ArticleMethods of information in medicine2016
A Factor Analysis Approach for Clustering Patient Reported Outcomes.
Article in Methods of information in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 16 citations in OpenAlex.
- An Oversampling-Enhanced Multi-Class Imbalanced Classification Framework for Patient Health Status Prediction Using Patient-Reported Outcomes.IEEE access : practical innovations, open solutions · 2025Article
- Psychometrics of a Persian patient-centered care scale for chronic diseases.Journal of education and health promotion · 2025Article
- Exploring symptom clusters in mild cognitive impairment and dementia with the NIH Toolbox.Journal of the International Neuropsychological Society : JINS · 2024Article
- Symptom clusters in breast cancer survivors with and without type 2 diabetes over the cancer trajectory.Asia-Pacific journal of oncology nursing · 2024Article
- Using Protection Motivation Theory to develop a survey of over-the-counter decision-making by older adults.Research in social & administrative pharmacy : RSAP · 2024Article
- Article
- Screening indices for cadmium-contaminated soil using earthworm as bioindicator.Environmental science and pollution research international · 2018Article
- Identifying radiation-induced survivorship syndromes affecting bowel health in a cohort of gynecological cancer survivors.PloS one · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
backgroundIn the field of radiation oncology, the use of extensive patient reported outcomes is increasingly common to measure adverse side effects after radiotherapy in cancer patients. Factor analysis has the potential to identify an optimal number of latent factors (i.e., symptom groups). However, the ultimate goal of treatment response modeling is to understand the relationship between treatment variables such as radiation dose and symptom groups resulting from FA. Hence, it is crucial to identify clinically more relevant symptom groups and improved response variables from those symptom groups for a quantitative analysis.
objectivesThe goal of this study is to design a computational method for finding clinically relevant symptom groups from PROs and to test associations between symptom groups and radiation dose.
methodsWe propose a novel approach where exploratory factor analysis is followed by confirmatory factor analysis to determine the relevant number of symptom groups. We also propose to use a combination of symptoms in a symptom group identified as a new response variable in linear regression analysis to investigate the relationship between the symptom group and dose-volume variables.
resultsWe analyzed patient-reported gastrointestinal symptom profiles from 3 datasets in prostate cancer patients treated with radiotherapy. The final structural model of each dataset was validated using the other two datasets and compared to four other existing FA methods. Our systematic EFA-CFA approach provided clinically more relevant solutions than other methods, resulting in new clinically relevant outcome variables that enabled a quantitative analysis. As a result, statistically significant correlations were found between some dose-volume variables to relevant anatomic structures and symptom groups identified by FA.
conclusionsOur proposed method can aid in the process of understanding PROs and provide a basis for improving our understanding of radiation-induced side effects.
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.