ArticleBMC nursing2023
Translation and validation of chinese version of MDASI immunotherapy for early-phase trials module: a cross-sectional study.
Article in BMC nursing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Psychometric validation of Chinese version of the immunotherapy of the M.D. Anderson Symptom Inventory for Early-Phase Trials module in a multi-cancer cohort.Frontiers in immunology · 2026Article
- Psychometric properties of patient-reported outcome measures for symptom assessment in patients with cancer receiving immunotherapy: A systematic review following the COSMIN 2.0 guidelines.Asia-Pacific journal of oncology nursing · 2025Review
- Career Calling and Professional Match Among Chinese Graduates: The Roles of Career Loyalty and Industry Income.Behavioral sciences (Basel, Switzerland) · 2025Article
- Development and validation of the self-report symptom inventory of immune-related adverse events in patients with lung cancer.Asia-Pacific journal of oncology nursing · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDuring immunotherapy treatment and survival, identifying symptoms requires a standardized and validated assessment tool. The aim of this study was to translate, validate and use the Chinese version of the Immunotherapy of the M.D. Anderson Symptom Inventory for Early-Phase Trials module (MDASI-Immunotherapy EPT) to assess the symptom burden of cancer patients receiving immunotherapy in China.
methodsThe MDASI-Immunotherapy EPT was translated into Chinese using Brislin's translation model and the back-translation method. In total, 312 Chinese-speaking colorectal cancer patients receiving immunotherapy were enrolled in the trial from August 2021 to July 2022 after receiving definitive diagnoses in our cancer center. The reliability and validity of the translated version was evaluated.
resultsCronbach's α values were 0.964 and 0.935 for the symptom severity and interference scales, respectively. Significant correlations were found between the MDASI-Immunotherapy EPT-C and FACT-G scores (-0.617-0.732, P < 0.001). Known-group validity was supported by significant differences in the scores of the four scales grouped by ECOG PS (all P < 0.01). The overall mean subscale scores for the core and interference subscales were 1.92 ± 1.75 and 1.46 ± 1.87, respectively. Fatigue, numbness/tingling, and disturbed sleep had the highest scores for the most serious symptoms.
conclusionThe MDASI-Immunotherapy EPT-C showed adequate reliability and validity for measuring symptoms among Chinese-speaking colorectal cancer patients receiving immunotherapy. The tool could be used in clinical practice and clinical trials to gather patients' health and quality of life data and manage their symptoms in a timely manner in the future.
Indexed as
Identifiers
What OpenQuestion holds
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.