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Methods Inf Med 2016; 55(05): 431-439
DOI: 10.3414/ME16-01-0035
Original Articles
Schattauer GmbH

A Factor Analysis Approach for Clustering Patient Reported Outcomes[*]

Jung Hun Oh
1   Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
,
Maria Thor
1   Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
,
Caroline Olsson
2   Division of Clinical Cancer Epidemiology, Department of Oncology, University of Gothenburg, Gothenburg, Sweden
,
Viktor Skokic
2   Division of Clinical Cancer Epidemiology, Department of Oncology, University of Gothenburg, Gothenburg, Sweden
,
Rebecka Jörnsten
3   Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden
,
David Alsadius
2   Division of Clinical Cancer Epidemiology, Department of Oncology, University of Gothenburg, Gothenburg, Sweden
,
Niclas Pettersson
2   Division of Clinical Cancer Epidemiology, Department of Oncology, University of Gothenburg, Gothenburg, Sweden
,
Gunnar Steineck
2   Division of Clinical Cancer Epidemiology, Department of Oncology, University of Gothenburg, Gothenburg, Sweden
,
Joseph O. Deasy
1   Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
› Author Affiliations
FundingsThis work was funded by an internal grant from Memorial Sloan Kettering Cancer Center and in part through the NIH / NCI Cancer Center Support Grant P30 CA008748; the Swedish Cancer Society, the King Gustav V Jubilee Clinic Cancer Foundation in Göteborg; the Swedish state under the ALF agreement in Göte-borg; Varian Corporation; and the Assar Gabrielsson Foundation, Tore Nilssons Foundation, and “Syskonen Svenssons fond för medicinsk forskning”.
Further Information

Publication History

Received 14 March 2016

Accepted in revised form: 19 May 2016

Publication Date:
08 January 2018 (online)

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Summary

Background: In the field of radiation oncology, the use of extensive patient reported outcomes is increasingly common to meas -ure 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. Objectives: The 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. Methods: We 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. Results: We 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. Conclusions: Our proposed method can aid in the process of understanding PROs and provide a basis for improving our understanding of radiation-induced side effects.

Keywords

Confirmatory factor analysis - exploratory factor analysis - factor analysis - radiotherapy - toxicity - patient reported outcomes

1 Supplementary material published on our web-site http://dx.doi.org/10.3414/ME16-01-0035


 

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