provides a useful and rapid measure for assessing quality of life in Chinese patients with hematologic malignancies, which providing a reference for further evaluation and care.

Indexed as

FACT-G7hematologic malignancymeasurementquality of lifereliabilityvalidity

Identifiers

PMID37637033
PMCPMC10448388

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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.