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      Latent class analysis suggests four distinct classes of complementary medicine users among women with breast cancer

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          Breast cancer patients commonly report using >1 form of complementary and alternative medicine (CAM). However, few studies have attempted to analyze predictors and outcomes of multiple CAM modalities. We sought to group breast cancer patients by clusters of type and intensity of complementary and alternative medicine (CAM) use following diagnosis.


          Detailed CAM use following breast cancer diagnosis was assessed in 2002–2003 among 764 female residents of Long Island, New York diagnosed with breast cancer in 1996–1997. Latent class analysis (LCA) was applied to CAM modalities while taking into account frequency and intensities.


          Four distinct latent classes of CAM use emerged: 1) “Low-dose supplement users” (40 %), who used only common nutritional supplements; 2) “Vitamin/mineral supplement users” (39 %), using an abundance of supplements in addition to other practices; 3) “Mind-body medicine users” (12 %), with near-universal use of supplements, mind-body medicine techniques, and massage; and 4) “Multi-modality high-dose users” (9 %), who were highly likely to use nearly all types of CAM. Predictors of membership in classes with substantial CAM use included younger age, more education, higher income, Jewish religion, ideal body mass index, higher fruit and vegetable intake, higher levels of physical activity, receipt of adjuvant chemotherapy, and prior use of oral contraceptives.


          LCA identified important subgroups of breast cancer patients characterized by varying degrees of complementary therapy use. Further research should explore the reproducibility of these classes and investigate the association between latent class membership and breast cancer outcomes.

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          Most cited references 30

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              Prevalence of complementary and alternative medicine (CAM) use by the general population: a systematic review and update.

              To update previous systematic reviews of 12-month prevalence of complementary and alternative medicine (CAM) use by general populations; to explore trends in CAM use by national populations; to develop and apply a brief tool for assessing methodological quality of published CAM-use prevalence surveys. Nine databases were searched for published studies from 1998 onwards. Studies prior to 1998 were identified from two previous systematic reviews. A six-item literature-based tool was devised to assess robustness and interpretability of CAM-use estimates. Fifty-one reports from 49 surveys conducted in 15 countries met the inclusion criteria. We extracted 32 estimates of 12-month prevalence of use of any CAM (range 9.8-76%) and 33 estimates of 12-month prevalence of visits to CAM practitioners (range 1.8-48.7%). Quality of methodological reporting was variable; 30/51 survey reports (59%) met four or more of six quality criteria. Estimates of 12-month prevalence of any CAM use (excluding prayer) from surveys using consistent measurement methods showed remarkable stability in Australia (49%, 52%, 52%; 1993, 2000, 2004) and USA (36%, 38%; 2002, 2007). There was evidence of substantial CAM use in the 15 countries surveyed. Where national trends were discernable because of consistent measurement, there was no evidence to suggest a change in 12-month prevalence of CAM use since the previous systematic reviews were published in 2000. Periodic surveys are important to monitor population-level CAM use. Use of government-sponsored health surveys may enhance robustness of population-based prevalence estimates. Comparisons across countries could be improved by standardising approaches to data collection. © 2012 Blackwell Publishing Ltd.

                Author and article information

                212-342-4130 ,
                BMC Complement Altern Med
                BMC Complement Altern Med
                BMC Complementary and Alternative Medicine
                BioMed Central (London )
                19 November 2015
                19 November 2015
                : 15
                [ ]Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th St, New York, NY USA
                [ ]Department of Epidemiology, University of North Carolina, 2101 McGavran-Greenberg Hall, CB #7435 Chapel Hill, NC USA
                [ ]Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, 161 Fort Washington Ave., New York, NY USA
                [ ]Department of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th St, New York, NY USA
                [ ]Department of Nutrition, University of North Carolina, 2200 McGavran-Greenberg Hall, CB #7461 Chapel Hill, NC USA
                [ ]Department of Preventive Medicine, Mount Sinai School of Medicine, 17 E 102nd Street, New York, NY USA
                [ ]Department of Medicine, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY USA
                [ ]Present address: 722 W. 168th St., Room 733, New York, NY 10032 USA
                © Strizich et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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