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Fenton BW, Grey SF, Tossone K, et al. Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures. Pain Res Treat. 2015;2015:940675doi: 10.1155/2015/940675.
Fenton, B. W., Grey, S. F., Tossone, K., McCarroll, M., & Von Gruenigen, V. E. (2015). Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures. Pain research and treatment, 2015940675. https://doi.org/10.1155/2015/940675
Fenton, Bradford W, et al. "Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures." Pain research and treatment vol. 2015 (2015): 940675. doi: https://doi.org/10.1155/2015/940675
Fenton BW, Grey SF, Tossone K, McCarroll M, Von Gruenigen VE. Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures. Pain Res Treat. 2015;2015:940675. doi: 10.1155/2015/940675. Epub 2015 Aug 18. PMID: 26355825; PMCID: PMC4556336.
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Pain Res Treat. 2015;2015:940675. doi: 10.1155/2015/940675. Epub 2015 Aug 18.

Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures.

Pain research and treatment

Bradford W Fenton, Scott F Grey, Krystel Tossone, Michele McCarroll, Vivian E Von Gruenigen

Affiliations

  1. Department of Obstetrics and Gynecology, Summa Health System, Akron, OH 44304, USA.
  2. Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical Center, Ann Arbor, MI 48109, USA.
  3. Department of Social and Behavioral Sciences, College of Public Health, Kent State University, Kent, OH 44242, USA.

PMID: 26355825 PMCID: PMC4556336 DOI: 10.1155/2015/940675

Abstract

Chronic pelvic pain affects multiple aspects of a patient's physical, social, and emotional functioning. Latent class analysis (LCA) of Patient Reported Outcome Measures Information System (PROMIS) domains has the potential to improve clinical insight into these patients' pain. Based on the 11 PROMIS domains applied to n=613 patients referred for evaluation in a chronic pelvic pain specialty center, exploratory factor analysis (EFA) was used to identify unidimensional superdomains. Latent profile analysis (LPA) was performed to identify the number of homogeneous classes present and to further define the pain classification system. The EFA combined the 11 PROMIS domains into four unidimensional superdomains of biopsychosocial dysfunction: Pain, Negative Affect, Fatigue, and Social Function. Based on multiple fit criteria, a latent class model revealed four distinct classes of CPP: No dysfunction (3.2%); Low Dysfunction (17.8%); Moderate Dysfunction (53.2%); and High Dysfunction (25.8%). This study is the first description of a novel approach to the complex disease process such as chronic pelvic pain and was validated by demographic, medical, and psychosocial variables. In addition to an essentially normal class, three classes of increasing biopsychosocial dysfunction were identified. The LCA approach has the potential for application to other complex multifactorial disease processes.

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